Genetic and Psychosocial Predictors of Aggression: Variable Selection and Model Building With Component-Wise Gradient Boosting.

Science.gov (United States)

Suchting, Robert; Gowin, Joshua L; Green, Charles E; Walss-Bass, Consuelo; Lane, Scott D

2018-01-01

Rationale : Given datasets with a large or diverse set of predictors of aggression, machine learning (ML) provides efficient tools for identifying the most salient variables and building a parsimonious statistical model. ML techniques permit efficient exploration of data, have not been widely used in aggression research, and may have utility for those seeking prediction of aggressive behavior. Objectives : The present study examined predictors of aggression and constructed an optimized model using ML techniques. Predictors were derived from a dataset that included demographic, psychometric and genetic predictors, specifically FK506 binding protein 5 (FKBP5) polymorphisms, which have been shown to alter response to threatening stimuli, but have not been tested as predictors of aggressive behavior in adults. Methods : The data analysis approach utilized component-wise gradient boosting and model reduction via backward elimination to: (a) select variables from an initial set of 20 to build a model of trait aggression; and then (b) reduce that model to maximize parsimony and generalizability. Results : From a dataset of N = 47 participants, component-wise gradient boosting selected 8 of 20 possible predictors to model Buss-Perry Aggression Questionnaire (BPAQ) total score, with R 2 = 0.66. This model was simplified using backward elimination, retaining six predictors: smoking status, psychopathy (interpersonal manipulation and callous affect), childhood trauma (physical abuse and neglect), and the FKBP5_13 gene (rs1360780). The six-factor model approximated the initial eight-factor model at 99.4% of R 2 . Conclusions : Using an inductive data science approach, the gradient boosting model identified predictors consistent with previous experimental work in aggression; specifically psychopathy and trauma exposure. Additionally, allelic variants in FKBP5 were identified for the first time, but the relatively small sample size limits generality of results and calls for

ARMAX, OE and SSIF model predictors for power transmission and ...

African Journals Online (AJOL)

Three mathematical model structures, namely: ARMAX, OE and a SSIF are first formulated followed by the formulation of their respective model predictors for the model identification and prediction of power transmission and distribution within Akure and its environs. A total of 51,350 data samples from the Power Holding ...

Genetic and Psychosocial Predictors of Aggression: Variable Selection and Model Building With Component-Wise Gradient Boosting

Directory of Open Access Journals (Sweden)

Robert Suchting

2018-05-01

Full Text Available Rationale: Given datasets with a large or diverse set of predictors of aggression, machine learning (ML provides efficient tools for identifying the most salient variables and building a parsimonious statistical model. ML techniques permit efficient exploration of data, have not been widely used in aggression research, and may have utility for those seeking prediction of aggressive behavior.Objectives: The present study examined predictors of aggression and constructed an optimized model using ML techniques. Predictors were derived from a dataset that included demographic, psychometric and genetic predictors, specifically FK506 binding protein 5 (FKBP5 polymorphisms, which have been shown to alter response to threatening stimuli, but have not been tested as predictors of aggressive behavior in adults.Methods: The data analysis approach utilized component-wise gradient boosting and model reduction via backward elimination to: (a select variables from an initial set of 20 to build a model of trait aggression; and then (b reduce that model to maximize parsimony and generalizability.Results: From a dataset of N = 47 participants, component-wise gradient boosting selected 8 of 20 possible predictors to model Buss-Perry Aggression Questionnaire (BPAQ total score, with R2 = 0.66. This model was simplified using backward elimination, retaining six predictors: smoking status, psychopathy (interpersonal manipulation and callous affect, childhood trauma (physical abuse and neglect, and the FKBP5_13 gene (rs1360780. The six-factor model approximated the initial eight-factor model at 99.4% of R2.Conclusions: Using an inductive data science approach, the gradient boosting model identified predictors consistent with previous experimental work in aggression; specifically psychopathy and trauma exposure. Additionally, allelic variants in FKBP5 were identified for the first time, but the relatively small sample size limits generality of results and calls for

Exploratory regression analysis: a tool for selecting models and determining predictor importance.

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Braun, Michael T; Oswald, Frederick L

2011-06-01

Linear regression analysis is one of the most important tools in a researcher's toolbox for creating and testing predictive models. Although linear regression analysis indicates how strongly a set of predictor variables, taken together, will predict a relevant criterion (i.e., the multiple R), the analysis cannot indicate which predictors are the most important. Although there is no definitive or unambiguous method for establishing predictor variable importance, there are several accepted methods. This article reviews those methods for establishing predictor importance and provides a program (in Excel) for implementing them (available for direct download at http://dl.dropbox.com/u/2480715/ERA.xlsm?dl=1) . The program investigates all 2(p) - 1 submodels and produces several indices of predictor importance. This exploratory approach to linear regression, similar to other exploratory data analysis techniques, has the potential to yield both theoretical and practical benefits.

Multiple Imputation of Predictor Variables Using Generalized Additive Models

NARCIS (Netherlands)

de Jong, Roel; van Buuren, Stef; Spiess, Martin

2016-01-01

The sensitivity of multiple imputation methods to deviations from their distributional assumptions is investigated using simulations, where the parameters of scientific interest are the coefficients of a linear regression model, and values in predictor variables are missing at random. The

Predictors of physical activity in persons with mental illness: Testing a social cognitive model.

Science.gov (United States)

Zechner, Michelle R; Gill, Kenneth J

2016-12-01

This study examined whether the social cognitive theory (SCT) model can be used to explain the variance in physical exercise among persons with serious mental illnesses. A cross-sectional, correlational design was employed. Participants from community mental health centers and supported housing programs (N = 120) completed 9 measures on exercise, social support, self-efficacy, outcome expectations, barriers, and goal-setting. Hierarchical regression tested the relationship between self-report physical activity and SCT determinants while controlling for personal characteristics. The model explained 25% of the variance in exercise. Personal characteristics explained 18% of the variance in physical activity, SCT variables of social support, self-efficacy, outcome expectations, barriers, and goals were entered simultaneously, and they added an r2 change value of .07. Gender (β = -.316, p = .001) and Brief Symptom Inventory Depression subscale (β = -2.08, p exercise. In a separate stepwise multiple regression, we entered only SCT variables as potential predictors of exercise. Goal-setting was the single significant predictor, F(1, 118) = 13.59, p exercise in persons with mental illnesses. Goal-setting practices, self-efficacy, outcome expectations and social support from friends for exercise should be encouraged by psychiatric rehabilitation practitioners. People with more depressive symptoms and women exercise less. More work is needed on theoretical exploration of predictors of exercise. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Exploring patient satisfaction predictors in relation to a theoretical model.

Science.gov (United States)

Grøndahl, Vigdis Abrahamsen; Hall-Lord, Marie Louise; Karlsson, Ingela; Appelgren, Jari; Wilde-Larsson, Bodil

2013-01-01

The aim is to describe patients' care quality perceptions and satisfaction and to explore potential patient satisfaction predictors as person-related conditions, external objective care conditions and patients' perception of actual care received ("PR") in relation to a theoretical model. A cross-sectional design was used. Data were collected using one questionnaire combining questions from four instruments: Quality from patients' perspective; Sense of coherence; Big five personality trait; and Emotional stress reaction questionnaire (ESRQ), together with questions from previous research. In total, 528 patients (83.7 per cent response rate) from eight medical, three surgical and one medical/surgical ward in five Norwegian hospitals participated. Answers from 373 respondents with complete ESRQ questionnaires were analysed. Sequential multiple regression analysis with ESRQ as dependent variable was run in three steps: person-related conditions, external objective care conditions, and PR (p person-related conditions) explained 51.7 per cent of the ESRQ variance. Step 2 (external objective care conditions) explained an additional 2.4 per cent. Step 3 (PR) gave no significant additional explanation (0.05 per cent). Steps 1 and 2 contributed statistical significance to the model. Patients rated both quality-of-care and satisfaction highly. The paper shows that the theoretical model using an emotion-oriented approach to assess patient satisfaction can explain 54 per cent of patient satisfaction in a statistically significant manner.

Simple Decision-Analytic Functions of the AUC for Ruling Out a Risk Prediction Model and an Added Predictor.

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Baker, Stuart G

2018-02-01

When using risk prediction models, an important consideration is weighing performance against the cost (monetary and harms) of ascertaining predictors. The minimum test tradeoff (MTT) for ruling out a model is the minimum number of all-predictor ascertainments per correct prediction to yield a positive overall expected utility. The MTT for ruling out an added predictor is the minimum number of added-predictor ascertainments per correct prediction to yield a positive overall expected utility. An approximation to the MTT for ruling out a model is 1/[P (H(AUC model )], where H(AUC) = AUC - {½ (1-AUC)} ½ , AUC is the area under the receiver operating characteristic (ROC) curve, and P is the probability of the predicted event in the target population. An approximation to the MTT for ruling out an added predictor is 1 /[P {(H(AUC Model:2 ) - H(AUC Model:1 )], where Model 2 includes an added predictor relative to Model 1. The latter approximation requires the Tangent Condition that the true positive rate at the point on the ROC curve with a slope of 1 is larger for Model 2 than Model 1. These approximations are suitable for back-of-the-envelope calculations. For example, in a study predicting the risk of invasive breast cancer, Model 2 adds to the predictors in Model 1 a set of 7 single nucleotide polymorphisms (SNPs). Based on the AUCs and the Tangent Condition, an MTT of 7200 was computed, which indicates that 7200 sets of SNPs are needed for every correct prediction of breast cancer to yield a positive overall expected utility. If ascertaining the SNPs costs $500, this MTT suggests that SNP ascertainment is not likely worthwhile for this risk prediction.

Significant Predictors for Effectiveness of Blended Learning in a Language Course

Science.gov (United States)

Wichadee, Saovapa

2018-01-01

A wide variety of technologies combined with traditional classroom methods can make learning easier in the digital age. This paper studied undergraduate students' learning performance and satisfaction after they had studied in a blended setting and investigated if variables of learner characteristics and course features would be predictors for…

OPLS statistical model versus linear regression to assess sonographic predictors of stroke prognosis.

Science.gov (United States)

Vajargah, Kianoush Fathi; Sadeghi-Bazargani, Homayoun; Mehdizadeh-Esfanjani, Robab; Savadi-Oskouei, Daryoush; Farhoudi, Mehdi

2012-01-01

The objective of the present study was to assess the comparable applicability of orthogonal projections to latent structures (OPLS) statistical model vs traditional linear regression in order to investigate the role of trans cranial doppler (TCD) sonography in predicting ischemic stroke prognosis. The study was conducted on 116 ischemic stroke patients admitted to a specialty neurology ward. The Unified Neurological Stroke Scale was used once for clinical evaluation on the first week of admission and again six months later. All data was primarily analyzed using simple linear regression and later considered for multivariate analysis using PLS/OPLS models through the SIMCA P+12 statistical software package. The linear regression analysis results used for the identification of TCD predictors of stroke prognosis were confirmed through the OPLS modeling technique. Moreover, in comparison to linear regression, the OPLS model appeared to have higher sensitivity in detecting the predictors of ischemic stroke prognosis and detected several more predictors. Applying the OPLS model made it possible to use both single TCD measures/indicators and arbitrarily dichotomized measures of TCD single vessel involvement as well as the overall TCD result. In conclusion, the authors recommend PLS/OPLS methods as complementary rather than alternative to the available classical regression models such as linear regression.

Improving the precision of lake ecosystem metabolism estimates by identifying predictors of model uncertainty

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Rose, Kevin C.; Winslow, Luke A.; Read, Jordan S.; Read, Emily K.; Solomon, Christopher T.; Adrian, Rita; Hanson, Paul C.

2014-01-01

Diel changes in dissolved oxygen are often used to estimate gross primary production (GPP) and ecosystem respiration (ER) in aquatic ecosystems. Despite the widespread use of this approach to understand ecosystem metabolism, we are only beginning to understand the degree and underlying causes of uncertainty for metabolism model parameter estimates. Here, we present a novel approach to improve the precision and accuracy of ecosystem metabolism estimates by identifying physical metrics that indicate when metabolism estimates are highly uncertain. Using datasets from seventeen instrumented GLEON (Global Lake Ecological Observatory Network) lakes, we discovered that many physical characteristics correlated with uncertainty, including PAR (photosynthetically active radiation, 400-700 nm), daily variance in Schmidt stability, and wind speed. Low PAR was a consistent predictor of high variance in GPP model parameters, but also corresponded with low ER model parameter variance. We identified a threshold (30% of clear sky PAR) below which GPP parameter variance increased rapidly and was significantly greater in nearly all lakes compared with variance on days with PAR levels above this threshold. The relationship between daily variance in Schmidt stability and GPP model parameter variance depended on trophic status, whereas daily variance in Schmidt stability was consistently positively related to ER model parameter variance. Wind speeds in the range of ~0.8-3 m s–1 were consistent predictors of high variance for both GPP and ER model parameters, with greater uncertainty in eutrophic lakes. Our findings can be used to reduce ecosystem metabolism model parameter uncertainty and identify potential sources of that uncertainty.

Using empirical Bayes predictors from generalized linear mixed models to test and visualize associations among longitudinal outcomes.

Science.gov (United States)

Mikulich-Gilbertson, Susan K; Wagner, Brandie D; Grunwald, Gary K; Riggs, Paula D; Zerbe, Gary O

2018-01-01

Medical research is often designed to investigate changes in a collection of response variables that are measured repeatedly on the same subjects. The multivariate generalized linear mixed model (MGLMM) can be used to evaluate random coefficient associations (e.g. simple correlations, partial regression coefficients) among outcomes that may be non-normal and differently distributed by specifying a multivariate normal distribution for their random effects and then evaluating the latent relationship between them. Empirical Bayes predictors are readily available for each subject from any mixed model and are observable and hence, plotable. Here, we evaluate whether second-stage association analyses of empirical Bayes predictors from a MGLMM, provide a good approximation and visual representation of these latent association analyses using medical examples and simulations. Additionally, we compare these results with association analyses of empirical Bayes predictors generated from separate mixed models for each outcome, a procedure that could circumvent computational problems that arise when the dimension of the joint covariance matrix of random effects is large and prohibits estimation of latent associations. As has been shown in other analytic contexts, the p-values for all second-stage coefficients that were determined by naively assuming normality of empirical Bayes predictors provide a good approximation to p-values determined via permutation analysis. Analyzing outcomes that are interrelated with separate models in the first stage and then associating the resulting empirical Bayes predictors in a second stage results in different mean and covariance parameter estimates from the maximum likelihood estimates generated by a MGLMM. The potential for erroneous inference from using results from these separate models increases as the magnitude of the association among the outcomes increases. Thus if computable, scatterplots of the conditionally independent empirical Bayes

Regulatory and personality predictors of the reliability of professional actions

Directory of Open Access Journals (Sweden)

Morosanova V.I.

2017-12-01

Full Text Available Background. The present research is carried out in the context of the conscious self-regulation of professional activity. Objective. It investigates the regulatory and personality predictors of reliability in rescue operations under stressful conditions. Design. The research sample includes 87 rescuers (72 men and 15 women aged from 25 to 50 years. Respondents were asked to complete the Morosanova’s Self-Regulation Profile Questionnaire – SRPQM, the Eysenck Personality Profile - Short (EPP-S, and the expert questionnaire “Professional Reliability of Rescue Operation” designed for this particular study. Results. On the basis of a correlation analysis, the structural model of the predictors of action reliability was constructed using the maximum likelihood method. Consistency indices showed a good agreement between the model and empirical data. The model contains three latent factors: “Self-regulation”, “Neuroticism” and “Reliability of actions”. As the model displays, the “Self-regulation” factor is a significant predictor of professional action reliability. There are two indicator variables for the factor “Self-regulation”: the self-regulation reliability considered as its stability in the stressful situations, and the rescuers’ levels of development of professionally critical regulatory features - modeling of conditions significant for the achievement of goals and the programming of actions. The study results also show that personality dispositions (by Eysenck have only indirect influence on action reliability. As the structural model reveals, the conscious self-regulation is a mediator in the relationship of neuroticism traits and action reliability. Conclusion. The conscious self-regulation is a significant predictor of professional action reliability under stressful conditions. It is also the mediator of the effects of personality dispositions on the reliability of action.

Uncertainties of statistical downscaling from predictor selection: Equifinality and transferability

Science.gov (United States)

Fu, Guobin; Charles, Stephen P.; Chiew, Francis H. S.; Ekström, Marie; Potter, Nick J.

2018-05-01

The nonhomogeneous hidden Markov model (NHMM) statistical downscaling model, 38 catchments in southeast Australia and 19 general circulation models (GCMs) were used in this study to demonstrate statistical downscaling uncertainties caused by equifinality to and transferability. That is to say, there could be multiple sets of predictors that give similar daily rainfall simulation results for both calibration and validation periods, but project different amounts (or even directions of change) of rainfall changing in the future. Results indicated that two sets of predictors (Set 1 with predictors of sea level pressure north-south gradient, u-wind at 700 hPa, v-wind at 700 hPa, and specific humidity at 700 hPa and Set 2 with predictors of sea level pressure north-south gradient, u-wind at 700 hPa, v-wind at 700 hPa, and dewpoint temperature depression at 850 hPa) as inputs to the NHMM produced satisfactory results of seasonal rainfall in comparison with observations. For example, during the model calibration period, the relative errors across the 38 catchments ranged from 0.48 to 1.76% with a mean value of 1.09% for the predictor Set 1, and from 0.22 to 2.24% with a mean value of 1.16% for the predictor Set 2. However, the changes of future rainfall from NHMM projections based on 19 GCMs produced projections with a different sign for these two different sets of predictors: Set 1 predictors project an increase of future rainfall with magnitudes depending on future time periods and emission scenarios, but Set 2 predictors project a decline of future rainfall. Such divergent projections may present a significant challenge for applications of statistical downscaling as well as climate change impact studies, and could potentially imply caveats in many existing studies in the literature.

Stable 1-Norm Error Minimization Based Linear Predictors for Speech Modeling

DEFF Research Database (Denmark)

Giacobello, Daniele; Christensen, Mads Græsbøll; Jensen, Tobias Lindstrøm

2014-01-01

In linear prediction of speech, the 1-norm error minimization criterion has been shown to provide a valid alternative to the 2-norm minimization criterion. However, unlike 2-norm minimization, 1-norm minimization does not guarantee the stability of the corresponding all-pole filter and can generate...... saturations when this is used to synthesize speech. In this paper, we introduce two new methods to obtain intrinsically stable predictors with the 1-norm minimization. The first method is based on constraining the roots of the predictor to lie within the unit circle by reducing the numerical range...... based linear prediction for modeling and coding of speech....

A predictor-corrector algorithm to estimate the fractional flow in oil-water models

International Nuclear Information System (INIS)

Savioli, Gabriela B; Berdaguer, Elena M Fernandez

2008-01-01

We introduce a predictor-corrector algorithm to estimate parameters in a nonlinear hyperbolic problem. It can be used to estimate the oil-fractional flow function from the Buckley-Leverett equation. The forward model is non-linear: the sought- for parameter is a function of the solution of the equation. Traditionally, the estimation of functions requires the selection of a fitting parametric model. The algorithm that we develop does not require a predetermined parameter model. Therefore, the estimation problem is carried out over a set of parameters which are functions. The algorithm is based on the linearization of the parameter-to-output mapping. This technique is new in the field of nonlinear estimation. It has the advantage of laying aside parametric models. The algorithm is iterative and is of predictor-corrector type. We present theoretical results on the inverse problem. We use synthetic data to test the new algorithm.

BMI, HOMA-IR, and Fasting Blood Glucose Are Significant Predictors of Peripheral Nerve Dysfunction in Adult Overweight and Obese Nondiabetic Nepalese Individuals: A Study from Central Nepal.

Science.gov (United States)

Thapa, Lekhjung; Rana, P V S

2016-01-01

Objective. Nondiabetic obese individuals have subclinical involvement of peripheral nerves. We report the factors predicting peripheral nerve function in overweight and obese nondiabetic Nepalese individuals. Methodology. In this cross-sectional study, we included 50 adult overweight and obese nondiabetic volunteers without features of peripheral neuropathy and 50 healthy volunteers to determine the normative nerve conduction data. In cases of abnormal function, the study population was classified on the basis of the number of nerves involved, namely, "HOMA-IR) was the significant predictor (P = 0.019, 96% CI = 1.420-49.322) of sensory nerve dysfunction. Body mass index (BMI) was the significant predictor (P = 0.034, 95% CI = 1.018-1.577) in case of ≥2 mixed nerves' involvement. Conclusion. FBG, HOMA-IR, and BMI were significant predictors of peripheral nerve dysfunction in overweight and obese Nepalese individuals.

Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model.

Science.gov (United States)

Islam, Mohammad Mafijul; Alam, Morshed; Tariquzaman, Md; Kabir, Mohammad Alamgir; Pervin, Rokhsona; Begum, Munni; Khan, Md Mobarak Hossain

2013-01-08

Malnutrition is one of the principal causes of child mortality in developing countries including Bangladesh. According to our knowledge, most of the available studies, that addressed the issue of malnutrition among under-five children, considered the categorical (dichotomous/polychotomous) outcome variables and applied logistic regression (binary/multinomial) to find their predictors. In this study malnutrition variable (i.e. outcome) is defined as the number of under-five malnourished children in a family, which is a non-negative count variable. The purposes of the study are (i) to demonstrate the applicability of the generalized Poisson regression (GPR) model as an alternative of other statistical methods and (ii) to find some predictors of this outcome variable. The data is extracted from the Bangladesh Demographic and Health Survey (BDHS) 2007. Briefly, this survey employs a nationally representative sample which is based on a two-stage stratified sample of households. A total of 4,460 under-five children is analysed using various statistical techniques namely Chi-square test and GPR model. The GPR model (as compared to the standard Poisson regression and negative Binomial regression) is found to be justified to study the above-mentioned outcome variable because of its under-dispersion (variance variable namely mother's education, father's education, wealth index, sanitation status, source of drinking water, and total number of children ever born to a woman. Consistencies of our findings in light of many other studies suggest that the GPR model is an ideal alternative of other statistical models to analyse the number of under-five malnourished children in a family. Strategies based on significant predictors may improve the nutritional status of children in Bangladesh.

Predictors of persistent pain after total knee arthroplasty: a systematic review and meta-analysis.

Science.gov (United States)

Lewis, G N; Rice, D A; McNair, P J; Kluger, M

2015-04-01

Several studies have identified clinical, psychosocial, patient characteristic, and perioperative variables that are associated with persistent postsurgical pain; however, the relative effect of these variables has yet to be quantified. The aim of the study was to provide a systematic review and meta-analysis of predictor variables associated with persistent pain after total knee arthroplasty (TKA). Included studies were required to measure predictor variables prior to or at the time of surgery, include a pain outcome measure at least 3 months post-TKA, and include a statistical analysis of the effect of the predictor variable(s) on the outcome measure. Counts were undertaken of the number of times each predictor was analysed and the number of times it was found to have a significant relationship with persistent pain. Separate meta-analyses were performed to determine the effect size of each predictor on persistent pain. Outcomes from studies implementing uni- and multivariable statistical models were analysed separately. Thirty-two studies involving almost 30 000 patients were included in the review. Preoperative pain was the predictor that most commonly demonstrated a significant relationship with persistent pain across uni- and multivariable analyses. In the meta-analyses of data from univariate models, the largest effect sizes were found for: other pain sites, catastrophizing, and depression. For data from multivariate models, significant effects were evident for: catastrophizing, preoperative pain, mental health, and comorbidities. Catastrophizing, mental health, preoperative knee pain, and pain at other sites are the strongest independent predictors of persistent pain after TKA. © The Author 2014. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

RS-WebPredictor

DEFF Research Database (Denmark)

Zaretzki, J.; Bergeron, C.; Huang, T.-W.

2013-01-01

Regioselectivity-WebPredictor (RS-WebPredictor) is a server that predicts isozyme-specific cytochrome P450 (CYP)-mediated sites of metabolism (SOMs) on drug-like molecules. Predictions may be made for the promiscuous 2C9, 2D6 and 3A4 CYP isozymes, as well as CYPs 1A2, 2A6, 2B6, 2C8, 2C19 and 2E1....... RS-WebPredictor is the first freely accessible server that predicts the regioselectivity of the last six isozymes. Server execution time is fast, taking on average 2s to encode a submitted molecule and 1s to apply a given model, allowing for high-throughput use in lead optimization projects.......Availability: RS-WebPredictor is accessible for free use at http://reccr.chem.rpi.edu/ Software/RS-WebPredictor....

Cognitive predictors of children's development in mathematics achievement: A latent growth modeling approach.

Science.gov (United States)

Xenidou-Dervou, Iro; Van Luit, Johannes E H; Kroesbergen, Evelyn H; Friso-van den Bos, Ilona; Jonkman, Lisa M; van der Schoot, Menno; van Lieshout, Ernest C D M

2018-04-24

Research has identified various domain-general and domain-specific cognitive abilities as predictors of children's individual differences in mathematics achievement. However, research into the predictors of children's individual growth rates, namely between-person differences in within-person change in mathematics achievement is scarce. We assessed 334 children's domain-general and mathematics-specific early cognitive abilities and their general mathematics achievement longitudinally across four time-points within the first and second grades of primary school. As expected, a constellation of multiple cognitive abilities contributed to the children's starting level of mathematical success. Specifically, latent growth modeling revealed that WM abilities, IQ, counting skills, nonsymbolic and symbolic approximate arithmetic and comparison skills explained individual differences in the children's initial status on a curriculum-based general mathematics achievement test. Surprisingly, however, only one out of all the assessed cognitive abilities was a unique predictor of the children's individual growth rates in mathematics achievement: their performance in the symbolic approximate addition task. In this task, children were asked to estimate the sum of two large numbers and decide if this estimated sum was smaller or larger compared to a third number. Our findings demonstrate the importance of multiple domain-general and mathematics-specific cognitive skills for identifying children at risk of struggling with mathematics and highlight the significance of early approximate arithmetic skills for the development of one's mathematical success. We argue the need for more research focus on explaining children's individual growth rates in mathematics achievement. © 2018 John Wiley & Sons Ltd.

Adaptive rival penalized competitive learning and combined linear predictor model for financial forecast and investment.

Science.gov (United States)

Cheung, Y M; Leung, W M; Xu, L

1997-01-01

We propose a prediction model called Rival Penalized Competitive Learning (RPCL) and Combined Linear Predictor method (CLP), which involves a set of local linear predictors such that a prediction is made by the combination of some activated predictors through a gating network (Xu et al., 1994). Furthermore, we present its improved variant named Adaptive RPCL-CLP that includes an adaptive learning mechanism as well as a data pre-and-post processing scheme. We compare them with some existing models by demonstrating their performance on two real-world financial time series--a China stock price and an exchange-rate series of US Dollar (USD) versus Deutschmark (DEM). Experiments have shown that Adaptive RPCL-CLP not only outperforms the other approaches with the smallest prediction error and training costs, but also brings in considerable high profits in the trading simulation of foreign exchange market.

Electricity curtailment behaviors in Greek households: Different behaviors, different predictors

International Nuclear Information System (INIS)

Botetzagias, Iosif; Malesios, Chrisovaladis; Poulou, Dimitra

2014-01-01

Highlights: • We study the self-reported energy (electricity) curtailment behaviors of Greek households (N=285). • We find that the curtailment behaviors are distinct and should be studied/analyzed separately. • ‘Age’, ‘Gender’ and ‘Perceived Behavioral Control’ are statistically significant predictors of most behaviors. • The demographic/structural and the psychological predictors contribute significantly explain the variance of the behaviors. • The cluster of moral predictors does not contribute statistically significantly to the explained variance. - Abstract: This paper argues that electricity ‘curtailment’ behaviors (i.e. frequent and/or low cost or free energy saving behaviors) in households are distinct from one another and they thus should be analyzed and promoted. We test this claim with data from telephone interviews with Greek households in the capital city of Athens (N=285), analyzing the impact of a number of demographical/structural, psychological (based on the Theory of Planned Behavior) and moral (based on norms’ activation) predictors though hierarchical binary logistic regression modeling. We find that that each electricity curtailment behavior depends on a different mix of predictors with ‘Age’, ‘Gender’ and ‘Perceived Behavioral Control’ being statistically significant for most behaviors. Overall, the psychological and the demographical/structural clusters of variables substantially contribute to the explained variance of electricity curtailment behaviors. The moral cluster's contribution is not statistically significant since moral concerns are largely interwoven in the psychological constructs

Prevalence and predictors of clinically significant depressive symptoms among Chinese and Malawian children: a cross-cultural comparative cross-sectional study.

Science.gov (United States)

Zgambo, Maggie; Kalembo, Fatch Welcome; Wang, Honghong; He, Guoping; Chen, Sanmei

2014-08-14

Multicultural comparative studies have recently increased scientific knowledge base regarding the mental health of diverse populations. This cross-cultural study was cross-sectionally designed to assess differences in the prevalence and predictors of clinically significant depressive symptoms between Chinese and Malawian children. A total of 478 children (237 Chinese and 241 Malawians) were randomly recruited in the study. The participants completed a Children Depression Inventory in the dimensions of Negative Mood, Interpersonal Problems, Ineffectiveness, Anhedonia, and Negative Self- Esteem. They further provided demographic and family structure information. Data were analyzed by Student's t-test, Chi-square test, and logistic regression. The prevalence of clinically significant depressive symptoms was 16% and 12.4% for Chinese and Malawian study participants, respectively. Multivariate logistic regression analysis showed that fighting among siblings (adjusted odds ratio [aOR] = 4.1, 95% CI, 3.5-5.9), fighting among children and parents (aOR = 7.7, 95% CI, 4.6-9.8) and living with father only (aOR = 4.1, 95% CI, 3.4-6.7) were significant predictors of clinically significant depressive symptoms among Chinese study participants. On the other hand, clinically significant depressive symptoms were predicted by employment status of a mom only among Malawian study participants (aOR = 3.0, 95% CI, 2.3-5.9). We conclude that diverse cultures affect children's mental health differently and this cluster of children has a noticeable amount of depressive symptoms that in the least requires further diagnosis and preventive measures.

Predictors of relationship power among drug-involved women.

Science.gov (United States)

Campbell, Aimee N C; Tross, Susan; Hu, Mei-chen; Pavlicova, Martina; Nunes, Edward V

2012-08-01

Gender-based relationship power is frequently linked to women's capacity to reduce sexual risk behaviors. This study offers an exploration of predictors of relationship power, as measured by the multidimensional and theoretically grounded sexual relationship power scale, among women in outpatient substance abuse treatment. Linear models were used to test nine predictors (age, race/ethnicity, education, time in treatment, economic dependence, substance use, sexual concurrency, partner abuse, and sex role orientation) of relationship power among 513 women participating in a multi-site HIV risk reduction intervention study. Significant predictors of relationship control included having a non-abusive male partner, only one male partner, and endorsing traditional masculine (or both masculine and feminine) sex role attributes. Predictors of decision-making dominance were interrelated, with substance use × partner abuse and age × sex role orientation interactions. Results contribute to the understanding of factors which may influence relationship power and to their potential role in HIV sexual risk reduction interventions.

Modeling Daily Rainfall Conditional on Atmospheric Predictors: An application to Western Greece

Science.gov (United States)

Langousis, Andreas; Kaleris, Vassilios

2013-04-01

Due to its intermittent and highly variable character, daily precipitation is the least well reproduced hydrologic variable by both General Circulation Models (GCMs) and Limited Area Models (LAMs). To that extent, several statistical procedures (usually referred to as downscaling schemes) have been suggested to generate synthetic rainfall time series conditional on predictor variables that are descriptive of the atmospheric circulation at the mesoscale. In addition to be more accurately simulated by GCMs and LAMs, large-scale atmospheric predictors are important indicators of the local weather. Currently used downscaling methods simulate rainfall series using either stable statistical relationships (usually referred to as transfer functions) between certain characteristics of the rainfall process and mesoscale atmospheric predictor variables, or simple stochastic schemes (e.g. properly transformed autoregressive models) with parameters that depend on the large-scale atmospheric conditions. The latter are determined by classifying large-scale circulation patterns into broad categories of weather states, using empirical or theoretically based classification schemes, and modeled by resampling from those categories; a process usually referred to as weather generation. In this work we propose a statistical framework to generate synthetic rainfall timeseries at a daily level, conditional on large scale atmospheric predictors. The latter include the mean sea level pressure (MSLP), the magnitude and direction of upper level geostrophic winds, and the 500 hPa geopotential height, relative vorticity and divergence. The suggested framework operates in continuous time, avoiding the use of transfer functions, and weather classification schemes. The suggested downscaling approach is validated using atmospheric data from the ERA-Interim archive (see http://www.ecmwf.int/research/era/do/get/index), and daily rainfall data from Western Greece, for the 14-year period from 01 October

Personality Traits as Prospective Predictors of Suicide Attempts

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Yen, Shirley; Shea, M. Tracie; Sanislow, Charles A.; Skodol, Andrew E.; Grilo, Carlos M.; Edelen, Maria Orlando; Stout, Robert L.; Morey, Leslie C.; Zanarini, Mary C.; Markowitz, John C.; McGlashan, Thomas H.; Daversa, Maria T.; Gunderson, John G.

2009-01-01

OBJECTIVE To examine higher order personality factors of negative affectivity (NA) and disinhibition (DIS), as well as lower order facets of impulsivity, as prospective predictors of suicide attempts in a predominantly personality disordered (PD) sample. METHOD Data were analyzed from 701 participants of the Collaborative Longitudinal Personality Disorders Study (CLPS) with available follow-up data for up to 7 years. Cox proportional hazards regression analyses was used to examine NA and DIS, and facets of impulsivity (e.g., urgency, lack of perseverance, lack of premeditation, and sensation seeking), as prospective predictors of suicide attempts. RESULTS NA, DIS, and all facets of impulsivity except for sensation seeking were significant in univariate analyses. In multivariate models which included sex, childhood sexual abuse (CSA), course of major depressive disorder (MDD) and substance use disorders (SUD), only NA and lack of premeditation remained significant in predicting suicide attempts. Disinhibition and the remaining impulsivity facets were not significant. CONCLUSION Negative affectivity emerged as a stronger and more robust predictor of suicide attempts than disinhibition and impulsivity, and warrants greater attention in suicide risk assessment. Distinguishing between facets of impulsivity is important for clinical risk assessment. PMID:19298413

A Nonlinear Dynamic Inversion Predictor-Based Model Reference Adaptive Controller for a Generic Transport Model

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Campbell, Stefan F.; Kaneshige, John T.

2010-01-01

Presented here is a Predictor-Based Model Reference Adaptive Control (PMRAC) architecture for a generic transport aircraft. At its core, this architecture features a three-axis, non-linear, dynamic-inversion controller. Command inputs for this baseline controller are provided by pilot roll-rate, pitch-rate, and sideslip commands. This paper will first thoroughly present the baseline controller followed by a description of the PMRAC adaptive augmentation to this control system. Results are presented via a full-scale, nonlinear simulation of NASA s Generic Transport Model (GTM).

A simplified multi-particle model for lithium ion batteries via a predictor-corrector strategy and quasi-linearization

International Nuclear Information System (INIS)

Li, Xiaoyu; Fan, Guodong; Rizzoni, Giorgio; Canova, Marcello; Zhu, Chunbo; Wei, Guo

2016-01-01

The design of a simplified yet accurate physics-based battery model enables researchers to accelerate the processes of the battery design, aging analysis and remaining useful life prediction. In order to reduce the computational complexity of the Pseudo Two-Dimensional mathematical model without sacrificing the accuracy, this paper proposes a simplified multi-particle model via a predictor-corrector strategy and quasi-linearization. In this model, a predictor-corrector strategy is used for updating two internal states, especially used for solving the electrolyte concentration approximation to reduce the computational complexity and reserve a high accuracy of the approximation. Quasi-linearization is applied to the approximations of the Butler-Volmer kinetics equation and the pore wall flux distribution to predict the non-uniform electrochemical reaction effects without using any nonlinear iterative solver. Simulation and experimental results show that the isothermal model and the model coupled with thermal behavior are greatly improve the computational efficiency with almost no loss of accuracy. - Highlights: • A simplified multi-particle model with high accuracy and computation efficiency is proposed. • The electrolyte concentration is solved based on a predictor-corrector strategy. • The non-uniform electrochemical reaction is solved based on quasi-linearization. • The model is verified by simulations and experiments at various operating conditions.

Predictors of intention to smoke among junior high school students in Shanghai, China: an empirical test of the information-motivation-behavioral skills (IMB) model.

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Zhu, Chendi; Cai, Yong; Ma, Jin; Li, Na; Zhu, Jingfen; He, Yaping; Redmon, Pamela; Qiao, Yun

2013-01-01

Adolescent smoking is a worldwide problem that is particularly severe in low- and middle-income countries. Many endogenous and environmental factors affect the intention to smoke, so a comprehensive model is needed to understand the significance and relationship of predictors. The study aimed to test the associations among information-motivation-behavioral skills (IMB) model constructs as predictors of intention to smoke in junior high school students in Shanghai, China. We conducted a cross-sectional study of 16,500 junior high school students in Shanghai, China. Data on tobacco-related information, motivation, behavioral skills, and behaviors were collected from students. Structural equation model (SEM) was used to assess the IMB model. The mean age of participants was 13.8 years old (standard deviation = 1.02; range 11-17). The experimental smoking rate among junior high school students was 6.6% and 8.7% of the participants expected that they would be smokers in 5 years. The IMB model provided acceptable fit to the data (comparative fit index = 0.984, root mean square error of approximation = 0.04). Intention to smoke was predicted by behavioral skills (β = 0.670, P motivation (β = 0.095, Pschool students. The IMB model provides a good understanding of the predictors of intention to smoke and it suggests future interventions among junior high school students should focus on improving motivation and behavioral skills.

[Psychosocial factors as predictors of atherosclerosis and cardiovascular events: contribution from animal models].

Science.gov (United States)

Alboni, Paolo; Alboni, Marco

2006-11-01

Conventional risk factors (abnormal lipids, hypertension, etc.) are independent predictors of atherosclerosis and cardiovascular events; however, these factors are not specific since about half patients with acute myocardial infarction paradoxically result at low cardiovascular risk. Recent prospective studies provide convincing evidence that some psychosocial factors are independent predictors of atherosclerosis and cardiovascular events, as well. Psychosocial factors that promote atherosclerosis can be divided into two general categories: chronic stressors, including social isolation/low social support and work stress (subordination without job control) and emotional factors, including affective disorders such as depression, severe anxiety and hostility/anger. The emotional factors, such as the chronic stressors, activate the biological mechanisms of chronic stress: increased activity of the hypothalamic-pituitary-adrenal axis, sympathetic system and inflammation processes, which have atherogenic effects, and an increase in blood coagulation. In spite of the amount of published data, psychosocial factors receive little attention in the medical setting. About 30 years ago, Kuller defined the criteria for a causal relation between a risk factor and atherosclerosis and cardiac events. The first of these criteria states that experimental research should demonstrate that any new factor would increase the extent of atherosclerosis or its complications in suitable animal models. We carried out a bibliographic research in order to investigate whether the results of the studies dealing with animal examination and experimentation support the psychosocial factors as predictors of atherosclerosis. Contributions related to some of the psychosocial factors such as social isolation, subordination and hostility/anger have been found. In these studies atherosclerotic extension has been evaluated at necroscopy; however, the incidence of cardiovascular events has not been

The Glasgow Prognostic Score as a significant predictor of diffuse large B cell lymphoma treated with R-CHOP in China.

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Li, Xiaoyang; Zhang, Yunxiang; Zhao, Weili; Liu, Zhao; Shen, Yang; Li, Junmin; Shen, Zhixiang

2015-01-01

The Glasgow Prognostic Score (GPS) incorporates C-reactive protein and albumin as clinically useful markers of tumor behavior and shows significant prognostic value in several types of solid tumors. The accuracy of the GPS in predicting outcomes in diffuse large B cell lymphoma (DLBCL) remains unknown. We performed this study to evaluate the prognostic significance of the GPS in DLBCL in China. We retrospectively analyzed 160 patients with newly diagnosed DLBCL at the Shanghai Ruijin Hospital (China). The prognostic value of the GPS was evaluated and compared with that of the International Prognostic Index (IPI) and immunohistochemical subtyping. The GPS was defined as follows: GPS-0, C-reactive protein (CRP) ≤10 mg/L and albumin ≥35 g/L; GPS-1, CRP >10 mg/L or albumin L; and GPS-2, CRP >10 mg/L and albumin L. Patients with lower GPS tended to have better outcomes including progression-free survival (PFS, P GPS and high IPI score were independent adverse predictors of OS. Similar to several other tumors, GPS is a reliable predictor of survival outcomes in DLBCL patients treated with R-CHOP therapy. Inflammatory responses are implicated in the progression and survival of patients with DLBCL.

Modelo estructural predictor de la salud mental y física en mujeres A structural equation model for predictors of mental and physical health in women

Directory of Open Access Journals (Sweden)

Mónica Teresa González Ramírez

2008-02-01

Full Text Available OBJETIVO: Valorar la capacidad predictora del estrés, el apoyo social y la autoestima respecto de la salud mental y física del individuo mediante ecuaciones estructurales, integrando modelos parciales estimados anteriormente, lo que permite simplificar los efectos entre las variables. MÉTODOS: La muestra estudiada abarcó 283 mujeres con hijos. Todas las participantes residían en el municipio de General Escobedo, estado de Nuevo León, México. Las encuestas se realizaron en el segundo semestre de 2003, en los domicilios, utilizando cuestionarios de autoevaluación para valorar cada una de las variables incluidas en el modelo. Cada participante respondió a los cuestionarios en una sola sesión. Los resultados se analizaron con el programa AMOS 5.0, empleando el método de máxima verosimilitud, comúnmente utilizado en los modelos de ecuaciones estructurales. RESULTADOS: Los resultados obtenidos indican un ajuste aceptable en el modelo propuesto (ji2/gl = 3,03, GFI (índice de bondad del ajuste = 0,894, AGFI (índice de bondad del ajuste corregido = 0,848, RMSEA (error de aproximación cuadrático medio = 0,08, IFI (índice de ajuste incremental = 0,910. La varianza explicada es del 31,9% respecto del estrés, del 27,4% respecto de la salud física y del 72,1% respecto de la salud mental. CONCLUSIONES: El apoyo social y la autoestima son predictores del estrés; la edad y el estrés, predictores de la salud física; y el estrés, la autoestima y la salud física, predictores de la salud mental.OBJECTIVE: To measure the extent to which stress, social support, and self-esteem are predictors of an individual's mental and physical health. Structural equations were integrated with previously-estimated partial models, which simplify the relationships among variables. METHODS: The study sample included 283 women with children. All of the participants resided in the municipality of General Escobedo, state of Nuevo León, Mexico. The surveys were

Predictors of non- hookah smoking among high-school students based on prototype/willingness model.

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Abedini, Sedigheh; MorowatiSharifabad, MohammadAli; Chaleshgar Kordasiabi, Mosharafeh; Ghanbarnejad, Amin

2014-01-01

The aim of the study was to determine predictors of refraining from hookah smoking among high-school students in Bandar Abbas, southern Iran based on Prototype/Willingness model. This cross- sectional with analytic approach was performed on 240 high-school students selected by a cluster random sampling. The data of demographic and Prototype-Willingness Model constructs were acquired via a self-administrated questionnaire. Data were analyzed by mean, frequency, correlation, liner and logistic regression statistical tests. Statistically significant determinants of the intention to refrain from hookah smoking were subjective norms, willingness, and attitude. Regression model indicated that the three items together explained 46.9% of the non-smoking hookah intention variance. Attitude and subjective norms predicted 36.0% of the non-smoking hookah intention variance. There was a significant relationship between the participants' negative prototype about the hookah smokers and the willingness to avoid from hookah smoking (P=0.002). Also willingness predicted non-smoking hookah better than the intention (P<0.001). Deigning intervention to increase negative prototype about the hookah smokers and reducing situations and conditions which facilitate hookah smoking, such as easy access to tobacco products in the cafés, beaches can be useful results among adolescents to hookah smoking prevention.

Attitudes of prejudice as a predictor of cultural competence among baccalaureate nursing students.

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Dunagan, Pamela B; Kimble, Laura P; Gunby, Susan Sweat; Andrews, Margaret M

2014-06-01

The purpose of this study was to explore the relationship between attitudes of prejudice and cultural competence among nursing students. Using a mixed-methods design, a convenience sample of students (N = 129) currently enrolled in a baccalaureate nursing program was recruited via Web networking. Data regarding attitudes of prejudice, cultural competence, prior cultural experience, and integration of cultural competence were obtained via a Web-based survey. Multiple linear regression was used to predict cultural knowledge, attitudes, and consciousness. Although all three regression models were statistically significant, the significant predictors varied within each model. Greater prejudice was a significant predictor of less culturally competent attitudes toward providing nursing care. Existing prejudice among nursing students needs to be addressed to help promote positive cultural attitudes and, ultimately, cultural competent nursing care.

Modeling soil organic carbon with Quantile Regression: Dissecting predictors' effects on carbon stocks

KAUST Repository

Lombardo, Luigi

2017-08-13

Soil Organic Carbon (SOC) estimation is crucial to manage both natural and anthropic ecosystems and has recently been put under the magnifying glass after the Paris agreement 2016 due to its relationship with greenhouse gas. Statistical applications have dominated the SOC stock mapping at regional scale so far. However, the community has hardly ever attempted to implement Quantile Regression (QR) to spatially predict the SOC distribution. In this contribution, we test QR to estimate SOC stock (0-30 $cm$ depth) in the agricultural areas of a highly variable semi-arid region (Sicily, Italy, around 25,000 $km2$) by using topographic and remotely sensed predictors. We also compare the results with those from available SOC stock measurement. The QR models produced robust performances and allowed to recognize dominant effects among the predictors with respect to the considered quantile. This information, currently lacking, suggests that QR can discern predictor influences on SOC stock at specific sub-domains of each predictors. In this work, the predictive map generated at the median shows lower errors than those of the Joint Research Centre and International Soil Reference, and Information Centre benchmarks. The results suggest the use of QR as a comprehensive and effective method to map SOC using legacy data in agro-ecosystems. The R code scripted in this study for QR is included.

Parenting Style and Behavior as Longitudinal Predictors of Adolescent Alcohol Use.

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Minaie, Matin Ghayour; Hui, Ka Kit; Leung, Rachel K; Toumbourou, John W; King, Ross M

2015-09-01

Adolescent alcohol use is a serious problem in Australia and other nations. Longitudinal data on family predictors are valuable to guide parental education efforts. The present study tested Baumrind's proposal that parenting styles are direct predictors of adolescent alcohol use. Latent class modeling was used to investigate adolescent perceptions of parenting styles and multivariate regression to examine their predictive effect on the development of adolescent alcohol use. The data set comprised 2,081 secondary school students (55.9% female) from metropolitan Melbourne, Australia, who completed three waves of annual longitudinal data starting in 2004. Baumrind's parenting styles were significant predictors in unadjusted analyses, but these effects were not maintained in multivariate models that also included parenting behavior dimensions. Family influences on the development of adolescent alcohol use appear to operate more directly through specific family management behaviors rather than through more global parenting styles.

Predictors of chain acquisition among independent dialysis facilities.

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Pozniak, Alyssa S; Hirth, Richard A; Banaszak-Holl, Jane; Wheeler, John R C

2010-04-01

To determine the predictors of chain acquisition among independent dialysis providers. Retrospective facility-level data combined from CMS Cost Reports, Medical Evidence Forms, Annual Facility Surveys, and claims for 1996-2003. Independent dialysis facilities' probability of acquisition by a dialysis chain (overall and by chain size) was estimated using a discrete time hazard rate model, controlling for financial and clinical performance, practice patterns, market factors, and other facility characteristics. The sample includes all U.S. freestanding dialysis facilities that report not being chain affiliated for at least 1 year between 1997 and 2003. Above-average costs and better quality outcomes are significant determinants of dialysis chain acquisition. Facilities in larger markets were more likely to be acquired by a chain. Furthermore, small dialysis chains have different acquisition strategies than large chains. Dialysis chains appear to employ a mix of turn-around and cream-skimming strategies. Poor financial health is a predictor of chain acquisition as in other health care sectors, but the increased likelihood of chain acquisition among higher quality facilities is unique to the dialysis industry. Significant differences among predictors of acquisition by small and large chains reinforce the importance of using a richer classification for chain status.

Predictors of handgrip strength among adults of a rural community in Malaysia.

Science.gov (United States)

Moy, Foong-Ming; Darus, Azlan; Hairi, Noran Naqiah

2015-03-01

Handgrip strength is useful for screening the nutritional status of adult population as it is strongly associated with physical disabilities and mortality. Therefore, we aimed to determine the predictors of handgrip strength among adults of a rural community in Malaysia using a cross-sectional study design with multistage sampling. All adults aged 30 years and older from 1250 households were invited to our study. Structured questionnaire on sociodemographic characteristics, medical history, occupation history, lifestyle practices, and measurements, including anthropometry and handgrip strength were taken. There were 2199 respondents with 55.2% females and majority were of Malay ethnicity. Their mean (standard deviation) age was 53.4 (13.2) years. The response rate for handgrip strength was 94.2%. Females had significantly lower handgrip strength than males (P < .05). In the multiple linear regression models, significant predictors of handgrip strength for males were age, height, job groups, and diabetes, while for females, the significant predictors were age, weight, height, and diabetes. © 2013 APJPH.

The baseline serum value of α-amylase is a significant predictor of distance running performance.

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Lippi, Giuseppe; Salvagno, Gian Luca; Danese, Elisa; Tarperi, Cantor; La Torre, Antonio; Guidi, Gian Cesare; Schena, Federico

2015-02-01

This study was planned to investigate whether serum α-amylase concentration may be associated with running performance, physiological characteristics and other clinical chemistry analytes in a large sample of recreational athletes undergoing distance running. Forty-three amateur runners successfully concluded a 21.1 km half-marathon at 75%-85% of their maximal oxygen uptake (VO2max). Blood was drawn during warm up and 15 min after conclusion of the run. After correction for body weight change, significant post-run increases were observed for serum values of alkaline phosphatase, alanine aminotransferase, aspartate aminotransferase, bilirubin, creatine kinase (CK), iron, lactate dehydrogenase (LDH), triglycerides, urea and uric acid, whereas the values of body weight, glomerular filtration rate, total and low density lipoprotein-cholesterol were significantly decreased. The concentration of serum α-amylase was unchanged. In univariate analysis, significant associations with running performance were found for gender, VO2max, training regimen and pre-run serum values of α-amylase, CK, glucose, high density lipoprotein-cholesterol, LDH, urea and uric acid. In multivariate analysis, only VO2max (p=0.042) and baseline α-amylase (p=0.021) remained significant predictors of running performance. The combination of these two variables predicted 71% of variance in running performance. The baseline concentration of serum α-amylase was positively correlated with variation of serum glucose during the trial (r=0.345; p=0.025) and negatively with capillary blood lactate at the end of the run (r=-0.352; p=0.021). We showed that the baseline serum α-amylase concentration significantly and independently predicts distance running performance in recreational runners.

Predictors of success after extracorporeal shock wave lithotripsy (ESWL) for renal calculi between 20-30 mm: a multivariate analysis model.

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El-Assmy, Ahmed; El-Nahas, Ahmed R; Abo-Elghar, Mohamed E; Eraky, Ibrahim; El-Kenawy, Mahmoud R; Sheir, Khaled Z

2006-03-23

The first-line management of renal stones between 20-30 mm remains controversial. The Extracorporeal Shock Wave Lithotripsy (ESWL) stone-free rates for such patient groups vary widely. The purpose of this study was to define factors that have a significant impact on the stone-free rate after ESWL in such controversial groups. Between January 1990 and January 2004, 594 patients with renal stones 20-30 mm in length underwent ESWL monotherapy. Stone surface area was measured for all stones. The results of treatment were evaluated after 3 months of follow-up. The stone-free rate was correlated with stone and patient characteristics using the Chi-square test; factors found to be significant were further analyzed using multivariate analysis. Repeat ESWL was needed in 56.9% of cases. Post-ESWL complications occurred in 5% of cases and post-ESWL secondary procedures were required in 5.9%. At 3-month follow-up, the overall stone-free rate was 77.2%. Using the Chi-square test, stone surface area, location, number, radiological renal picture, and congenital renal anomalies had a significant impact on the stone-free rate. Multivariate analysis excluded radiological renal picture from the logistic regression model while other factors maintained their statistically significant effect on success rate, indicating that they were independent predictors. A regression analysis model was designed to estimate the probability of stone-free status after ESWL. The sensitivity of the model was 97.4%, the specificity 90%, and the overall accuracy 95.6%. Stone surface area, location, number, and congenital renal anomalies are prognostic predictors determining stone clearance after ESWL of renal calculi of 20-30 mm. High probability of stone clearance is obtained with single stone ESWL in such controversial groups and can define patients who would need other treatment modality.

[Predictors of remission from major depressive disorder in secondary care].

Science.gov (United States)

Salvo, Lilian; Saldivia, Sandra; Parra, Carlos; Cifuentes, Manuel; Bustos, Claudio; Acevedo, Paola; Díaz, Marcela; Ormazabal, Mitza; Guerra, Ivonne; Navarrete, Nicol; Bravo, Verónica; Castro, Andrea

2017-12-01

Background The knowledge of predictive factors in depression should help to deal with the disease. Aim To assess potential predictors of remission of major depressive disorders (MDD) in secondary care and to propose a predictive model. Material and Methods A 12 month follow-up study was conducted in a sample of 112 outpatients at three psychiatric care centers of Chile, with baseline and quarterly assessments. Demographic, psychosocial, clinical and treatment factors as potential predictors, were assessed. A clinical interview with the checklist of DSM-IV diagnostic criteria, the Hamilton Depression Scale and the List of Threatening Experiences and Multidimensional Scale of Perceived Social Support were applied. Results The number of stressful events, perceived social support, baseline depression scores, melancholic features, time prior to beginning treatment at the secondary level and psychotherapeutic sessions were included in the model as predictors of remission. Sex, age, number of previous depressive episodes, psychiatric comorbidity and medical comorbidity were not significantly related with remission. Conclusions This model allows to predict depression score at six months with 70% of accuracy and the score at 12 months with 72% of accuracy.

Predictors of physical performance and functional ability in people 50+ with and without fibromyalgia.

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Jones, C Jessie; Rutledge, Dana N; Aquino, Jordan

2010-07-01

The purposes of this study were to determine whether people with and without fibromyalgia (FM) age 50 yr and above showed differences in physical performance and perceived functional ability and to determine whether age, gender, depression, and physical activity level altered the impact of FM status on these factors. Dependent variables included perceived function and 6 performance measures (multidimensional balance, aerobic endurance, overall functional mobility, lower body strength, and gait velocity-normal or fast). Independent (predictor) variables were FM status, age, gender, depression, and physical activity level. Results indicated significant differences between adults with and without FM on all physical-performance measures and perceived function. Linear-regression models showed that the contribution of significant predictors was in expected directions. All regression models were significant, accounting for 16-65% of variance in the dependent variables.

Predictors of initial weight loss among women with abdominal obesity: a path model using self-efficacy and health-promoting behaviour.

Science.gov (United States)

Choo, Jina; Kang, Hyuncheol

2015-05-01

To identify predictors of initial weight loss among women with abdominal obesity by using a path model. Successful weight loss in the initial stages of long-term weight management may promote weight loss maintenance. A longitudinal study design. Study participants were 75 women with abdominal obesity, who were enrolled in a 12-month Community-based Heart and Weight Management Trial and followed until a 6-month assessment. The Weight Efficacy Lifestyle, Exercise Self-Efficacy and Health Promoting Lifestyle Profile-II measured diet self-efficacy, exercise self-efficacy and health-promoting behaviour respectively. All endogenous and exogenous variables used in our path model were change variables from baseline to 6 months. Data were collected between May 2011-May 2012. Based on the path model, increases in both diet and exercise self-efficacy had significant effects on increases in health-promoting behaviour. Increases in diet self-efficacy had a significant indirect effect on initial weight loss via increases in health-promoting behaviour. Increases in health-promoting behaviour had a significant effect on initial weight loss. Among women with abdominal obesity, increased diet self-efficacy and health-promoting behaviour were predictors of initial weight loss. A mechanism by which increased diet self-efficacy predicts initial weight loss may be partially attributable to health-promoting behavioural change. However, more work is still needed to verify causality. Based on the current findings, intensive nursing strategies for increasing self-efficacy for weight control and health-promoting behaviour may be essential components for better weight loss in the initial stage of a weight management intervention. © 2015 John Wiley & Sons Ltd.

Discrimination, acculturation and other predictors of depression among pregnant Hispanic women.

Science.gov (United States)

Walker, Janiece L; Ruiz, R Jeanne; Chinn, Juanita J; Marti, Nathan; Ricks, Tiffany N

2012-01-01

The purpose of our study was to examine the effects of socioeconomic status, acculturative stress, discrimination, and marginalization as predictors of depression in pregnant Hispanic women. A prospective observational design was used. Central and Gulf coast areas of Texas in obstetrical offices. A convenience sample of 515 pregnant, low income, low medical risk, and self-identified Hispanic women who were between 22-24 weeks gestation was used to collect data. The predictor variables were socioeconomic status, discrimination, acculturative stress, and marginalization. The outcome variable was depression. Education, frequency of discrimination, age, and Anglo marginality were significant predictors of depressive symptoms in a linear regression model, F (6, 458) = 8.36, Pdiscrimination was the strongest positive predictor of increased depressive symptoms. It is important that health care providers further understand the impact that age and experiences of discrimination throughout the life course have on depressive symptoms during pregnancy.

A multiparametric magnetic resonance imaging-based risk model to determine the risk of significant prostate cancer prior to biopsy.

Science.gov (United States)

van Leeuwen, Pim J; Hayen, Andrew; Thompson, James E; Moses, Daniel; Shnier, Ron; Böhm, Maret; Abuodha, Magdaline; Haynes, Anne-Maree; Ting, Francis; Barentsz, Jelle; Roobol, Monique; Vass, Justin; Rasiah, Krishan; Delprado, Warick; Stricker, Phillip D

2017-12-01

To develop and externally validate a predictive model for detection of significant prostate cancer. Development of the model was based on a prospective cohort including 393 men who underwent multiparametric magnetic resonance imaging (mpMRI) before biopsy. External validity of the model was then examined retrospectively in 198 men from a separate institution whom underwent mpMRI followed by biopsy for abnormal prostate-specific antigen (PSA) level or digital rectal examination (DRE). A model was developed with age, PSA level, DRE, prostate volume, previous biopsy, and Prostate Imaging Reporting and Data System (PIRADS) score, as predictors for significant prostate cancer (Gleason 7 with >5% grade 4, ≥20% cores positive or ≥7 mm of cancer in any core). Probability was studied via logistic regression. Discriminatory performance was quantified by concordance statistics and internally validated with bootstrap resampling. In all, 393 men had complete data and 149 (37.9%) had significant prostate cancer. While the variable model had good accuracy in predicting significant prostate cancer, area under the curve (AUC) of 0.80, the advanced model (incorporating mpMRI) had a significantly higher AUC of 0.88 (P prostate cancer. Individualised risk assessment of significant prostate cancer using a predictive model that incorporates mpMRI PIRADS score and clinical data allows a considerable reduction in unnecessary biopsies and reduction of the risk of over-detection of insignificant prostate cancer at the cost of a very small increase in the number of significant cancers missed. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

Predictors of relationship satisfaction for men and women

Directory of Open Access Journals (Sweden)

Gaja Zager Kocjan

2014-06-01

Full Text Available The present study was designed to examine the differences between genders in the perception of romantic relationship as well as in aspects of the relationship that are important for their relationship satisfaction. However, previous studies rarely report significant differences between genders in various predictors of the relationship satisfaction. In our study, similar conclusions were obtained. Relationship satisfaction was predicted with attachment, self-esteem, and partner's social support. The study included 200 participants (63.5% of women who completed the following questionnaires: Experience in Close Relationships – Revised Short ECR-RS, Quality of Relationship Inventory QRI, Relationship Satisfaction Scale RSS, and a single-item self-esteem measure. For both genders, significant positive predictor of their relationship satisfaction was self-esteem, while avoidance, anxiety, and conflict in the relationship were significant negative predictors. There were no significant differences between genders. These findings are consistent with the findings of previous studies, which rarely report significant gender differences in the various predictors.

Prevalence and clinical significance of nonorgan specific antibodies in patients with autoimmune thyroiditis as predictor markers for rheumatic diseases.

Science.gov (United States)

Elnady, Basant M; Kamal, Naglaa M; Shaker, Raneyah H M; Soliman, Amal F; Hasan, Waleed A; Alghamdi, Hamed A; Algethami, Mohammed M; Jajah, Mohamed Bilal

2016-09-01

Autoimmune diseases are considered the 3rd leading cause of morbidity and mortality in the industrialized countries. Autoimmune thyroid diseases (ATDs) are associated with high prevalence of nonorgan-specific autoantibodies, such as antinuclear antibodies (ANA), antidouble-stranded deoxyribonucleic acid (anti-dsDNA), antiextractable-nuclear antigens (anti-ENAs), rheumatoid factor (RF), and anticyclic-citrullinated peptides (anti-CCP) whose clinical significance is unknown.We aimed to assess the prevalence of various nonorgan-specific autoantibodies in patients with ATD, and to investigate the possible association between these autoantibodies and occurrence of rheumatic diseases and, if these autoantibodies could be considered as predictor markers for autoimmune rheumatic diseases in the future.This study had 2 phases: phase 1; in which 61 ATD patients free from rheumatic manifestations were assessed for the presence of these nonorgan-specific autoantibodies against healthy 61 control group, followed by 2nd phase longitudinal clinical follow-up in which cases are monitored systematically to establish occurrence and progression of any rheumatic disease in association to these autoantibodies with its influences and prognosis.Regarding ATD patients, ANA, anti-dsDNA, Anti-ENA, and RF were present in a percentage of (50.8%), (18%), (21.3%), and (34.4%), respectively, with statistically significance difference (P rheumatic diseases, over 2 years follow-up. It was obvious that those with positive anti-dsDNA had higher risk (2.45 times) to develop rheumatic diseases than those without. There was a statistically significant positive linear relationship between occurrence of disease in months and (age, anti-dsDNA, anti-CCP, RF, and duration of thyroiditis). Anti-dsDNA and RF are the most significant predictors (P rheumatic diseases than previously thought. Anti-dsDNA, RF, and anti-CCP antibodies may be used as predictive screening markers of systemic lupus erythematosus

Predictor-Year Subspace Clustering Based Ensemble Prediction of Indian Summer Monsoon

Directory of Open Access Journals (Sweden)

Moumita Saha

2016-01-01

Full Text Available Forecasting the Indian summer monsoon is a challenging task due to its complex and nonlinear behavior. A large number of global climatic variables with varying interaction patterns over years influence monsoon. Various statistical and neural prediction models have been proposed for forecasting monsoon, but many of them fail to capture variability over years. The skill of predictor variables of monsoon also evolves over time. In this article, we propose a joint-clustering of monsoon years and predictors for understanding and predicting the monsoon. This is achieved by subspace clustering algorithm. It groups the years based on prevailing global climatic condition using statistical clustering technique and subsequently for each such group it identifies significant climatic predictor variables which assist in better prediction. Prediction model is designed to frame individual cluster using random forest of regression tree. Prediction of aggregate and regional monsoon is attempted. Mean absolute error of 5.2% is obtained for forecasting aggregate Indian summer monsoon. Errors in predicting the regional monsoons are also comparable in comparison to the high variation of regional precipitation. Proposed joint-clustering based ensemble model is observed to be superior to existing monsoon prediction models and it also surpasses general nonclustering based prediction models.

Body image flexibility: A predictor and moderator of outcome in transdiagnostic outpatient eating disorder treatment.

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Pellizzer, Mia L; Waller, Glenn; Wade, Tracey D

2018-04-01

Predictors of attrition and predictors and moderators of outcome were explored in a transdiagnostic sample of patients who received ten-session cognitive behavioral therapy (CBT-T) for nonunderweight eating disorders. Body image flexibility, a protective positive body image construct, was hypothesized to be a significant moderator. Data from two case series were combined to form a sample of 78 participants who received CBT-T. Baseline measures of body image, negative affect, personality, and motivation (readiness to change and self-efficacy) were included as potential predictors. Global eating disorder psychopathology at each assessment point (baseline, mid- and post-treatment, 1- and 3-month follow-up) was the outcome variable. Predictors of attrition were assessed using logistic regression, and multilevel modeling was applied for predictors and moderators of outcome. Body image flexibility emerged as the strongest predictor and moderator of global eating disorder psychopathology, followed by body image avoidance. Body checking, negative affect, personality beliefs, and self-efficacy were significant predictors of global eating disorder psychopathology. Higher body image flexibility predicted lower global eating disorder psychopathology at every assessment point. Further research is required to replicate findings and explore the benefit of focusing on positive body image in treatment. © 2018 Wiley Periodicals, Inc.

Predictors of monoterpene exposure in the Danish furniture industry.

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Hagström, Katja; Jacobsen, Gitte; Sigsgaard, Torben; Schaumburg, Inger; Erlandsen, Mogens; Schlunssen, Vivi

2012-04-01

Individuals who work with pine in the furniture industry may be exposed to monoterpenes, the most abundant of which are α-pinene, β-pinene, and Δ(3)-carene. Monoterpenes are suspected to cause dermatitis and to harm the respiratory system. An understanding of the predictors of monoterpene exposure is therefore important in preventing these adverse effects. These predictors may include general characteristics of the work environment and specific work operations. We sought to assess the extent to which workers are exposed to monoterpenes and to identify possible predictors of monoterpene exposure in the pine furniture industry in Denmark. Passive measurements of the levels of selected monoterpenes (α-pinene, β-pinene, and Δ(3)-carene) were performed on 161 subjects from 17 pine furniture factories in Viborg County, Denmark; one sample was acquired from each worker. Additionally, wood dust samples were collected from 145 workers. Data on potential predictors of exposure were acquired over the course of the day on which the exposure measurements were recorded and could be assigned to one of four hierarchic ordered levels: worker, machine, department, and factory. In addition to univariate analyses, a mixed model was used to account for imbalances within the data and random variation with each of the hierarchically ordered levels. The geometric mean (GM) monoterpene content observed over the 161 measurements was 7.8 mg m(-3) [geometric standard deviation (GSD): 2.4]; the GM wood dust level over 145 measurements was 0.58 mg m(-3) (GSD: 1.49). None of the measured samples exceeded the occupational exposure limit for terpenes in Denmark (25 ppm, 150 mg m(-3)). In the univariate analyses, half of the predictors tested were found to be significant; the multivariate model indicated that only three of the potential predictors were significant. These were the recirculation of air in rooms used for the processing of wood (a factory level predictor), the presence of a

Predictors of life disability in trichotillomania.

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Tung, Esther S; Flessner, Christopher A; Grant, Jon E; Keuthen, Nancy J

2015-01-01

Limited research has investigated disability and functional impairment in trichotillomania (TTM) subjects. This study examined the relationships between hair pulling (HP) style and severity and disability while controlling for mood severity. Disability was measured in individual life areas (work, social, and family/home life) instead of as a total disability score as in previous studies. One hundred fifty three adult hair pullers completed several structured interviews and self-report instruments. HP style and severity, as well as depression, anxiety, and stress were correlated with work, social, and family/home life impairment on the Sheehan Disability Scale (SDS). Multiple regression analyses were performed to determine significant predictors of life impairment. Depressive severity was a significant predictor for all SDS life areas. In addition, interference/avoidance associated with HP was a predictor for work and social life disability. Distress from HP was a significant predictor of social and family/home life disability. Focused HP score and anxiety were significant predictors of family/home life disability. As expected, depression in hair pullers predicted disability across life domains. Avoiding work and social situations can seriously impair functioning in those life domains. Severity of distress and worry about HP may be most elevated in social situations with friends and family and thus predict impairment in those areas. Finally, since HP often occurs at home, time spent in focused hair pulling would have a greater negative impact on family and home responsibilities than social and work life. Copyright © 2014 Elsevier Inc. All rights reserved.

Inflammatory markers as predictors of depression and anxiety in adolescents: Statistical model building with component-wise gradient boosting.

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Walss-Bass, Consuelo; Suchting, Robert; Olvera, Rene L; Williamson, Douglas E

2018-07-01

Immune system abnormalities have been repeatedly observed in several psychiatric disorders, including severe depression and anxiety. However, whether specific immune mediators play an early role in the etiopathogenesis of these disorders remains unknown. In a longitudinal design, component-wise gradient boosting was used to build models of depression, assessed by the Mood-Feelings Questionnaire-Child (MFQC), and anxiety, assessed by the Screen for Child Anxiety Related Emotional Disorders (SCARED) in 254 adolescents from a large set of candidate predictors, including sex, race, 39 inflammatory proteins, and the interactions between those proteins and time. Each model was reduced via backward elimination to maximize parsimony and generalizability. Component-wise gradient boosting and model reduction found that female sex, growth- regulated oncogene (GRO), and transforming growth factor alpha (TGF-alpha) predicted depression, while female sex predicted anxiety. Differential onset of puberty as well as a lack of control for menstrual cycle may also have been responsible for differences between males and females in the present study. In addition, investigation of all possible nonlinear relationships between the predictors and the outcomes was beyond the computational capacity and scope of the present research. This study highlights the need for novel statistical modeling to identify reliable biological predictors of aberrant psychological behavior. Copyright © 2018 Elsevier B.V. All rights reserved.

Predictor variable resolution governs modeled soil types

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Soil mapping identifies different soil types by compressing a unique suite of spatial patterns and processes across multiple spatial scales. It can be quite difficult to quantify spatial patterns of soil properties with remotely sensed predictor variables. More specifically, matching the right scale...

Minimal percentage of dose received by 90% of the urethra (%UD90) is the most significant predictor of PSA bounce in patients who underwent low-dose-rate brachytherapy (LDR-brachytherapy) for prostate cancer.

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Tanaka, Nobumichi; Asakawa, Isao; Fujimoto, Kiyohide; Anai, Satoshi; Hirayama, Akihide; Hasegawa, Masatoshi; Konishi, Noboru; Hirao, Yoshihiko

2012-09-14

To clarify the significant clinicopathological and postdosimetric parameters to predict PSA bounce in patients who underwent low-dose-rate brachytherapy (LDR-brachytherapy) for prostate cancer. We studied 200 consecutive patients who received LDR-brachytherapy between July 2004 and November 2008. Of them, 137 patients did not receive neoadjuvant or adjuvant androgen deprivation therapy. One hundred and forty-two patients were treated with LDR-brachytherapy alone, and 58 were treated with LDR-brachytherapy in combination with external beam radiation therapy. The cut-off value of PSA bounce was 0.1 ng/mL. The incidence, time, height, and duration of PSA bounce were investigated. Clinicopathological and postdosimetric parameters were evaluated to elucidate independent factors to predict PSA bounce in hormone-naïve patients who underwent LDR-brachytherapy alone. Fifty patients (25%) showed PSA bounce and 10 patients (5%) showed PSA failure. The median time, height, and duration of PSA bounce were 17 months, 0.29 ng/mL, and 7.0 months, respectively. In 103 hormone-naïve patients treated with LDR-brachytherapy alone, and univariate Cox proportional regression hazard model indicated that age and minimal percentage of the dose received by 30% and 90% of the urethra were independent predictors of PSA bounce. With a multivariate Cox proportional regression hazard model, minimal percentage of the dose received by 90% of the urethra was the most significant parameter of PSA bounce. Minimal percentage of the dose received by 90% of the urethra was the most significant predictor of PSA bounce in hormone-naïve patients treated with LDR-brachytherapy alone.

Developmental trajectories of paediatric headache - sex-specific analyses and predictors.

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Isensee, Corinna; Fernandez Castelao, Carolin; Kröner-Herwig, Birgit

2016-01-01

Headache is the most common pain disorder in children and adolescents and is associated with diverse dysfunctions and psychological symptoms. Several studies evidenced sex-specific differences in headache frequency. Until now no study exists that examined sex-specific patterns of change in paediatric headache across time and included pain-related somatic and (socio-)psychological predictors. Latent Class Growth Analysis (LCGA) was used in order to identify different trajectory classes of headache across four annual time points in a population-based sample (n = 3 227; mean age 11.34 years; 51.2 % girls). In multinomial logistic regression analyses the influence of several predictors on the class membership was examined. For girls, a four-class model was identified as the best fitting model. While the majority of girls reported no (30.5 %) or moderate headache frequencies (32.5 %) across time, one class with a high level of headache days (20.8 %) and a class with an increasing headache frequency across time (16.2 %) were identified. For boys a two class model with a 'no headache class' (48.6 %) and 'moderate headache class' (51.4 %) showed the best model fit. Regarding logistic regression analyses, migraine and parental headache proved to be stable predictors across sexes. Depression/anxiety was a significant predictor for all pain classes in girls. Life events, dysfunctional stress coping and school burden were also able to differentiate at least between some classes in both sexes. The identified trajectories reflect sex-specific differences in paediatric headache, as seen in the number and type of classes extracted. The documented risk factors can deliver ideas for preventive actions and considerations for treatment programmes.

Predictors of Onset of Wheezing in Grain Elevator Workers

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Punam Pahwa

1998-01-01

Full Text Available A longitudinal study of Canadian grain elevator workers over a 12-year period was conducted. Data on respiratory symptoms and pulmonary function tests were collected once every three years as part of the Grain Dust Medical Surveillance Program started by Labour Canada in 1978; each three-year interval was called a 'cycle'. Of workers who had two or more observations, 1848 subjects (67.2% were free of respiratory symptoms (wheeze, dyspnea, cough or sputum at the baseline (cycle II. Predictors of first episode of wheezing were examined in these symptoms-free grain workers. Baseline mean age ± SD of the grain workers was 34.0±11.4 years and mean duration of work in the industry was 9.9±8.7 years. Of the 1848 symptoms-free grain workers at cycle II, 203 (11.0% subsequently reported wheezing during the study. Cox's proportional hazards model for analysis of survival data was used to determine significant predictors of first episode of wheezing. Significant predictors for first episode of wheezing were current smoking (relative risk [RR] 2.33; 95% CI 1.63 to 3.33; P<0.0001 and baseline forced expiratory volume in 1 s to forced vital capacity ratio [RR 0.02; 95% CI 0.003 to 0.20; P<0.0001. Baseline pulmonary function measurements and smoking habits appear to be important predictors of future development of asthma-like symptoms in grain elevator workers.

Predictor Relationships between Values Held by Married Individuals, Resilience and Conflict Resolution Styles: A Model Suggestion

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Tosun, Fatma; Dilmac, Bulent

2015-01-01

The aim of the present research is to reveal the predictor relationships between the values held by married individuals, resilience and conflict resolution styles. The research adopts a relational screening model that is a sub-type of the general screening model. The sample of the research consists of 375 married individuals, of which 173 are…

Predictors of Success after Extracorporeal Shock Wave Lithotripsy (ESWL for Renal Calculi Between 20—30 mm: A Multivariate Analysis Model

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Ahmed El-Assmy

2006-01-01

Full Text Available The first-line management of renal stones between 20—30 mm remains controversial. The Extracorporeal Shock Wave Lithotripsy (ESWL stone-free rates for such patient groups vary widely. The purpose of this study was to define factors that have a significant impact on the stone-free rate after ESWL in such controversial groups. Between January 1990 and January 2004, 594 patients with renal stones 20—30 mm in length underwent ESWL monotherapy. Stone surface area was measured for all stones. The results of treatment were evaluated after 3 months of follow-up. The stone-free rate was correlated with stone and patient characteristics using the Chi-square test; factors found to be significant were further analyzed using multivariate analysis.Repeat ESWL was needed in 56.9% of cases. Post-ESWL complications occurred in 5% of cases and post-ESWL secondary procedures were required in 5.9%. At 3-month follow-up, the overall stone-free rate was 77.2%. Using the Chi-square test, stone surface area, location, number, radiological renal picture, and congenital renal anomalies had a significant impact on the stone-free rate. Multivariate analysis excluded radiological renal picture from the logistic regression model while other factors maintained their statistically significant effect on success rate, indicating that they were independent predictors. A regression analysis model was designed to estimate the probability of stone-free status after ESWL. The sensitivity of the model was 97.4%, the specificity 90%, and the overall accuracy 95.6%.Stone surface area, location, number, and congenital renal anomalies are prognostic predictors determining stone clearance after ESWL of renal calculi of 20—30 mm. High probability of stone clearance is obtained with single stone ≤400 mm2 located in renal pelvis with no congenital anomalies. Our regression model can predict the probability of the success of ESWL in such controversial groups and can define patients who

Epigenetic Signature: A New Player as Predictor of Clinically Significant Prostate Cancer (PCa) in Patients on Active Surveillance (AS).

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Ferro, Matteo; Ungaro, Paola; Cimmino, Amelia; Lucarelli, Giuseppe; Busetto, Gian Maria; Cantiello, Francesco; Damiano, Rocco; Terracciano, Daniela

2017-05-27

Widespread prostate-specific antigen (PSA) testing notably increased the number of prostate cancer (PCa) diagnoses. However, about 30% of these patients have low-risk tumors that are not lethal and remain asymptomatic during their lifetime. Overtreatment of such patients may reduce quality of life and increase healthcare costs. Active surveillance (AS) has become an accepted alternative to immediate treatment in selected men with low-risk PCa. Despite much progress in recent years toward identifying the best candidates for AS in recent years, the greatest risk remains the possibility of misclassification of the cancer or missing a high-risk cancer. This is particularly worrisome in men with a life expectancy of greater than 10-15 years. The Prostate Cancer Research International Active Surveillance (PRIAS) study showed that, in addition to age and PSA at diagnosis, both PSA density (PSA-D) and the number of positive cores at diagnosis (two compared with one) are the strongest predictors for reclassification biopsy or switching to deferred treatment. However, there is still no consensus upon guidelines for placing patients on AS. Each institution has its own protocol for AS that is based on PRIAS criteria. Many different variables have been proposed as tools to enrol patients in AS: PSA-D, the percentage of freePSA, and the extent of cancer on biopsy (number of positive cores or percentage of core involvement). More recently, the Prostate Health Index (PHI), the 4 Kallikrein (4K) score, and other patient factors, such as age, race, and family history, have been investigated as tools able to predict clinically significant PCa. Recently, some reports suggested that epigenetic mapping differs significantly between cancer patients and healthy subjects. These findings indicated as future prospect the use of epigenetic markers to identify PCa patients with low-grade disease, who are likely candidates for AS. This review explores literature data about the potential of

Prevalence and Predictors of Pre-Diabetes and Diabetes among Adults 18 Years or Older in Florida: A Multinomial Logistic Modeling Approach.

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Ifechukwude Obiamaka Okwechime

Full Text Available Individuals with pre-diabetes and diabetes have increased risks of developing macro-vascular complications including heart disease and stroke; which are the leading causes of death globally. The objective of this study was to estimate the prevalence of pre-diabetes and diabetes, and to investigate their predictors among adults ≥18 years in Florida.Data covering the time period January-December 2013, were obtained from Florida's Behavioral Risk Factor Surveillance System (BRFSS. Survey design of the study was declared using SVYSET statement of STATA 13.1. Descriptive analyses were performed to estimate the prevalence of pre-diabetes and diabetes. Predictors of pre-diabetes and diabetes were investigated using multinomial logistic regression model. Model goodness-of-fit was evaluated using both the multinomial goodness-of-fit test proposed by Fagerland, Hosmer, and Bofin, as well as, the Hosmer-Lemeshow's goodness of fit test.There were approximately 2,983 (7.3% and 5,189 (12.1% adults in Florida diagnosed with pre-diabetes and diabetes, respectively. Over half of the study respondents were white, married and over the age of 45 years while 36.4% reported being physically inactive, overweight (36.4% or obese (26.4%, hypertensive (34.6%, hypercholesteremic (40.3%, and 26% were arthritic. Based on the final multivariable multinomial model, only being overweight (Relative Risk Ratio [RRR] = 1.85, 95% Confidence Interval [95% CI] = 1.41, 2.42, obese (RRR = 3.41, 95% CI = 2.61, 4.45, hypertensive (RRR = 1.69, 95% CI = 1.33, 2.15, hypercholesterolemic (RRR = 1.94, 95% CI = 1.55, 2.43, and arthritic (RRR = 1.24, 95% CI = 1.00, 1.55 had significant associations with pre-diabetes. However, more predictors had significant associations with diabetes and the strengths of associations tended to be higher than for the association with pre-diabetes. For instance, the relative risk ratios for the association between diabetes and being overweight (RRR = 2.00, 95

Serum Predictors of Percent Lean Mass in Young Adults.

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Lustgarten, Michael S; Price, Lori L; Phillips, Edward M; Kirn, Dylan R; Mills, John; Fielding, Roger A

2016-08-01

Lustgarten, MS, Price, LL, Phillips, EM, Kirn, DR, Mills, J, and Fielding, RA. Serum predictors of percent lean mass in young adults. J Strength Cond Res 30(8): 2194-2201, 2016-Elevated lean (skeletal muscle) mass is associated with increased muscle strength and anaerobic exercise performance, whereas low levels of lean mass are associated with insulin resistance and sarcopenia. Therefore, studies aimed at obtaining an improved understanding of mechanisms related to the quantity of lean mass are of interest. Percent lean mass (total lean mass/body weight × 100) in 77 young subjects (18-35 years) was measured with dual-energy x-ray absorptiometry. Twenty analytes and 296 metabolites were evaluated with the use of the standard chemistry screen and mass spectrometry-based metabolomic profiling, respectively. Sex-adjusted multivariable linear regression was used to determine serum analytes and metabolites significantly (p ≤ 0.05 and q ≤ 0.30) associated with the percent lean mass. Two enzymes (alkaline phosphatase and serum glutamate oxaloacetate aminotransferase) and 29 metabolites were found to be significantly associated with the percent lean mass, including metabolites related to microbial metabolism, uremia, inflammation, oxidative stress, branched-chain amino acid metabolism, insulin sensitivity, glycerolipid metabolism, and xenobiotics. Use of sex-adjusted stepwise regression to obtain a final covariate predictor model identified the combination of 5 analytes and metabolites as overall predictors of the percent lean mass (model R = 82.5%). Collectively, these data suggest that a complex interplay of various metabolic processes underlies the maintenance of lean mass in young healthy adults.

Pre-treatment growth and IGF-I deficiency as main predictors of response to growth hormone therapy in neural models

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Urszula Smyczyn´ska

2018-01-01

Full Text Available Mathematical models have been applied in prediction of growth hormone treatment effectiveness in children since the end of 1990s. Usually they were multiple linear regression models; however, there are also examples derived by empirical non-linear methods. Proposed solution consists in application of machine learning technique – artificial neural networks – to analyse this problem. This new methodology, contrary to previous ones, allows detection of both linear and non-linear dependencies without assuming their character a priori. The aims of this work included: development of models predicting separately growth during 1st year of treatment and final height as well as identification of important predictors and in-depth analysis of their influence on treatment’s effectiveness. The models were derived on the basis of clinical data of 272 patients treated for at least 1 year, 133 of whom have already attained final height. Starting from models containing 17 and 20 potential predictors, respectively for 1st year and final height model, we were able to reduce their number to 9 and 10. Basing on the final models, IGF-I concentration and earlier growth were indicated as belonging to most important predictors of response to GH therapy, while results of GH secretion tests were automatically excluded as insignificant. Moreover, majority of the dependencies were observed to be non-linear, thus using neural networks seems to be reasonable approach despite it being more complex than previously applied methods.

High-Order Sparse Linear Predictors for Audio Processing

DEFF Research Database (Denmark)

Giacobello, Daniele; van Waterschoot, Toon; Christensen, Mads Græsbøll

2010-01-01

Linear prediction has generally failed to make a breakthrough in audio processing, as it has done in speech processing. This is mostly due to its poor modeling performance, since an audio signal is usually an ensemble of different sources. Nevertheless, linear prediction comes with a whole set...... of interesting features that make the idea of using it in audio processing not far fetched, e.g., the strong ability of modeling the spectral peaks that play a dominant role in perception. In this paper, we provide some preliminary conjectures and experiments on the use of high-order sparse linear predictors...... in audio processing. These predictors, successfully implemented in modeling the short-term and long-term redundancies present in speech signals, will be used to model tonal audio signals, both monophonic and polyphonic. We will show how the sparse predictors are able to model efficiently the different...

The Predictors of Diet Quality among Australian Children Aged 3.5 Years.

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Collins, Laura J; Lacy, Kathleen E; Campbell, Karen J; McNaughton, Sarah A

2016-07-01

It is critical to promote healthy eating early in life. The aim of this study was to examine diet quality and its predictors among Australian preschool-aged children. Diet was assessed at age 3.5 years using multiple 24-hour recalls. Diet quality was assessed using an adapted version of the Revised Children's Diet Quality Index (RC-DQI). Potential predictors of diet quality were from questionnaires at age 3, 9, and 18 months and informed by the ecologic model of childhood overweight. Potential predictors included child's sex, age of introduction to solid foods, breastfeeding status, food acceptance, maternal nutrition knowledge, modeling of healthy eating, self-efficacy, education, and home food availability. Data from 244 children participating in the Melbourne Infant Feeding, Activity, and Nutrition Trial in 2008-2010 and follow-up data collection in 2011-2013 were examined. Diet quality at age 3.5 years. Bivariate logistic regression was performed to assess the relationship between diet quality and each predictor. A multivariable logistic regression model accounting for influences of covariates, treatment arm, and clustering by group tested associations between diet quality and significant predictors from bivariate analyses. RC-DQI scores had a mean±standard deviation score of 62.8±8.3 points out of a maximum of 85 points. Breastfeeding status (odds ratio [OR] 2.34, 95% CI 1.33 to 4.10) and maternal modeling of healthy eating (OR 1.75, 95% CI 1.01 to 3.03) were positively associated with RC-DQI scores. Both breastfeeding status (OR 3.09, 95% CI 1.63 to 5.85) and modeling (OR 2.01, 95% CI 1.04 to 3.88) remained positively associated with diet quality after adjustment for child age, body mass index z score, energy intake, treatment arm, and clustering. Breastfeeding status and modeling of healthy eating were independently associated with children's diet quality. Early intervention could assist mothers to practice these behaviors to provide support for improving

Analysis of the Modified Smith Predictor

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Jorge A. Herrera-Cuartas

2013-11-01

Full Text Available In this paper an analysis about the modified Smith predictor, is presented. The modified Smith predictor is a scheme used to control stable, unstable and integrative systems. The closed loop equation is developed and analyzed. Additionally, various test are made to verify the behavior of the control scheme. Specify, three test are made. First, it is verify the behavior of the scheme to deal with an uncertainty in the delay model. Second, it is verify the behavior in the face of uncertainties in the parameter of the rational model. 

Predictors of suicidal ideation in older people: a decision tree analysis.

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Handley, Tonelle E; Hiles, Sarah A; Inder, Kerry J; Kay-Lambkin, Frances J; Kelly, Brian J; Lewin, Terry J; McEvoy, Mark; Peel, Roseanne; Attia, John R

2014-11-01

Suicide among older adults is a major public health issue worldwide. Although studies have identified psychological, physical, and social contributors to suicidal thoughts in older adults, few have explored the specific interactions between these factors. This article used a novel statistical approach to explore predictors of suicidal ideation in a community-based sample of older adults. Prospective cohort study. Participants aged 55-85 years were randomly selected from the Hunter Region, a large regional center in New South Wales, Australia. Baseline psychological, physical, and social factors, including psychological distress, physical functioning, and social support, were used to predict suicidal ideation at the 5-year follow-up. Classification and regression tree modeling was used to determine specific risk profiles for participants depending on their individual well-being in each of these key areas. Psychological distress was the strongest predictor, with 25% of people with high distress reporting suicidal ideation. Within high psychological distress, lower physical functioning significantly increased the likelihood of suicidal ideation, with high distress and low functioning being associated with ideation in 50% of cases. A substantial subgroup reported suicidal ideation in the absence of psychological distress; dissatisfaction with social support was the most important predictor among this group. The performance of the model was high (area under the curve: 0.81). Decision tree modeling enabled individualized "risk" profiles for suicidal ideation to be determined. Although psychological factors are important for predicting suicidal ideation, both physical and social factors significantly improved the predictive ability of the model. Assessing these factors may enhance identification of older people at risk of suicidal ideation. Copyright © 2014. Published by Elsevier Inc.

First-grade cognitive abilities as long-term predictors of reading comprehension and disability status.

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Fuchs, Douglas; Compton, Donald L; Fuchs, Lynn S; Bryant, V Joan; Hamlett, Carol L; Lambert, Warren

2012-01-01

In a sample of 195 first graders selected for poor reading performance, the authors explored four cognitive predictors of later reading comprehension and reading disability (RD) status. In fall of first grade, the authors measured the children's phonological processing, rapid automatized naming (RAN), oral language comprehension, and nonverbal reasoning. Throughout first grade, they also modeled the students' reading progress by means of weekly Word Identification Fluency (WIF) tests to derive December and May intercepts. The authors assessed their reading comprehension in the spring of Grades 1-5. With the four cognitive variables and the WIF December intercept as predictors, 50.3% of the variance in fifth-grade reading comprehension was explained: 52.1% of this 50.3% was unique to the cognitive variables, 13.1% to the WIF December intercept, and 34.8% was shared. All five predictors were statistically significant. The same four cognitive variables with the May (rather than December) WIF intercept produced a model that explained 62.1% of the variance. Of this amount, the cognitive variables and May WIF intercept accounted for 34.5% and 27.7%, respectively; they shared 37.8%. All predictors in this model were statistically significant except RAN. Logistic regression analyses indicated that the accuracy with which the cognitive variables predicted end-of-fifth-grade RD status was 73.9%. The May WIF intercept contributed reliably to this prediction; the December WIF intercept did not. Results are discussed in terms of a role for cognitive abilities in identifying, classifying, and instructing students with severe reading problems.

Predictors of Transience among Homeless Emerging Adults

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Ferguson, Kristin M.; Bender, Kimberly; Thompson, Sanna J.

2014-01-01

This study identified predictors of transience among homeless emerging adults in three cities. A total of 601 homeless emerging adults from Los Angeles, Austin, and Denver were recruited using purposive sampling. Ordinary least squares regression results revealed that significant predictors of greater transience include White ethnicity, high…

Predictors of smoking among the secondary high school boy students based on the health belief model

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Samira Mohammadi

2017-01-01

Full Text Available Background: Smoking is one of the most important risk factors for health and also health problems, such as heart diseases, especially for young people. This study aimed to investigate the effect of factors related to smoking among the secondary high school students in the city of Marivan (Kurdistan-Iran, in 2015, based on the constructs of health belief model (HBM. Methods: This cross-sectional study was conducted in 470 secondary high school students in Marivan in 2015. The samples were selected by random cluster sampling. A question with four sections was used to collect data (demographic questions, knowledge section, attitude section, and questions related to e constructs of HBM. Results: According to the results, the correlation of smoking was stronger with attitude (r = 0.269 and odds ratio = 0.89 but weaker with perceived barriers (r = 0.101. There was not a significant correlation between smoking behavior and knowledge of the harms of smoking (r = −0.005. Moreover, Cues to action was effective predictor of smoking behavior (r = 0.259. Conclusions: The findings of this study show that the prevalence of smoking in the studied sample is somewhat lower than other regions of Iran, but it should be noted that if no interventions are done to prevent smoking in this age group. The findings of the study also showed that the structure of attitudes, self-efficacy, and Cues to action are the strongest predictors of smoking among students. Albeit, attitude was strongest predictor of smoking that shows the prevalence of smoking can be reduced by focusing in this part. Considering the mean age of participants (16/2 ± 0.25 years, that shows the riskiest period for smoking is 16 years and authorities can make change in policies of cigarette selling only for over 18 years.

Perceived Resources as a Predictor of Satisfaction with Food-Related Life among Chilean Elderly: An Approach with Generalized Linear Models.

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Lobos, G; Schnettler, B; Grunert, K G; Adasme, C

2017-01-01

The main objective of this study is to show why perceived resources are a strong predictor of satisfaction with food-related life in Chilean older adults. Design, sampling and participants: A survey was conducted in rural and urban areas in 30 communes of the Maule Region with 785 participants over 60 years of age who live in their own homes. The Satisfaction with Food-related Life (SWFL) scale was used. Generalized linear models (GLM) were used for the regression analysis. The results led to different considerations: First, older adults' perceived levels of resources are a good reflection of their actual levels of resources. Second, the individuals rated the sum of the perceived resources as 'highly important' to explain older adults' satisfaction with food-related life. Third, SWFL was predicted by satisfaction with economic situation, family importance, quantity of domestic household goods and a relative health indicator. Fourth, older adults who believe they have more resources compared to others are more satisfied with their food-related life. Finally, Poisson and binomial logistic models showed that the sum of perceived resources significantly increased the prediction of SWFL. The main conclusion is that perceived personal resources are a strong predictor of SWFL in Chilean older adults.

Is parenting style a predictor of suicide attempts in a representative sample of adolescents?

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Donath, Carolin; Graessel, Elmar; Baier, Dirk; Bleich, Stefan; Hillemacher, Thomas

2014-04-26

Suicidal ideation and suicide attempts are serious but not rare conditions in adolescents. However, there are several research and practical suicide-prevention initiatives that discuss the possibility of preventing serious self-harm. Profound knowledge about risk and protective factors is therefore necessary. The aim of this study is a) to clarify the role of parenting behavior and parenting styles in adolescents' suicide attempts and b) to identify other statistically significant and clinically relevant risk and protective factors for suicide attempts in a representative sample of German adolescents. In the years 2007/2008, a representative written survey of N = 44,610 students in the 9th grade of different school types in Germany was conducted. In this survey, the lifetime prevalence of suicide attempts was investigated as well as potential predictors including parenting behavior. A three-step statistical analysis was carried out: I) As basic model, the association between parenting and suicide attempts was explored via binary logistic regression controlled for age and sex. II) The predictive values of 13 additional potential risk/protective factors were analyzed with single binary logistic regression analyses for each predictor alone. Non-significant predictors were excluded in Step III. III) In a multivariate binary logistic regression analysis, all significant predictor variables from Step II and the parenting styles were included after testing for multicollinearity. Three parental variables showed a relevant association with suicide attempts in adolescents - (all protective): mother's warmth and father's warmth in childhood and mother's control in adolescence (Step I). In the full model (Step III), Authoritative parenting (protective: OR: .79) and Rejecting-Neglecting parenting (risk: OR: 1.63) were identified as significant predictors (p parental separation events. Parenting style does matter. While children of Authoritative parents profit, children of

Predictors of Career Adaptability Skill among Higher Education Students in Nigeria

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Amos Shaibu Ebenehi

2016-12-01

Full Text Available This paper examined predictors of career adaptability skill among higher  education students in Nigeria. A sample of 603 higher education students randomly selected from six colleges of education in Nigeria participated in this study.  A set of self-reported questionnaire was used for data collection, and multiple linear regression analysis was used to analyze the data.  Results indicated that 33.3% of career adaptability skill was explained by the model.  Four out of the five predictor variables significantly predicted career adaptability skill among higher education students in Nigeria.  Among the four predictors, career self-efficacy sources was the most statistically significant predictor of career adaptability skill among higher education students in Nigeria, followed by personal goal orientation, career future concern, and perceived social support respectively.  Vocational identity did not statistically predict career adaptability skill among higher education students in Nigeria.  The study suggested that similar study should be replicated in other parts of the world in view of the importance of career adaptability skill to the smooth transition of graduates from school to the labor market.  The study concluded by requesting stakeholders of higher institutions in Nigeria to provide career exploration database for the students, and encourage career intervention program in order to enhance career adaptability skill among the students.

Psychosocial predictors of energy underreporting in a large doubly labeled water study.

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Tooze, Janet A; Subar, Amy F; Thompson, Frances E; Troiano, Richard; Schatzkin, Arthur; Kipnis, Victor

2004-05-01

Underreporting of energy intake is associated with self-reported diet measures and appears to be selective according to personal characteristics. Doubly labeled water is an unbiased reference biomarker for energy intake that may be used to assess underreporting. Our objective was to determine which factors are associated with underreporting of energy intake on food-frequency questionnaires (FFQs) and 24-h dietary recalls (24HRs). The study participants were 484 men and women aged 40-69 y who resided in Montgomery County, MD. Using the doubly labeled water method to measure total energy expenditure, we considered numerous psychosocial, lifestyle, and sociodemographic factors in multiple logistic regression models for prediction of the probability of underreporting on the FFQ and 24HR. In the FFQ models, fear of negative evaluation, weight-loss history, and percentage of energy from fat were the best predictors of underreporting in women (R(2) = 0.09); body mass index, comparison of activity level with that of others of the same sex and age, and eating frequency were the best predictors in men (R(2) = 0.10). In the 24HR models, social desirability, fear of negative evaluation, body mass index, percentage of energy from fat, usual activity, and variability in number of meals per day were the best predictors of underreporting in women (R(2) = 0.22); social desirability, dietary restraint, body mass index, eating frequency, dieting history, and education were the best predictors in men (R(2) = 0.25). Although the final models were significantly related to underreporting on both the FFQ and the 24HR, the amount of variation explained by these models was relatively low, especially for the FFQ.

Assessing Breast Cancer Risk Estimates Based on the Gail Model and Its Predictors in Qatari Women.

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Bener, Abdulbari; Çatan, Funda; El Ayoubi, Hanadi R; Acar, Ahmet; Ibrahim, Wanis H

2017-07-01

The Gail model is the most widely used breast cancer risk assessment tool. An accurate assessment of individual's breast cancer risk is very important for prevention of the disease and for the health care providers to make decision on taking chemoprevention for high-risk women in clinical practice in Qatar. To assess the breast cancer risk among Arab women population in Qatar using the Gail model and provide a global comparison of risk assessment. In this cross-sectional study of 1488 women (aged 35 years and older), we used the Gail Risk Assessment Tool to assess the risk of developing breast cancer. Sociodemographic features such as age, lifestyle habits, body mass index, breast-feeding duration, consanguinity among parents, and family history of breast cancer were considered as possible risks. The mean age of the study population was 47.8 ± 10.8 years. Qatari women and Arab women constituted 64.7% and 35.3% of the study population, respectively. The mean 5-year and lifetime breast cancer risks were 1.12 ± 0.52 and 10.57 ± 3.1, respectively. Consanguineous marriage among parents was seen in 30.6% of participants. We found a relationship between the 5-year and lifetime risks of breast cancer and variables such as age, age at menarche, gravidity, parity, body mass index, family history of cancer, menopause age, occupation, and level of education. The linear regression analysis identified the predictors for breast cancer in women such as age, age at menarche, age of first birth, family history and age of menopausal were considered the strong predictors and significant contributing risk factors for breast cancer after adjusting for ethnicity, parity and other variables. The current study is the first to evaluate the performance of the Gail model for Arab women population in the Gulf Cooperation Council. Gail model is an appropriate breast cancer risk assessment tool for female population in Qatar.

Application of Interval Predictor Models to Space Radiation Shielding

Science.gov (United States)

Crespo, Luis G.; Kenny, Sean P.; Giesy,Daniel P.; Norman, Ryan B.; Blattnig, Steve R.

2016-01-01

This paper develops techniques for predicting the uncertainty range of an output variable given input-output data. These models are called Interval Predictor Models (IPM) because they yield an interval valued function of the input. This paper develops IPMs having a radial basis structure. This structure enables the formal description of (i) the uncertainty in the models parameters, (ii) the predicted output interval, and (iii) the probability that a future observation would fall in such an interval. In contrast to other metamodeling techniques, this probabilistic certi cate of correctness does not require making any assumptions on the structure of the mechanism from which data are drawn. Optimization-based strategies for calculating IPMs having minimal spread while containing all the data are developed. Constraints for bounding the minimum interval spread over the continuum of inputs, regulating the IPMs variation/oscillation, and centering its spread about a target point, are used to prevent data over tting. Furthermore, we develop an approach for using expert opinion during extrapolation. This metamodeling technique is illustrated using a radiation shielding application for space exploration. In this application, we use IPMs to describe the error incurred in predicting the ux of particles resulting from the interaction between a high-energy incident beam and a target.

Is parenting style a predictor of suicide attempts in a representative sample of adolescents?

Science.gov (United States)

2014-01-01

Background Suicidal ideation and suicide attempts are serious but not rare conditions in adolescents. However, there are several research and practical suicide-prevention initiatives that discuss the possibility of preventing serious self-harm. Profound knowledge about risk and protective factors is therefore necessary. The aim of this study is a) to clarify the role of parenting behavior and parenting styles in adolescents’ suicide attempts and b) to identify other statistically significant and clinically relevant risk and protective factors for suicide attempts in a representative sample of German adolescents. Methods In the years 2007/2008, a representative written survey of N = 44,610 students in the 9th grade of different school types in Germany was conducted. In this survey, the lifetime prevalence of suicide attempts was investigated as well as potential predictors including parenting behavior. A three-step statistical analysis was carried out: I) As basic model, the association between parenting and suicide attempts was explored via binary logistic regression controlled for age and sex. II) The predictive values of 13 additional potential risk/protective factors were analyzed with single binary logistic regression analyses for each predictor alone. Non-significant predictors were excluded in Step III. III) In a multivariate binary logistic regression analysis, all significant predictor variables from Step II and the parenting styles were included after testing for multicollinearity. Results Three parental variables showed a relevant association with suicide attempts in adolescents – (all protective): mother’s warmth and father’s warmth in childhood and mother’s control in adolescence (Step I). In the full model (Step III), Authoritative parenting (protective: OR: .79) and Rejecting-Neglecting parenting (risk: OR: 1.63) were identified as significant predictors (p < .001) for suicidal attempts. Seven further variables were interpreted to be

Interprofessional teamwork skills as predictors of clinical outcomes in a simulated healthcare setting.

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Shrader, Sarah; Kern, Donna; Zoller, James; Blue, Amy

2013-01-01

Teaching interprofessional (IP) teamwork skills is a goal of interprofessional education. The purpose of this study was to examine the relationship between IP teamwork skills, attitudes and clinical outcomes in a simulated clinical setting. One hundred-twenty health professions students (medicine, pharmacy, physician assistant) worked in interprofessional teams to manage a "patient" in a health care simulation setting. Students completed the Interdisciplinary Education Perception Scale (IEPS) attitudinal survey instrument. Students' responses were averaged by team to create an IEPS attitudes score. Teamwork skills for each team were rated by trained observers using a checklist to calculate a teamwork score (TWS). Clinical outcome scores (COS) were determined by summation of completed clinical tasks performed by the team based on an expert developed checklist. Regression analyses were conducted to determine the relationship of IEPS and TWS with COS. IEPS score was not a significant predictor of COS (p=0.054), but TWS was a significant predictor (pstudents' interprofessional teamwork skills are significant predictors of positive clinical outcomes. Interprofessional curricular models that produce effective teamwork skills can improve student performance in clinical environments and likely improve teamwork practice to positively affect patient care outcomes.

Clinical features and predictors of outcome in acute hepatitis A and hepatitis E virus hepatitis on cirrhosis.

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Radha Krishna, Yellapu; Saraswat, Vivek Anand; Das, Khaunish; Himanshu, Goel; Yachha, Surender Kumar; Aggarwal, Rakesh; Choudhuri, Gour

2009-03-01

Acute hepatitis A and E are recognized triggers of hepatic decompensation in patients with cirrhosis, particularly from the Indian subcontinent. However, the resulting acute-on-chronic liver failure (ACLF) has not been well characterized and no large studies are available. Our study aimed to evaluate the clinical profile and predictors of 3-month mortality in patients with this distinctive form of liver failure. ACLF was diagnosed in patients with acute hepatitis A or E [abrupt rise in serum bilirubin and/or alanine aminotransferase with positive immunoglobulin M anti-hepatitis A virus (HAV)/anti-hepatitis E virus (HEV)] presenting with clinical evidence of liver failure (significant ascites and/or hepatic encephalopathy) and clinical, biochemical, endoscopic (oesophageal varices at least grade II in size), ultrasonographical (presence of nodular irregular liver with porto-systemic collaterals) or histological evidence of cirrhosis. Clinical and laboratory profile were evaluated, predictors of 3-month mortality were determined using univariate and multivariate logistic regression and a prognostic model was constructed. Receiver-operating curves were plotted to measure performance of the present prognostic model, model for end-stage liver disease (MELD) score and Child-Turcotte-Pugh (CTP) score. ACLF occurred in 121 (3.75%) of 3220 patients (mean age 36.3+/-18.0 years; M:F 85:36) with liver cirrhosis admitted from January 2000 to June 2006. It was due to HEV in 80 (61.1%), HAV in 33 (27.2%) and both in 8 (6.1%). The underlying liver cirrhosis was due to HBV (37), alcohol (17), Wilson's disease (8), HCV (5), autoimmune (6), Budd-Chiari syndrome (2), haemochromatosis (2) and was cryptogenic in the rest (42). Common presentations were jaundice (100%), ascites (78%) and hepatic encephalopathy (55%). Mean (SD) CTP score was 11.4+/-1.6 and mean MELD score was 28.6+/-9.06. Three-month mortality was 54 (44.6%). Complications seen were sepsis in 42 (31.8%), renal failure in

Are competition and extrinsic motivation reliable predictors of academic cheating?

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Gábor eOrosz

2013-02-01

Full Text Available Previous studies suggest that extrinsic motivation and competition are reliable predictors of academic cheating. The aim of the present questionnaire study was to separate the effects of motivation- and competition-related variables on academic cheating by Hungarian high school students (N = 620, M = 264, F = 356. Structural equation modeling showed that intrinsic motivation has a negative effect, and amotivation has a positive indirect effect on self-reported academic cheating. In contrast, extrinsic motivation had no significant effect. Indirect positive influence on cheating, based on some characteristics of hypercompetition, was also found, whereas attitudes towards self-developmental competition had a mediated negative influence. Neither constructive nor destructive competitive classroom climate had a significant impact on academic dishonesty. Acceptance of cheating and guilt has significant and direct effect on self-reported cheating. In comparison with them, the effects of motivational and competition-related variables are relatively small, even negligible. These results suggest that extrinsic motivation and competition are not amongst the most reliable predictors of academic cheating behavior.

Are competition and extrinsic motivation reliable predictors of academic cheating?

Science.gov (United States)

Orosz, Gábor; Farkas, Dávid; Roland-Lévy, Christine

2013-01-01

Previous studies suggest that extrinsic motivation and competition are reliable predictors of academic cheating. The aim of the present questionnaire study was to separate the effects of motivation- and competition-related variables on academic cheating by Hungarian high school students (N = 620, M = 264, F = 356). Structural equation modeling showed that intrinsic motivation has a negative effect, and amotivation has a positive indirect effect on self-reported academic cheating. In contrast, extrinsic motivation had no significant effect. Indirect positive influence on cheating, based on some characteristics of hypercompetition, was also found, whereas attitudes toward self-developmental competition had a mediated negative influence. Neither constructive nor destructive competitive classroom climate had a significant impact on academic dishonesty. Acceptance of cheating and guilt has significant and direct effect on self-reported cheating. In comparison with them, the effects of motivational and competition-related variables are relatively small, even negligible. These results suggest that extrinsic motivation and competition are not amongst the most reliable predictors of academic cheating behavior.

Predictors of business return in New Orleans after Hurricane Katrina.

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Nina S N Lam

Full Text Available We analyzed the business reopening process in New Orleans after Hurricane Katrina, which hit the region on August 29, 2005, to better understand what the major predictors were and how their impacts changed through time. A telephone survey of businesses in New Orleans was conducted in October 2007, 26 months after Hurricane Katrina. The data were analyzed using a modified spatial probit regression model to evaluate the importance of each predictor variable through time. The results suggest that the two most important reopening predictors throughout all time periods were the flood depth at the business location and business size as represented by its wages in a logarithmic form. Flood depth was a significant negative predictor and had the largest marginal effects on the reopening probabilities. Smaller businesses had lower reopening probabilities than larger ones. However, the nonlinear response of business size to the reopening probability suggests that recovery aid would be most effective for smaller businesses than for larger ones. The spatial spillovers effect was a significant positive predictor but only for the first nine months. The findings show clearly that flood protection is the overarching issue for New Orleans. A flood protection plan that reduces the vulnerability and length of flooding would be the first and foremost step to mitigate the negative effects from climate-related hazards and enable speedy recovery. The findings cast doubt on the current coastal protection efforts and add to the current debate of whether coastal Louisiana will be sustainable or too costly to protect from further land loss and flooding given the threat of sea-level rise. Finally, a plan to help small businesses to return would also be an effective strategy for recovery, and the temporal window of opportunity that generates the greatest impacts would be the first 6∼9 months after the disaster.

Predictors of business return in New Orleans after Hurricane Katrina.

Science.gov (United States)

Lam, Nina S N; Arenas, Helbert; Pace, Kelley; LeSage, James; Campanella, Richard

2012-01-01

We analyzed the business reopening process in New Orleans after Hurricane Katrina, which hit the region on August 29, 2005, to better understand what the major predictors were and how their impacts changed through time. A telephone survey of businesses in New Orleans was conducted in October 2007, 26 months after Hurricane Katrina. The data were analyzed using a modified spatial probit regression model to evaluate the importance of each predictor variable through time. The results suggest that the two most important reopening predictors throughout all time periods were the flood depth at the business location and business size as represented by its wages in a logarithmic form. Flood depth was a significant negative predictor and had the largest marginal effects on the reopening probabilities. Smaller businesses had lower reopening probabilities than larger ones. However, the nonlinear response of business size to the reopening probability suggests that recovery aid would be most effective for smaller businesses than for larger ones. The spatial spillovers effect was a significant positive predictor but only for the first nine months. The findings show clearly that flood protection is the overarching issue for New Orleans. A flood protection plan that reduces the vulnerability and length of flooding would be the first and foremost step to mitigate the negative effects from climate-related hazards and enable speedy recovery. The findings cast doubt on the current coastal protection efforts and add to the current debate of whether coastal Louisiana will be sustainable or too costly to protect from further land loss and flooding given the threat of sea-level rise. Finally, a plan to help small businesses to return would also be an effective strategy for recovery, and the temporal window of opportunity that generates the greatest impacts would be the first 6∼9 months after the disaster.

Psychosocial predictors of treatment outcome for trauma-affected refugees

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Charlotte Sonne

2016-05-01

Full Text Available Background: The effects of treatment in trials with trauma-affected refugees vary considerably not only between studies but also between patients within a single study. However, we know little about why some patients benefit more from treatment, as few studies have analysed predictors of treatment outcome. Objective: The objective of the study was to examine possible psychosocial predictors of treatment outcome for trauma-affected refugees. Method: The participants were 195 adult refugees with posttraumatic stress disorder (PTSD who were enrolled in a 6- to 7-month treatment programme at the Competence Centre for Transcultural Psychiatry (CTP, Denmark. The CTP Predictor Index used in the study included 15 different possible outcome predictors concerning the patients’ past, chronicity of mental health problems, pain, treatment motivation, prerequisites for engaging in psychotherapy, and social situation. The primary outcome measure was PTSD symptoms measured on the Harvard Trauma Questionnaire (HTQ. Other outcome measures included the Hopkins Symptom Check List-25, the WHO-5 Well-being Index, Sheehan Disability Scale, Hamilton Depression and Anxiety Scales, the somatisation scale of the Symptoms Checklist-90, Global Assessment of Functioning scales, and pain rated on visual analogue scales. The relations between treatment outcomes and the total score as well as subscores of the CTP Predictor Index were analysed. Results: Overall, the total score of the CTP Predictor Index was significantly correlated to pre- to post treatment score changes on the majority of the ratings mentioned above. While employment status was the only single item significantly correlated to HTQ-score changes, a number of single items from the CTP Predictor Index correlated significantly with changes in depression and anxiety symptoms, but the size of the correlation coefficients were modest. Conclusions: The total score of the CTP Predictor Index correlated significantly

Significantly reduced hypoxemic events in morbidly obese patients undergoing gastrointestinal endoscopy: Predictors and practice effect

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Basavana Gouda Goudra

2014-01-01

Full Text Available Background: Providing anesthesia for gastrointestinal (GI endoscopy procedures in morbidly obese patients is a challenge for a variety of reasons. The negative impact of obesity on the respiratory system combined with a need to share the upper airway and necessity to preserve the spontaneous ventilation, together add to difficulties. Materials and Methods: This retrospective cohort study included patients with a body mass index (BMI >40 kg/m 2 that underwent out-patient GI endoscopy between September 2010 and February 2011. Patient data was analyzed for procedure, airway management technique as well as hypoxemic and cardiovascular events. Results: A total of 119 patients met the inclusion criteria. Our innovative airway management technique resulted in a lower rate of intraoperative hypoxemic events compared with any published data available. Frequency of desaturation episodes showed statistically significant relation to previous history of obstructive sleep apnea (OSA. These desaturation episodes were found to be statistically independent of increasing BMI of patients. Conclusion: Pre-operative history of OSA irrespective of associated BMI values can be potentially used as a predictor of intra-procedural desaturation. With suitable modification of anesthesia technique, it is possible to reduce the incidence of adverse respiratory events in morbidly obese patients undergoing GI endoscopy procedures, thereby avoiding the need for endotracheal intubation.

Significantly reduced hypoxemic events in morbidly obese patients undergoing gastrointestinal endoscopy: Predictors and practice effect.

Science.gov (United States)

Goudra, Basavana Gouda; Singh, Preet Mohinder; Penugonda, Lakshmi C; Speck, Rebecca M; Sinha, Ashish C

2014-01-01

Providing anesthesia for gastrointestinal (GI) endoscopy procedures in morbidly obese patients is a challenge for a variety of reasons. The negative impact of obesity on the respiratory system combined with a need to share the upper airway and necessity to preserve the spontaneous ventilation, together add to difficulties. This retrospective cohort study included patients with a body mass index (BMI) >40 kg/m(2) that underwent out-patient GI endoscopy between September 2010 and February 2011. Patient data was analyzed for procedure, airway management technique as well as hypoxemic and cardiovascular events. A total of 119 patients met the inclusion criteria. Our innovative airway management technique resulted in a lower rate of intraoperative hypoxemic events compared with any published data available. Frequency of desaturation episodes showed statistically significant relation to previous history of obstructive sleep apnea (OSA). These desaturation episodes were found to be statistically independent of increasing BMI of patients. Pre-operative history of OSA irrespective of associated BMI values can be potentially used as a predictor of intra-procedural desaturation. With suitable modification of anesthesia technique, it is possible to reduce the incidence of adverse respiratory events in morbidly obese patients undergoing GI endoscopy procedures, thereby avoiding the need for endotracheal intubation.

Pretreatment Predictors of Adverse Radiation Effects After Radiosurgery for Arteriovenous Malformation

International Nuclear Information System (INIS)

Hayhurst, Caroline; Monsalves, Eric; Prooijen, Monique van; Cusimano, Michael; Tsao, May; Menard, Cynthia; Kulkarni, Abhaya V.; Schwartz, Michael; Zadeh, Gelareh

2012-01-01

Purpose: To identify vascular and dosimetric predictors of symptomatic T2 signal change and adverse radiation effects after radiosurgery for arteriovenous malformation, in order to define and validate preexisting risk models. Methods and Materials: A total of 125 patients with arteriovenous malformations (AVM) were treated at our institution between 2005 and 2009. Eighty-five patients have at least 12 months of clinical and radiological follow-up. Any new-onset headaches, new or worsening seizures, or neurological deficit were considered adverse events. Follow-up magnetic resonance images were assessed for new onset T2 signal change and the volume calculated. Pretreatment characteristics and dosimetric variables were analyzed to identify predictors of adverse radiation effects. Results: There were 19 children and 66 adults in the study cohort, with a mean age of 34 (range 6–74). Twenty-three (27%) patients suffered adverse radiation effects (ARE), 9 patients with permanent neurological deficit (10.6%). Of these, 5 developed fixed visual field deficits. Target volume and 12 Gy volume were the most significant predictors of adverse radiation effects on univariate analysis (p 3 , above which the rate of ARE increased dramatically. Multivariate analysis target volume and the absence of prior hemorrhage are the only significant predictors of ARE. The volume of T2 signal change correlates to ARE, but only target volume is predictive of a higher volume of T2 signal change. Conclusions: Target volume and the absence of prior hemorrhage is the most accurate predictor of adverse radiation effects and complications after radiosurgery for AVMs. A high percentage of permanent visual field defects in this series suggest the optic radiation is a critical radiosensitive structure.

Sociodemographic predictors of elderly's psychological well-being in Malaysia.

Science.gov (United States)

Momtaz, Yadollah A; Ibrahim, Rahimah; Hamid, Tengku A; Yahaya, Nurizan

2011-05-01

Psychological well-being as one of the most important indicators of successful aging has received substantial attention in the gerontological literature. Prior studies show that sociodemographic factors influencing elderly's psychological well-being are multiple and differ across cultures. The aim of this study was to identify significant sociodemographic predictors of psychological well-being among Malay elders. The study included 1415 older Malays (60-100 years, 722 women), randomly selected through a multistage stratified random method from Peninsular Malaysia. WHO-Five well-being index was used to measure psychological well-being. Data analysis was conducted using the Statistical Package for Social Sciences (SPSS) version 13.0. Using multiple regression analysis a significant model emerged (F(7, 1407) = 20.14, p ≤ 0.001), where age, sex, marital status, and household income were significant predictor variables of psychological well-being among Malay elders. However, level of education, employment status, and place of residence failed to predict psychological well-being. This study showed that the oldest old, elderly women, unmarried, and the poor elderly people are at risk for experiencing low psychological well-being. Therefore, they need special attention from family, policy makers, and those who work with elderly people.

Social network predictors of latrine ownership.

Science.gov (United States)

Shakya, Holly B; Christakis, Nicholas A; Fowler, James H

2015-01-01

Poor sanitation, including the lack of clean functioning toilets, is a major factor contributing to morbidity and mortality from infectious diseases in the developing world. We examine correlates of latrine ownership in rural India with a focus on social network predictors. Participants from 75 villages provided the names of their social contacts as well as their own relevant demographic and household characteristics. Using these measures, we test whether the latrine ownership of an individual's social contacts is a significant predictor of individual latrine ownership. We also investigate whether network centrality significantly predicts latrine ownership, and if so, whether it moderates the relationship between the latrine ownership of the individual and that of her social contacts. Our results show that, controlling for the standard predictors of latrine ownership such as caste, education, and income, individuals are more likely to own latrines if their social contacts own latrines. Interaction models suggest that this relationship is stronger among those of the same caste, the same education, and those with stronger social ties. We also find that more central individuals are more likely to own latrines, but the correlation in latrine ownership between social contacts is strongest among individuals on the periphery of the network. Although more data is needed to determine how much the clustering of latrine ownership may be caused by social influence, the results here suggest that interventions designed to promote latrine ownership should consider focusing on those at the periphery of the network. The reason is that they are 1) less likely to own latrines and 2) more likely to exhibit the same behavior as their social contacts, possibly as a result of the spread of latrine adoption from one person to another. Copyright © 2014 Elsevier Ltd. All rights reserved.

Concurrent sexual partners-A predictor of Chlamydia

DEFF Research Database (Denmark)

Jørgensen, Marianne Johansson; Olesen, Frede; Maindal, Helle Terkildsen

2013-01-01

, but the significance of this compared with other well-known predictors has only been briefly described. Aim: The aim is to examine if concurrent partners isan independent predictor for C. trachomatis infection in young Danes aged 15-29 years. Methods: Detailed sexual behavior data were collected via a web......:These preliminary results suggest that concurrent sexual partners is an important predictor for C.trachomatis infections among young Danes aged 15-29. A more concise conclusion will be presented at the Ph.D day......Background:Chlamydia trachomatis is the most common sexually transmitted bacterial infection among young Danes and the spread is highly dependent on the population’s sexual behavior. Previous studies have found concurrent partnerships to be a possible predictor for C. trachomatis...

The Job Demands-Resources model as predictor of work identity and work engagement: A comparative analysis

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Roslyn De Braine

2011-05-01

Research purpose: This study explored possible differences in the Job Demands-Resources model (JD-R as predictor of overall work engagement, dedication only and work-based identity, through comparative predictive analyses. Motivation for the study: This study may shed light on the dedication component of work engagement. Currently no literature indicates that the JD-R model has been used to predict work-based identity. Research design: A census-based survey was conducted amongst a target population of 23134 employees that yielded a sample of 2429 (a response rate of about 10.5%. The Job Demands- Resources scale (JDRS was used to measure job demands and job resources. A work-based identity scale was developed for this study. Work engagement was studied with the Utrecht Work Engagement Scale (UWES. Factor and reliability analyses were conducted on the scales and general multiple regression models were used in the predictive analyses. Main findings: The JD-R model yielded a greater amount of variance in dedication than in work engagement. It, however, yielded the greatest amount of variance in work-based identity, with job resources being its strongest predictor. Practical/managerial implications: Identification and work engagement levels can be improved by managing job resources and demands. Contribution/value-add: This study builds on the literature of the JD-R model by showing that it can be used to predict work-based identity.

Psychological predictors of the antihypertensive effects of music-guided slow breathing.

Science.gov (United States)

Modesti, Pietro Amedeo; Ferrari, Antonella; Bazzini, Cristina; Costanzo, Giusi; Simonetti, Ignazio; Taddei, Stefano; Biggeri, Annibale; Parati, Gianfranco; Gensini, Gian Franco; Sirigatti, Saulo

2010-05-01

The possibility that daily sessions of music-guided slow breathing may reduce 24-h ambulatory blood pressure (ABP), and predictors of efficacy were explored in a randomized, placebo-controlled trial with parallel design. Age-matched and sex-matched hypertensive patients were randomized to music-guided slow breathing exercises (4-6 breaths/min; 1: 2 ratio of inspiration: expiration duration) (Intervention; n = 29) or to control groups who were thought to relax while either listening to slow music (Control-M; n = 26) or reading a book (Control-R; n = 31). At baseline and at follow-up visits (1 week and 1, 3 and 6 months), ABP monitoring was performed. At mixed model analysis, intervention was associated with a significant reduction of 24-h (P = 0.001) and night-time (0100-0600 h) (P music-guided slow breathing significantly reduce 24-h systolic ABP, and psychological predictors of efficacy can be identified.

Carbon conversion predictor for fluidized bed gasification of biomass fuels - from TGA measurements to char gasification particle model

Energy Technology Data Exchange (ETDEWEB)

Konttinen, J.T. [University of Jyvaeskylae, Department of Chemistry, Renewable Energy Programme, POB 35, Jyvaeskylae (Finland); Moilanen, A. [VTT Technical Research Centre of Finland, POB 1000, Espoo (Finland); Martini, N. de; Hupa, M. [Abo Akademi University, Process Chemistry Centre, Combustion and Materials Chemistry, Turku (Finland)

2012-09-15

When a solid fuel particle is injected into a hot fluidized bed, the reactivity of fuel char in gasification reactions (between char carbon and steam and CO{sub 2}) plays a significant role for reaching a good carbon conversion. In this paper, the gasification reactivity data of some solid waste recovered fuels (SRF) obtained from thermogravimetric analysis (TGA) experiments is presented. Gas mixtures (H{sub 2}O, H{sub 2}, CO{sub 2}, CO), were used in the experiments to find the inhibitive effects of CO and H{sub 2}. Average char gasification reactivity values are determined from the TGA results. Kinetic parameters for char carbon gasification reactivity correlations are determined from this data. The Uniform Conversion model is used to account for the change of gasification reaction rate as function of carbon conversion. Some discrepancies, due to complicated ash-carbon interactions, are subjects of further research. In the carbon conversion predictor, laboratory measured reactivity numbers are converted into carbon conversion numbers in a real-scale fluidized bed gasifier. The predictor is a relatively simple and transparent tool for the comparison of the gasification reactivity of different fuels in fluidized bed gasification. The residence times for solid fuels in fluidized bed gasifiers are simulated. Simulations against some pilot-scale results show reasonable agreement. (orig.)

Evaluating the influence of spatial resolution of Landsat predictors on the accuracy of biomass models for large-area estimation across the eastern USA

Science.gov (United States)

Deo, Ram K.; Domke, Grant M.; Russell, Matthew B.; Woodall, Christopher W.; Andersen, Hans-Erik

2018-05-01

Aboveground biomass (AGB) estimates for regional-scale forest planning have become cost-effective with the free access to satellite data from sensors such as Landsat and MODIS. However, the accuracy of AGB predictions based on passive optical data depends on spatial resolution and spatial extent of target area as fine resolution (small pixels) data are associated with smaller coverage and longer repeat cycles compared to coarse resolution data. This study evaluated various spatial resolutions of Landsat-derived predictors on the accuracy of regional AGB models at three different sites in the eastern USA: Maine, Pennsylvania-New Jersey, and South Carolina. We combined national forest inventory data with Landsat-derived predictors at spatial resolutions ranging from 30–1000 m to understand the optimal spatial resolution of optical data for large-area (regional) AGB estimation. Ten generic models were developed using the data collected in 2014, 2015 and 2016, and the predictions were evaluated (i) at the county-level against the estimates of the USFS Forest Inventory and Analysis Program which relied on EVALIDator tool and national forest inventory data from the 2009–2013 cycle and (ii) within a large number of strips (~1 km wide) predicted via LiDAR metrics at 30 m spatial resolution. The county-level estimates by the EVALIDator and Landsat models were highly related (R 2 > 0.66), although the R 2 varied significantly across sites and resolution of predictors. The mean and standard deviation of county-level estimates followed increasing and decreasing trends, respectively, with models of coarser resolution. The Landsat-based total AGB estimates were larger than the LiDAR-based total estimates within the strips, however the mean of AGB predictions by LiDAR were mostly within one-standard deviations of the mean predictions obtained from the Landsat-based model at any of the resolutions. We conclude that satellite data at resolutions up to 1000 m provide

Predictors of musculoskeletal discomfort: A cross-cultural comparison between Malaysian and Australian office workers.

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Maakip, Ismail; Keegel, Tessa; Oakman, Jodi

2017-04-01

Prevalence and predictors associated with musculoskeletal disorders (MSDs) vary considerably between countries. It is plausible that socio-cultural contexts may contribute to these differences. We conducted a cross-sectional survey with 1184 Malaysian and Australian office workers with the aim to examine predictors associated with MSD discomfort. The 6-month period prevalence of self-reported MSD discomfort for Malaysian office workers was 92.8% and 71.2% among Australian workers. In Malaysia, a model regressing level of musculoskeletal discomfort against possible risk factors was significant overall (F [6, 370] = 17.35; p work-life balance (β = -0.13). In Australia, the regression model is also significant (F [6, 539] = 16.47; p importance differed. Work-life balance was significantly associated with increased MSD discomfort for the Malaysian population only. Design and implementation of MSD risk management needs to take into account the work practices and culture of the target population. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Predictors of job satisfaction among Academic Faculty: Do instructional and clinical faculty differ?

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Chung, Kevin C.; Song, Jae W.; Kim, H. Myra; Woolliscroft, James O.; Quint, Elisabeth H.; Lukacs, Nicholas W.; Gyetko, Margaret R.

2010-01-01

Objectives To identify and compare predictors of job satisfaction between the instructional and clinical faculty tracks. Method A 61-item faculty job satisfaction survey was distributed to 1,898 academic faculty at the University of Michigan Medical School. The anonymous survey was web-based. Questions covered topics on departmental organization, research, clinical and teaching support, compensation, mentorship, and promotion. Levels of satisfaction were contrasted between the two tracks, and predictors of job satisfaction were identified using linear regression models. Results The response rates for the instructional and clinical tracks were 43.1% and 41.3%, respectively. Clinical faculty reported being less satisfied with how they are mentored, and fewer reported understanding the process for promotion. There was no significant difference in overall job satisfaction between faculty tracks. Surprisingly, clinical faculty with mentors were significantly less satisfied with how they were being mentored, with career advancement and overall job satisfaction, compared to instructional faculty mentees. Additionally, senior-level clinical faculty were significantly less satisfied with their opportunities to mentor junior faculty compared to senior-level instructional faculty. Significant predictors of job satisfaction for both tracks included areas of autonomy, meeting career expectations, work-life balance, and departmental leadership. Unique to the clinical track, compensation and career advancement variables also emerged as significant predictors. Conclusion Greater effort must be placed in the continued attention to faculty well-being both at the institutional level and at the level of departmental leadership. Success in enhancing job satisfaction is more likely if directed by locally designed assessments involving department chairs, specifically in fostering more effective mentoring relationships focused on making available career advancement activities such as

Moderation analysis with missing data in the predictors.

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Zhang, Qian; Wang, Lijuan

2017-12-01

The most widely used statistical model for conducting moderation analysis is the moderated multiple regression (MMR) model. In MMR modeling, missing data could pose a challenge, mainly because the interaction term is a product of two or more variables and thus is a nonlinear function of the involved variables. In this study, we consider a simple MMR model, where the effect of the focal predictor X on the outcome Y is moderated by a moderator U. The primary interest is to find ways of estimating and testing the moderation effect with the existence of missing data in X. We mainly focus on cases when X is missing completely at random (MCAR) and missing at random (MAR). Three methods are compared: (a) Normal-distribution-based maximum likelihood estimation (NML); (b) Normal-distribution-based multiple imputation (NMI); and (c) Bayesian estimation (BE). Via simulations, we found that NML and NMI could lead to biased estimates of moderation effects under MAR missingness mechanism. The BE method outperformed NMI and NML for MMR modeling with missing data in the focal predictor, missingness depending on the moderator and/or auxiliary variables, and correctly specified distributions for the focal predictor. In addition, more robust BE methods are needed in terms of the distribution mis-specification problem of the focal predictor. An empirical example was used to illustrate the applications of the methods with a simple sensitivity analysis. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Predictors of Discharge Disposition in Older Adults With Burns: A Study of the Burn Model Systems.

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Pham, Tam N; Carrougher, Gretchen J; Martinez, Erin; Lezotte, Dennis; Rietschel, Carly; Holavanahalli, Radha; Kowalske, Karen; Esselman, Peter C

2015-01-01

Older patients with burn injury have a greater likelihood for discharge to nursing facilities. Recent research indicates that older patients discharged to nursing facilities are two to three times as likely to die within a 3-year period relative to those discharged to home. In light of these poor long-term outcomes, we conducted this study to identify predictors for discharge to independent vs nonindependent living status in older patients hospitalized for burns. We retrospectively reviewed all older adults (age ≥ 55 years) who were prospectively enrolled in a longitudinal multicenter study of outcomes from 1993 to 2011. Patient, injury, and treatment outcomes data were analyzed. Recognizing that transfer to inpatient rehabilitation may have impacted final hospital discharge disposition: we assessed the likelihood of inpatient rehabilitation stay, based on identified predictors of inpatient rehabilitation. We subsequently performed a logistic regression analysis on the clustered, propensity-matched cohort to assess associations of burn and injury characteristics on the primary outcome of final discharge status. A total of 591 patients aged ≥55 years were treated and discharged alive from three participating U.S. burn centers during the study period. Mean burn size was 14.8% (SD 11.2%) and mean age was 66.7 years (SD 9.3 years). Ninety-three patients had an inpatient rehabilitation stay before discharge (15.7%). Significant factors predictive of inpatient rehabilitation included a burn >20% TBSA, mechanical ventilation, older age, range of motion deficits at acute care discharge, and study site. These factors were included in the propensity model. Four hundred seventy-one patients (80%) were discharged to independent living status. By matched propensity analysis, older age was significantly associated with a higher likelihood of discharge to nonindependent living (P burn centers need to be elucidated to better understand discharge disposition status in older

Gender and single nucleotide polymorphisms in MTHFR, BHMT, SPTLC1, CRBP2R, and SCARB1 are significant predictors of plasma homocysteine normalized by RBC folate in healthy adults.

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Using linear regression models, we studied the main and two-way interaction effects of the predictor variables gender, age, BMI, and 64 folate/vitamin B-12/homocysteine/lipid/cholesterol-related single nucleotide polymorphisms (SNP) on log-transformed plasma homocysteine normalized by red blood cell...

Comparison of Designated Coefficients and their Predictors in Functional Evaluation of Wheelchair Rugby Athletes

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Zwierzchowska Anna

2015-12-01

Full Text Available The objectives of the present study were twofold: to determine differences between groups by means of chosen coefficients and to create significant predictors using regression models for athletes in wheelchair rugby who had the same spinal cord injury (tetraplegia and were classified as low point and high point players. The study sample consisted of 24 subjects, who had sustained cervical spinal cord injury (CSCI. They were divided into low point (n=15 and high point (n=9 groups according to the IWRF Classification System. A one-way ANOVA revealed statistically significant differences in the following coefficients differentiating the groups: AC (η2=0.778, LC (η2=0.687, IC (η2=0.565, SC (η2=0.580. The Tukey’s HSD post-hoc test indicated statistically significant higher values of coefficients in the HP compared to the LP group: AC=0.958 (p=0.022, LC=0.989 (p=0.031, IC=0.971 (p=0.044, SC=0.938 (p=0.039. In the HP group, the most significant predictor was the sum of visceral and trunk fat which was negatively correlated with the SC (what constituted a positive adaptive change in response to training. With regard to the LP group, body height and circumference of the chest appeared to be most significant predictors and were positively correlated with the SC. In the LP group no predictor with respect to the SC was significantly correlated to sports training. Therefore, the functional classification system confirmed lower status of the LP players. The results of the present study indicate that both metabolic and somatic profiles which highly determine potential of wheelchair rugby athletes are significantly different in LP and HP players, what confirms the reliability of the functional classification system.

Predictors of stethoscope disinfection among pediatric health care providers.

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Muniz, Jeanette; Sethi, Rosh K V; Zaghi, Justin; Ziniel, Sonja I; Sandora, Thomas J

2012-12-01

Stethoscopes are contaminated with bacteria, but predictors of stethoscope disinfection frequency are unknown. We sought to describe health care provider stethoscope disinfection attitudes and practices and determine predictors of frequent disinfection. We used an anonymous online survey of nurses, nurse practitioners, and physicians at a pediatric hospital. We assessed frequency and methods of disinfection, perceptions of contamination, and barriers to disinfection. Multivariate logistic regression models were used to identify independent predictors of disinfecting after every use. One thousand four hundred one respondents completed the survey: 76% believed that infection transmission occurs via stethoscopes, but only 24% reported disinfecting after every use. In multivariate analyses, belief that infection transmission occurs via stethoscopes significantly increased the odds of disinfection after every use (odds ratio [OR], 2.06 [95% confidence interval (CI): 1.38-3.06]). The odds of disinfection after every use were significantly decreased in those who perceived the following barriers: lack of time (OR, 0.31 [95% CI: 0.18-0.54]), lack of access to disinfection material (OR, 0.41 [95% CI: 0.29-0.57]), or lack of visual reminders to disinfect (OR, 0.22 [95% CI: 0.14-0.34]). Only a minority of pediatric health care providers reported disinfecting their stethoscopes after every use. Increasing access to disinfection materials and visual reminders in health care facilities may improve stethoscope disinfection practices. Copyright © 2012 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Mosby, Inc. All rights reserved.

Family and Cultural Predictors of Depression among Samoan American Middle and High School Students

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Yeh, Christine J.; Borrero, Noah E.; Tito, Patsy

2013-01-01

This study investigated family intergenerational conflict and collective self-esteem as predictors of depression in a sample of 128 Samoan middle and high school students. Simultaneous regression analyses revealed that each independent variable significantly contributed to an overall model that accounted for 13% of the variance in depression.…

Predictors of initiation and persistence of unhealthy weight control behaviours in adolescents

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Haines Jess

2009-10-01

Full Text Available Abstract Background Unhealthy weight control behaviours (UWCB among adolescents have significant health and weight consequences. The current longitudinal study aimed to identify personal and socio-environmental predictors of initiation or persistence of adolescent UWCB, in order to inform development of programs aimed at both preventing and stopping UWCB. Methods A diverse sample included 1106 boys and 1362 girls from 31 middle schools and high schools in the United States who were enrolled in Project EAT (Eating Among Teens. Project EAT explored personal, behavioural, and socio-environmental factors associated with dietary intake and body weight in adolescence. Participants completed questionnaires to assess demographics, UWCB (including several methods of food restriction, purging by vomiting or medications, smoking to control weight, or food substitutions and personal and socio-environmental variables at two time points, five years apart, between 1998 and 2004. Logistic regression models examined personal and socio-environmental predictors of initiation and persistence of UWCB among Project EAT participants. Results Results indicate that 15.5% of boys and 19.7% of girls initiated UWCB by Time 2, and 15.9% of boys and 43.3% of girls persisted with these behaviours from Time 1 to Time 2. After controlling for race/ethnicity and weight status changes between assessments, logistic regression models indicated that similar factors and patterns of factors were associated significantly with initiation and persistence of UWCB. For both boys and girls, personal factors had more predictive value than socio-environmental factors (Initiation models: for boys: R2 = 0.35 for personal vs. 0.27 for socio-environmental factors; for girls, R2 = 0.46 for personal vs. 0.26 for socio-environmental factors. Persistence models: for boys: R2 = 0.53 for personal vs. 0.33 for socio-environmental factors; for girls, R2 = 0.41 for personal vs. 0.19 for socio

Neuropsychological predictors of performance-based measures of functional capacity and social skills in individuals with severe mental illness.

Science.gov (United States)

Mahmood, Zanjbeel; Burton, Cynthia Z; Vella, Lea; Twamley, Elizabeth W

2018-04-13

Neuropsychological abilities may underlie successful performance of everyday functioning and social skills. We aimed to determine the strongest neuropsychological predictors of performance-based functional capacity and social skills performance across the spectrum of severe mental illness (SMI). Unemployed outpatients with SMI (schizophrenia, bipolar disorder, or major depression; n = 151) were administered neuropsychological (expanded MATRICS Consensus Cognitive Battery), functional capacity (UCSD Performance-Based Skills Assessment-Brief; UPSA-B), and social skills (Social Skills Performance Assessment; SSPA) assessments. Bivariate correlations between neuropsychological performance and UPSA-B and SSPA total scores showed that most neuropsychological tests were significantly associated with each performance-based measure. Forward entry stepwise regression analyses were conducted entering education, diagnosis, symptom severity, and neuropsychological performance as predictors of functional capacity and social skills. Diagnosis, working memory, sustained attention, and category and letter fluency emerged as significant predictors of functional capacity, in a model that explained 43% of the variance. Negative symptoms, sustained attention, and letter fluency were significant predictors of social skill performance, in a model explaining 35% of the variance. Functional capacity is positively associated with neuropsychological functioning, but diagnosis remains strongly influential, with mood disorder participants outperforming those with psychosis. Social skill performance appears to be positively associated with sustained attention and verbal fluency regardless of diagnosis; however, negative symptom severity strongly predicts social skills performance. Improving neuropsychological functioning may improve psychosocial functioning in people with SMI. Published by Elsevier Ltd.

Cognitive predictors of children's development in mathematics achievement : A latent growth modeling approach

NARCIS (Netherlands)

Xenidou-Dervou, Iro; Van Luit, Johannes E H; Kroesbergen, Evelyn H; Friso-van den Bos, Ilona; Jonkman, Lisa M; van der Schoot, Menno; van Lieshout, Ernest C D M

2018-01-01

Research has identified various domain-general and domain-specific cognitive abilities as predictors of children's individual differences in mathematics achievement. However, research into the predictors of children's individual growth rates, namely between-person differences in within-person change

FUNCTIONAL ABILITIES AS PREDICTORS OF PREADOSLESCENT STUDENTS’ ATHLETIC RESULTS OUTCOME

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Miroljub Ivanović

2011-09-01

Full Text Available Aim of this research has been directed to the functional abilities relation testing (as predictors and athletic results (as criterion of students, who are VII and VIII grade of primary school (Χ= 13, 9 years; SD = 1, 17. The research has been conducted in Valjevo during November 2010. on the sample of 108 examinees. Variables’ sample has been assembled from 3 tests for functional abilities (maximal oxygen consumption, pulse frequency and vital lungs capacity evaluation and 4 athletic disciplines (high jump, long jump, shot put and 60 meters low start sprint from current physical education curriculum. Crombah-alfa coefficient values indicate to satisfactory reliability of applied instruments. In data processing canonical correlation analysis and multiple regression analysis have been used. Achieved canonical correlation analysis results showed that functional abilities set is statistically and significantly related to criterion variables set (R=.67, manifesting one canonical factor on the level p<.03. Achieved determination coefficient (R² = .43 indicates to functional abilities prognostic significance of explained variance 46% criterion. Using hierarchy regression model following statistically significant beta coefficient of functional abilities as partial predictors of athletics outcome have been determined: I for vital lungs capacity- high jump (β = .67, p < .01, II for vital lungs capacity- long jump (β = .55, p < .01, III for vital lungs capacity and pulse frequency- shot put (β =.-.34, p < .01; β =.42, p < .02 and IV for vital lungs capacity- 60 meters sprint (β = .-.39. Regression equation calculation of other applied functional abilities preadolescents’ predictor variables has not statistically and significantly contributed to univariance prediction of criterion variable variance

Detection of major climatic and environmental predictors of liver fluke exposure risk in Ireland using spatial cluster analysis.

Science.gov (United States)

Selemetas, Nikolaos; de Waal, Theo

2015-04-30

Fasciolosis caused by Fasciola hepatica (liver fluke) can cause significant economic and production losses in dairy cow farms. The aim of the current study was to identify important weather and environmental predictors of the exposure risk to liver fluke by detecting clusters of fasciolosis in Ireland. During autumn 2012, bulk-tank milk samples from 4365 dairy farms were collected throughout Ireland. Using an in-house antibody-detection ELISA, the analysis of BTM samples showed that 83% (n=3602) of dairy farms had been exposed to liver fluke. The Getis-Ord Gi* statistic identified 74 high-risk and 130 low-risk significant (Pclimatic variables (monthly and seasonal mean rainfall and temperatures, total wet days and rain days) and environmental datasets (soil types, enhanced vegetation index and normalised difference vegetation index) were used to investigate dissimilarities in the exposure to liver fluke between clusters. Rainfall, total wet days and rain days, and soil type were the significant classes of climatic and environmental variables explaining the differences between significant clusters. A discriminant function analysis was used to predict the exposure risk to liver fluke using 80% of data for modelling and the remaining subset of 20% for post hoc model validation. The most significant predictors of the model risk function were total rainfall in August and September and total wet days. The risk model presented 100% sensitivity and 91% specificity and an accuracy of 95% correctly classified cases. A risk map of exposure to liver fluke was constructed with higher probability of exposure in western and north-western regions. The results of this study identified differences between clusters of fasciolosis in Ireland regarding climatic and environmental variables and detected significant predictors of the exposure risk to liver fluke. Copyright © 2015 Elsevier B.V. All rights reserved.

Exploring Predictors of Information Use to Self-Manage Blood Pressure in Midwestern African American Women with Hypertension.

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Jones, Lenette M; Veinot, Tiffany; Pressler, Susan J; Coleman-Burns, Patricia; McCall, Alecia

2018-06-01

Self-management of hypertension requires patients to find, understand, and use information to lower their blood pressure. Little is known about information use among African American women with hypertension, therefore the purpose of this study was to examine predictors of self-reported information use to self-manage blood pressure. Ninety-four Midwestern African American women (mean age = 59) completed questionnaires about information behaviors (seeking, sharing, use) and personal beliefs (attitude, social norms) related to self-management of blood pressure. Linear regression was used to identify significant predictors of information use. The total variance explained by the model was 36%, F(7, 79) = 6.29, p < .001. Information sharing was the only significant predictor (beta = .46, p < .001). These results provide evidence that information sharing is a potential health behavior to support intervention strategies for African American women with hypertension.

Big Five Personality Traits as the Predictor of Teachers' Organizational Psychological Capital

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Bozgeyikli, Hasan

2017-01-01

The method of the research was defined as the descriptive survey model since it was aimed to test whether the personality traits of teachers are a significant predictor of their psychological capital levels in this study. 416 teachers (60.3% female, 39.7% male) who were teaching in the schools of Ministry of National Education in Istanbul and were…

Spatial modelling of marine organisms in Forsmark and Oskarshamn. Including calculation of physical predictor variables

Energy Technology Data Exchange (ETDEWEB)

Carlen, Ida; Nikolopoulos, Anna; Isaeus, Martin (AquaBiota Water Research, Stockholm (SE))

2007-06-15

GIS grids (maps) of marine parameters were created using point data from previous site investigations in the Forsmark and Oskarshamn areas. The proportion of global radiation reaching the sea bottom in Forsmark and Oskarshamn was calculated in ArcView, using Secchi depth measurements and the digital elevation models for the respective area. The number of days per year when the incoming light exceeds 5 MJ/m2 at the bottom was then calculated using the result of the previous calculations together with measured global radiation. Existing modelled grid-point data on bottom and pelagic temperature for Forsmark were interpolated to create surface covering grids. Bottom and pelagic temperature grids for Oskarshamn were calculated using point measurements to achieve yearly averages for a few points and then using regressions with existing grids to create new maps. Phytoplankton primary production in Forsmark was calculated using point measurements of chlorophyll and irradiance, and a regression with a modelled grid of Secchi depth. Distribution of biomass of macrophyte communities in Forsmark and Oskarshamn was calculated using spatial modelling in GRASP, based on field data from previous surveys. Physical parameters such as those described above were used as predictor variables. Distribution of biomass of different functional groups of fish in Forsmark was calculated using spatial modelling based on previous surveys and with predictor variables such as physical parameters and results from macrophyte modelling. All results are presented as maps in the report. The quality of the modelled predictions varies as a consequence of the quality and amount of the input data, the ecology and knowledge of the predicted phenomena, and by the modelling technique used. A substantial part of the variation is not described by the models, which should be expected for biological modelling. Therefore, the resulting grids should be used with caution and with this uncertainty kept in mind. All

Spatial modelling of marine organisms in Forsmark and Oskarshamn. Including calculation of physical predictor variables

International Nuclear Information System (INIS)

Carlen, Ida; Nikolopoulos, Anna; Isaeus, Martin

2007-06-01

GIS grids (maps) of marine parameters were created using point data from previous site investigations in the Forsmark and Oskarshamn areas. The proportion of global radiation reaching the sea bottom in Forsmark and Oskarshamn was calculated in ArcView, using Secchi depth measurements and the digital elevation models for the respective area. The number of days per year when the incoming light exceeds 5 MJ/m2 at the bottom was then calculated using the result of the previous calculations together with measured global radiation. Existing modelled grid-point data on bottom and pelagic temperature for Forsmark were interpolated to create surface covering grids. Bottom and pelagic temperature grids for Oskarshamn were calculated using point measurements to achieve yearly averages for a few points and then using regressions with existing grids to create new maps. Phytoplankton primary production in Forsmark was calculated using point measurements of chlorophyll and irradiance, and a regression with a modelled grid of Secchi depth. Distribution of biomass of macrophyte communities in Forsmark and Oskarshamn was calculated using spatial modelling in GRASP, based on field data from previous surveys. Physical parameters such as those described above were used as predictor variables. Distribution of biomass of different functional groups of fish in Forsmark was calculated using spatial modelling based on previous surveys and with predictor variables such as physical parameters and results from macrophyte modelling. All results are presented as maps in the report. The quality of the modelled predictions varies as a consequence of the quality and amount of the input data, the ecology and knowledge of the predicted phenomena, and by the modelling technique used. A substantial part of the variation is not described by the models, which should be expected for biological modelling. Therefore, the resulting grids should be used with caution and with this uncertainty kept in mind. All

Predictors of Hospitalization Among Newly Admitted Skilled Nursing Facility Residents: Rethinking the Role of Functional Decline

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Sun J. Kim

2014-05-01

Full Text Available Purpose: Hospital transfer from a skilled nursing facility (SNF is costly, and many are potentially preventable. This study examines: 1 whether functional decline is a predictor of hospital transfer, and 2 the magnitude of relationships between predictors (functional impairment and chronic medical illness and hospital transfer from SNFs. Methods: We used Minimum Data Set (MDS Version 2.0 in the state of Michigan between 2007 and 2009. In total, 196,662 new SNF admissions were observed. Multilevel generalized estimating equations and regression models were performed for each functional and clinical domain while adjusting for demographic variables and change in activities of daily living (ADL. Results: 65% of recently admitted SNF residents experienced functional decline after SNF admission, and 58% were readmitted to a hospital. Residents who needed extensive assistance or were completely dependent in their functional domains had pressure ulcers, deteriorated mood or lower cognitive performance scale scores. These residents experienced higher chances of hospital transfer. However, a deteriorated ADL played a significant role in all multivariate models, indicating that a decline in ADL is a stronger predictor of hospital transfer than other functional or clinical predictors. Conclusion: Although all functional impairments and chronic medical illness can be associated with hospital transfer, functional decline may be the most important predictor of hospital transfer in patients newly admitted to an SNF.

Predictors of effects of lifestyle intervention on diabetes mellitus type 2 patients.

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Jacobsen, Ramune; Vadstrup, Eva; Røder, Michael; Frølich, Anne

2012-01-01

The main aim of the study was to identify predictors of the effects of lifestyle intervention on diabetes mellitus type 2 patients by means of multivariate analysis. Data from a previously published randomised clinical trial, which compared the effects of a rehabilitation programme including standardised education and physical training sessions in the municipality's health care centre with the same duration of individual counseling in the diabetes outpatient clinic, were used. Data from 143 diabetes patients were analysed. The merged lifestyle intervention resulted in statistically significant improvements in patients' systolic blood pressure, waist circumference, exercise capacity, glycaemic control, and some aspects of general health-related quality of life. The linear multivariate regression models explained 45% to 80% of the variance in these improvements. The baseline outcomes in accordance to the logic of the regression to the mean phenomenon were the only statistically significant and robust predictors in all regression models. These results are important from a clinical point of view as they highlight the more urgent need for and better outcomes following lifestyle intervention for those patients who have worse general and disease-specific health.

Predictors of length of stay in a ward for demented elderly: gender differences.

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Ono, Toshiyuki; Tamai, Akira; Takeuchi, Daisuke; Tamai, Yuzuru; Iseki, Hidenori; Fukushima, Hiromi; Kasahara, Sumie

2010-09-01

In our previous studies, we found both gender differences among care recipients and predictors that influenced outcomes after discharge from a ward for demented elderly. Here, we investigate predictors that influence the length of stay for each sex. We studied the data of 390 patients with dementia who were hospitalized in a ward for demented elderly between 1 April 2000 and 31 March 2008, and treated until 31 March 2009. The patients were divided into groups classified by gender. We analyzed the gender differences of characteristics and evaluated the predictors that influenced the length of stay in the ward for demented elderly using Cox's proportional hazards model. A model using the initial scores of the Revised Hasegawa Dementia Scale (HDS-R), Assessment Scale for Symptoms of Dementia (ASSD) and Nishimura's activity of daily living scale (N-ADL), which were examined on admission, was named Model 1. In Model 1, we checked the effect of each patient's characteristics, except for complications and destinations, on their length of stay. Model 2 used the final scores of HDS-R, ASSD and N-ADL including complications and destinations. There was a clear gender difference in the length of stay. The length of stay of women was longer than that of men. It was difficult to predict the length of stay in Model 1. Age was the only predictor in women and no predictor was identified in men. In Model 2, complications and the final HDS-R and N-ADL scores were predictors of the length of stay in men. Age, complications and destinations were predictors of the length of stay in women. It was observed that there were gender differences among predictors of the length of stay. However, it was difficult to predict the length of stay on admission. Retrospectively, the length of stay was determined by physical and psychological conditions, not by the social variables in men. In women, it was supposed that the caregiver's wish to give care at home reduced the length of stay. Besides

Feminist identity as a predictor of eating disorder diagnostic status.

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Green, Melinda A; Scott, Norman A; Riopel, Cori M; Skaggs, Anna K

2008-06-01

Passive Acceptance (PA) and Active Commitment (AC) subscales of the Feminist Identity Development Scale (FIDS) were examined as predictors of eating disorder diagnostic status as assessed by the Questionnaire for Eating Disorder Diagnoses (Q-EDD). Results of a hierarchical regression analysis revealed PA and AC scores were not statistically significant predictors of ED diagnostic status after controlling for diagnostic subtype. Results of a multiple regression analysis revealed FIDS as a statistically significant predictor of ED diagnostic status when failing to control for ED diagnostic subtype. Discrepancies suggest ED diagnostic subtype may serve as a moderator variable in the relationship between ED diagnostic status and FIDS. (c) 2008 Wiley Periodicals, Inc.

Genetic Algorithm Tuning of PID Controller in Smith Predictor for Glucose Concentration Control

OpenAIRE

Tsonyo Slavov; Olympia Roeva

2011-01-01

This paper focuses on design of a glucose concentration control system based on nonlinear model plant of E. coli MC4110 fed-batch cultivation process. Due to significant time delay in real time glucose concentration measurement, a correction is proposed in glucose concentration measurement and a Smith predictor (SP) control structure based on universal PID controller is designed. To reduce the influence of model error in SP structure the estimate of measured glucose concentration is used. For...

Psychological Predictors of Anabolic Steroid Use: An Exploratory Study.

Science.gov (United States)

Schwerin, Michael J.; Corcoran, Kevin J.; LaFleur, Bonnie J.; Fisher, Leslee; Patterson, David; Olrich, Tracy

1997-01-01

Examined social physique anxiety, upper body esteem, social anxiety, and body dissatisfaction as possible predictors of anabolic steroid (AS) use. Results based on 185 AS-using bodybuilders and various control groups indicated that the upper body strength subscale of two measures, along with age, were significant predictors of AS use. (RJM)

Carboxyhemoglobin levels as a predictor of risk for significant hyperbilirubinemia in African-American DAT(+) infants.

Science.gov (United States)

Schutzman, D L; Gatien, E; Ajayi, S; Wong, R J

2016-05-01

To compare the degree of hemolysis in a group of direct antiglobulin test (DAT) positive (pos) African-American (AA) infants as measured by carboxyhemoglobin corrected (COHbc) for carbon monoxide in ambient air to a similar group of DAT negative (neg) ABO incompatible infants and a group without blood group incompatibility. To determine if COHbc is a better predictor of significant hyperbilirubinemia than DAT status. A prospective study of 180 AA infants from the Well-Baby Nursery of an inner city community hospital, all of whose mothers were type O pos. Infants (60) were ABO incompatible DAT pos, 60 were ABO incompatible DAT neg and 60 were type O(+). Blood for COHbc was drawn at the time of the infants' initial bilirubin and the infants' precise percentile on the Bhutani nomogram was calculated. Mean COHbc of type O(+) infants was 0.76±0.21 and 0.78±0.24% for ABO incompatible DAT neg infants (P=0.63). Mean CoHbc for the ABO incompatible DAT pos infants was 1.03±0.41% (P0.90% (area under the curve(AUC) 0.8113). This was similar to the AUC of the receiver operating characteristic curve using any titer strength of DAT pos as a cutoff (0.7960). Although not greatly superior to the titer strength of DAT pos, COHbc is useful in determining if the etiology of severe hyperbilirubinemia is a hemolytic process.

Predictors of Traditional Medical Practices in Illness Behavior in Northwestern Ethiopia: An Integrated Model of Behavioral Prediction Based Logistic Regression Analysis

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Abenezer Yared

2017-01-01

Full Text Available This study aimed at investigating traditional medical beliefs and practices in illness behavior as well as predictors of the practices in Gondar city, northwestern Ethiopia, by using the integrated model of behavioral prediction. A cross-sectional quantitative survey was conducted to collect data through interviewer administered structured questionnaires from 496 individuals selected by probability proportional to size sampling technique. Unadjusted bivariate and adjusted multivariate logistic regression analyses were performed, and the results indicated that sociocultural predictors of normative response and attitude as well as psychosocial individual difference variables of traditional understanding of illness causation and perceived efficacy had statistically significant associations with traditional medical practices. Due to the influence of these factors, majority of the study population (85% thus relied on both herbal and spiritual varieties of traditional medicine to respond to their perceived illnesses, supporting the conclusion that characterized the illness behavior of the people as mainly involving traditional medical practices. The results implied two-way medicine needs to be developed with ongoing research, and health educations must take the traditional customs into consideration, for integrating interventions in the health care system in ways that the general public accepts yielding a better health outcome.

Bagging Weak Predictors

DEFF Research Database (Denmark)

Lukas, Manuel; Hillebrand, Eric

Relations between economic variables can often not be exploited for forecasting, suggesting that predictors are weak in the sense that estimation uncertainty is larger than bias from ignoring the relation. In this paper, we propose a novel bagging predictor designed for such weak predictor variab...

Predictors and consequences of job insecurity: Comparison of Slovakia and Estonia

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Lucia Ištoňová

2016-03-01

Full Text Available Job insecurity is a significant current social issue in many European countries. Slovakia and Estonia significantly differ in the prevalence of job insecurity. The main aim of the present study was to compare Slovakia and Estonia in regard to job insecurity by looking at socio-demographic, job and organisational predictors and individual and social consequences based on ESS round five data. The secondary aim was to examine relationships between job insecurity and its predictors as well as job insecurity and its consequences. The analysis covered employed people with unlimited or limited contracts, working 40-50 hours per week, within the age range of 20-60. The results suggested significant differences in the predictors of job insecurity for Slovakia and Estonia. However, the individual, social and economic consequences of job insecurity were similar for both countries. This study contributes to an enhanced understanding of job insecurity predictors and consequences in the European region.

Examining a Stage-Based Intervention and Predictors of Exercise Behavior among Iranian Sedentary Adolescents

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Zeinab Ghiami

2015-01-01

Full Text Available This study evaluated the effect of an intervention based on Transtheoretical Model on exercise behavior and examined TTM constructs as predictors of stages of change among Iranian adolescents. Fifty-six sedentary adolescents completed an assessment at baseline, 2 months, and 4 months. Repeated measures ANOVA and logistic regression were used to analyze the data. The analysis showed a statistically significant difference in the mean scores on stages of change for the experimental group. Thus, students in the experiment group significantly improved their stages compared to the baseline. Furthermore, stages of change were found to correlate with TTM constructs, and self-efficacy was shown to be a strong predictor of stages of change. This study indicated that a stage-based intervention using TTM constructs could effectively improve adolescents’ intention to engage in physical activity. Moreover, the level of physical activity in adolescent can be improved by increasing their self-efficacy to exercise. Keywords: Physical Activity; Stage of Change; Processes of Change; Decisional Balance; Self-efficacy; Transtheoretical Model

Predictors of success after laparoscopic gastric bypass: a multivariate analysis of socioeconomic factors.

Science.gov (United States)

Lutfi, R; Torquati, A; Sekhar, N; Richards, W O

2006-06-01

Laparoscopic gastric bypass (LGB) has proven efficacy in causing significant and durable weight loss. However, the degree of postoperative weight loss and metabolic improvement varies greatly among individuals. Our study is aimed to identify independent predictors of successful weight loss after LGB. Socioeconomic demographics were prospectively collected on patients undergoing LGB. Primary endpoint was percent of excess weight loss (EWL) at 1-year follow-up. Insufficient weight loss was defined as EWL or=52.8%. According to this definition, 147 patients (81.7%) achieved successful weight loss 1 year after LGB. On univariate analysis, preoperative BMI had a significant effect on EWL, with patients with BMI vs 61.6%; p = 0.001). Marriage status was also a significant predictor of successful outcome, with single patients achieving a higher percentage of EWL than married patients (89.8% vs 77.7%; p = 0.04). Race had a noticeable but not statistically significant effect, with Caucasian patients achieving a higher percentage of EWL than African Americans (82.9% vs 60%; p = 0.06). Marital status remained an independent predictor of success in the multivariate logistic regression model after adjusting for covariates. Married patients were at more than two times the risk of failure compared to those who were unmarried (OR 2.6; 95% CI: 1.1-6.5, p = 0.04). Weight loss achieved at 1 year after LGB is suboptimal in superobese patients. Single patients with BMI < 50 had the best chance of achieving greater weight loss.

Dragon polya spotter: Predictor of poly(A) motifs within human genomic DNA sequences

KAUST Repository

Kalkatawi, Manal M.; Rangkuti, Farania; Schramm, Michael C.; Jankovic, Boris R.; Kamau, Allan; Chowdhary, Rajesh; Archer, John A.C.; Bajic, Vladimir B.

2011-01-01

. These models are trained to recognize 12 most common poly(A) motifs in human DNA. Our predictors are available as a free web-based tool accessible at http://cbrc.kaust.edu.sa/dps. Compared with other reported predictors, our models achieve higher sensitivity

Predictors of mental health competence in a population cohort of Australian children.

Science.gov (United States)

Goldfeld, Sharon; Kvalsvig, Amanda; Incledon, Emily; O'Connor, Meredith; Mensah, Fiona

2014-05-01

The child mental health epidemiology literature focuses almost exclusively on reporting the prevalence and predictors of child mental disorders. However, there is growing recognition of positive mental health or mental health competence as an independent outcome that cannot be inferred from the absence of problems, and requires epidemiological investigation in its own right. We developed a novel measure of child mental health competence within the framework of the Australian Early Development Index, a three-yearly national census of early child development. Predictors of this outcome were investigated by linking these census data at individual level to detailed background information collected by a large longitudinal cohort study. Predictors of competence were consistent with previously described theoretical and empirical models. Overall, boys were significantly less likely than girls to demonstrate a high level of competence (OR 0.60, 95% CI 0.39 to 0.91). Other strong predictors of competence were parent education and a relative absence of maternal psychological distress; these factors also appeared to attenuate the negative effect of family hardship on child competence. This measure of mental health competence shows promise as a population-level indicator with the potential benefit of informing and evaluating evidence-based public health intervention strategies that promote positive mental health.

On the Identification of Associations between Five World Health Organization Water, Sanitation and Hygiene Phenotypes and Six Predictors in Low and Middle-Income Countries.

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Ellis, Hugh; Schoenberger, Erica

2017-01-01

According to the most recent estimates, 842,000 deaths in low- to middle-income countries were attributable to inadequate water, sanitation and hygiene in 2012. Despite billions of dollars and decades of effort, we still lack a sound understanding of which kinds of WASH interventions are most effective in improving public health outcomes, and an important corollary-whether the right things are being measured. The World Health Organization (WHO) has made a concerted effort to compile comprehensive data on drinking water quality and sanitation in the developing world. A recent 2014 report provides information on three phenotypes (responses): Unsafe Water Deaths, Unsafe Sanitation Deaths, Unsafe Hygiene Deaths; two grouped phenotypes: Unsafe Water and Sanitation Deaths and Unsafe Water, Sanitation and Hygiene Deaths; and six explanatory variables (predictors): Improved Sanitation, Unimproved Water Source, Piped Water To Premises, Other Improved Water Source, Filtered and Bottled Water in the Household and Handwashing. Regression analyses were performed to identify statistically significant associations between these mortality responses and predictors. Good fitted-model performance required: (1) the use of population-normalized death fractions as opposed to number of deaths; (2) transformed response (logit or power); and (3) square-root predictor transformation. Given the complexity and heterogeneity of the relationships and countries being studied, these models exhibited remarkable performance and explained, for example, about 85% of the observed variance in population-normalized Unsafe Sanitation Death fraction, with a high F-statistic and highly statistically significant predictor p-values. Similar performance was found for all other responses, which was an unexpected result (the expected associations between responses and predictors-i.e., water-related with water-related, etc. did not occur). The set of statistically significant predictors remains the same across

On the Identification of Associations between Five World Health Organization Water, Sanitation and Hygiene Phenotypes and Six Predictors in Low and Middle-Income Countries.

Directory of Open Access Journals (Sweden)

Hugh Ellis

Full Text Available According to the most recent estimates, 842,000 deaths in low- to middle-income countries were attributable to inadequate water, sanitation and hygiene in 2012. Despite billions of dollars and decades of effort, we still lack a sound understanding of which kinds of WASH interventions are most effective in improving public health outcomes, and an important corollary-whether the right things are being measured. The World Health Organization (WHO has made a concerted effort to compile comprehensive data on drinking water quality and sanitation in the developing world. A recent 2014 report provides information on three phenotypes (responses: Unsafe Water Deaths, Unsafe Sanitation Deaths, Unsafe Hygiene Deaths; two grouped phenotypes: Unsafe Water and Sanitation Deaths and Unsafe Water, Sanitation and Hygiene Deaths; and six explanatory variables (predictors: Improved Sanitation, Unimproved Water Source, Piped Water To Premises, Other Improved Water Source, Filtered and Bottled Water in the Household and Handwashing.Regression analyses were performed to identify statistically significant associations between these mortality responses and predictors. Good fitted-model performance required: (1 the use of population-normalized death fractions as opposed to number of deaths; (2 transformed response (logit or power; and (3 square-root predictor transformation. Given the complexity and heterogeneity of the relationships and countries being studied, these models exhibited remarkable performance and explained, for example, about 85% of the observed variance in population-normalized Unsafe Sanitation Death fraction, with a high F-statistic and highly statistically significant predictor p-values. Similar performance was found for all other responses, which was an unexpected result (the expected associations between responses and predictors-i.e., water-related with water-related, etc. did not occur. The set of statistically significant predictors remains the

Environmental and social-demographic predictors of the southern house mosquito Culex quinquefasciatus in New Orleans, Louisiana.

Science.gov (United States)

Moise, Imelda K; Riegel, Claudia; Muturi, Ephantus J

2018-04-17

Understanding the major predictors of disease vectors such as mosquitoes can guide the development of effective and timely strategies for mitigating vector-borne disease outbreaks. This study examined the influence of selected environmental, weather and sociodemographic factors on the spatial and temporal distribution of the southern house mosquito Culex quinquefasciatus Say in New Orleans, Louisiana, USA. Adult mosquitoes were collected over a 4-year period (2006, 2008, 2009 and 2010) using CDC gravid traps. Socio-demographic predictors were obtained from the United States Census Bureau, 2005-2009 American Community Survey and the City of New Orleans Department of Code Enforcement. Linear mixed effects models and ERDAS image processing software were used for statistical analysis and image processing. Only two of the 22 predictors examined were significant predictors of Cx. quinquefasciatus abundance. Mean temperature during the week of mosquito collection was positively associated with Cx. quinquefasciatus abundance while developed high intensity areas were negatively associated with Cx. quinquefasciatus abundance. The findings of this study illustrate the power and utility of integrating biophysical and sociodemographic data using GIS analysis to identify the biophysical and sociodemographic processes that increase the risk of vector mosquito abundance. This knowledge can inform development of accurate predictive models that ensure timely implementation of mosquito control interventions.

Predictors of Relationship Power among Drug-involved Women

OpenAIRE

Campbell, Aimee N. C.; Tross, Susan; Hu, Mei-chen; Pavlicova, Martina; Nunes, Edward V.

2012-01-01

Gender-based relationship power is frequently linked to women’s capacity to reduce sexual risk behaviors. This study offers an exploration of predictors of relationship power, as measured by the multidimensional and theoretically grounded Sexual Relationship Power Scale (SRPS), among women in outpatient substance abuse treatment. Linear models were used to test nine predictors (age, race/ethnicity, education, time in treatment, economic dependence, substance use, sexual concurrency, partner a...

Predictors of job satisfaction among academic faculty members: do instructional and clinical staff differ?

Science.gov (United States)

Chung, Kevin C; Song, Jae W; Kim, H Myra; Woolliscroft, James O; Quint, Elisabeth H; Lukacs, Nicholas W; Gyetko, Margaret R

2010-10-01

This study aimed to identify and compare predictors of job satisfaction between instructional and clinical faculty members. A 61-item faculty job satisfaction survey was distributed to 1898 academic faculty members at the University of Michigan Medical School. The anonymous survey was web-based. Questions covered topics on departmental organisation, research, clinical and teaching support, compensation, mentorship, and promotion. Levels of satisfaction were contrasted between faculty members on the two tracks, and predictors of job satisfaction were identified using linear regression models. Response rates for the instructional and clinical faculty groups were 43.1% and 46.7%, respectively. Clinical faculty members reported being less satisfied with how they were mentored and fewer reported understanding the process for promotion. There was no significant difference in overall job satisfaction between the two faculty groups. Surprisingly, clinical faculty members with mentors were significantly less satisfied with how they were mentored and with career advancement, and were significantly less likely to choose an academic career if they had to do it all over again compared with instructional faculty mentees. Additionally, senior-level clinical faculty members were significantly less satisfied with their opportunities to mentor junior faculty members compared with senior-level instructional faculty staff. Significant predictors of job satisfaction for both groups included areas of autonomy, meeting career expectations, work-life balance, and departmental leadership. In the clinical track only, compensation and career advancement variables also emerged as significant predictors of overall job satisfaction. Greater emphasis must be placed on faculty members' well-being at both the institutional level and the level of departmental leadership. Efforts to enhance job satisfaction and improve retention are more likely to succeed if they are directed by locally designed

Statistical downscaling based on dynamically downscaled predictors: Application to monthly precipitation in Sweden

Science.gov (United States)

Hellström, Cecilia; Chen, Deliang

2003-11-01

A prerequisite of a successful statistical downscaling is that large-scale predictors simulated by the General Circulation Model (GCM) must be realistic. It is assumed here that features smaller than the GCM resolution are important in determining the realism of the large-scale predictors. It is tested whether a three-step method can improve conventional one-step statistical downscaling. The method uses predictors that are upscaled from a dynamical downscaling instead of predictors taken directly from a GCM simulation. The method is applied to downscaling of monthly precipitation in Sweden. The statistical model used is a multiple regression model that uses indices of large-scale atmospheric circulation and 850-hPa specific humidity as predictors. Data from two GCMs (HadCM2 and ECHAM4) and two RCM experiments of the Rossby Centre model (RCA1) driven by the GCMs are used. It is found that upscaled RCA1 predictors capture the seasonal cycle better than those from the GCMs, and hence increase the reliability of the downscaled precipitation. However, there are only slight improvements in the simulation of the seasonal cycle of downscaled precipitation. Due to the cost of the method and the limited improvements in the downscaling results, the three-step method is not justified to replace the one-step method for downscaling of Swedish precipitation.

Religiosity and Authoritarianism as Predictors of Attitude toward the Disabled: A Regression Analysis.

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Tunick, Roy H.; And Others

1979-01-01

This study identifies predictors and correlates of attitudes toward the disabled. Authoritarianism, church attendance, religious orthodoxy, age, and education were significantly related to these attitudes of people in a Rocky Mountain Community. Significant predictors of the criterion were authoritarianism, religiosity, and age. Recommendations…

Insight, rumination, and self-reflection as predictors of well-being.

Science.gov (United States)

Harrington, Rick; Loffredo, Donald A

2011-01-01

Dispositional private self-focused attention variables such as insight, internal self-awareness (ISA), and self-reflectiveness (SR) have been found to relate to well-being. The present study sought to determine which dispositional private self-focused attention variables have the most predictive power for subjective well-being as measured by the Satisfaction With Life Scale (E. Diener, R. A. Emmons, R. J. Larsen, & S. Griffin, 1985) and for a eudaemonic form of well-being as measured by the Psychological Well-Being Scale (C. D. Ryff, 1989). A total of 121 college student participants completed an online version of the Self-Consciousness Scale-Revised, the Rumination-Reflection Questionnaire, the Self-Reflection and Insight Scale, the Satisfaction With Life Scale, and the Psychological WellBeing Scale. Results of a multivariate regression analysis using the Self-Consciousness Scale-Revised's (M. F. Scheier & C. S. Carver, 1985) subfactors of SR and ISA, the Rumination-Reflection Questionnaire's (P. D. Trapnell & J. D. Campbell, 1999) subscales of Rumination and Reflection, and the Self-Reflection and Insight Scale's (A. M. Grant, J. Franklin, & P. Langford, 2002) Self-Reflection and Insight subscales revealed that the Insight subscale was the only statistically significant predictor (a positive predictor) for all 6 dimensions of psychological well-being. Insight was also the only significant positive predictor for satisfaction with life. The Rumination subscale was a significant negative predictor for 3 dimensions of psychological well-being, and the Reflection subscale was a significant positive predictor for 1 dimension. Implications of dispositional self-awareness variables and their relation to dimensions of well-being are discussed.

Differences in Psychosocial Predictors of Obesity Among LGBT Subgroups.

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Warren, Jacob C; Smalley, K Bryant; Barefoot, K Nikki

2016-08-01

The purpose of the current study was to examine the overall presence of and differences in rates of overweight/obesity among a large, nationally diverse sample of lesbian, gay, bisexual, transgender (LGBT)-identified individuals (i.e., cisgender lesbians, cisgender gay men, cisgender bisexual women, cisgender bisexual men, transgender women, and transgender men) and to identify specific psychosocial predictors of obesity within each of the six LGBT subgroups. A total of 2702 LGBT-identified participants participated in the online study. Participants completed a series of demographic questions (including weight and height) and the Depression Anxiety Stress Scale 21. The percentage of participants who were overweight/obese did not differ significantly across LGBT subgroups, with 61.1% of the total sample being overweight/obese. However, the percentage of participants who self-reported body mass indexes in the obese range differed significantly across the six LGBT subgroups, with the highest prevalence in transgender men (46.0%). In addition, the predictors of obesity varied by subgroup, with age a significant predictor for cisgender lesbians, cisgender gay men, and cisgender bisexual women, relationship status for cisgender bisexual women, employment status for both cisgender gay men and cisgender bisexual women, education level for cisgender lesbians, and depression, anxiety, and stress for cisgender gay men. None of the examined psychosocial factors emerged as predictors of obesity for cisgender bisexual men, transgender women, or transgender men. These findings suggest that there are substantial variations in the presence and predictors of obesity across LGBT subgroups that support the need for culturally tailored healthy weight promotion efforts within the LGBT community.

The use of the health belief model to assess predictors of intent to receive the novel (2009 H1N1 influenza vaccine

Directory of Open Access Journals (Sweden)

Jean-Venable “Kelly” R.Goode, PharmD, BCPS, FAPhA, FCCP

2012-01-01

Full Text Available Objectives: 1 Assess participants’ perceptions of severity, risk, and susceptibility to the novel H1N1 influenza virus and/or vaccine, vaccine benefits and barriers, and cues to action and 2 Identify predictors of participants’ intention to receive the novel H1N1 vaccine.Design: Cross-sectional, descriptive studySetting: Local grocery store chain and university in the central Virginia areaParticipants: Convenience sample of adult college students and grocery store patronsIntervention: Participants filled out an anonymous, self-administered questionnaire based upon the Health Belief Model.Main Outcome Measures: Participants’ predictors of intention to receive the novel H1N1 vaccineResults: A total of 664 participants completed a questionnaire. The majority of participants were aged 25-64 years old (66.9%. The majority were female (69.1%, Caucasian (73.7%, and felt at risk for getting sick from the virus (70.3%. Most disagreed that they would die from the virus (68.0%. Participants received novel H1N1 vaccine recommendations from their physicians (28.2%, pharmacists (20.7%, and nurses (16.1%. The majority intended to receive the H1N1 vaccine (58.1%. Participants were significantly more likely to intend to receive the H1N1 vaccine if they had lower scores on the perceived vaccine barriers domain (OR= 0.57, CI: 0.35-0.93. Physicians’ recommendations (OR=0.26, CI: 0.11-0.62 and 2008 seasonal flu vaccination (OR=0.45, CI: 0.24-0.83 were significant predictors of intention to receive the H1N1 vaccine.Conclusions: Most participants felt at risk for getting the novel H1N1 virus and intended to receive the novel H1N1 vaccine. Educating patients about vaccine benefits and increasing healthcare professionals' vaccine recommendations may increase vaccination rates in future pandemics.

Significant Independent Predictors of Vitamin D Deficiency in Inpatients and Outpatients of a Nephrology Unit

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Recep Bentli

2013-01-01

Full Text Available Aims. Kidney disease was found to be a major risk factor for vitamin D deficiency in a population study of patients hospitalized. The aims of the study were to describe the prevalence of vitamin D deficiency inpatients and outpatients in a nephrology department during fall and to evaluate effect of assessing serum 25-hydroxyvitamin D (25(OHD levels and previous supplementation of cholecalciferol on vitamin D status. Methods. We studied 280 subjects in total, between October and January. The subjects were recruited from the following two groups: (a inpatients and (b outpatients in nephrology unit. We examined previous documentary evidence of vitamin D supplementation of the patients. Results. The prevalence of vitamin D deficiency among these 280 patients was 62,1% (174 patients. Fifty-three patients (18.9% had severe vitamin D deficiency, 121 patients (43.2% moderate vitamin D deficiency, and 66 patients (23.6% vitamin D insufficiency. In logistic regression analysis female gender, not having vitamin D supplementation history, low serum albumin, and low blood urea nitrogen levels were significant independent predictors of vitamin D deficiency while no association of vitamin D deficiency with diabetes mellitus, serum creatinine, eGFR, and being hospitalized was found. Conclusion. Vitamin D deficiency, seems to be an important problem in both inpatients and outpatients of nephrology. Monitoring serum 25(OHD concentrations regularly and replacement of vitamin D are important. Women in Turkey are at more risk of deficiency and may therefore need to consume higher doses of vitamin D.

[A systematic review of the predictors of return to work following vocational retraining].

Science.gov (United States)

Streibelt, M; Egner, U

2013-04-01

Vocational Rehabilitation (VR) is an essential element of interventions aimed at re-integrating people with work disability into work. In this context, vocational retraining is of special importance. However, the success of vocational retraining, represented by subsequent returning to work (RTW), is only to a limited extent attributable to intervention quality. Apart from methodical influences participant-related as well as context-related attributes are discussed as influencing factors. To know these RTW predictors is a necessary condition for a valid comparative evaluation of intervention quality. A structured literature search was conducted. All studies meeting the following criteria were included: publication between 2006 and 2011; context: German rehabilitation system and vocational retraining; multivariate analysis of RTW predictors. The evidence for or against the influence of a predictor was rated as strong if more than 75% of the models, and moderate if more than 50% of the models reported or excluded a significant relationship between predictor and RTW. All predictors included in more than 2 studies were considered in this review. 15 publications from 6 studies were included in the analysis. Due to differentiation of the models between different types of retraining the evidence was based on 9 prediction models. Strong evidence of an effect on RTW can be assumed for income before admission, subjective health rating and regular completion of retraining. There is moderate evidence for an effect of age and target job. Strong evidence against an effect on RTW is found for employment and occupational status before admission. There is moderate evidence against an RTW effect of sex, education and locus of control. Ambiguous evidence is obtained for the local job market, the type of retraining, social support and mobility. For the first time the review provides findings on the relevant influence factors of RTW following vocational retraining. These findings on the

One-leg balance is an important predictor of injurious falls in older persons.

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Vellas, B J; Wayne, S J; Romero, L; Baumgartner, R N; Rubenstein, L Z; Garry, P J

1997-06-01

To test the hypothesis that one-leg balance is a significant predictor of falls and injurious falls. Analysis of data from a longitudinal cohort study. Healthy, community-living volunteers older than age 60 enrolled in the Albuquerque Falls Study and followed for 3 years (N = 316; mean age 73 years). Falls and injurious falls detected via reports every other month. Baseline measures of demographics, history, physical examination, Iowa Self Assessment Inventory, balance and gait assessment, and one-leg balance (ability to stand unassisted for 5 seconds on one leg). At baseline, 84.5% of subjects could perform one-leg balance. (Impairment was associated with older age and gait abnormalities.) Over the 3-year follow-up, 71% experienced a fall and 22% an injurious fall. The only independent significant predictor of all falls using logistic regression was age greater than 73. However, impaired one-leg balance was the only significant independent predictor of injurious falls (relative risk: 2.13; 95% CI: 1.04, 4.34; P = .03). One-leg balance appears to be a significant and easy-to-administer predictor of injurious falls, but not of all falls. In our study, it was the strongest individual predictor. However, no single factor seems to be accurate enough to be relied on as a sole predictor of fall risk or fall injury risk because so many diverse factors are involved in falling.

PID-controller with predictor and auto-tuning algorithm: study of efficiency for thermal plants

Science.gov (United States)

Kuzishchin, V. F.; Merzlikina, E. I.; Hoang, Van Va

2017-09-01

The problem of efficiency estimation of an automatic control system (ACS) with a Smith predictor and PID-algorithm for thermal plants is considered. In order to use the predictor, it is proposed to include an auto-tuning module (ATC) into the controller; the module calculates parameters for a second-order plant module with a time delay. The study was conducted using programmable logical controllers (PLC), one of which performed control, ATC, and predictor functions. A simulation model was used as a control plant, and there were two variants of the model: one of them was built on the basis of a separate PLC, and the other was a physical model of a thermal plant in the form of an electrical heater. Analysis of the efficiency of the ACS with the predictor was carried out for several variants of the second order plant model with time delay, and the analysis was performed on the basis of the comparison of transient processes in the system when the set point was changed and when a disturbance influenced the control plant. The recommendations are given on correction of the PID-algorithm parameters when the predictor is used by means of using the correcting coefficient k for the PID parameters. It is shown that, when the set point is changed, the use of the predictor is effective taking into account the parameters correction with k = 2. When the disturbances influence the plant, the use of the predictor is doubtful, because the transient process is too long. The reason for this is that, in the neighborhood of the zero frequency, the amplitude-frequency characteristic (AFC) of the system with the predictor has an ascent in comparison with the AFC of the system without the predictor.

School Climate as a Predictor of Incivility and Bullying among Public School Employees: A Multilevel Analysis

Science.gov (United States)

Powell, Joshua E.; Powell, Anna L.; Petrosko, Joseph M.

2015-01-01

We surveyed public school educators on the workplace incivility and workplace bullying they experienced and obtained their ratings of the organizational climate of the school. We used multilevel modeling to determine the effects of individual-level and school-level predictors. Ratings of school climate were significantly related to incivility and…

Predictors of Energy Compensation during Exercise Interventions: A Systematic Review

Directory of Open Access Journals (Sweden)

Marie-Ève Riou

2015-05-01

Full Text Available Weight loss from exercise-induced energy deficits is usually less than expected. The objective of this systematic review was to investigate predictors of energy compensation, which is defined as body energy changes (fat mass and fat-free mass over the total amount of exercise energy expenditure. A search was conducted in multiple databases without date limits. Of 4745 studies found, 61 were included in this systematic review with a total of 928 subjects. The overall mean energy compensation was 18% ± 93%. The analyses indicated that 48% of the variance of energy compensation is explained by the interaction between initial fat mass, age and duration of exercise interventions. Sex, frequency, intensity and dose of exercise energy expenditure were not significant predictors of energy compensation. The fitted model suggested that for a shorter study duration, lower energy compensation was observed in younger individuals with higher initial fat mass (FM. In contrast, higher energy compensation was noted for younger individuals with lower initial FM. From 25 weeks onward, energy compensation was no longer different for these predictors. For studies of longer duration (about 80 weeks, the energy compensation approached 84%. Lower energy compensation occurs with short-term exercise, and a much higher level of energy compensation accompanies long-term exercise interventions.

Predictors of Better Self-Care in Patients with Heart Failure after Six Months of Follow-Up Home Visits

Science.gov (United States)

Trojahn, Melina Maria; Ruschel, Karen Brasil; Nogueira de Souza, Emiliane; Mussi, Cláudia Motta; Naomi Hirakata, Vânia; Nogueira Mello Lopes, Alexandra; Rabelo-Silva, Eneida Rejane

2013-01-01

This study aimed to examine the predictors of better self-care behavior in patients with heart failure (HF) in a home visiting program. This is a longitudinal study nested in a randomized controlled trial (ISRCTN01213862) in which the home-based educational intervention consisted of a six-month followup that included four home visits by a nurse, interspersed with four telephone calls. The self-care score was measured at baseline and at six months using the Brazilian version of the European Heart Failure Self-Care Behaviour Scale. The associations included eight variables: age, sex, schooling, having received the intervention, social support, income, comorbidities, and symptom severity. A simple linear regression model was developed using significant variables (P ≤ 0.20), followed by a multivariate model to determine the predictors of better self-care. One hundred eighty-eight patients completed the study. A better self-care behavior was associated with patients who received intervention (P < 0.001), had more years of schooling (P = 0.016), and had more comorbidities (P = 0.008). Having received the intervention (P < 0.001) and having a greater number of comorbidities (P = 0.038) were predictors of better self-care. In the multivariate regression model, being in the intervention group and having more comorbidities were a predictor of better self-care. PMID:24083023

Community College Faculty Recruitment: Predictors of Applicant Attraction to Faculty Positions.

Science.gov (United States)

Winter, Paul A.; Kjorlien, Chad L.

2000-01-01

Utilizes MBA students' biographical data and reactions to simulated position ads for community college business faculty positions to identify predictors of applicant decisions. Reveals four significant predictors of participants' ratings of simulated positions: applicant's current job satisfaction, spouse's contribution to household income,…

The Job Demands-Resources model as predictor of work identity and work engagement: A comparative analysis

OpenAIRE

Roslyn De Braine; Gert Roodt

2011-01-01

Orientation: Research shows that engaged employees experience high levels of energy and strong identification with their work, hence this study’s focus on work identity and dedication. Research purpose: This study explored possible differences in the Job Demands-Resources model (JD-R) as predictor of overall work engagement, dedication only and work-based identity, through comparative predictive analyses. Motivation for the study: This study may shed light on the dedication component o...

Predictors of Enrolling in Online Courses: An Exploratory Study of Students in Undergrad Marketing Courses

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Renée J. Fontenot

2015-01-01

Full Text Available An exploratory study of undergraduate students enrolled in marketing courses at a Southeastern regional university was conducted to determine the motivations and characteristics of marketing students who plan to be online learners and examined for differences between those who have taken and those who have not taken online classes. An online survey of Likert scales, open-ended questions and demographic questions was sent via class learning management websites. A total of 165 students of the 438 invited to participate completed the survey. A structural model was developed using SMART-PLS to estimate the relationships of constructs that predict taking online courses. Results of the study showed differences in predictors of those that have taken online courses compared to those who plan on taking online courses. A significant predictor of those planning on taking online courses is quality of learning while a significant predictor of those who have taken online courses is scheduling and timing. The results can be used to examine ways to improve/enhance the student’s educational experience, as well as an institution’s effectiveness in attracting the growing body of online learners.

Sleep and academic performance in undergraduates: a multi-measure, multi-predictor approach.

Science.gov (United States)

Gomes, Ana Allen; Tavares, Jos; de Azevedo, Maria Helena P

2011-11-01

The present study examined the associations of sleep patterns with multiple measures of academic achievement of undergraduate university students and tested whether sleep variables emerged as significant predictors of subsequent academic performance when other potential predictors, such as class attendance, time devoted to study, and substance use are considered. A sample of 1654 (55% female) full-time undergraduates 17 to 25 yrs of age responded to a self-response questionnaire on sleep, academics, lifestyle, and well-being that was administered at the middle of the semester. In addition to self-reported measures of academic performance, a final grade for each student was collected at the end of the semester. Univariate analyses found that sleep phase, morningness/eveningness preference, sleep deprivation, sleep quality, and sleep irregularity were significantly associated with at least two academic performance measures. Among 15 potential predictors, stepwise multiple regression analysis identified 5 significant predictors of end-of-semester marks: previous academic achievement, class attendance, sufficient sleep, night outings, and sleep quality (R(2)=0.14 and adjusted R(2)=0.14, F(5, 1234)= 40.99, p academic achievement and the remaining sleep variables as well as the academic, well-being, and lifestyle variables lost significance in stepwise regression. Together with class attendance, night outings, and previous academic achievement, self-reported sleep quality and self-reported frequency of sufficient sleep were among the main predictors of academic performance, adding an independent and significant contribution, regardless of academic variables and lifestyles of the students.

Using an external surrogate for predictor model training in real-time motion management of lung tumors

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Rottmann, Joerg; Berbeco, Ross [Brigham and Women’s Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115 (United States)

2014-12-15

Purpose: Precise prediction of respiratory motion is a prerequisite for real-time motion compensation techniques such as beam, dynamic couch, or dynamic multileaf collimator tracking. Collection of tumor motion data to train the prediction model is required for most algorithms. To avoid exposure of patients to additional dose from imaging during this procedure, the feasibility of training a linear respiratory motion prediction model with an external surrogate signal is investigated and its performance benchmarked against training the model with tumor positions directly. Methods: The authors implement a lung tumor motion prediction algorithm based on linear ridge regression that is suitable to overcome system latencies up to about 300 ms. Its performance is investigated on a data set of 91 patient breathing trajectories recorded from fiducial marker tracking during radiotherapy delivery to the lung of ten patients. The expected 3D geometric error is quantified as a function of predictor lookahead time, signal sampling frequency and history vector length. Additionally, adaptive model retraining is evaluated, i.e., repeatedly updating the prediction model after initial training. Training length for this is gradually increased with incoming (internal) data availability. To assess practical feasibility model calculation times as well as various minimum data lengths for retraining are evaluated. Relative performance of model training with external surrogate motion data versus tumor motion data is evaluated. However, an internal–external motion correlation model is not utilized, i.e., prediction is solely driven by internal motion in both cases. Results: Similar prediction performance was achieved for training the model with external surrogate data versus internal (tumor motion) data. Adaptive model retraining can substantially boost performance in the case of external surrogate training while it has little impact for training with internal motion data. A minimum

Evaluating significance in linear mixed-effects models in R.

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Luke, Steven G

2017-08-01

Mixed-effects models are being used ever more frequently in the analysis of experimental data. However, in the lme4 package in R the standards for evaluating significance of fixed effects in these models (i.e., obtaining p-values) are somewhat vague. There are good reasons for this, but as researchers who are using these models are required in many cases to report p-values, some method for evaluating the significance of the model output is needed. This paper reports the results of simulations showing that the two most common methods for evaluating significance, using likelihood ratio tests and applying the z distribution to the Wald t values from the model output (t-as-z), are somewhat anti-conservative, especially for smaller sample sizes. Other methods for evaluating significance, including parametric bootstrapping and the Kenward-Roger and Satterthwaite approximations for degrees of freedom, were also evaluated. The results of these simulations suggest that Type 1 error rates are closest to .05 when models are fitted using REML and p-values are derived using the Kenward-Roger or Satterthwaite approximations, as these approximations both produced acceptable Type 1 error rates even for smaller samples.

Are there clinically useful predictors and early warning signs for pending relapse?

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Gaebel, Wolfgang; Riesbeck, Mathias

2014-02-01

Despite the availability of effective long-term treatment strategies in schizophrenia, relapse is still common. Relapse prevention is one of the major treatment objectives, because relapse represents burden and costs for patients, their environment, and society and seems to increase illness progression at the biological level. Valid predictors for relapse are urgently needed to enable more individualized recommendations and treatment decisions to be made. Mainly recent evidence regarding predictors and early warning signs of relapse in schizophrenia was reviewed. In addition, data from the first-episode (long-term) study (FES; Gaebel et al., 2007, 2011) performed within the German Research Network on Schizophrenia were analyzed. On the basis of FES data, premorbid adjustment, residual symptoms and some side effects are significant predictors. Although a broad spectrum of potential parameters has been investigated in several other studies, only a few and rather general valid predictors were identified consistently. Data of the FES also indicated that predictive power could be enhanced by considering interacting conjunctions, as suggested by the Vulnerability-Stress-Coping model. Prospective studies, however, are rare. In addition, prodromal symptoms as course-related characteristics likewise investigated in the FES add substantially to early recognition of relapse and may serve as early warning signs, but prognosis nevertheless remains a challenge. Comprehensive and well-designed studies are needed to identify and confirm valid predictors for relapse in schizophrenia. In this respect, broadly accepted and specifically defined criteria for relapse would greatly facilitate comparison of results across studies. © 2013 Elsevier B.V. All rights reserved.

Psychosocial predictors of the onset of anxiety disorders in women: Results from a prospective 3-year longitudinal study

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Calkins, Amanda W.; Otto, Michael W.; Cohen, Lee S.; Soares, Claudio N.; Vitonis, Alison F.; Hearon, Bridget A.; Harlow, Bernard L.

2009-01-01

In a prospective, longitudinal, population-based study of 643 women participating in the Harvard Study of Moods and Cycles we examined whether psychosocial variables predicted a new or recurrent onset of an anxiety disorder. Presence of anxiety disorders was assessed every six months over three years via structured clinical interviews. Among individuals who had a new episode of anxiety, we confirmed previous findings that history of anxiety, increased anxiety sensitivity (the fear of anxiety related sensations), and increased neuroticism were significant predictors. We also found trend level support for assertiveness as a predictor of anxiety onset. However, of these variables, only history of anxiety and anxiety sensitivity provided unique prediction. We did not find evidence for negative life events as a predictor of onset of anxiety either alone or in interaction with other variables in a diathesis-stress model. These findings from a prospective longitudinal study are discussed in relation to the potential role of such predictors in primary or relapse prevention efforts. PMID:19699609

Nonlinear control of a multicomponent distillation process coupled with a binary distillation model as an EKF predictor.

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Jana, Amiya Kumar; Ganguly, Saibal; Samanta, Amar Nath

2006-10-01

The work is devoted to design the globally linearizing control (GLC) strategy for a multicomponent distillation process. The control system is comprised with a nonlinear transformer, a nonlinear closed-loop state estimator [extended Kalman filter (EKF)], and a linear external controller [conventional proportional integral (PI) controller]. The model of a binary distillation column has been used as a state predictor to avoid huge design complexity of the EKF estimator. The binary components are the light key and the heavy key of the multicomponent system. The proposed GLC-EKF (GLC in conjunction with EKF) control algorithm has been compared with the GLC-ROOLE [GLC coupled with reduced-order open-loop estimator (ROOLE)] and the dual-loop PI controller based on set point tracking and disturbance rejection performance. Despite huge process/predictor mismatch, the superiority of the GLC-EKF has been inspected over the GLC-ROOLE control structure.

A gene expression predictor of response to EGFR-targeted therapy stratifies progression-free survival to cetuximab in KRAS wild-type metastatic colorectal cancer

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Black Esther P

2009-05-01

Full Text Available Abstract Background The anti-EGFR monoclonal antibody cetuximab is used in metastatic colorectal cancer (CRC, and predicting responsive patients garners great interest, due to the high cost of therapy. Mutations in the KRAS gene occur in ~40% of CRC and are a negative predictor of response to cetuximab. However, many KRAS-wildtype patients do not benefit from cetuximab. We previously published a gene expression predictor of sensitivity to erlotinib, an EGFR inhibitor. The purpose of this study was to determine if this predictor could identify KRAS-wildtype CRC patients who will benefit from cetuximab therapy. Methods Microarray data from 80 metastatic CRC patients subsequently treated with cetuximab were extracted from the study by Khambata-Ford et al. The study included KRAS status, response, and PFS for each patient. The gene expression data were scaled and analyzed using our predictive model. An improved predictive model of response was identified by removing features in the 180-gene predictor that introduced noise. Results Forty-three of eighty patients were identified as harboring wildtype-KRAS. When the model was applied to these patients, the predicted-sensitive group had significantly longer PFS than the predicted-resistant group (median 88 days vs. 56 days; mean 117 days vs. 63 days, respectively, p = 0.008. Kaplan-Meier curves were also significantly improved in the predicted-sensitive group (p = 0.0059, HR = 0.4109. The model was simplified to 26 of the original 180 genes and this further improved stratification of PFS (median 147 days vs. 56.5 days in the predicted sensitive and resistant groups, respectively, p Conclusion Our model of sensitivity to EGFR inhibition stratified PFS following cetuximab in KRAS-wildtype CRC patients. This study represents the first true external validation of a molecular predictor of response to cetuximab in KRAS-WT metastatic CRC. Our model may hold clinical utility for identifying patients responsive

National Trends and Predictors of Locally Advanced Penile Cancer in the United States (1998-2012).

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Chipollini, Juan; Chaing, Sharon; Peyton, Charles C; Sharma, Pranav; Kidd, Laura C; Giuliano, Anna R; Johnstone, Peter A; Spiess, Philippe E

2017-08-12

We analyzed the trends in presentation of squamous cell carcinoma (SCC) of the penis and determined the socioeconomic predictors for locally advanced (cT3-cT4) disease in the United States. The National Cancer Database was queried for patients with clinically nonmetastatic penile SCC and staging available from 1998 to 2012. Temporal trends per tumor stage were evaluated, and a multivariable logistic regression model was used to identify predictors for advanced presentation during the study period. A total of 5767 patients with stage ≤ T1-T2 (n = 5423) and T3-T4 (n = 344) disease were identified. Increasing trends were noted in all stages of penile SCC with a greater proportion of advanced cases over time (P = .001). Significant predictors of advanced presentation were age > 55 years, the presence of comorbidities, and Medicaid or no insurance (P guide targeted interventions in vulnerable populations. Copyright © 2017 Elsevier Inc. All rights reserved.

Personal and perceived public mental-health stigma as predictors of help-seeking intentions in adolescents.

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Nearchou, Finiki A; Bird, Niamh; Costello, Audrey; Duggan, Sophie; Gilroy, Jessica; Long, Roisin; McHugh, Laura; Hennessy, Eilis

2018-05-22

This study aimed to determine predictors of help-seeking intentions for symptoms of depression/anxiety and self-harm in adolescents. It focused on personal and perceived public stigma to gather data of value for the design of anti-stigma interventions. Participants (n = 722; 368 girls) were recruited from three cohorts of secondary school students in Ireland (mean ages: 1st = 12.9 years; 3rd = 14.9 years; 5th = 16.6 years). Hierarchical regression models indicated that perceived public stigma is a significant unique predictor of help-seeking intentions for depression [F(4, 717) = 13.4, p stigma towards mental health problems was a stronger predictor of help-seeking intentions than their own stigma beliefs. These findings highlight the importance of looking separately at different types of stigma when investigating the role of stigma in predicting help-seeking intentions. Copyright © 2018 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Associative learning versus fear habituation as predictors of long-term extinction retention.

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Brown, Lily A; LeBeau, Richard T; Chat, Ka Yi; Craske, Michelle G

2017-06-01

Violation of unconditioned stimulus (US) expectancy during extinction training may enhance associative learning and result in improved long-term extinction retention compared to within-session habituation. This experiment examines variation in US expectancy (i.e., expectancy violation) as a predictor of long-term extinction retention. It also examines within-session habituation of fear-potentiated startle (electromyography, EMG) and fear of conditioned stimuli (CS) throughout extinction training as predictors of extinction retention. Participants (n = 63) underwent fear conditioning, extinction and retention and provided continuous ratings of US expectancy and EMG, as well as CS fear ratings before and after each phase. Variation in US expectancy throughout extinction and habituation of EMG and fear was entered into a regression as predictors of retention and reinstatement of levels of expectancy and fear. Greater variation in US expectancy throughout extinction training was significantly predictive of enhanced extinction performance measured at retention test, although not after reinstatement test. Slope of EMG and CS fear during extinction did not predict retention of extinction. Within-session habituation of EMG and self-reported fear is not sufficient for long-term retention of extinction learning, and models emphasizing expectation violation may result in enhanced outcomes.

Explaining Variance and Identifying Predictors of Children's Communication via a Multilevel Model of Single-Case Design Research: Brief Report

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Ottley, Jennifer Riggie; Ferron, John M.; Hanline, Mary Frances

2016-01-01

The purpose of this study was to explain the variability in data collected from a single-case design study and to identify predictors of communicative outcomes for children with developmental delays or disabilities (n = 4). Using SAS® University Edition, we fit multilevel models with time nested within children. Children's level of baseline…

Erectile dysfunction is a strong predictor of poor quality of life in men with Type 2 diabetes mellitus.

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Malavige, L S; Jayaratne, S D; Kathriarachchi, S T; Sivayogan, S; Ranasinghe, P; Levy, J C

2014-06-01

To identify predictors of poor quality of life among men with diabetes from a comprehensive set of sexual, clinical, socio-economic and lifestyle variables. This was a cross-sectional observational-study of 253 men with Type 2 diabetes, randomly selected from a clinic in Colombo, Sri Lanka. Erectile dysfunction was assessed using the five-item International Index of Erectile Function and quality of life was assessed using the Sri Lankan version of the 36-item short form health survey questionnaire and the disease-specific Psychological Impact of Erectile Dysfunction scale. The presence of premature ejaculation, reduced libido, socio-demographic and lifestyle data was obtained using an interviewer-administered questionnaire. Significant predictors of quality of life were identified by stepwise multivariate linear regression models for short form-36 subscales, summary scales and two scales of Psychological Impact of Erectile Dysfunction. Significant predictors on the physical summary scale of the 36-item short form were erectile dysfunction (β = 7.93, 95% CI 3.70-12.17, P 27.5 kg/m(2) (β = 9.12, 95% CI 1.38-17.44, P strong predictor of poor generic and disease-specific quality of life among other sexual and clinical variables in men with diabetes. © 2014 The Authors. Diabetic Medicine © 2014 Diabetes UK.

Stroke Location Is an Independent Predictor of Cognitive Outcome.

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Munsch, Fanny; Sagnier, Sharmila; Asselineau, Julien; Bigourdan, Antoine; Guttmann, Charles R; Debruxelles, Sabrina; Poli, Mathilde; Renou, Pauline; Perez, Paul; Dousset, Vincent; Sibon, Igor; Tourdias, Thomas

2016-01-01

On top of functional outcome, accurate prediction of cognitive outcome for stroke patients is an unmet need with major implications for clinical management. We investigated whether stroke location may contribute independent prognostic value to multifactorial predictive models of functional and cognitive outcomes. Four hundred twenty-eight consecutive patients with ischemic stroke were prospectively assessed with magnetic resonance imaging at 24 to 72 hours and at 3 months for functional outcome using the modified Rankin Scale and cognitive outcome using the Montreal Cognitive Assessment (MoCA). Statistical maps of functional and cognitive eloquent regions were derived from the first 215 patients (development sample) using voxel-based lesion-symptom mapping. We used multivariate logistic regression models to study the influence of stroke location (number of eloquent voxels from voxel-based lesion-symptom mapping maps), age, initial National Institutes of Health Stroke Scale and stroke volume on modified Rankin Scale and MoCA. The second part of our cohort was used as an independent replication sample. In univariate analyses, stroke location, age, initial National Institutes of Health Stroke Scale, and stroke volume were all predictive of poor modified Rankin Scale and MoCA. In multivariable analyses, stroke location remained the strongest independent predictor of MoCA and significantly improved the prediction compared with using only age, initial National Institutes of Health Stroke Scale, and stroke volume (area under the curve increased from 0.697-0.771; difference=0.073; 95% confidence interval, 0.008-0.155). In contrast, stroke location did not persist as independent predictor of modified Rankin Scale that was mainly driven by initial National Institutes of Health Stroke Scale (area under the curve going from 0.840 to 0.835). Similar results were obtained in the replication sample. Stroke location is an independent predictor of cognitive outcome (MoCA) at 3

Family Functioning and Predictors of Runaway Behavior Among At-Risk Youth.

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Holliday, Stephanie Brooks; Edelen, Maria Orlando; Tucker, Joan S

2017-06-01

Adolescent runaway behavior is associated with a host of negative outcomes in young adulthood. Therefore, it is important to understand the factors that predict running away in youth. Longitudinal data from 111 at-risk families were used to identify proximal predictors of runaway behavior over a 12-week period. On average, youth were 14.96 years old, and 45% were female. Ten percent of youth ran away during the 12-week follow-up period. In bivariate analyses, running away was predicted by poorer youth- and parent-rated family functioning, past runaway behavior, and other problem behaviors (e.g., substance use, delinquency), but not poorer perceived academic functioning. Results of a hierarchical logistic regression revealed a relationship between youth-rated family functioning and runaway behavior. However, this effect became non-significant after accounting for past runaway behavior and other problem behaviors, both of which remained significant predictors in the multivariable model. These findings suggest that youth who run away may be engaged in a more pervasive pattern of problematic behavior, and that screening and prevention programs need to address the cycle of adolescent defiant behavior associated with running away. Recommendations for clinical practice with this at-risk population are discussed.

The University Matriculation Examination as a Predictor of ...

African Journals Online (AJOL)

The University Matriculation Examination as a Predictor of Performance in Post University Matriculation Examination: a Model for Educational development in the 21st Century. SO Uhunmwuangho, O Ogunbadeniyi ...

Predictors of hepatitis C testing intention among African American Baby Boomers

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Mohamed Rashrash

2017-06-01

Full Text Available Baby Boomers (BBs are responsible for three-quarters of hepatitis C virus (HCV infections in the United States; however, HCV testing is distinctly underused by them. A cross-sectional study was conducted to assess the prevalence of HCV testing and to evaluate predictors of HCV testing intention among African–American BBs. The study was guided by the Health Belief Model and theory of reasoned action frameworks. Of the 137 participants included in the study, 44.8% had at least a college education; 13.9% received prior to 1992 blood transfusion. Findings related to HCV testing showed that 32.1% of the participants intended to test for HCV within 6 months and 43.8% had received a previous HCV test. Significant predictors of HCV testing intention within 6 months included having a blood transfusion prior to 1992 [odds ratio (OR = 8.25, 95% confidence interval (CI: 2.02–33.61], perceptions of benefits (OR = 1.57, 95% CI: 1.13–2.18, severity (OR = 1.39, 95% CI: 1.17–1.65, and subjective norms (OR = 1.42, 95% CI: 1.12–1.79. These predictors of HCV testing intention can be used to develop future HCV testing initiatives for African–American BBs.

Clinical predictors and prognostic significance of electrical storm in patients with implantable cardioverter defibrillators.

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Brigadeau, François; Kouakam, Claude; Klug, Didier; Marquié, Christelle; Duhamel, Alain; Mizon-Gérard, Frédérique; Lacroix, Dominique; Kacet, Salem

2006-03-01

Insufficient data exists regarding predictors of electrical storms (ES) and clinical outcome in patients treated with an implantable cardioverter defibrillator (ICD). The purpose of this study was to delineate a subgroup of patients likely to experience ES and to determine the impact of ES on mortality in ICD recipients. Baseline characteristics of 307 ICD-treated patients were retrospectively analysed. ES was defined as two or more ventricular tachyarrhythmias within 24 h leading to an immediate electrical therapy (antitachycardia pacing and/or shock), separated by a period of sinus rhythm. Clinical characteristics and survival of 123 patients experiencing a total of 294 episodes of ES (median 2 ES/patient, range 1-9), were compared with those of 184 ES-free patients during a median follow-up of 826 days (inter-quartile 1141 days). Median actuarial duration for the first ES occurrence after ICD implant was 1417 days [95% confidence interval (CI) 1061-2363] with a median follow-up of 816 days (7-4642 days) in ES-free patients. Univariate analysis identified older age, depressed left ventricular ejection fraction (LVEF), ventricular tachycardia (VT) as index arrhythmia, chronic renal failure and absence of lipid-lowering drugs as variables significantly associated with an increased risk of ES. Multivariable Cox analysis confirmed an independent predictive value for chronic renal failure [hazard ratio (HR) 1.54, 95% CI 0.95-2.51, P=0.052], VT (HR 2.20, 95% CI 1.44-3.37, P=0.0003), and LVEF (HR 0.98, 95% CI 0.97-0.99, P=0.027). In contrast, diabetics (HR 0.49, 95% CI 0.27-0.90, P=0.022) were less affected by ES. There was no difference in survival between both groups. ES is frequent but does not increase mortality in ICD's recipients. Patients with severe systolic dysfunction, chronic renal failure and VT as initial arrhythmia are likely to experience ES. Diabetics are less affected by ES.

Predictors of Discharge to Home after Thrombolytic Treatment in Right Hemisphere Infarct Patients

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E-I. Ruuskanen

2010-01-01

Full Text Available Background The aim of the study was to assess the association between thrombolysis and length of hospital stay after right hemisphere (RH infarct, and to identify which cognitive functions were predictive of discharge. Methods The study group consisted of 75 acute RH patients. Thirty-three patients had thrombolysis. Neuropsychologicalexaminations were performed within 11 days of stroke onset. The cognitive predictors were visual neglect, visual memory, visual search and reasoning and visuoconstructive abilities. The outcome variable was time from stroke to discharge to home. Results Thrombolysis emerged as a statistically significant predictor of discharge time in patients with moderate/severe stroke (NIHSS ≥5. In the total series of patients and in patients with mild stroke (NIHSS <5, thrombolysiswas not significantly associated with discharge time. Milder visuoconstructive defects shortened the hospital stay of the whole patient group and of patients with moderate/severe stroke. In all patient groups, independence in activitiesof daily living (ADL was a significant single predictor of a shorter hospital stay. The best combination of predictors for discharge was independence in ADL in the total series of patients and in patients with mild stroke, and thrombolysis and independence in ADL in patients with moderate/severe stroke. Conclusions Thrombolytic treatment was a significant predictor of earlier discharge to home in patients with moderate/severe RH infarct, while cognitive functions had less predictive power.

Value of computed tomography as outcome predictor of supraglottic squamous cell carcinoma treated by definitive radiation therapy

International Nuclear Information System (INIS)

Hermans, Robert; Bogaert, Walter van den; Rijnders, Alexis; Baert, Albert L.

1999-01-01

Purpose: To investigate the value of several CT-derived tumor parameters as predictors of local outcome of supraglottic squamous cell carcinoma treated by definitive radiation therapy. Methods and Materials: The pretreatment CT studies of 103 patients with supraglottic squamous cell carcinoma were reviewed for tumoral involvement of specific laryngeal anatomic subsites and extralaryngeal tumor spread. After redigitizing the films, tumor volume was calculated with the summation-of-areas technique. Mean follow-up time was 3.4 years. Actuarial statistical analysis of local and locoregional outcome was done for each of the covariates; multivariate analysis was performed using Cox's proportional hazards model. Results: In the actuarial analysis CT-determined primary tumor volume was significantly correlated with local recurrence rate (p < 0.001). Degree of involvement of the paraglottic space at the level of the true vocal cord (p < 0.05) and subglottic extension (p < 0.001) were also significantly correlated with local recurrence rate. In the multivariate analysis, only degree of involvement of the preepiglottic space (p < 0.01) and subglottic extension (p < 0.01) were found to be independent predictors of local recurrence. Total tumor volume was the strongest independent predictor of locoregional failure (p < 0.01). Conclusions: CT-determined tumor parameters are strong predictors of local and locoregional outcome of supraglottic carcinoma treated by definitive irradiation

Predictors of WAIS-R vocabulary in late life: Differences by race.

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Morin, Ruth T; Midlarsky, Elizabeth

2017-11-01

Vocabulary scores tend to be significantly related to education in heterogeneous groups of older adults, even after controlling for confounding variables. However, there may be other factors that impinge on cognitive functioning for certain demographic groups, particularly those whose educational opportunities were limited, and who may have experienced considerable stress as a result of their minority status. This study sought to explore possible predictors of vocabulary scores among African American and White older adults. In this study, samples of African American (N = 165) and White (N = 146) community-dwelling older adults reported their level of education, perceived health status, and number of stressful life events, and were administered the Wechsler Adult Intelligence Scale-Revised (WAIS-R) Vocabulary subtest. Among the White participants, level of education was the only significant predictor of vocabulary score after controlling for perceived health and exposure to stress. Among African American participants, education was also a significant predictor of vocabulary score. However perceived health and number of stressful life events were also significantly predictors of vocabulary score. Findings indicate that for certain cohorts of older adults, especially those who may have experienced stressful life circumstances and health disparities as a result of racial inequality, education may not be the only variable that predicts verbal intelligence. The importance of investigating cognitive functioning within a broader sociocultural context is discussed.

Predictors of serious bacterial infections in pediatric burn patients with fever.

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Vyles, David; Sinha, Madhumita; Rosenberg, David I; Foster, Kevin N; Tran, Melissa; Drachman, David

2014-01-01

To determine predictors of serious bacterial infections in pediatric burn patients with fever (core temp ≥38.5°C), the authors conducted a retrospective review of medical records of pediatric (0-18 years) patients admitted to the Arizona Burn Center between 2008 and 2011 with greater than 5% TBSA and inpatient hospitalization for ≥72 hours. The study group comprised patients with a febrile episode during their inpatient stay. Serious bacterial infection (the primary outcome variable) was defined as: bacteremia, urinary tract infection, meningitis (blood, urine, or cerebrospinal fluid culture positive for a pathogen respectively), pneumonia, line, and wound infection. A generalized estimating equation analysis was done to predict the presence or absence of serious bacterial infection. Of 1082 pediatric burn patients hospitalized during the study period, 353 met the study eligibility criteria. A total of 108 patients (30.6%) had at least one fever episode (fever group). No difference in demographic characteristics was noted between the fever and no-fever groups; significant differences were observed for: third-degree TBSA, second-degree TBSA, total operating room visits, length of stay, Injury Severity Score, and death. A total of 47.2% of the patients had one or more episodes of fever with serious bacterial infection. In a generalized estimating equation predictive model, presence of a central line, second-, and third-degree TBSA were predictive of serious bacterial infection in burn patients with fever. In this study, individual clinical variables such as tachypnea and tachycardia were not predictive of serious bacterial infections, but the presence of a central line, and larger TBSA were significant predictors of serious bacterial infections. Younger age (P =.08) and ventilator support (P =.057) also approached significance as predictors of serious bacterial infections.

Facebook Addiction: Onset Predictors.

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Biolcati, Roberta; Mancini, Giacomo; Pupi, Virginia; Mugheddu, Valeria

2018-05-23

Worldwide, Facebook is becoming increasingly widespread as a communication platform. Young people especially use this social networking site daily to maintain and establish relationships. Despite the Facebook expansion in the last few years and the widespread acceptance of this social network, research into Facebook Addiction (FA) is still in its infancy. Hence, the potential predictors of Facebook overuse represent an important matter for investigation. This study aimed to deepen the understanding of the relationship between personality traits, social and emotional loneliness, life satisfaction, and Facebook addiction. A total of 755 participants (80.3% female; n = 606) aged between 18 and 40 (mean = 25.17; SD = 4.18) completed the questionnaire packet including the Bergen Facebook Addiction Scale, the Big Five, the short version of Social and Emotional Loneliness Scale for Adults, and the Satisfaction with Life Scale. A regression analysis was used with personality traits, social, family, romantic loneliness, and life satisfaction as independent variables to explain variance in Facebook addiction. The findings showed that Conscientiousness, Extraversion, Neuroticism, and Loneliness (Social, Family, and Romantic) were strong significant predictors of FA. Age, Openness, Agreeableness, and Life Satisfaction, although FA-related variables, were not significant in predicting Facebook overuse. The risk profile of this peculiar behavioral addiction is also discussed.

Predictors of successful external cephalic version in an Australian maternity hospital.

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Mowat, Alex; Gardener, Glenn

2014-02-01

There are minimal data involving predictors of success of external cephalic version (ECV) in an Australian healthcare setting. To determine the predictors of successful ECV as well as the success rate of ECV and the mode of, and presentation at, delivery for women undergoing ECV for breech presentation from 36-weeks gestation. A prospective review was carried out on all women who had undergone ECV from 36-weeks gestation at the Mater Mothers Hospital over an 8-year period from 2001 to 2008. Data were collected prospectively and were collated in conjunction with database review, chart review and telephonic patient interviews. A total of 355 women underwent ECV for breech presentation. The overall success rate was 66% (57% for nulliparous, 76% for multiparous). A woman who underwent ECV had a 46% chance of a vaginal birth. If the ECV was successful, she had a 70% chance of vaginal birth. From bivariate analysis, parity, amniotic fluid index (AFI) and estimated fetal weight (EFW) were determined to be possible predictors of success of ECV and were included in the logistic regression modelling. In the regression analysis, multiparity increased the odds of successful ECV by 2.18. For every one unit increase in AFI, the odds of successful ECV increased by 1.18. Multiparity and amniotic fluid volume as assessed by AFI were the significant predictors of immediate success of ECV. Conversely, lower AFI and nulliparity are factors that are likely to reduce the likelihood of successful ECV. © 2013 The Royal Australian and New Zealand College of Obstetricians and Gynaecologists.

Epidemiological predictors of metabolic syndrome in urban West Bengal, India.

Science.gov (United States)

Chakraborty, Sasthi Narayan; Roy, Sunetra Kaviraj; Rahaman, Md Abdur

2015-01-01

Metabolic syndrome is one of the emerging health problems of the world. Its prevalence is high in urban areas. Though pathogenesis is complex, but the interaction of obesity, sedentary lifestyle, dietary, and genetic factors are known as contributing factors. Community-based studies were very few to find out the prevalence or predictors of the syndrome. To ascertain the prevalence and epidemiological predictors of metabolic syndrome. A total of 690 study subjects were chosen by 30 clusters random sampling method from 43 wards of Durgapur city. Data were analyzed in SPSS version 20 software and binary logistic regression was done to find out statistical significance of the predictors. Among 32.75% of the study population was diagnosed as metabolic syndrome according to National Cholesterol Education Program Adult Treatment Panel III definition with a modification for Asia Pacific cut-off of waist circumference. Odds were more among females (2.43), upper social class (14.89), sedentary lifestyle (17.00), and positive family history. The overall prevalence of metabolic syndrome was high in urban areas of Durgapur. Increased age, female gender, higher social status, sedentary lifestyle, positive family history, and higher education were the statistically significant predictors of metabolic syndrome.

Examining Predictors of Help Giving Toward People With a Mental Illness

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Alyssia Rossetto

2014-05-01

Full Text Available Little is known about factors influencing helping behaviors toward a person with mental illness. This study explored a range of predictors of helping intentions and behaviors using data from a national survey of Australian adults. Participants (n = 6,019 were randomly assigned one of six vignettes and asked how they would help the character if it was someone they knew and cared about, and asked whether and how they had helped a person in real life with a similar problem. Responses were scored using a system based on the Mental Health First Aid action plan. Regression analyses examined predictors of high helping scores in relation to type of disorder and respondent demographics, mental health literacy, and experiences with mental illness. Predictors of harmful responses and seeking advice on how to help appropriately were also assessed. Significant predictors varied by vignette, with the only consistent predictor being female gender. Participants aged under 30 provided less helpful responses to people with social phobia. Mental health literacy variables were inconsistently related to helping, whereas more stigmatizing attitudes significantly predicted harmful responses and poor helping scores. Targeting males and young people may improve rates of helpful responses. Education campaigns aiming to reduce stigma and increase knowledge of schizophrenia may also minimize potentially harmful actions.

Subjective cognitive concerns and neuropsychiatric predictors of progression to the early clinical stages of Alzheimer disease.

Science.gov (United States)

Donovan, Nancy J; Amariglio, Rebecca E; Zoller, Amy S; Rudel, Rebecca K; Gomez-Isla, Teresa; Blacker, Deborah; Hyman, Bradley T; Locascio, Joseph J; Johnson, Keith A; Sperling, Reisa A; Marshall, Gad A; Rentz, Dorene M

2014-12-01

To examine neuropsychiatric and neuropsychological predictors of progression from normal to early clinical stages of Alzheimer disease (AD). From a total sample of 559 older adults from the Massachusetts Alzheimer's Disease Research Center longitudinal cohort, 454 were included in the primary analysis: 283 with clinically normal cognition (CN), 115 with mild cognitive impairment (MCI), and 56 with subjective cognitive concerns (SCC) but no objective impairment, a proposed transitional group between CN and MCI. Two latent cognitive factors (memory-semantic, attention-executive) and two neuropsychiatric factors (affective, psychotic) were derived from the Alzheimer's Disease Centers' Uniform Data Set neuropsychological battery and Neuropsychiatric Inventory brief questionnaire. Factors were analyzed as predictors of time to progression to a worse diagnosis using a Cox proportional hazards regression model with backward elimination. Covariates included baseline diagnosis, gender, age, education, prior depression, antidepressant medication, symptom duration, and interaction terms. Higher/better memory-semantic factor score predicted lower hazard of progression (hazard ratio [HR] = 0.4 for 1 standard deviation [SD] increase, p factor score predicted higher hazard (HR = 1.3 for one SD increase, p = 0.01). No other predictors were significant in adjusted analyses. Using diagnosis as a sole predictor of transition to MCI, the SCC diagnosis carried a fourfold risk of progression compared with CN (HR = 4.1, p factors as significant predictors of more rapid progression from normal to early stages of cognitive decline and highlight the subgroup of cognitively normal elderly with SCC as those with elevated risk of progression to MCI. Copyright © 2014 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

Predictors of postpartum depression.

Science.gov (United States)

Katon, Wayne; Russo, Joan; Gavin, Amelia

2014-09-01

To examine sociodemographic factors, pregnancy-associated psychosocial stress and depression, health risk behaviors, prepregnancy medical and psychiatric illness, pregnancy-related illnesses, and birth outcomes as risk factors for post-partum depression (PPD). A prospective cohort study screened women at 4 and 8 months of pregnancy and used hierarchical logistic regression analyses to examine predictors of PPD. The study sample include 1,423 pregnant women at a university-based high risk obstetrics clinic. A score of ≥10 on the Patient Health Questionnaire-9 (PHQ-9) indicated clinically significant depressive symptoms. Compared with women without significant postpartum depressive symptoms, women with PPD were significantly younger (pdepressive symptoms (pdepression case finding for pregnant women.

Gender and distance influence performance predictors in young swimmers

Directory of Open Access Journals (Sweden)

Paulo Victor Mezzaroba

2013-12-01

Full Text Available Predictors of performance in adult swimmers are constantly changing during youth especially because the training routine begins even before puberty in the modality. Therefore this study aimed to determine the group of parameters that best predict short and middle swimming distance performances of young swimmers of both genders. Thirty-three 10-to 16-years-old male and female competitive swimmers participated in the study. Multiple linear regression (MLR was used considering mean speed of maximum 100, 200 and 400 m efforts as dependent variables, and five parameters groups as possible predictors (anthropometry, body composition, physiological and biomechanical parameters, chronological age/pubic hair. The main results revealed explanatory powers of almost 100% for both genders and all performances, but with different predictors entered in MLR models of each parameter group or all variables. Thus, there are considerable differences in short and middle swimming distance, and males and females predictors that should be considered in training programs.

[Predictors of success of external cephalic version: Bi-center study].

Science.gov (United States)

Dochez, V; Delbos, L; Esbelin, J; Volteau, C; Winer, N; Sentilhes, L

2016-05-01

In the literature, success rate of external cephalic version (ECV) is 39 to 65%. This study aims to identify potential predictors of a successful ECV. Retrospective bi-center study performed from January 2011 through December 2012 at Angers University Hospital and Nantes University Hospital from January 2011 through December 2011. Were identified the demographic and ultrasonography characteristics of patients and the data of the process. One hundred and seventy-eight patients were included, 88 in Angers and 90 in Nantes; 16.3% of ECV were successful. Multiparity (OR 28.45; P<0.01) and transverse position (OR 0.63; P<0.01) are the two significant predictors. There is no significant difference found for center, operator, position of the placenta, amniotic fluid or presence of a uterine scar. The success rate in our two French university centers is much lower than that reported in the literature. Parity and transverse position are the only 2 significant predictors of ECV success. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Autonomic nervous system activity as risk predictor in the medical emergency department: a prospective cohort study.

Science.gov (United States)

Eick, Christian; Rizas, Konstantinos D; Meyer-Zürn, Christine S; Groga-Bada, Patrick; Hamm, Wolfgang; Kreth, Florian; Overkamp, Dietrich; Weyrich, Peter; Gawaz, Meinrad; Bauer, Axel

2015-05-01

To evaluate heart rate deceleration capacity, an electrocardiogram-based marker of autonomic nervous system activity, as risk predictor in a medical emergency department and to test its incremental predictive value to the modified early warning score. Prospective cohort study. Medical emergency department of a large university hospital. Five thousand seven hundred thirty consecutive patients of either sex in sinus rhythm, who were admitted to the medical emergency department of the University of Tübingen, Germany, between November 2010 and March 2012. None. Deceleration capacity of heart rate was calculated within the first minutes after emergency department admission. The modified early warning score was assessed from respiratory rate, heart rate, systolic blood pressure, body temperature, and level of consciousness as previously described. Primary endpoint was intrahospital mortality; secondary endpoints included transfer to the ICU as well as 30-day and 180-day mortality. One hundred forty-two patients (2.5%) reached the primary endpoint. Deceleration capacity was highly significantly lower in nonsurvivors than survivors (2.9 ± 2.1 ms vs 5.6 ± 2.9 ms; p model yielded an area under the receiver-operator characteristic curve of 0.706 (0.667-0.750). Implementing deceleration capacity into the modified early warning score model led to a highly significant increase of the area under the receiver-operator characteristic curve to 0.804 (0.770-0.835; p capacity was also a highly significant predictor of 30-day and 180-day mortality as well as transfer to the ICU. Deceleration capacity is a strong and independent predictor of short-term mortality among patients admitted to a medical emergency department.

Longitudinal Predictors of High School Completion

Science.gov (United States)

Barry, Melissa; Reschly, Amy L.

2012-01-01

This longitudinal study examined predictors of dropout assessed in elementary school. Student demographic data, achievement, attendance, and ratings of behavior from the Behavior Assessment System for Children were used to predict dropout and completion. Two models, which varied on student sex and race, predicted dropout at rates ranging from 75%…

Recent predictors of Indian summer monsoon based on Indian and Pacific Ocean SST

Science.gov (United States)

Shahi, Namendra Kumar; Rai, Shailendra; Mishra, Nishant

2018-02-01

This study investigates the relationship between sea surface temperature (SST) of various geographical locations of Indian and Pacific Ocean with the Indian summer monsoon rainfall (ISMR) to identify possible predictors of ISMR. We identified eight SST predictors based on spatial patterns of correlation coefficients between ISMR and SST of the regions mentioned above during the time domain 1982-2013. The five multiple linear regression (MLR) models have been developed by these predictors in various combinations. The stability and performance of these MLR models are verified using cross-validation method and other statistical methods. The skill of forecast to predict observed ISMR from these MLR models is found to be substantially better based on various statistical verification measures. It is observed that the MLR models constructed using the combination of SST indices in tropical and extra tropical Indian and Pacific is able to predict ISMR accurately for almost all the years during the time domain of our study. We tried to propose the physical mechanism of the teleconnection through regression analysis with wind over Indian subcontinent and the eight predictors and the results are in the conformity with correlation coefficient analysis. The robustness of these models is seen by predicting the ISMR during recent independent years of 2014-2017 and found the model 5 is able to predict ISMR accurately in these years also.

Predictors of transformational leadership of nurse managers.

Science.gov (United States)

Echevarria, Ilia M; Patterson, Barbara J; Krouse, Anne

2017-04-01

The aim of this study was to examine the relationships among education, leadership experience, emotional intelligence and transformational leadership of nurse managers. Nursing leadership research provides limited evidence of predictors of transformational leadership style in nurse managers. A predictive correlational design was used with a sample of nurse managers (n = 148) working in varied health care settings. Data were collected using the Genos Emotional Intelligence Inventory, the Multi-factor Leadership Questionnaire and a demographic questionnaire. Simple linear and multiple regression analyses were used to examine relationships. A statistically significant relationship was found between emotional intelligence and transformational leadership (r = 0.59, P transformational leadership. Nurse managers should be well informed of the predictors of transformational leadership in order to pursue continuing education and development opportunities related to those predictors. The results of this study emphasise the need for emotional intelligence continuing education, leadership development and leader assessment programmes. © 2016 John Wiley & Sons Ltd.

Short-Run Asset Selection using a Logistic Model

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Walter Gonçalves Junior

2011-06-01

Full Text Available Investors constantly look for significant predictors and accurate models to forecast future results, whose occasional efficacy end up being neutralized by market efficiency. Regardless, such predictors are widely used for seeking better (and more unique perceptions. This paper aims to investigate to what extent some of the most notorious indicators have discriminatory power to select stocks, and if it is feasible with such variables to build models that could anticipate those with good performance. In order to do that, logistical regressions were conducted with stocks traded at Bovespa using the selected indicators as explanatory variables. Investigated in this study were the outputs of Bovespa Index, liquidity, the Sharpe Ratio, ROE, MB, size and age evidenced to be significant predictors. Also examined were half-year, logistical models, which were adjusted in order to check the potential acceptable discriminatory power for the asset selection.

Individual and Social Predictors of Prosocial Behavior among Chinese Adolescents in Hong Kong

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Lai, Frank H. Y.; Siu, Andrew M. H.; Shek, Daniel T. L.

2015-01-01

Based on the human ecological model, this study hypothesized that individual competence in empathy, prosocial moral reasoning, and social influence from parents, peers, and school are the key determinants of prosocial behavior among Chinese adolescents in Hong Kong. We recruited a sample of high school students who engaged in volunteering activities regularly (N = 580). They completed a self-administrated questionnaire designed to measure prosocial behavior and its hypothesized predictors using a number of standardized instruments. The results of multiple regression show that social influence factors, including peer, school, and parent influence, are strong predictors of helping intention and prosocial behavior, while individual competence factors like empathy and prosocial moral reasoning are not. Male participants had higher empathy scores and helping intention than females, perceived their parents as more helpful, and their schools as more supportive of prosocial behavior. However, the significant predictors of prosocial behavior and helping intention were similar across gender. The findings indicate that social influence is strongly linked to prosocial behavior. This implies that socialization and social support for prosocial norms and behavior can exert a powerful influence on the behavior of young people in a Chinese population. PMID:26029684

Individual and Social Predictors of Prosocial Behaviour among Chinese Adolescents in Hong Kong

Directory of Open Access Journals (Sweden)

Frank H.Y. Lai

2015-05-01

Full Text Available Based on the human ecological model, this study hypothesized that individual competence in empathy, prosocial moral reasoning, and social influence from parents, peers, and school are the key determinants of prosocial behaviour among Chinese adolescents in Hong Kong. We recruited a sample of high school students who engaged in volunteering activities regularly (N = 580. They completed a self-administrated questionnaire designed to measure prosocial behaviour and its hypothesized predictors using a number of standardized instruments. The results of multiple regression show that social influence factors, including peer, school, and parent influence, are strong predictors of helping intention and prosocial behaviour, while individual competence factors like empathy and prosocial moral reasoning are not. Male participants had higher empathy scores and helping intention than males, perceived their parents as more helpful, and their schools as more supportive of prosocial behaviour. However, the significant predictors of prosocial behaviour and helping intention were similar across gender. The findings indicate that social influence is strongly linked to prosocial behaviour. This implies that socialization and social support for prosocial norms and behaviour can exert a powerful influence on the behaviour of young people in a Chinese population.

Early Predictors of Ten-Year Course in First-Episode Psychosis

DEFF Research Database (Denmark)

Friis, Svein; Melle, Ingrid; Johannessen, Jan Olav

2016-01-01

, five, and ten years (N=186 at ten years). Time in psychosis was defined as time with scores ≥4 on any of the Positive and Negative Syndrome Scale items P1, P3, P5, P6, and G9. Evaluations were retrospective, based on clinical interviews and all available clinical information. During the first two years......, patients were also evaluated by their clinicians at least biweekly. Baseline and early-course predictors of long-term course were identified with linear mixed-model analyses. RESULTS: Four variables provided significant, additive predictions of longer time in psychosis during the ten-year follow...

Self-efficacy, stress, and acculturation as predictors of first year science success among Latinos at a South Texas university

Science.gov (United States)

McNamara, Mark W.

The study tested the hypothesis that self-efficacy, stress, and acculturation are useful predictors of academic achievement in first year university science, independent of high school GPA and SAT scores, in a sample of Latino students at a South Texas Hispanic serving institution of higher education. The correlational study employed a mixed methods explanatory sequential model. The non-probability sample consisted of 98 university science and engineering students. The study participants had high science self-efficacy, low number of stressors, and were slightly Anglo-oriented bicultural to strongly Anglo-oriented. As expected, the control variables of SAT score and high school GPA were statistically significant predictors of the outcome measures. Together, they accounted for 19.80% of the variation in first year GPA, 13.80% of the variation in earned credit hours, and 11.30% of the variation in intent to remain in the science major. After controlling for SAT scores and high school GPAs, self-efficacy was a statistically significant predictor of credit hours earned and accounted for 5.60% of the variation; its unique contribution in explaining the variation in first year GPA and intent to remain in the science major was not statistically significant. Stress and acculturation were not statistically significant predictors of any of the outcome measures. Analysis of the qualitative data resulted in six themes (a) high science self-efficacy, (b) stressors, (c) positive role of stress, (d) Anglo-oriented, (e) bicultural, and (f) family. The quantitative and qualitative results were synthesized and practical implications were discussed.

Evaluating the performance of different predictor strategies in regression-based downscaling with a focus on glacierized mountain environments

Science.gov (United States)

Hofer, Marlis; Nemec, Johanna

2016-04-01

This study presents first steps towards verifying the hypothesis that uncertainty in global and regional glacier mass simulations can be reduced considerably by reducing the uncertainty in the high-resolution atmospheric input data. To this aim, we systematically explore the potential of different predictor strategies for improving the performance of regression-based downscaling approaches. The investigated local-scale target variables are precipitation, air temperature, wind speed, relative humidity and global radiation, all at a daily time scale. Observations of these target variables are assessed from three sites in geo-environmentally and climatologically very distinct settings, all within highly complex topography and in the close proximity to mountain glaciers: (1) the Vernagtbach station in the Northern European Alps (VERNAGT), (2) the Artesonraju measuring site in the tropical South American Andes (ARTESON), and (3) the Brewster measuring site in the Southern Alps of New Zealand (BREWSTER). As the large-scale predictors, ERA interim reanalysis data are used. In the applied downscaling model training and evaluation procedures, particular emphasis is put on appropriately accounting for the pitfalls of limited and/or patchy observation records that are usually the only (if at all) available data from the glacierized mountain sites. Generalized linear models and beta regression are investigated as alternatives to ordinary least squares regression for the non-Gaussian target variables. By analyzing results for the three different sites, five predictands and for different times of the year, we look for systematic improvements in the downscaling models' skill specifically obtained by (i) using predictor data at the optimum scale rather than the minimum scale of the reanalysis data, (ii) identifying the optimum predictor allocation in the vertical, and (iii) considering multiple (variable, level and/or grid point) predictor options combined with state

Predictors of Traditional and Cyber-Bullying Victimization: A Longitudinal Study of Australian Secondary School Students.

Science.gov (United States)

Hemphill, Sheryl A; Tollit, Michelle; Kotevski, Aneta; Heerde, Jessica A

2015-09-01

The purpose of the present article is to compare the individual, peer, family, and school risk and protective factors for both traditional and cyber-bullying victimization. This article draws on data from 673 students from Victoria, Australia, to examine Grade 7 (aged 12-13 years) predictors of traditional and cyber-bullying victimization in Grade 9 (aged 14-15 years). Participants completed a modified version of the Communities That Care youth survey. There were few similarities and important differences in the predictors of traditional and cyber-bullying victimization. For Grade 9 cyber-bullying victimization, in the fully adjusted model, having been a victim of traditional bullying in Grade 7 and emotional control in Grade 7 were predictors. For Grade 9 traditional bullying victimization, predictors were Grade 7 traditional bullying victimization, association with antisocial peers, and family conflict, with family attachment and emotional control marginally statistically significant. The use of evidence-based bullying prevention programs is supported to reduce experiences of both traditional and cyber-bullying victimization, as is the implementation of programs to assist students to regulate their emotions effectively. In addition, traditional bullying victimization may be reduced by addressing association with antisocial friends, family conflict, and bonding to families. © The Author(s) 2014.

Sociocultural predictors of motor development of athletes from ...

African Journals Online (AJOL)

Sociocultural predictors of motor development of athletes from Botswana, Lesotho and Swaziland. ... variables as they influenced the athletes' motor skill development. The social situations, family and the schools were found to significantly ...

H/L transition time estimation in JET using conformal predictors

Energy Technology Data Exchange (ETDEWEB)

Gonzalez, S., E-mail: sergio.gonzalez@ciemat.es [Asociacion EURATOM/CIEMAT para Fusion, Madrid 28040 (Spain); Vega, J. [Asociacion EURATOM/CIEMAT para Fusion, Madrid 28040 (Spain); Murari, A. [Consorzio RFX, Associazione EURATOM/ENEA per la Fusione, Padova 4-25127 (Italy); Pereira, A. [Asociacion EURATOM/CIEMAT para Fusion, Madrid 28040 (Spain); Dormido-Canto, S.; Ramirez, J.M. [Departamento de Informatica y Automatica, UNED, Madrid 28040 (Spain)

2012-12-15

Highlights: Black-Right-Pointing-Pointer H/L transitions have been predicted using H/L and L/H models. Black-Right-Pointing-Pointer Models have been built using conformal predictors to hedge the prediction with confidence and credibility measures. Black-Right-Pointing-Pointer Models have been trained using linear and radial basis function kernels. Black-Right-Pointing-Pointer Conformal measures have proven their usefulness to validate data-driven models. - Abstract: Recent advances in data mining allow the automatic recognition of physical phenomena in the databases of fusion devices without human intervention. This is important to create large databases of physical events (thereby increasing the statistical relevance) in an unattended manner. Important examples are the L/H and H/L transitions. In this contribution, a novel technique is introduced to automatically locate H/L transitions in JET by using conformal predictors. The focus is on H/L transitions because typically there is not a clear signature in the time series of the most widely available signals to recognize the change of confinement. Conformal predictors hedge their prediction by means of two parameters: confidence and credibility. The technique has been based on binary supervised classifiers to separate the samples of the respective confinement modes. Results with several underlying classifiers are presented.

Cognitive predictors of adaptive functioning in children with symptomatic epilepsy.

Science.gov (United States)

Kerr, Elizabeth N; Fayed, Nora

2017-10-01

The current study sought to understand the contribution of the attention and working memory challenges experienced by children with active epilepsy without an intellectual disability to adaptive functioning (AF) while taking into account intellectual ability, co-occurring brain-based psychosocial diagnoses, and epilepsy-related variables. The relationship of attention and working memory with AF was examined in 76 children with active epilepsy with intellectual ability above the 2nd percentile recruited from a tertiary care center. AF was measured using the Scales of Independent Behavior-Revised (SIB-R) and compared with norm-referenced data. Standardized clinical assessments of attention span, sustained attention, as well as basic and more complex working memory were administered to children. Commonality analysis was used to investigate the importance of the variables with respect to the prediction of AF and to construct parsimonious models to elucidate the factors most important in explaining AF. Seventy-one percent of parents reported that their child experienced mild to severe difficulties with overall AF. Similar proportions of children displayed limitations in domain-specific areas of AF (Motor, Social/Communication, Person Living, and Community Living). The reduced models for Broad and domain-specific AF produced a maximum of seven predictor variables, with little loss in overall explained variance compared to the full models. Intellectual ability was a powerful predictor of Broad and domain-specific AF. Complex working memory was the only other cognitive predictor retained in each of the parsimonious models of AF. Sustained attention and complex working memory explained a large amount of the total variance in Motor AF. Children with a previously diagnosed comorbidity displayed lower Social/Communication, Personal Living, and Broad AF than those without a diagnosis. At least one epilepsy-related variable appeared in each of the reduced models, with age of

Predictors and overestimation of recalled mobile phone use among children and adolescents.

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Aydin, Denis; Feychting, Maria; Schüz, Joachim; Andersen, Tina Veje; Poulsen, Aslak Harbo; Prochazka, Michaela; Klæboe, Lars; Kuehni, Claudia E; Tynes, Tore; Röösli, Martin

2011-12-01

A growing body of literature addresses possible health effects of mobile phone use in children and adolescents by relying on the study participants' retrospective reconstruction of mobile phone use. In this study, we used data from the international case-control study CEFALO to compare self-reported with objectively operator-recorded mobile phone use. The aim of the study was to assess predictors of level of mobile phone use as well as factors that are associated with overestimating own mobile phone use. For cumulative number and duration of calls as well as for time since first subscription we calculated the ratio of self-reported to operator-recorded mobile phone use. We used multiple linear regression models to assess possible predictors of the average number and duration of calls per day and logistic regression models to assess possible predictors of overestimation. The cumulative number and duration of calls as well as the time since first subscription of mobile phones were overestimated on average by the study participants. Likelihood to overestimate number and duration of calls was not significantly different for controls compared to cases (OR=1.1, 95%-CI: 0.5 to 2.5 and OR=1.9, 95%-CI: 0.85 to 4.3, respectively). However, likelihood to overestimate was associated with other health related factors such as age and sex. As a consequence, such factors act as confounders in studies relying solely on self-reported mobile phone use and have to be considered in the analysis. Copyright © 2011 Elsevier Ltd. All rights reserved.

Socio-Demographic Indicators, Intelligence, and Locus of Control as Predictors of Adult Financial Well-Being

Directory of Open Access Journals (Sweden)

Adrian Furnham

2017-04-01

Full Text Available The current study investigated a longitudinal data set of 4790 adults examining a set of socio-demographic and psychological factors that influence adult financial well-being. Parental social status (at birth, childhood intelligence and self-esteem (at age 10, locus of control (at age 16, psychological distress (age 30, educational qualifications (age 34, current occupation, weekly net income, house ownership status, and number of rooms (all measured at age 38 years were examined. Structural Equation Modelling showed that childhood intelligence, locus of control, education and occupation were all independent predictors of adult financial well-being for both men and women. Parental social status and psychological distress were also significant predictors of the outcome variable for men, but not for women. Whereas for women, in comparison to men, the effects of current occupation and childhood intelligence on the outcome variable appeared to be stronger. The strongest predictor of adult financial well-being was current occupational prestige, followed by educational achievement. The gender deferential of financial well-being indicators and its implications are discussed.

The Controlling Nutritional Status Score Is a Significant Independent Predictor of Poor Prognosis in Patients With Malignant Pleural Mesothelioma.

Science.gov (United States)

Takamori, Shinkichi; Toyokawa, Gouji; Taguchi, Kenichi; Edagawa, Makoto; Shimamatsu, Shinichiro; Toyozawa, Ryo; Nosaki, Kaname; Seto, Takashi; Hirai, Fumihiko; Yamaguchi, Masafumi; Shoji, Fumihiro; Okamoto, Tatsuro; Takenoyama, Mitsuhiro; Ichinose, Yukito

2017-07-01

Malignant pleural mesothelioma (MPM) is a devastating neoplasm; however, some patients exhibit a good response to chemotherapy or multidisciplinary therapy, including surgery and chemotherapy. It is therefore important to discover the factors that can be used to select patients who will benefit from such treatment. Although the Controlling Nutritional Status (CONUT) score has been used to predict the prognosis in other types of malignancy, its utility in patients with MPM is unknown. The aim of this study was to clarify the clinical significance of the CONUT in patients with MPM. The data of 83 patients, who were treated with surgery, chemotherapy, or multidisciplinary therapy, were analyzed in the present study. A cut-off CONUT score of 2 was used to classify all of the patients into low or high CONUT groups. Fifty-two of the 83 patients were classified into the low CONUT group. A high CONUT score was significantly correlated with chemotherapy alone (P = .011). The high CONUT group had significantly poorer overall survival (OS) (P clinical stage and the CONUT score were found to be independent predictive factors for the OS: clinical stage, I/II and III/IV; P = .001 and CONUT score, ≥ 3 and ≤ 2; P = .011, respectively. The clinical stage and the CONUT score were also independent predictive factors for DFS/PFS: clinical stage, I/II and III/IV; P = .006 and CONUT score, ≥ 3 and ≤ 2; P = .013, respectively. The CONUT score was an independent predictor of a poor prognosis in the patients with MPM. This score provides useful information for selecting patients who will benefit from the treatment. Copyright © 2017 Elsevier Inc. All rights reserved.

Perioperative Blood Transfusion as a Significant Predictor of Biochemical Recurrence and Survival after Radical Prostatectomy in Patients with Prostate Cancer.

Directory of Open Access Journals (Sweden)

Jung Kwon Kim

Full Text Available There have been conflicting reports regarding the association of perioperative blood transfusion (PBT with oncologic outcomes including recurrence rates and survival outcomes in prostate cancer. We aimed to evaluate whether perioperative blood transfusion (PBT affects biochemical recurrence-free survival (BRFS, cancer-specific survival (CSS, and overall survival (OS following radical prostatectomy (RP for patients with prostate cancer.A total of 2,713 patients who underwent RP for clinically localized prostate cancer between 1993 and 2014 were retrospectively analyzed. We performed a comparative analysis based on receipt of transfusion (PBT group vs. no-PBT group and transfusion type (autologous PBT vs. allogeneic PBT. Univariate and multivariate Cox-proportional hazard regression analysis were performed to evaluate variables associated with BRFS, CSS, and OS. The Kaplan-Meier method was used to calculate survival estimates for BRFS, CSS, and OS, and log-rank test was used to conduct comparisons between the groups.The number of patients who received PBT was 440 (16.5%. Among these patients, 350 (79.5% received allogeneic transfusion and the other 90 (20.5% received autologous transfusion. In a multivariate analysis, allogeneic PBT was found to be statistically significant predictors of BRFS, CSS, and OS; conversely, autologous PBT was not. The Kaplan-Meier survival analysis showed significantly decreased 5-year BRFS (79.2% vs. 70.1%, log-rank, p = 0.001, CSS (98.5% vs. 96.7%, log-rank, p = 0.012, and OS (95.5% vs. 90.6%, log-rank, p < 0.001 in the allogeneic PBT group compared to the no-allogeneic PBT group. In the autologous PBT group, however, none of these were statistically significant compared to the no-autologous PBT group.We found that allogeneic PBT was significantly associated with decreased BRFS, CSS, and OS. This provides further support for the immunomodulation hypothesis for allogeneic PBT.

Exploring predictors and consequences of embitterment in the workplace.

Science.gov (United States)

Michailidis, Evie; Cropley, Mark

2017-09-01

Research on the feeling of embitterment at work is still in its infancy. The present study investigated the predictors and consequences of the feeling of embitterment at work. It was hypothesised that organisational injustice as well as over-controlling supervision would predict embitterment at work and that embitterment would be associated with work-related rumination. Three hundred and thirty-seven employees completed an online survey. Regression analysis revealed that procedural injustice and over-controlling supervision were significant predictors of embitterment and that embitterment contributed significantly to the prediction of increased affective rumination and reduction in detachment. Mediation analysis indicated that embitterment at work was a significant mechanism through which organisational injustice and over-controlling supervision exerted their effect on affective rumination, which is indicative of insufficient recovery from work. Findings suggest that breaches in organisational justice can generate feelings of embitterment at work, which in turn can interfere with employees' ability to adequately recover from work. Practitioner Summary: The purpose of this study was to investigate predictors and consequences of embitterment in the workplace using an online questionnaire. Findings suggest that perceived unfairness, because of structural and organisational aspects, predicts feelings of embitterment and that feeling embittered at work can prevent employees from adequately recovering from work.

Exploring predictors of change in behavioral problems over a 1-year period in preterm born preschoolers.

Science.gov (United States)

Schappin, Renske; Wijnroks, Lex; Uniken Venema, Monica; Jongmans, Marian

2018-02-01

Although predictors of the prevalence of behavioral problems in preterm-born children have been frequently studied, predictors of behavioral change in these children remain unknown. Therefore, in this study we explore predictors of short-term changes in problem behavior in preterm-born preschoolers, an age period characterized by rapid behavioral change. Two- to 5-year-old children born with a gestational age behavioral problems. Following screening, 59 children with a t-score ≥60 on either the internal, external or total problem scale of the Child Behavior Checklist were included in the study. Linear mixed modeling was used to investigate predictors of change in behavior over a 1-year period. Higher levels of parenting stress, parent perceived child vulnerability, and parental hostility towards the child and lower educational levels of the mother significantly predicted increases in externalizing behavior. The higher the age of the child, the more internalizing problems decreased. Parenting stress, parent perceived child vulnerability and parental hostility towards the child were the only modifiable predictors of increases in externalizing behavior, whilst no modifiable predictors of internalizing behavior were found. There may be a reciprocal interaction between stress in parents and child externalizing problems. Furthermore, stress and worries may directly influence parents' reports on behavioral measures, because it could cause them to be concerned by behavior otherwise perceived as normal. Therefore, future interventions for parents of preterm-born children should primarily address parental stress and concerns regarding their child. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Teacher and child predictors of achieving IEP goals of children with autism.

Science.gov (United States)

Ruble, Lisa; McGrew, John H

2013-12-01

It is encouraging that children with autism show a strong response to early intervention, yet more research is needed for understanding the variability in responsiveness to specialized programs. Treatment predictor variables from 47 teachers and children who were randomized to receive the COMPASS intervention (Ruble et al. in The collaborative model for promoting competence and success for students with ASD. Springer, New York, 2012a) were analyzed. Predictors evaluated against child IEP goal attainment included child, teacher, intervention practice, and implementation practice variables based on an implementation science framework (Dunst and Trivette in J Soc Sci 8:143-148, 2012). Findings revealed one child (engagement), one teacher (exhaustion), two intervention quality (IEP quality for targeted and not targeted elements), and no implementation quality variables accounted for variance in child outcomes when analyzed separately. When the four significant variables were compared against each other in a single regression analysis, IEP quality accounted for one quarter of the variance in child outcomes.

Epidemiological predictors of metabolic syndrome in urban West Bengal, India

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Sasthi Narayan Chakraborty

2015-01-01

Full Text Available Introduction: Metabolic syndrome is one of the emerging health problems of the world. Its prevalence is high in urban areas. Though pathogenesis is complex, but the interaction of obesity, sedentary lifestyle, dietary, and genetic factors are known as contributing factors. Community-based studies were very few to find out the prevalence or predictors of the syndrome. Objectives: To ascertain the prevalence and epidemiological predictors of metabolic syndrome. Materials and Methods: A total of 690 study subjects were chosen by 30 clusters random sampling method from 43 wards of Durgapur city. Data were analyzed in SPSS version 20 software and binary logistic regression was done to find out statistical significance of the predictors. Results: Among 32.75% of the study population was diagnosed as metabolic syndrome according to National Cholesterol Education Program Adult Treatment Panel III definition with a modification for Asia Pacific cut-off of waist circumference. Odds were more among females (2.43, upper social class (14.89, sedentary lifestyle (17.00, and positive family history. Conclusion: The overall prevalence of metabolic syndrome was high in urban areas of Durgapur. Increased age, female gender, higher social status, sedentary lifestyle, positive family history, and higher education were the statistically significant predictors of metabolic syndrome.

Job satisfaction among nurses: a predictor of burnout levels.

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Kalliath, Thomas; Morris, Rita

2002-12-01

This study assessed the impact of differential levels of job satisfaction on burnout among nurses, hypothesizing that higher levels of job satisfaction predict lower levels of burnout. Social environmental factors of the workplace arising from organizational restructuring cost containment strategies, diminishing resources, and increasing responsibilities, cause highly stressed, burned out nurses to leave the profession. This study used the Maslach Burnout Inventory (MBI) to measure emotional exhaustion, depersonalization, and personal accomplishment. The job satisfaction scale of Katzell et al was used to measure overall job satisfaction. Statistical tests for significance used were Confirmatory Factor Analysis, Structural Equation Modeling, the chi statistic, Root Mean Square Error of Approximation, Goodness of Fit Index, and Comparative Fit Index. The findings show that job satisfaction has a significant direct negative effect on emotional exhaustion, whereas emotional exhaustion has a direct positive effect on depersonalization. A significant indirect effect was seen of job satisfaction on depersonalization via exhaustion. The path coefficient shows that job satisfaction has both direct and indirect effects on burnout, confirming job satisfaction as a significant predictor of burnout. Collaborative efforts between nurses, administrators, and educators to research and test practical models to improve job satisfaction may work as an antidote to burnout.

Predictors of Homophobia in Female College Students.

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Basow, Susan A.; Johnson, Kelly

2000-01-01

Investigated how self-esteem, self-discrepancy, and gender-attribute importance related to homophobia in predominantly white college women, noting sex role attitudes, authoritarian attitudes, and extent of contact with homosexuals. The only significant predictor of homophobia was authoritarian attitudes. Other correlations included belief in sex…

Predictors of Psychological Distress Trajectories in the First Year After a Breast Cancer Diagnosis

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Jin-Hee Park, RN, Ph.D.

2017-12-01

Full Text Available Purpose: Psychological distress is a significant and ongoing problem for breast cancer. These mental health problems are often neglected as they are not always properly understood. This study was performed to explore the trajectory of psychological distress over 1 year since breast cancer surgery and to identify the associated factors for the trajectory. Methods: One hundred seventeen women who underwent surgery for breast cancer completed the psychological distress thermometer and problem lists from after surgery to 12 months after surgery. Information on their sociodemographic and clinical characteristics was also obtained. Group-based trajectory modeling was performed to identify the distinct trajectories of psychological distress. Chi-square test and logistic regression analysis were performed to determine predictors of psychological distress trajectories. Results: A two-group linear trajectory model was optimal for modeling psychological distress (Bayesian information criterion = −777.41. Group-based trajectory modeling identified consistently high-distress (19.4% and low-decreasing distress (80.6% trajectories. Old age, depression, nervousness, and pain were significant predictors of consistently high-distress trajectory. Conclusion: Our results indicate that distinct trajectory groups can be used as a screening tool to identify patients who may be at an increased risk of psychological distress over time. Screening for psychological distress during disease diagnosis is important and necessary to identify patients who are at an increased risk of elevated distress or at risk of experiencing psychological distress over time. Keywords: anxiety, breast neoplasms, depression, pain, psychological stress

Methodological development for selection of significant predictors explaining fatal road accidents.

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Dadashova, Bahar; Arenas-Ramírez, Blanca; Mira-McWilliams, José; Aparicio-Izquierdo, Francisco

2016-05-01

Identification of the most relevant factors for explaining road accident occurrence is an important issue in road safety research, particularly for future decision-making processes in transport policy. However model selection for this particular purpose is still an ongoing research. In this paper we propose a methodological development for model selection which addresses both explanatory variable and adequate model selection issues. A variable selection procedure, TIM (two-input model) method is carried out by combining neural network design and statistical approaches. The error structure of the fitted model is assumed to follow an autoregressive process. All models are estimated using Markov Chain Monte Carlo method where the model parameters are assigned non-informative prior distributions. The final model is built using the results of the variable selection. For the application of the proposed methodology the number of fatal accidents in Spain during 2000-2011 was used. This indicator has experienced the maximum reduction internationally during the indicated years thus making it an interesting time series from a road safety policy perspective. Hence the identification of the variables that have affected this reduction is of particular interest for future decision making. The results of the variable selection process show that the selected variables are main subjects of road safety policy measures. Published by Elsevier Ltd.

Automated computer-based CT stratification as a predictor of outcome in hypersensitivity pneumonitis

International Nuclear Information System (INIS)

Jacob, Joseph; Mak, S.M.; Mok, W.; Hansell, D.M.; Bartholmai, B.J.; Rajagopalan, S.; Karwoski, R.; Della Casa, G.; Sugino, K.; Walsh, S.L.F.; Wells, A.U.

2017-01-01

Hypersensitivity pneumonitis (HP) has a variable clinical course. Modelling of quantitative CALIPER-derived CT data can identify distinct disease phenotypes. Mortality prediction using CALIPER analysis was compared to the interstitial lung disease gender, age, physiology (ILD-GAP) outcome model. CALIPER CT analysis of parenchymal patterns in 98 consecutive HP patients was compared to visual CT scoring by two radiologists. Functional indices including forced vital capacity (FVC) and diffusion capacity for carbon monoxide (DLco) in univariate and multivariate Cox mortality models. Automated stratification of CALIPER scores was evaluated against outcome models. Univariate predictors of mortality included visual and CALIPER CT fibrotic patterns, and all functional indices. Multivariate analyses identified only two independent predictors of mortality: CALIPER reticular pattern (p = 0.001) and DLco (p < 0.0001). Automated stratification distinguished three distinct HP groups (log-rank test p < 0.0001). Substitution of automated stratified groups for FVC and DLco in the ILD-GAP model demonstrated no loss of model strength (C-Index = 0.73 for both models). Model strength improved when automated stratified groups were combined with the ILD-GAP model (C-Index = 0.77). CALIPER-derived variables are the strongest CT predictors of mortality in HP. Automated CT stratification is equivalent to functional indices in the ILD-GAP model for predicting outcome in HP. (orig.)

Automated computer-based CT stratification as a predictor of outcome in hypersensitivity pneumonitis

Energy Technology Data Exchange (ETDEWEB)

Jacob, Joseph; Mak, S.M.; Mok, W.; Hansell, D.M. [Royal Brompton and Harefield NHS Foundation Trust, Department of Radiology, Royal Brompton Hospital, London (United Kingdom); Bartholmai, B.J. [Mayo Clinic Rochester, Division of Radiology, Rochester, MN (United States); Rajagopalan, S.; Karwoski, R. [Mayo Clinic Rochester, Biomedical Imaging Resource, Rochester, MN (United States); Della Casa, G. [Universita degli Studi di Modena e Reggio Emilia, Modena, Emilia-Romagna (Italy); Sugino, K. [Toho University Omori Medical Centre, Tokyo (Japan); Walsh, S.L.F. [Kings College Hospital, London (United Kingdom); Wells, A.U. [Royal Brompton and Harefield NHS Foundation Trust, Interstitial Lung Disease Unit, Royal Brompton Hospital, London (United Kingdom)

2017-09-15

Hypersensitivity pneumonitis (HP) has a variable clinical course. Modelling of quantitative CALIPER-derived CT data can identify distinct disease phenotypes. Mortality prediction using CALIPER analysis was compared to the interstitial lung disease gender, age, physiology (ILD-GAP) outcome model. CALIPER CT analysis of parenchymal patterns in 98 consecutive HP patients was compared to visual CT scoring by two radiologists. Functional indices including forced vital capacity (FVC) and diffusion capacity for carbon monoxide (DLco) in univariate and multivariate Cox mortality models. Automated stratification of CALIPER scores was evaluated against outcome models. Univariate predictors of mortality included visual and CALIPER CT fibrotic patterns, and all functional indices. Multivariate analyses identified only two independent predictors of mortality: CALIPER reticular pattern (p = 0.001) and DLco (p < 0.0001). Automated stratification distinguished three distinct HP groups (log-rank test p < 0.0001). Substitution of automated stratified groups for FVC and DLco in the ILD-GAP model demonstrated no loss of model strength (C-Index = 0.73 for both models). Model strength improved when automated stratified groups were combined with the ILD-GAP model (C-Index = 0.77). CALIPER-derived variables are the strongest CT predictors of mortality in HP. Automated CT stratification is equivalent to functional indices in the ILD-GAP model for predicting outcome in HP. (orig.)

Psychometric and demographic predictors of the perceived risk of terrorist threats and the willingness to pay for terrorism risk management programs.

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Mumpower, Jeryl L; Shi, Liu; Stoutenborough, James W; Vedlitz, Arnold

2013-10-01

A 2009 national telephone survey of 924 U.S. adults assessed perceptions of terrorism and homeland security issues. Respondents rated severity of effects, level of understanding, number affected, and likelihood of four terrorist threats: poisoned water supply; explosion of a small nuclear device in a major U.S. city; an airplane attack similar to 9/11; and explosion of a bomb in a building, train, subway, or highway. Respondents rated perceived risk and willingness to pay (WTP) for dealing with each threat. Demographic, attitudinal, and party affiliation data were collected. Respondents rated bomb as highest in perceived risk but gave the highest WTP ratings to nuclear device. For both perceived risk and WTP, psychometric variables were far stronger predictors than were demographic ones. OLS regression analyses using both types of variables to predict perceived risk found only two significant demographic predictors for any threat--Democrat (a negative predictor for bomb) and white male (a significant positive predictor for airline attack). In contrast, among psychometric variables, severity, number affected, and likelihood were predictors of all four threats and level of understanding was a predictor for one. For WTP, education was a negative predictor for three threats; no other demographic variables were significant predictors for any threat. Among psychometric variables, perceived risk and number affected were positive predictors of WTP for all four threats; severity and likelihood were predictors for three; level of understanding was a significant predictor for two. © 2013 Society for Risk Analysis.

Talent predictors

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Raquel Lorenzo

2007-07-01

Full Text Available The knowledge of talent predictors is the initial point for building diagnosis and encouragement procedures in this field. The meaning of word predictor is to anticipate the future, to divine. Early prediction of high performance is complex problem no resolute by the science yet. There are many discrepancies about what measure and how to do. The article analyze the art state in this problematic because the excellence is determined by the interaction between internal and environmental factors.

Predictors of suicide ideation among older adults with bipolar disorder.

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O'Rourke, Norm; Heisel, Marnin J; Canham, Sarah L; Sixsmith, Andrew

2017-01-01

Bipolar disorder (BD) carries the greatest risk of death by suicide of all psychiatric conditions as 25%-50% of those with BD will make one or more suicide attempt, and about 15% will intentionally end their lives. Among young adults with BD, substance misuse, medication non-adherence, age at onset, and comorbid psychiatric conditions each predict self-harm. It is currently unclear if these same factors or others predict suicide ideation among older adults with BD. We recruited a global sample of 220 older adults with BD over 19 days using socio-demographically targeted, social media advertising and online data collection (Mean = 58.50, SD = 5.42; range 50 to 81 years). Path analyses allowed us to identify direct and indirect predictors of suicide ideation among older adults with BD. Cognitive failures (perception, memory, and motor function), depressive symptoms, alcohol misuse, and dissatisfaction with life as direct predictors of suicide ideation; duration of BD symptoms and medication non-adherence emerged as indirect predictors. Of note, the significant impact of sleep on suicide ideation is indirect via depressive symptoms, cognitive failures, medication non-adherence and life dissatisfaction. As with young adults with BD, alcohol misuse and medication non-adherence emerged as significant predictors of suicide ideation. In addition, cognitive failures directly and indirectly predict suicide ideation in this sample of older adults with BD. Population aging and treatment efficacy are leading to ever growing numbers of older adults with BD. Both direct and indirect predictors of suicide ideation need to be considered in future BD research and treatment planning.

Predictors of nurses' experience of verbal abuse by nurse colleagues.

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Keller, Ronald; Krainovich-Miller, Barbara; Budin, Wendy; Djukic, Maja

Between 45% and 94% of registered nurses (RNs) experience verbal abuse, which is associated with physical and psychological harm. Although several studies examined predictors of RNs' verbal abuse, none examined predictors of RNs' experiences of verbal abuse by RN colleagues. To examine individual, workplace, dispositional, contextual, and interpersonal predictors of RNs' reported experiences of verbal abuse from RN colleagues. In this secondary analysis, a cross-sectional design with multiple linear regression analysis was used to examine the effect of 23 predictors on verbal abuse by RN colleagues in a sample of 1,208 early career RNs. Selected variables in the empirical intragroup conflict model explained 23.8% of variance in RNs' experiences of verbal abuse by RN colleagues. A number of previously unstudied factors were identified that organizational leaders can monitor and develop or modify policies to prevent early career RNs' experiences of verbal abuse by RN colleagues. Copyright © 2017 Elsevier Inc. All rights reserved.

Crowdsourcing Novel Childhood Predictors of Adult Obesity

NARCIS (Netherlands)

Bevelander, K.E.; Kaipainen, K.; Swain, R.; Dohle, S.; Bongard, J.C.; Hines, P.D.H.; Wansink, B.

2014-01-01

Effective and simple screening tools are needed to detect behaviors that are established early in life and have a significant influence on weight gain later in life. Crowdsourcing could be a novel and potentially useful tool to assess childhood predictors of adult obesity. This exploratory study

Severe virus associated community acquired pneumonia: predictors of lethality

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T. O. Pertseva

2016-06-01

Full Text Available Despite the fact that the influenza virus pathogenicity factors have been well studied in vitro, in vivo lack is presented in understanding of the those risk factors, objective and laboratory parameters, which related most of all to the fatal virus-associated community-aquired pneumonia (CAP. That is why the purpose of the study was to study the clinical and laboratory characteristics of patients with severe virus-associated CAP during the 2015–2016 influenza epidemic and their role as predictors of patients’ mortality. To do this, patients with severe virus-associated CAP were examined. They were divided into 2 groups depending on the outcome of treatment: 1st- deaths from the virus-associated severe CAP and 2nd - patients with successful treatment of the severe virus-associated CAP. Special statistical method was used – one-dimensional analysis of variance to compare individual parameters between the two groups of patients (surviving and deceased. Pearson χ2 test (contingency table was used for categorical variables. Factors that were significant predictors of mortality as a result of univariate analysis were tested using multifactorial analysis using logistic regression. In the final model, each parameter must have had a significant impact on mortality. It was found that risk factors for death in patients with severe virus-associated CAP according to univariate analysis were: presence of obesity, disorders of consciousness, BH≥35 min, SaO2<80%, PaO2<50 mm Hg, mmHg PaCO2 ≥50 mmHg during hospitalization. Independent predictors of mortality according to the logistic regression are the presence of obesity, disorders of consciousness, PaO2<50 mm Hg, mmHg PaCO2 ≥50 mmHg. Given that among clinical and laboratory parameters key parameters that significantly influence the outcome, are indicators of the severity of hypoxia and hypoxemia, a major step in determining the severity of the patients with virus-associated severe emergency is

Predictors of Sunburn Risk Among Florida Residents.

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Arutyunyan, Sergey; Alfonso, Sarah V; Hernandez, Nilda; Favreau, Tracy; Fernández, M Isabel

2017-03-01

The incidence of skin cancer, the most common type of cancer in the United States, is increasing. Sunburn is a major modifiable risk factor for skin cancer, and its prevalence among the US population is high. To identify predictors of having had a red or painful sunburn in the past 12 months among people living in Florida. Florida residents were recruited from public places and online. They were asked to complete an anonymous cross-sectional survey that assessed demographic information, dermatologic history, as well as knowledge, attitude, and behavior factors associated with sunburn. A total of 437 participants whose data were complete for all variables were included in the multivariate analysis. In multivariate logistic regression, younger age (18-29 years) was the most significant predictor of sunburn (OR, 15.26; 95% CI, 5.97-38.98; PSunburn prevention programs that osteopathic physicians can readily implement in clinical practice are urgently needed, particularly for young adult patients. This study identified 7 predictors of sunburn in Florida residents. With additional research findings, promoting attitude change toward sun protection may be a viable strategy.

Predictors of Memory and Processing Speed Dysfunctions after Traumatic Brain Injury

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William Winardi

2014-01-01

Full Text Available Background. The aims of this study were to evaluate the predictive value of admission Glasgow Coma Scale (GCS scores, duration of unconsciousness, neurosurgical intervention, and countercoup lesion on the impairment of memory and processing speed functions six months after a traumatic brain injury (TBI based on a structural equation modeling. Methods. Thirty TBI patients recruited from Neurosurgical Department at the Kaohsiung Medical University Hospital were administered the Wechsler Memory Scale-III (WMS-III and the Wechsler Adult Intelligence Scale-III processing speed index to evaluate the memory and processing speed functions. Results. The study showed that GCS scores accounted for 40% of the variance in memory/processing speed. No significant predictive effects were found for the other three variables. GCS classification at the time of TBI seems to correspond moderately to the severity of memory/processing speed dysfunctions. Conclusions. The present study demonstrated that admission GCS score is a robust predictor of memory/processing speed dysfunctions after TBI. The results should be replicated with a large sample of patients with TBI, or be extended by examining other potential clinical predictors.

Narcissism as a predictor of motivations behind Facebook profile picture selection.

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Kapidzic, Sanja

2013-01-01

The rising popularity of social networking sites raises the question of whether and how personality differences are manifested on them. The present study explores this topic through an analysis of the relationship between narcissism and motivations behind Facebook profile picture selection. A survey that assesses motivations emphasizing physical attractiveness, personality, and social ties was conducted with 288 undergraduate students. The study found narcissism to be a significant predictor of the motivation for selecting profile pictures that emphasize attractiveness and personality for both men and women. The findings are discussed in terms of the dynamic self-regulatory processing model of narcissism.

Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape

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Christophe Coupé

2018-04-01

Full Text Available As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because scientific articles still often fall short of reporting whether such assumptions are met. Progress is being, however, made in various directions, one of them being the introduction of techniques able to model data that cannot be properly analyzed with simpler linear regression models. We report recent advances in statistical modeling in linguistics. We first describe linear mixed-effects regression models (LMM, which address grouping of observations, and generalized linear mixed-effects models (GLMM, which offer a family of distributions for the dependent variable. Generalized additive models (GAM are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS. We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for ‘difficult’ variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships. We discuss the use of random effects to account for genealogical relationships, the choice of appropriate distributions to model count data, and non-linear relationships

Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape.

Science.gov (United States)

Coupé, Christophe

2018-01-01

As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because scientific articles still often fall short of reporting whether such assumptions are met. Progress is being, however, made in various directions, one of them being the introduction of techniques able to model data that cannot be properly analyzed with simpler linear regression models. We report recent advances in statistical modeling in linguistics. We first describe linear mixed-effects regression models (LMM), which address grouping of observations, and generalized linear mixed-effects models (GLMM), which offer a family of distributions for the dependent variable. Generalized additive models (GAM) are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS). We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for 'difficult' variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships. We discuss the use of random effects to account for genealogical relationships, the choice of appropriate distributions to model count data, and non-linear relationships. Relying on GAMLSS, we

Predictors of 30-day readmission after aneurysmal subarachnoid hemorrhage: a case-control study.

Science.gov (United States)

Greenberg, Jacob K; Guniganti, Ridhima; Arias, Eric J; Desai, Kshitij; Washington, Chad W; Yan, Yan; Weng, Hua; Xiong, Chengjie; Fondahn, Emily; Cross, DeWitte T; Moran, Christopher J; Rich, Keith M; Chicoine, Michael R; Dhar, Rajat; Dacey, Ralph G; Derdeyn, Colin P; Zipfel, Gregory J

2017-06-01

nursing facility (OR 3.2), and the final model was sensitive to criteria used to enter and retain variables. Furthermore, despite the significant association between discharge disposition and readmission, less than 25% of readmitted patients were discharged to a skilled nursing facility. CONCLUSIONS Although discharge disposition remained significant in multivariate analysis, most routinely collected variables appeared to be weak independent predictors of 30-day readmission after SAH. Consequently, hospitals interested in decreasing readmission rates may consider multifaceted, cost-efficient interventions that can be broadly applied to most if not all SAH patients.

Predictors of running-related injuries in novice runners enrolled in a systematic training program: a prospective cohort study.

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Buist, Ida; Bredeweg, Steef W; Lemmink, Koen A P M; van Mechelen, Willem; Diercks, Ron L

2010-02-01

The popularity of running is still growing. As participation increases, running-related injuries also increase. Until now, little is known about the predictors for injuries in novice runners. Predictors for running-related injuries (RRIs) will differ between male and female novice runners. Cohort study; Level of evidence, 2. Participants were 532 novice runners (226 men, 306 women) preparing for a recreational 4-mile (6.7-km) running event. After completing a baseline questionnaire and undergoing an orthopaedic examination, they were followed during the training period of 13 weeks. An RRI was defined as any self-reported running-related musculoskeletal pain of the lower extremity or back causing a restriction of running for at least 1 week. Twenty-one percent of the novice runners had at least one RRI during follow-up. The multivariate adjusted Cox regression model for male participants showed that body mass index (BMI) (hazard ratio [HR], 1.15; 95% confidence interval [CI], 1.05-1.26), previous injury in the past year (HR, 2.7; 95% CI, 1.36-5.55), and previous participation in sports without axial load (HR, 2.05; 95% CI, 1.03-4.11) were associated with RRI. In female participants, only navicular drop (HR, 0.85; 95% CI, 0.75-0.97) remained a significant predictor for RRI in the multivariate Cox regression modeling. Type A behavior and range of motion (ROM) of the hip and ankle did not affect risk. Male and female novice runners have different risk profiles. Higher BMI, previous injury, and previous sports participation without axial loading are important predictors for RRI in male participants. Further research is needed to detect more predictors for female novice runners.

Predictors of mental health in female teachers.

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Seibt, Reingard; Spitzer, Silvia; Druschke, Diana; Scheuch, Klaus; Hinz, Andreas

2013-12-01

Teaching profession is characterised by an above-average rate of psychosomatic and mental health impairment due to work-related stress. The aim of the study was to identify predictors of mental health in female teachers. A sample of 630 female teachers (average age 47 ± 7 years) participated in a screening diagnostic inventory. Mental health was surveyed with the General Health Questionnaire GHQ-12. The following parameters were measured: specific work conditions (teacher-specific occupational history), scales of the Effort-Reward-Imbalance (ERI) Questionnaire as well as cardiovascular risk factors, physical complaints (BFB) and personal factors such as inability to recover (FABA), sense of coherence (SOC) and health behaviour. First, mentally fit (MH(+)) and mentally impaired teachers (MH(-)) were differentiated based on the GHQ-12 sum score (MH(+): teachers showed evidence of mental impairment. There were no differences concerning work-related and cardiovascular risk factors as well as health behaviour between MH(+) and MH(-). Binary logistic regressions identified 4 predictors that showed a significant effect on mental health. The effort-reward-ratio proved to be the most relevant predictor, while physical complaints as well as inability to recover and sense of coherence were identified as advanced predictors (explanation of variance: 23%). Contrary to the expectations, classic work-related factors can hardly contribute to the explanation of mental health. Additionally, cardiovascular risk factors and health behaviour have no relevant influence. However, effort-reward-ratio, physical complaints and personal factors are of considerable influence on mental health in teachers. These relevant predictors should become a part of preventive arrangements for the conservation of teachers' health in the future.

Surrounding land cover types as predictors of palustrine wetland vegetation quality in conterminous USA

Science.gov (United States)

Stapanian, Martin A.; Gara, Brian; Schumacher, William

2018-01-01

The loss of wetland habitats and their often-unique biological communities is a major environmental concern. We examined vegetation data obtained from 380 wetlands sampled in a statistical survey of wetlands in the USA. Our goal was to identify which surrounding land cover types best predict two indices of vegetation quality in wetlands at the regional scale. We considered palustrine wetlands in four regions (Coastal Plains, North Central East, Interior Plains, and West) in which the dominant vegetation was emergent, forested, or scrub-shrub. For each wetland, we calculated weighted proportions of eight land cover types surrounding the area in which vegetation was assessed, in four zones radiating from the edge of the assessment area to 2 km. Using Akaike's Information Criterion, we determined the best 1-, 2- and 3-predictor models of the two indices, using the weighted proportions of the land cover types as potential predictors. Mean values of the two indices were generally higher in the North Central East and Coastal Plains than the other regions for forested and emergent wetlands. In nearly all cases, the best predictors of the indices were not the dominant surrounding land cover types. Overall, proportions of forest (positive effect) and agriculture (negative effect) surrounding the assessment area were the best predictors of the two indices. One or both of these variables were included as predictors in 65 of the 72 models supported by the data. Wetlands surrounding the assessment area had a positive effect on the indices, and ranked third (33%) among the predictors included in supported models. Development had a negative effect on the indices and was included in only 28% of supported models. These results can be used to develop regional management plans for wetlands, such as creating forest buffers around wetlands, or to conserve zones between wetlands to increase habitat connectivity.

Predictors of delayed Antenatal Care (ANC) visits in Nigeria: secondary analysis of 2013 Nigeria Demographic and Health Survey (NDHS).

Science.gov (United States)

Aliyu, Alhaji Abubakar; Dahiru, Tukur

2017-01-01

Antenatal Care (ANC) is an important component of maternal health and covers a wide range of activities with huge potential benefits for positive pregnancy out comes. However, large proportions of women do initiate ANC early resulting in adverse consequences. The study utilized the nationally-representative sample of women of reproductive age interviewed during the 2013 Nigeria DHS. Analysis was restricted to 20, 467 women aged 15-49 years who had a live birth in the five-year period prior to the survey. Multinomial logistic regression was performed using Stata v13 to determine significant factors related to timing of initiation of ANC. Relative risk ratio (RRR) was used to assess the strength of association between independent and dependent variables. Overall, 27%, 62% and 12% of women initiated ANC in the first, second and third trimesters respectively. In both the two model, the findings reveal that maternal education, level of media exposure, region and place of residence are the uniform predictors of initiation of ANC; having health insurance is a significant predictor of third trimester ANC initiation relative to first to first trimester only. Within the categories of household wealth, levels of participation in household decision-making and region some categories are significant predictors while others are not. Maternal education, level of media exposure, region and place of residence are the uniform and consistent predictors of delay in ANC initiation. This suggests that girl-child education, universal health coverage and universal health insurance could be the interventions required to improve service utilization and maternal health.

Psychosocial predictors of treatment outcome for trauma-affected refugees

DEFF Research Database (Denmark)

Sonne, Charlotte; Carlsson, Jessica; Bech, Per

2016-01-01

situation. The primary outcome measure was PTSD symptoms measured on the Harvard Trauma Questionnaire (HTQ). Other outcome measures included the Hopkins Symptom Check List-25, the WHO-5 Well-being Index, Sheehan Disability Scale, Hamilton Depression and Anxiety Scales, the somatisation scale of the Symptoms...... Checklist-90, Global Assessment of Functioning scales, and pain rated on visual analogue scales. The relations between treatment outcomes and the total score as well as subscores of the CTP Predictor Index were analysed. Results Overall, the total score of the CTP Predictor Index was significantly...

Individual differences and predictors of forgetting in old age: the role of processing speed and working memory.

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Zimprich, Daniel; Kurtz, Tanja

2013-01-01

The goal of the present study was to examine whether individual differences in basic cognitive abilities, processing speed, and working memory, are reliable predictors of individual differences in forgetting rates in old age. The sample for the present study comprised 364 participants aged between 65 and 80 years from the Zurich Longitudinal Study on Cognitive Aging. The impact of basic cognitive abilities on forgetting was analyzed by modeling working memory and processing speed as predictors of the amount of forgetting of 27 words, which had been learned across five trials. Forgetting was measured over a 30-minute interval by using parceling and a latent change model, in which the latent difference between recall performance after five learning trials and a delayed recall was modeled. Results implied reliable individual differences in forgetting. These individual differences in forgetting were strongly related to processing speed and working memory. Moreover, an age-related effect, which was significantly stronger for forgetting than for learning, emerged even after controlling effects of processing speed and working memory.

Predictors of fibromyalgia: a population-based twin cohort study.

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Markkula, Ritva A; Kalso, Eija A; Kaprio, Jaakko A

2016-01-15

Fibromyalgia (FM) is a pain syndrome, the mechanisms and predictors of which are still unclear. We have earlier validated a set of FM-symptom questions for detecting possible FM in an epidemiological survey and thereby identified a cluster with "possible FM". This study explores prospectively predictors for membership of that FM-symptom cluster. A population-based sample of 8343 subjects of the older Finnish Twin Cohort replied to health questionnaires in 1975, 1981, and 1990. Their answers to the set of FM-symptom questions in 1990 classified them in three latent classes (LC): LC1 with no or few symptoms, LC2 with some symptoms, and LC3 with many FM symptoms. We analysed putative predictors for these symptom classes using baseline (1975 and 1981) data on regional pain, headache, migraine, sleeping, body mass index (BMI), physical activity, smoking, and zygosity, adjusted for age, gender, and education. Those with a high likelihood of having fibromyalgia at baseline were excluded from the analysis. In the final multivariate regression model, regional pain, sleeping problems, and overweight were all predictors for membership in the class with many FM symptoms. The strongest non-genetic predictor was frequent headache (OR 8.6, CI 95% 3.8-19.2), followed by persistent back pain (OR 4.7, CI 95% 3.3-6.7) and persistent neck pain (OR 3.3, CI 95% 1.8-6.0). Regional pain, frequent headache, and persistent back or neck pain, sleeping problems, and overweight are predictors for having a cluster of symptoms consistent with fibromyalgia.

Projections of the Ganges-Brahmaputra precipitation: downscaled from GCM predictors

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Pervez, Md Shahriar; Henebry, Geoffrey M.

2014-01-01

Downscaling Global Climate Model (GCM) projections of future climate is critical for impact studies. Downscaling enables use of GCM experiments for regional scale impact studies by generating regionally specific forecasts connecting global scale predictions and regional scale dynamics. We employed the Statistical Downscaling Model (SDSM) to downscale 21st century precipitation for two data-sparse hydrologically challenging river basins in South Asia—the Ganges and the Brahmaputra. We used CGCM3.1 by Canadian Center for Climate Modeling and Analysis version 3.1 predictors in downscaling the precipitation. Downscaling was performed on the basis of established relationships between historical Global Summary of Day observed precipitation records from 43 stations and National Center for Environmental Prediction re-analysis large scale atmospheric predictors. Although the selection of predictors was challenging during the set-up of SDSM, they were found to be indicative of important physical forcings in the basins. The precipitation of both basins was largely influenced by geopotential height: the Ganges precipitation was modulated by the U component of the wind and specific humidity at 500 and 1000 h Pa pressure levels; whereas, the Brahmaputra precipitation was modulated by the V component of the wind at 850 and 1000 h Pa pressure levels. The evaluation of the SDSM performance indicated that model accuracy for reproducing precipitation at the monthly scale was acceptable, but at the daily scale the model inadequately simulated some daily extreme precipitation events. Therefore, while the downscaled precipitation may not be the suitable input to analyze future extreme flooding or drought events, it could be adequate for analysis of future freshwater availability. Analysis of the CGCM3.1 downscaled precipitation projection with respect to observed precipitation reveals that the precipitation regime in each basin may be significantly impacted by climate change

Time to and Predictors of CD4+ T-Lymphocytes Recovery in HIV-Infected Children Initiating Highly Active Antiretroviral Therapy in Ghana

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Lorna Renner

2011-01-01

Full Text Available Background. CD4+ T-lymphocyte monitoring is not routinely available in most resource-limited settings. We investigated predictors of time to CD4+ T-lymphocyte recovery in HIV-infected children on highly active antiretroviral (HAART at Korle-Bu Teaching Hospital, Ghana. Methods. Time to CD4+ T-lymphocyte recovery was defined as achieving percent CD4+ T-lymphocytes of 25%. We used Cox proportional hazard models for identifying significant predictor variables. Results. Of the 233 children with complete CD4+ T-lymphocyte data, the mean age at HAART initiation was 5.5 (SD=3.1 years. The median recovery time was 60 weeks (95% CL: 55–65. Evidence at baseline of severe suppression in CD4+ T-lymphocyte count adjusted for age, age at HAART initiation, gender, and having parents alive were statistically significant in predicting time to CD4+ T-lymphocyte recovery. Conclusions. A targeted approach based on predictors of CD4+ T-lymphocyte recovery can be a viable and cost-effective way of monitoring HAART in HIV-infected children in resource-limited settings.

Predictors of mortality in patients initiating antiretroviral therapy in ...

African Journals Online (AJOL)

a history of oral candidiasis (HR 2.58, 95% CI 1.37 - 4.88) remained significant in multivariate analysis. A history of tuberculosis was not a significant predictor of mortality. Conclusions. Simple clinical and laboratory data independently predict mortality and allow for risk stratification in patients initiating ART in South Africa.

[Cost analysis of radiotherapy provided in inpatient setting -  testing potential predictors for a new prospective payment system].

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Sedo, J; Bláha, M; Pavlík, T; Klika, P; Dušek, L; Büchler, T; Abrahámová, J; Srámek, V; Slampa, P; Komínek, L; Pospíšil, P; Sláma, O; Vyzula, R

2014-01-01

As a part of the development of a new prospective payment model for radiotherapy we analyzed data on costs of care provided by three comprehensive cancer centers in the Czech Republic. Our aim was to find a combination of variables (predictors) which could be used to sort hospitalization cases into groups according to their costs, with each group having the same reimbursement rate. We tested four variables as possible predictors -  number of fractions, stage of disease, radiotherapy technique and diagnostic group. We analyzed 7,440 hospitalization cases treated in three comprehensive cancer centers from 2007 to 2011. We acquired data from the I COP database developed by Institute of Biostatistics and Analyses of Masaryk University in cooperation with oncology centers that contains records from the National Oncological Registry along with data supplied by healthcare providers to insurance companies for the purpose of retrospective reimbursement. When comparing the four variables mentioned above we found that number of fractions and radiotherapy technique were much stronger predictors than the other two variables. Stage of disease did not prove to be a relevant indicator of cost distinction. There were significant differences in costs among diagnostic groups but these were mostly driven by the technique of radiotherapy and the number of fractions. Within the diagnostic groups, the distribution of costs was too heterogeneous for the purpose of the new payment model. The combination of number of fractions and radiotherapy technique appears to be the most appropriate cost predictors to be involved in the prospective payment model proposal. Further analysis is planned to test the predictive value of intention of radiotherapy in order to determine differences in costs between palliative and curative treatment.

Modified Smith-predictor multirate control utilizing secondary process measurements

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Rolf Ergon

2007-01-01

Full Text Available The Smith-predictor is a well-known control structure for industrial time delay systems, where the basic idea is to estimate the non-delayed process output by use of a process model, and to use this estimate in an inner feedback control loop combined with an outer feedback loop based on the delayed estimation error. The model used may be either mechanistic or identified from input-output data. The paper discusses improvements of the Smith-predictor for systems where also secondary process measurements without time delay are available as a basis for the primary output estimation. The estimator may then be identified also in the common case with primary outputs sampled at a lower rate than the secondary outputs. A simulation example demonstrates the feasibility and advantages of the suggested control structure.

Nutritional parameters as mortality predictors in haemodialysis: Differences between genders.

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Oliveira, Telma Sobral; Valente, Ana Tentúgal; Caetano, Cristina Guerreiro; Garagarza, Cristina Antunes

2017-06-01

Malnutrition is common in patients undergoing haemodialysis (HD). Several studies have described different nutritional parameters as mortality predictors but few have studied whether there are differences between genders. This study aimed to evaluate which nutrition parameters may be associated with mortality in patients undergoing long-term HD depending on their gender. Longitudinal prospective multicentre study with 12 months of follow-up. Anthropometric and laboratory measures were obtained from 697 patients. Men who died were older, had lower dry weight, body mass index, potassium, phosphorus and albumin, compared with male patients who survived. Female patients who died had lower albumin and nPCR compared with survivors. Kaplan-Meier analysis displayed a significantly worse survival in patients with albumin mortality was related to body mass index mortality risk continued to be significant after adjustments for age, length of time on dialysis and diabetes for males. However, in women, only albumin persisted as an independent predictor of death. Depending on the gender, different parameters such as protein intake, potassium, phosphorus, body mass index and albumin are associated with mortality in patients undergoing HD. Albumin mortality predictor in both genders, whereas a body mass index <23 kg/m 2 is an independent predictor of death, but only in men. © 2017 European Dialysis and Transplant Nurses Association/European Renal Care Association.

Sexting Rates and Predictors From an Urban Midwest High School.

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Gregg, David; Somers, Cheryl L; Pernice, Francesca Maria; Hillman, Stephen B; Kernsmith, Poco

2018-06-01

Risks associated with teen sexting draw increasing concern from teachers and communities as developments in communication software and devices make sharing private content faster and simpler each year. We examined rates, recipients, and predictors of teen sexting to better plan education and preventative policies and strategies. A comprehensive literature review was conducted to determine the most likely predictors of teen sexting using prior survey studies and theoretical conceptions. We surveyed 314 high school students in an urban area of a large Midwestern city. Males were found to more frequently report sexting. Impulsivity, frequency of electronic communication, peer pressure, peer sexting, and social learning significantly predicted sexting beyond age, race, and sex. Self-esteem did not moderate the effect of peer pressure to sext. Structural predictive models attained good fit to the data, and neither were moderated by sex. Sexting was highly associated with reported peer pressure, perceived norms, and impulsive decision making. Adolescents in relationships may be at particular risk of sexting. These findings will help parents, teens, and educators take appropriate measures to inform about and encourage the safe use of technology. © 2018, American School Health Association.

Predictors of Parenting Stress Trajectories in Premature Infant–Mother Dyads

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Spinelli, Maria; Poehlmann, Julie; Bolt, Daniel

2014-01-01

This prospective longitudinal study examined predictors of parenting stress trajectories over time in a sample of 125 mothers and their preterm infants. Infant (multiple birth, gestational age, days hospitalized, and neonatal health risks) and maternal (socioeconomic, education, depressive symptoms, social support, and quality of interaction during infant feeding) characteristics were collected just prior to infant hospital discharge. Parenting stress and maternal interaction quality during play were measured at 4, 24, and 36 months corrected age. Hierarchical linear modeling was used to analyze infant and maternal characteristics as predictors of parenting stress scores and change over time. Results indicated significant variability across individuals in parenting stress at 4 months and in change trajectories. Mothers of multiples and infants with more medical risks and shorter hospitalization, and mothers with lower education and more depressive symptoms, reported more parenting stress at 4 months of age. Parenting stress decreased over time for mothers of multiples and for mothers with lower education more than for mothers of singletons or for mothers with higher educational levels. Changes in parenting stress scores over time were negatively associated with maternal behaviors during mother–infant interactions. Results are interpreted for their implications for preventive interventions. PMID:24188086

Predictors of pre-game anxiety dysphoria among teenage soccer ...

African Journals Online (AJOL)

Predictors of pre-game anxiety dysphoria among teenage soccer players. ... The result confirmed a significant composite effect of the dependent variable on the independent variables (0.87637, 74.49548, ... AJOL African Journals Online.

Psychosocial Predictors for Cancer Prevention Behaviors in Workplace Using Protection Motivation Theory.

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Zare Sakhvidi, Mohammad Javad; Zare, Maryam; Mostaghaci, Mehrdad; Mehrparvar, Amir Houshang; Morowatisharifabad, Mohammad Ali; Naghshineh, Elham

2015-01-01

Backgrounds. The aim of this study was to describe the preventive behaviors of industrial workers and factors influencing occupational cancer prevention behaviors using protection motivation theory. Methods. A self-administered questionnaire was completed by 161 petrochemical workers in Iran in 2014 which consisted of three sections: background information, protection motivation theory measures, and occupational cancers preventive behaviors. Results. A statistically significant positive correlation was found between PM and self-efficacy, response efficacy, and the cancer preventive behaviors. Meanwhile, statistically significant negative correlations were found between PM, cost, and reward. Conclusions. Among available PMT constructs, only self-efficacy and cost were significant predictors of preventive behaviors. Protection motivation model based health promotion interventions with focus on self-efficacy and cost would be desirable in the case of occupational cancers prevention.

Psychosocial Predictors for Cancer Prevention Behaviors in Workplace Using Protection Motivation Theory

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Mohammad Javad Zare Sakhvidi

2015-01-01

Full Text Available Backgrounds. The aim of this study was to describe the preventive behaviors of industrial workers and factors influencing occupational cancer prevention behaviors using protection motivation theory. Methods. A self-administered questionnaire was completed by 161 petrochemical workers in Iran in 2014 which consisted of three sections: background information, protection motivation theory measures, and occupational cancers preventive behaviors. Results. A statistically significant positive correlation was found between PM and self-efficacy, response efficacy, and the cancer preventive behaviors. Meanwhile, statistically significant negative correlations were found between PM, cost, and reward. Conclusions. Among available PMT constructs, only self-efficacy and cost were significant predictors of preventive behaviors. Protection motivation model based health promotion interventions with focus on self-efficacy and cost would be desirable in the case of occupational cancers prevention.

Baseline Predictors for Success Following Strategy-Based Cognitive Remediation Group Training in Schizophrenia.

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Farreny, Aida; Aguado, Jaume; Corbera, Silvia; Ochoa, Susana; Huerta-Ramos, Elena; Usall, Judith

2016-08-01

Our aim was to examine predictive variables associated with the improvement in cognitive, clinical, and functional outcomes after outpatient participation in REPYFLEC strategy-based Cognitive Remediation (CR) group training. In addition, we investigated which factors might be associated with some long-lasting effects at 6 months' follow-up. Predictors of improvement after CR were studied in a sample of 29 outpatients with schizophrenia. Partial correlations were computed between targeted variables and outcomes of response to explore significant associations. Subsequently, we built linear regression models for each outcome variable and predictors of improvement. The improvement in negative symptoms at posttreatment was linked to faster performance in the Trail Making Test B. Disorganization and cognitive symptoms were related to changes in executive function at follow-up. Lower levels of positive symptoms were related to durable improvements in life skills. Levels of symptoms and cognition were associated with improvements following CR, but the pattern of resulting associations was nonspecific.

Clinical predictors for the prognosis of myasthenia gravis.

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Wang, Lili; Zhang, Yun; He, Maolin

2017-04-19

Clinical predictors for myasthenia gravis relapse and ocular myasthenia gravis secondary generalization during the first two years after disease onset remain incompletely identified. This study attempts to investigate the clinical predictors for the prognosis of Myasthenia Gravis. Eighty three patients with myasthenia gravis were concluded in this study. Baseline characteristics were analyzed as predictors. Relapse of myasthenia gravis developed in 26 patients (34%). Generalization developed in 34 ocular myasthenia gravis patients (85%). Other autoimmune diseases were observed more commonly in relapsed myasthenia gravis (P = 0.012). Second generalization group contained more late onset patients (P = 0.021). Ocular myasthenia gravis patients with thymus hyperplasia progressed more rapidly than those with other thymus pathology (P = 0.027). Single onset symptom of ocular myasthenia gravis such as ptosis or diplopia predicted early progression than concurrence of ptosis and diplopia (P = 0.027). Treatment effect including glucocorticoid, pyridostigmine, thymectomy, IVIG, immunosuppressive drugs did not show significant difference between the relapsed and non-relapsed groups. The treatment outcome also showed no difference between the single OMG and second generalized groups. Occurrence of associated autoimmune disease can serve as a potential predictor for myasthenia gravis relapse. Either ptosis or diplopia, as well as thymic hyperplasia can predict generalization in the first six months.

Seeking new surgical predictors of mesh exposure after transvaginal mesh repair.

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Wu, Pei-Ying; Chang, Chih-Hung; Shen, Meng-Ru; Chou, Cheng-Yang; Yang, Yi-Ching; Huang, Yu-Fang

2016-10-01

The purpose of this study was to explore new preventable risk factors for mesh exposure. A retrospective review of 92 consecutive patients treated with transvaginal mesh (TVM) in the urogynecological unit of our university hospital. An analysis of perioperative predictors was conducted in patients after vaginal repairs using a type 1 mesh. Mesh complications were recorded according to International Urogynecological Association (IUGA) definitions. Mesh-exposure-free durations were calculated by using the Kaplan-Meier method and compared between different closure techniques using log-rank test. Hazard ratios (HR) of predictors for mesh exposure were estimated by univariate and multivariate analyses using Cox proportional hazards regression models. The median surveillance interval was 24.1 months. Two late occurrences were found beyond 1 year post operation. No statistically significant correlation was observed between mesh exposure and concomitant hysterectomy. Exposure risks were significantly higher in patients with interrupted whole-layer closure in univariate analysis. In the multivariate analysis, hematoma [HR 5.42, 95 % confidence interval (CI) 1.26-23.35, P = 0.024), Prolift mesh (HR 5.52, 95 % CI 1.15-26.53, P = 0.033), and interrupted whole-layer closure (HR 7.02, 95 % CI 1.62-30.53, P = 0.009) were the strongest predictors of mesh exposure. Findings indicate the risks of mesh exposure and reoperation may be prevented by avoiding hematoma, large amount of mesh, or interrupted whole-layer closure in TVM surgeries. If these risk factors are prevented, hysterectomy may not be a relative contraindication for TVM use. We also provide evidence regarding mesh exposure and the necessity for more than 1 year of follow-up and preoperative counselling.

Systematic profiling of alternative splicing signature reveals prognostic predictor for ovarian cancer.

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Zhu, Junyong; Chen, Zuhua; Yong, Lei

2018-02-01

The majority of genes are alternatively spliced and growing evidence suggests that alternative splicing is modified in cancer and is associated with cancer progression. Systematic analysis of alternative splicing signature in ovarian cancer is lacking and greatly needed. We profiled genome-wide alternative splicing events in 408 ovarian serous cystadenocarcinoma (OV) patients in TCGA. Seven types of alternative splicing events were curated and prognostic analyses were performed with predictive models and splicing network built for OV patients. Among 48,049 mRNA splicing events in 10,582 genes, we detected 2,611 alternative splicing events in 2,036 genes which were significant associated with overall survival of OV patients. Exon skip events were the most powerful prognostic factors among the seven types. The area under the curve of the receiver-operator characteristic curve for prognostic predictor, which was built with top significant alternative splicing events, was 0.937 at 2,000 days of overall survival, indicating powerful efficiency in distinguishing patient outcome. Interestingly, splicing correlation network suggested obvious trends in the role of splicing factors in OV. In summary, we built powerful prognostic predictors for OV patients and uncovered interesting splicing networks which could be underlying mechanisms. Copyright © 2017 Elsevier Inc. All rights reserved.

Prevalence and predictors of valvular heart disease in patients with systemic lupus erythematosus.

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Vivero, Florencia; Gonzalez-Echavarri, Cristina; Ruiz-Estevez, Beatriz; Maderuelo, Irene; Ruiz-Irastorza, Guillermo

2016-12-01

We aimed to study the frequency, severity and predictors of valvular heart disease (VHD) in our lupus cohort. 211 patients were included. A transthoracic echocardiogram was used for this study. Significant valvular lesions were classified into two groups: valvular thickening and valvular dysfunction. Univariate logistic regression was performed in order to find associations with valvular thickening and dysfunction. Those variables with a p value ≤0.1 in the univariate analysis were subsequently included in multiple logistic regression models. Significant valve lesions were found in 53 patients (25%). The independent predictors of valvular thickening were the age at the time of the echocardiogram (OR 1.05, 95% CI 1.02-1.7), lymphopenia (OR 3.6, 95%CI 1.4-9.5), thrombocytopenia (OR 2.65, 95%CI 1.24-5.72), and anti-Sm antibodies (OR 3.28, 95%CI 1.44-7.33). The independent predictors of valvular dysfunction were age at the time of the echocardiogram (OR 1.045, 95%CI 1.009-1.083), thrombocytopenia (OR 5, 95%CI 1.66-14.86), hypertension (OR 6.2, 95%CI 2.1-18.4) and aPL (OR 6.2, 95%CI 2.1-18.4). Regarding the latter, the independent relation with valvular dysfunction was only seen for the double positivity aCL/LA, (OR 13.2, 95%CI 3.8-45.2, p<0.0001). Our study confirms the high prevalence of significant VHD in SLE patients. Clinical variables related with persistent inflammatory activity were associated with VHD. The association between VHD and aPL positivity was confirmed. Double-positive aCL/LA patients were most likely to suffer from valvular dysfunction. Copyright © 2016 Elsevier B.V. All rights reserved.

Predictors of Playing Augmented Reality Mobile Games While Walking Based on the Theory of Planned Behavior: Web-Based Survey

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Oh, Jeeyun; Mackert, Michael

2017-01-01

Background There has been a sharp increase in the number of pedestrians injured while using a mobile phone, but little research has been conducted to explain how and why people use mobile devices while walking. Therefore, we conducted a survey study to explicate the motivations of mobile phone use while walking Objective The purpose of this study was to identify the critical predictors of behavioral intention to play a popular mobile game, Pokemon Go, while walking, based on the theory of planned behavior (TPB). In addition to the three components of TPB, automaticity, immersion, and enjoyment were added to the model. This study is a theory-based investigation that explores the underlying mechanisms of mobile phone use while walking focusing on a mobile game behavior. Methods Participants were recruited from a university (study 1; N=262) and Amazon Mechanical Turk (MTurk) (study 2; N=197) in the United States. Participants completed a Web-based questionnaire, which included measures of attitude, subjective norms, perceived behavioral control (PBC), automaticity, immersion, and enjoyment. Participants also answered questions regarding demographic items. Results Hierarchical regression analyses were conducted to examine hypotheses. The model we tested explained about 41% (study 1) and 63% (study 2) of people’s intention to play Pokemon Go while walking. The following 3 TPB variables were significant predictors of intention to play Pokemon Go while walking in study 1 and study 2: attitude (P<.001), subjective norms (P<.001), and PBC (P=.007 in study 1; P<.001 in study 2). Automaticity tendency (P<.001), immersion (P=.02), and enjoyment (P=.04) were significant predictors in study 1, whereas enjoyment was the only significant predictor in study 2 (P=.01). Conclusions Findings from this study demonstrated the utility of TPB in predicting a new behavioral domain—mobile use while walking. To sum up, younger users who are habitual, impulsive, and less immersed players

Stress predictors in two Asian dental schools with an integrated curriculum and traditional curriculum.

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Nguyen, T T T; Seki, N; Morio, I

2018-05-01

This study explored stress predictors and the role of instructional methods and institutional differences in perceived stress levels amongst students at two Asian dental schools. An anonymous questionnaire was distributed to undergraduate dental students at Tokyo Medical and Dental University (TMDU), Japan and the University of Medicine and Pharmacy (UMP), Hochiminh City, Vietnam in 2016. Data concerning the students' demographic information and grades, and responses to the Perceived Stress Scale (PSS) and Dental Environment Stress questionnaire (DES) were collected. The questionnaires were prepared in English and translated into Japanese and Vietnamese following a forward-backward translation process. Altogether 684 students answered the questionnaire with a response rate of 97% for TMDU and 89% for UMP. The mean DES score of UMP students was significantly higher than TMDU (P stress scores in several areas than UMP preclinical students. Having dentistry as their first choice of educational programme was a significant stress predictor for Japanese students whilst the clinical practicum was a significant stress predictor for Vietnamese students. Previous academic performance was not a significant stress predictor for students at either dental school. Dental students of an integrated, active-learning curriculum reported lower stress levels than students of a traditional, discipline-based curriculum. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A systematic review of preoperative predictors for postoperative clinical outcomes following lumbar discectomy.

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Wilson, Courtney A; Roffey, Darren M; Chow, Donald; Alkherayf, Fahad; Wai, Eugene K

2016-11-01

Sciatica is often caused by a herniated lumbar intervertebral disc. When conservative treatment fails, a lumbar discectomy can be performed. Surgical treatment via lumbar discectomy is not always successful and may depend on a variety of preoperative factors. It remains unclear which, if any, preoperative factors can predict postsurgical clinical outcomes. This review aimed to determine preoperative predictors that are associated with postsurgical clinical outcomes in patients undergoing lumbar discectomy. This is a systematic review. This systematic review of the scientific literature followed the Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines. MEDLINE and PubMed were systematically searched through June 2014. Results were screened for relevance independently, and full-text studies were assessed for eligibility. Reporting quality was assessed using a modified Newcastle-Ottawa Scale. Quality of evidence was assessed using a modified version of Sackett's Criteria of Evidence Support. No financial support was provided for this study. No potential conflict of interest-associated biases were present from any of the authors. The search strategy yielded 1,147 studies, of which a total of 40 high-quality studies were included. There were 17 positive predictors, 20 negative predictors, 43 non-significant predictors, and 15 conflicting predictors determined. Preoperative predictors associated with positive postoperative outcomes included more severe leg pain, better mental health status, shorter duration of symptoms, and younger age. Preoperative predictors associated with negative postoperative outcomes included intact annulus fibrosus, longer duration of sick leave, worker's compensation, and greater severity of baseline symptoms. Several preoperative factors including motor deficit, side and level of herniation, presence of type 1 Modic changes and degeneration, age, and gender had non-significant associations with postoperative clinical

Dieting behaviours, obesity and predictors of dieting among female college students at Palestinian universities.

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Bayyari, W D; Henry, L J; Jones, C

2013-01-01

The purpose of this study was to explore dieting practices of female Palestinian college students. Participants ( = 410) were selected by cluster-sampling from 4 Palestinian universities. A regression model investigated dieting using: body mass index (BMI); body satisfaction; self-esteem; dress style; exercise; sociocultural factors; residence; strength of faith; perceived impact of weight on social interaction; and number of previous times dieting. Significant predictors of dieting were low body satisfaction, number of previous dieting times, perceived media pressure, regular exercising, BMI, and perceived impact of weight on social interaction, The model accounted for 45% of the variance in dieting. Body satisfaction was not significantly correlated with self-esteem or strength of faith, which indicates that "internalization of thinness" may be becoming evident among populations in certain developing countries, as in "Western" countries.

A clinical algorithm for triaging patients with significant lymphadenopathy in primary health care settings in Sudan

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Eltahir A.G. Khalil

2013-06-01

Full Text Available Background: Tuberculosis is a major health problem in developing countries. The distinction between tuberculous lymphadenitis, non-specific lymphadenitis and malignant lymph node enlargement has to be made at primary health care levels using easy, simple and cheap methods. Objective: To develop a reliable clinical algorithm for primary care settings to triage cases ofnon-specific, tuberculous and malignant lymphadenopathies. Methods: Calculation of the odd ratios (OR of the chosen predictor variables was carried out using logistic regression. The numerical score values of the predictor variables were weighed against their respective OR. The performance of the score was evaluated by the ROC (ReceiverOperator Characteristic curve. Results: Four predictor variables; Mantoux reading, erythrocytes sedimentation rate (ESR,nocturnal fever and discharging sinuses correlated significantly with TB diagnosis and were included in the reduced model to establish score A. For score B, the reduced model included Mantoux reading, ESR, lymph-node size and lymph-node number as predictor variables for malignant lymph nodes. Score A ranged 0 to 12 and a cut-off point of 6 gave a best sensitivity and specificity of 91% and 90% respectively, whilst score B ranged -3 to 8 and a cut-off point of3 gave a best sensitivity and specificity of 83% and 76% respectively. The calculated area underthe ROC curve was 0.964 (95% CI, 0.949 – 0.980 and -0.856 (95% CI, 0.787 ‑ 0.925 for scores Aand B respectively, indicating good performance. Conclusion: The developed algorithm can efficiently triage cases with tuberculous andmalignant lymphadenopathies for treatment or referral to specialised centres for furtherwork-up.

Childhood cardiovascular risk factors, a predictor of late adolescent overweight

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Saeed Kalantari

2016-01-01

Conclusion: Increased CVD risk factors are predictors of future overweight in childhood and adolescent and increased weight is linked significantly with dyslipidemia and hypertension in this age group.

Predictors of mental health in female teachers

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Reingard Seibt

2013-12-01

Full Text Available Objective: Teaching profession is characterised by an above-average rate of psychosomatic and mental health impairment due to work-related stress. The aim of the study was to identify predictors of mental health in female teachers. Material and Methods: A sample of 630 female teachers (average age 47±7 years participated in a screening diagnostic inventory. Mental health was surveyed with the General Health Questionnaire GHQ-12. The following parameters were measured: specific work conditions (teacher-specific occupational history, scales of the Effort-Reward-Imbalance (ERI Questionnaire as well as cardiovascular risk factors, physical complaints (BFB and personal factors such as inability to recover (FABA, sense of coherence (SOC and health behaviour. Results: First, mentally fit (MH+ and mentally impaired teachers (MH- were differentiated based on the GHQ-12 sum score (MH+: < 5; MH-: ≥ 5; 18% of the teachers showed evidence of mental impairment. There were no differences concerning work-related and cardiovascular risk factors as well as health behaviour between MH+ and MH-. Binary logistic regressions identified 4 predictors that showed a significant effect on mental health. The effort-reward-ratio proved to be the most relevant predictor, while physical complaints as well as inability to recover and sense of coherence were identified as advanced predictors (explanation of variance: 23%. Conclusion: Contrary to the expectations, classic work-related factors can hardly contribute to the explanation of mental health. Additionally, cardiovascular risk factors and health behaviour have no relevant influence. However, effort-reward-ratio, physical complaints and personal factors are of considerable influence on mental health in teachers. These relevant predictors should become a part of preventive arrangements for the conservation of teachers' health in the future.

Modelling fourier regression for time series data- a case study: modelling inflation in foods sector in Indonesia

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Prahutama, Alan; Suparti; Wahyu Utami, Tiani

2018-03-01

Regression analysis is an analysis to model the relationship between response variables and predictor variables. The parametric approach to the regression model is very strict with the assumption, but nonparametric regression model isn’t need assumption of model. Time series data is the data of a variable that is observed based on a certain time, so if the time series data wanted to be modeled by regression, then we should determined the response and predictor variables first. Determination of the response variable in time series is variable in t-th (yt), while the predictor variable is a significant lag. In nonparametric regression modeling, one developing approach is to use the Fourier series approach. One of the advantages of nonparametric regression approach using Fourier series is able to overcome data having trigonometric distribution. In modeling using Fourier series needs parameter of K. To determine the number of K can be used Generalized Cross Validation method. In inflation modeling for the transportation sector, communication and financial services using Fourier series yields an optimal K of 120 parameters with R-square 99%. Whereas if it was modeled by multiple linear regression yield R-square 90%.

Identifying cytokine predictors of cognitive functioning in breast cancer survivors up to 10 years post chemotherapy using machine learning.

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Henneghan, Ashley M; Palesh, Oxana; Harrison, Michelle; Kesler, Shelli R

2018-07-15

The purpose of this study is to explore 13 cytokine predictors of chemotherapy-related cognitive impairment (CRCI) in breast cancer survivors (BCS) 6 months to 10 years after chemotherapy completion using a multivariate, non-parametric approach. Cross sectional data collection included completion of a survey, cognitive testing, and non-fasting blood from 66 participants. Data were analyzed using random forest regression to identify the most significant predictors for each of the cognitive test scores. A different cytokine profile predicted each cognitive test. Adjusted R 2 for each model ranged from 0.71-0.77 (p's < 9.50 -10 ). The relationships between all the cytokine predictors and cognitive test scores were non-linear. Our findings are unique to the field of CRCI and suggest non-linear cytokine specificity to neural networks underlying cognitive functions assessed in this study. Copyright © 2018 Elsevier B.V. All rights reserved.

Measures for Predictors of Innovation Adoption

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Chor, Ka Ho Brian; Wisdom, Jennifer P.; Olin, Su-Chin Serene; Hoagwood, Kimberly E.; Horwitz, Sarah M.

2014-01-01

Building on a narrative synthesis of adoption theories by Wisdom et al. (2013), this review identifies 118 measures associated with the 27 adoption predictors in the synthesis. The distribution of measures is uneven across the predictors and predictors vary in modifiability. Multiple dimensions and definitions of predictors further complicate measurement efforts. For state policymakers and researchers, more effective and integrated measurement can advance the adoption of complex innovations such as evidence-based practices. PMID:24740175

Systematic analysis of ECG predictors of sinus rhythm maintenance after electrical cardioversion for persistent atrial fibrillation.

Science.gov (United States)

Lankveld, Theo; de Vos, Cees B; Limantoro, Ione; Zeemering, Stef; Dudink, Elton; Crijns, Harry J; Schotten, Ulrich

2016-05-01

Electrical cardioversion (ECV) is one of the rhythm control strategies in patients with persistent atrial fibrillation (AF). Unfortunately, recurrences of AF are common after ECV, which significantly limits the practical benefit of this treatment in patients with AF. The objectives of this study were to identify noninvasive complexity or frequency parameters obtained from the surface electrocardiogram (ECG) to predict sinus rhythm (SR) maintenance after ECV and to compare these ECG parameters with clinical predictors. We studied a wide variety of ECG-derived time- and frequency-domain AF complexity parameters in a prospective cohort of 502 patients with persistent AF referred for ECV. During 1-year follow-up, 161 patients (32%) maintained SR. The best clinical predictor of SR maintenance was antiarrhythmic drug (AAD) treatment. A model including clinical parameters predicted SR maintenance with a mean cross-validated area under the receiver operating characteristic curve (AUC) of 0.62 ± 0.05. The best single ECG parameter was the dominant frequency (DF) on lead V6. Combining several ECG parameters predicted SR maintenance with a mean AUC of 0.64 ± 0.06. Combining clinical and ECG parameters improved prediction to a mean AUC of 0.67 ± 0.05. Although the DF was affected by AAD treatment, excluding patients taking AADs did not significantly lower the predictive performance captured by the ECG. ECG-derived parameters predict SR maintenance during 1-year follow-up after ECV at least as good as known clinical predictors of rhythm outcome. The DF proved to be the most powerful ECG-derived predictor. Copyright © 2016 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Fasting triglycerides as a predictor of incident diabetes, insulin resistance and β-cell function in a Canadian First Nation.

Science.gov (United States)

Riediger, Natalie D; Clark, Kirsten; Lukianchuk, Virginia; Roulette, Joanne; Bruce, Sharon

2017-01-01

Diabetes prevalence is substantially higher among Canadian First Nations populations than the non-First Nation population. Fasting serum triglycerides have been found to be an important predictor of incident diabetes among non-indigenous populations. However, there is a great need to understand diabetes progression within specific ethnic groups, particularly First Nations populations. The purpose of this study was to test for an association between fasting serum triglycerides and incident diabetes, changes in insulin resistance and changes in β-cell function in a Manitoba First Nation cohort. Study data were from two diabetes screening studies in Sandy Bay First Nation in Manitoba, Canada, collected in 2002/2003 and 2011/2012. The cohort was composed of respondents to both screening studies (n=171). Fasting blood samples and anthropometric, health and demographic data were collected. A generalised linear model with Poisson distribution was used to test for an association between fasting triglycerides and incident diabetes. There were 35 incident cases of diabetes among 128 persons without diabetes at baseline. Participants who developed incident type 2 diabetes were significantly older and had significantly higher body mass index (BMI; p=0.012), total cholesterol (p=0.007), fasting triglycerides (ptriglyceride level was found to be a statistically significant positive predictor of incident diabetes independent of age, sex and waist circumference at baseline. Participants with triglycerides in the highest tertile (≥2.11 mmol/l) had a 4.0-times higher risk of developing incident diabetes compared to those in the lowest tertile (p=0.03). Notably, neither waist circumference nor BMI were significant predictors of incident diabetes independent of age, sex and triglycerides. Fasting triglycerides may be useful as a clinical predictor of insulin resistance and diabetes development among First Nations populations. Unlike other ethnic groups, BMI and waist circumference

Predictors of subjective health status 10 years post-PCI.

Science.gov (United States)

van den Berge, Jan C; Dulfer, Karolijn; Utens, Elisabeth M W J; Hartman, Eline M J; Daemen, Joost; van Geuns, Robert J; van Domburg, Ron T

2016-06-01

Subjective health status is an increasingly important parameter to assess the effect of percutaneous coronary intervention (PCI) in clinical practice. Aim of this study was to determine medical and psychosocial predictors of poor subjective health status over a 10 years' post-PCI period. We included a series of consecutive PCI patients (n = 573) as part of the RESEARCH registry, a Dutch single-center retrospective cohort study. These patients completed the 36-item Short-Form Health Survey (SF-36) at baseline and 10 years post-PCI. We found 6 predictors of poor subjective health status 10 years post-PCI: SF-36 at baseline, age, previous PCI, obesity, acute myocardial infarction as indication for PCI, and diabetes mellitus (arranged from most to least numbers of sub domains). SF-36 scores at baseline, age, and previous PCI were significant predictors of subjective health status 10 years post-PCI. Specifically, the SF-36 score at baseline was an important predictor. Thus assessment of subjective health status at baseline is useful as an indicator to predict long-term subjective health status. Subjective health status becomes better by optimal medical treatment, cardiac rehabilitation and psychosocial support. This is the first study determining predictors of subjective health status 10 years post-PCI.

School and Child Level Predictors of Academic Success for African American Children in Third Grade: Implications for No Child Left behind

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Graves, Scott

2011-01-01

The purpose of this study was to examine correlates of being at expected grade level in reading in the third grade. Participants for this study were a nationally representative sample of African American children from the Early Childhood Longitudinal Study (ECLS-K). Multilevel modeling was conducted to determine significant predictors of academic…

Assimilating Non-linear Effects of Customized Large-Scale Climate Predictors on Downscaled Precipitation over the Tropical Andes

Science.gov (United States)

Molina, J. M.; Zaitchik, B. F.

2016-12-01

Recent findings considering high CO2 emission scenarios (RCP8.5) suggest that the tropical Andes may experience a massive warming and a significant precipitation increase (decrease) during the wet (dry) seasons by the end of the 21st century. Variations on rainfall-streamflow relationships and seasonal crop yields significantly affect human development in this region and make local communities highly vulnerable to climate change and variability. We developed an expert-informed empirical statistical downscaling (ESD) algorithm to explore and construct robust global climate predictors to perform skillful RCP8.5 projections of in-situ March-May (MAM) precipitation required for impact modeling and adaptation studies. We applied our framework to a topographically-complex region of the Colombian Andes where a number of previous studies have reported El Niño-Southern Oscillation (ENSO) as the main driver of climate variability. Supervised machine learning algorithms were trained with customized and bias-corrected predictors from NCEP reanalysis, and a cross-validation approach was implemented to assess both predictive skill and model selection. We found weak and not significant teleconnections between precipitation and lagged seasonal surface temperatures over El Niño3.4 domain, which suggests that ENSO fails to explain MAM rainfall variability in the study region. In contrast, series of Sea Level Pressure (SLP) over American Samoa -likely associated with the South Pacific Convergence Zone (SPCZ)- explains more than 65% of the precipitation variance. The best prediction skill was obtained with Selected Generalized Additive Models (SGAM) given their ability to capture linear/nonlinear relationships present in the data. While SPCZ-related series exhibited a positive linear effect in the rainfall response, SLP predictors in the north Atlantic and central equatorial Pacific showed nonlinear effects. A multimodel (MIROC, CanESM2 and CCSM) ensemble of ESD projections revealed

Refined histopathological predictors of BRCA1 and BRCA2 mutation status

DEFF Research Database (Denmark)

Spurdle, Amanda B; Couch, Fergus J; Parsons, Michael T

2014-01-01

INTRODUCTION: The distribution of histopathological features of invasive breast tumors in BRCA1 or BRCA2 germline mutation carriers differs from that of individuals with no known mutation. Histopathological features thus have utility for mutation prediction, including statistical modeling to assess...... pathogenicity of BRCA1 or BRCA2 variants of uncertain clinical significance. We analyzed large pathology datasets accrued by the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and the Breast Cancer Association Consortium (BCAC) to reassess histopathological predictors of BRCA1 and BRCA2 mutation...... status, and provide robust likelihood ratio (LR) estimates for statistical modeling. METHODS: Selection criteria for study/center inclusion were estrogen receptor (ER) status or grade data available for invasive breast cancer diagnosed younger than 70 years. The dataset included 4,477 BRCA1 mutation...

One-year Mortality after an Acute Coronary Event and its Clinical Predictors: The ERICO Study

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Itamar Souza Santos

2015-01-01

Full Text Available Background: Information about post-acute coronary syndrome (ACS survival have been mostly short-term findings or based on specialized, cardiology referral centers. Objectives: To describe one-year case-fatality rates in the Strategy of Registry of Acute Coronary Syndrome (ERICO cohort, and to study baseline characteristics as predictors. Methods: We analyzed data from 964 ERICO participants enrolled from February 2009 to December 2012. We assessed vital status by telephone contact and official death certificate searches. The cause of death was determined according to the official death certificates. We used log-rank tests to compare the probabilities of survival across subgroups. We built crude and adjusted (for age, sex and ACS subtype Cox regression models to study if the ACS subtype or baseline characteristics were independent predictors of all-cause or cardiovascular mortality. Results: We identified 110 deaths in the cohort (case-fatality rate, 12.0%. Age [Hazard ratio (HR = 2.04 per 10 year increase; 95% confidence interval (95%CI = 1.75–2.38], non-ST elevation myocardial infarction (HR = 3.82 ; 95%CI = 2.21–6.60 or ST elevation myocardial infarction (HR = 2.59; 95%CI = 1.38–4.89 diagnoses, and diabetes (HR = 1.78; 95%CI = 1.20‑2.63 were significant risk factors for all-cause mortality in the adjusted models. We found similar results for cardiovascular mortality. A previous coronary artery disease diagnosis was also an independent predictor of all-cause mortality (HR = 1.61; 95%CI = 1.04–2.50, but not for cardiovascular mortality. Conclusion: We found an overall one-year mortality rate of 12.0% in a sample of post-ACS patients in a community, non-specialized hospital in São Paulo, Brazil. Age, ACS subtype, and diabetes were independent predictors of poor one‑year survival for overall and cardiovascular-related causes.

Predictors of Happiness and Emotional Intelligence in Secondary Education

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Federico Pulido Acosta

2018-01-01

Full Text Available This study analyzed predictors of happiness and emotional intelligence taking into account age, sex, culture and status and the relationship among these variables. 811 persons participated; 71.6% were Muslims and 28.4% Christians, with 46.1% males and 53.9% females. One questionnaire was used to evaluate happiness and another to evaluate emotional intelligence. The results indicate that predictors of happiness are age, culture, status and sex, while those of emotional intelligence are age, culture and sex. The study found that there is a statistically significant and direct correlation between happiness and emotional intelligence.

Longitudinal course and predictors of suicidal ideation in a rural community sample.

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Handley, Tonelle E; Attia, John R; Inder, Kerry J; Kay-Lambkin, Frances J; Barker, Daniel; Lewin, Terry J; Kelly, Brian J

2013-11-01

Suicide rates in rural Australia are higher than in urban areas. No existing research has explored the long-term patterns and predictors of change in suicidal ideation within rural areas. This report uses longitudinal data and multiple time points to determine predictors of the trajectory of suicidal ideation in rural Australia. Participants in the Australian Rural Mental Health Study (ARMHS) completed self-report surveys at baseline, 12 and 36 months, reporting their psychological and social well-being, and suicidal ideation. Generalised linear mixed models explored these factors as correlates and predictors of suicidal ideation across 3 years using multiple data points. A total of 2135 participants completed at least one wave of ARMHS, and hence were included in the current analysis. Overall, 8.1% reported suicidal ideation during at least one study wave, 76% of whom reported suicidal ideation intermittently rather than consistently across waves. Across the three time points, suicidal ideation was significantly associated with higher psychological distress (OR 1.30, 95% CI 1.23 to 1.37), neuroticism (OR 1.15, 95% CI 1.04 to 1.27), and availability of support (OR 0.80, 95% CI 0.69 to 0.92), with a non-significant association with unemployment (OR 1.73, 95% CI 0.93 to 3.24) even after controlling for the effects of perceived financial hardship. Future suicidal ideation was significantly predicted by distress (OR 1.16, 95% CI 1.09 to 1.23) and neuroticism (OR 1.17, 95% CI 1.03 to 1.32), with a non-significant association with unemployment (OR 2.11, 95% CI 0.41 to 2.27). Predictive effects for marital status, social networks, sense of community and availability of support did not remain significant in the full multivariate analysis. Fluctuations in suicidal ideation are common, and may be associated with changes in psychological and social well-being. Public health strategies, focusing on encouraging help-seeking among those with higher psychological distress, lower

Temporal predictors of health-related quality of life in elderly people with diabetes: results of a German cohort study.

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Maatouk, Imad; Wild, Beate; Wesche, Daniela; Herzog, Wolfgang; Raum, Elke; Müller, Heiko; Rothenbacher, Dietrich; Stegmaier, Christa; Schellberg, Dieter; Brenner, Hermann

2012-01-01

The aim of the study was to determine predictors that influence health-related quality of life (HRQOL) in a large cohort of elderly diabetes patients from primary care over a follow-up period of five years. At the baseline measurement of the ESTHER cohort study (2000-2002), 1375 out of 9953 participants suffered from diabetes (13.8%). 1057 of these diabetes patients responded to the second-follow up (2005-2007). HRQOL at baseline and follow-up was measured using the SF-12; mental component scores (MCS) and physical component scores (PCS) were calculated; multiple linear regression models were used to determine predictors of HRQOL at follow-up. As possible predictors for HRQOL, the following baseline variables were examined: treatment with insulin, glycated hemoglobin (HbA1c), number of diabetes related complications, number of comorbid diseases, Body-Mass-Index (BMI), depression and HRQOL. Regression analyses were adjusted for sociodemographic variables and smoking status. 1034 patients (97.8%) responded to the SF-12 both at baseline and after five years and were therefore included in the study. Regression analyses indicated that significant predictors of decreased MCS were a lower HRQOL, a higher number of diabetes related complications and a reported history of depression at baseline. Complications, BMI, smoking and HRQOL at baseline significantly predicted PCS at the five year follow-up. Our findings expand evidence from previous cross-sectional data indicating that in elderly diabetes patients, depression, diabetes related complications, smoking and BMI are temporally predictive for HRQOL.

Teacher and Child Predictors of Achieving IEP Goals of Children with Autism

OpenAIRE

Ruble, Lisa; McGrew, John H.

2013-01-01

It is encouraging that children with autism show a strong response to early intervention, yet more research is needed for understanding the variability in responsiveness to specialized programs. Treatment predictor variables from 47 teachers and children who were randomized to receive the COMPASS intervention (Ruble et al. in The collaborative model for promoting competence and success for students with ASD. Springer, New York, 2012a) were analyzed. Predictors evaluated agai...

The Predictors for Maternal Self-efficacy in Early Parenthood

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Elham Azmoude

2015-04-01

Full Text Available Background & aim: Many parents do not believe in their ability to fulfill their parental responsibilities. Parental self-efficacy is crucial to parents’ sense of well-being and is considered a predictor for quality of life. However, evidence is scarce on the factors that influence parents’ perception of efficacy. Therefore, this study aimed to investigate the predictors for parental self-efficacy in the early postpartum period. Methods:This descriptive analytical study was conducted on 150 primiparous women referring to the health care centers of Mashhad during their early postpartum months. For data collection, we used demographic questionnaires, Bates’ Infant Characteristics Questionnaire (ICQ, Scale of Perceived Social Support, Reece’s parent expectations survey (PES, and Edinburgh Postnatal Depression Scale (EPDS. For data analysis, independent T-test, one-way ANOVA, Pearson’s correlation coefficient, and stepwise regression were performed, using SPSS version 16. Results: In this study, a significant association was observed between self-efficacy scores and the parents’ income, educational status, depression, and infant’s gender. Furthermore, there was a significant correlation between self-efficacy scores and infant’s characteristics, mother’s satisfaction with childbirth experience, perceived support from friends, infant’s perceived temperament, infant’s gender, mother’s educational level, and depression, which could predict 26.1% of parental self-efficacy. Conclusion: According to the results of this study, the most significant predictors of maternal self-efficacy during the early postpartum months were maternal depression and educational status, infant’s gender, and infant’s characteristics.

Sex differences in predictors of violent and non-violent juvenile offending.

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Stephenson, Zoe; Woodhams, Jessica; Cooke, Claire

2014-01-01

In response to concerns regarding the rise in female juvenile violent crime and the dearth of gender-specific research, this study aimed to identify predictors of violent offending in female offenders. Data were extracted from risk assessments of 586 male and female juvenile offenders (aged 11-17 years) conducted between 2005 and 2009 by the Youth Offending Service in Gloucestershire, an English county. Information regarding the young people's living arrangements, family and personal relationships, education, emotional/mental health, thinking and behavior, and attitudes to offending was recorded. Comparisons were made between the violent male offenders (N = 185), the violent female offenders (N = 113), the non-violent male offenders (N = 150), and the non-violent female offenders (N = 138) for these variables. These were followed by a multinomial logistic regression analysis. The findings indicated that engaging in self-harm was the best predictor of being a female violent offender, with the predictors of giving into pressure from others and attempted suicide nearing significance. Furthermore, non-violent females were significantly less likely to lose control of their temper and more likely to give in to pressure from others than their violent counterparts. Non-violent males were significantly less likely to lose control of their temper and more likely to self-harm and give in to pressure from others than violent males. Although many similarities existed between sexes for predictors of violent offending, the findings of this study indicate that more attention needs to be paid to the mental health of female offenders. © 2013 Wiley Periodicals, Inc.

Predictors of cognitive decline in older adult type 2 diabetes from the Veterans Affairs Diabetes Trial

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Mark Zimering

2016-09-01

Full Text Available Aims: Cognitive decline disproportionately affects older adult type 2 diabetes. We tested whether randomized intensive glucose-lowering reduces the rate(s of cognitive decline in adults with advanced type 2 diabetes (mean: age, 60 years; diabetes duration, 11 years from the Veterans Affairs Diabetes Trial. Methods: A battery of neuropsychological tests (digit span, digit symbol substitution (DSym, and Trails-making Part B (TMT-B was administered at baseline in ~1700 participants and repeated at year 5. Thirty-six risk factors were evaluated as predictors of cognitive decline in multivariable regression analyses.Results: The mean age-adjusted, DSym or TMT-B declined significantly in all study participants (P < 0.001. Randomized intensive glucose-lowering did not significantly alter the rate of cognitive decline. The final model of risk factors associated with 5-year decline in age-adjusted TMT-B included as significant predictors: longer baseline diabetes duration (beta = -0.028; P = 0.0057, lower baseline diastolic blood pressure (beta = 0.028; P < 0.001, and baseline calcium channel blocker medication use (beta = -0.639; P < 0.001. Higher baseline pulse pressure was significantly associated with decline in age-adjusted TMT-B suggesting a role for both higher systolic and lower diastolic blood pressure. Baseline thiazide diuretic use (beta= -0.549; P =0.015 was an additional significant predictor of 5-year decline in age-adjusted digit symbol score. Post-baseline systolic blood pressure-lowering was significantly associated (P < 0.001 with decline in TMT-B performance. There was a significant inverse association between post-baseline plasma triglyceride- lowering (P = 0.045 and decline in digit symbol substitution task performance.Conclusions: A five-year period of randomized intensive glucose-lowering did not significantly reduce the rate of cognitive decline in older-aged adults with type 2 diabetes. Systolic and diastolic blood pressure as

Predictors of Immunosuppressive Regulatory T Lymphocytes in Healthy Women

International Nuclear Information System (INIS)

Hampras, S. S.; Nesline, M.; Davis, W.; Moysich, K. B.; Wallace, P. K.; Odunsi, K.; Furlani, N.

2012-01-01

Immunosuppressive regulatory T (Treg) cells play an important role in antitumor immunity, self-tolerance, transplantation tolerance, and attenuation of allergic response. Higher proportion of Treg cells has been observed in peripheral blood of cancer cases compared to controls. Little is known about potential epidemiological predictors of Treg cell levels in healthy individuals. We conducted a cross-sectional study including 75 healthy women, between 20 and 80 years of age, who participated in the Data Bank and Bio Repository (DBBR) program at Roswell Park Cancer Institute (RPCI), Buffalo, NY, USA. Peripheral blood levels of CD4 + CD25 + FOXP3 + Treg cells were measured using flow cytometric analysis. A range of risk factors was evaluated using Wilcoxon Rank-Sum test, Kruskal-Wallis test, and linear regression. Age, smoking, medications for treatment of osteoporosis, postmenopausal status, body mass index (BMI), and hormone replacement therapy (HRT) were found to be significant positive predictors of Treg cell levels in peripheral blood (π≤0.05 ). Higher education, exercise, age at first birth, oral contraceptives, and use of Ibuprofen were found be significant (π<0.05) negative predictors of Treg levels. Thus, various epidemiological risk factors might explain interindividual variation in immune response to pathological conditions, including cancer.

Predictors of Suicide Attempts in Clinically Depressed Korean Adolescents

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Kwon, Ahye; Song, Jungeun; Yook, Ki-Hwan; Jon, Duk-In; Jung, Myung Hun; Hong, Narei; Hong, Hyun Ju

2016-01-01

We examined predictors of suicide attempts in clinically depressed adolescents in Korea and gender differences in suicidal behavior. In total, 106 adolescents diagnosed with depressive disorder were recruited in South Korea. We assessed various variables that might affect suicide attempts, and used a structured interview for the diagnosis of depression and comorbidities and to evaluate suicidality. Demographic and clinical characteristics of the subjects were compared between suicide attempt and non-suicide attempt groups and we examined significant predictors of suicide attempts. Gender differences in suicidal ideation and suicidal behavior were also analyzed. Among 106 depressed participants, 50 (47.2%) adolescents were classified in the suicide attempt group. Generally, the suicide attempt and non-suicide attempt group shared similar clinical characteristics. The suicide attempt group had more females, more major depressive disorder diagnoses, more depressive episodes, and higher suicidal ideation than the non-suicide attempt group. Suicidal ideation was the only significant predictor of suicidal attempt, regardless of gender. Higher suicidal ideation frequency scores and more non-suicidal self-injurious behaviors were shown in the female suicide attempt group than the male suicide attempt group. It is recommended that suicidal ideation be assessed regularly and managed rigorously to decrease suicide risks in depressive adolescents. PMID:27776392

Meta-Analyses of Predictors of Hope in Adolescents.

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Yarcheski, Adela; Mahon, Noreen E

2016-03-01

The purposes of this study were to identify predictors of hope in the literature reviewed, to use meta-analysis to determine the mean effect size (ES) across studies between each predictor and hope, and to examine four moderators on each predictor-hope relationship. Using preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines for the literature reviewed, 77 published studies or doctoral dissertations completed between 1990 and 2012 met the inclusion criteria. Eleven predictors of hope were identified and each predictor in relation to hope was subjected to meta-analysis. Five predictors (positive affect, life satisfaction, optimism, self-esteem, and social support) of hope had large mean ESs, 1 predictor (depression) had a medium ES, 4 predictors (negative affect, stress, academic achievement, and violence) had small ESs, and 1 predictor (gender) had a trivial ES. Findings are interpreted for the 11 predictors in relation to hope. Limitations and conclusions are addressed; future studies are recommended. © The Author(s) 2014.

Predictors of early stable symptomatic remission after an exacerbation of schizophrenia: the significance of symptoms, neuropsychological performance and cognitive biases.

Science.gov (United States)

Andreou, Christina; Roesch-Ely, Daniela; Veckenstedt, Ruth; Bohn, Francesca; Aghotor, Julia; Köther, Ulf; Pfueller, Ute; Moritz, Steffen

2013-12-30

Neuropsychological deficits and severity of initial psychopathology have been repeatedly associated with poor symptomatic outcomes in schizophrenia. The role of higher-order cognitive biases on symptomatic outcomes of the disorder has not yet been investigated. The present study aimed to assess the contribution of cognitive biases, psychopathology and neuropsychological deficits on the probability of achieving early symptomatic remission after a psychotic episode in patients with schizophrenia. Participants were 79 patients with a DSM-IV diagnosis of schizophrenia or schizoaffective disorder undergoing an acute psychotic episode, and 25 healthy controls. According to psychopathology assessments, patients were split into those who had achieved remission after an average follow-up interval of 7 months, and those who had not (NR). Patients who achieved remission exhibited higher premorbid IQ and better performance on the TMT-B, as well as lower baseline positive, disorganized and distress symptoms than NR patients. TMT-B performance and positive symptoms at baseline were the best predictors of remission. Cognitive biases and negative symptoms were not associated with later remission. The findings highlight the significance of initial symptom severity for at least short-term symptomatic outcomes and, thus, the importance of adequate symptomatic treatment and prevention of psychotic outbreaks in patients. © 2013 Elsevier Ireland Ltd. All rights reserved.

A smart predictor for material property testing

International Nuclear Information System (INIS)

Wang, Wilson; Kanneg, Derek

2008-01-01

A reliable predictor is very useful for real-world industrial applications to forecast the future behavior of dynamic systems. A smart predictor, based on a novel recurrent neural fuzzy (RNF) scheme, is developed in this paper for multi-step-ahead prediction of material properties. A systematic investigation based on two benchmark data sets is conducted in terms of performance and efficiency. Analysis results reveal that, of the data-driven forecasting schemes, predictors based on step input patterns outperform those based on sequential input patterns; the RNF predictor outperforms those based on recurrent neural networks and ANFIS schemes in multi-step-ahead prediction of nonlinear time series. An adaptive Levenberg–Marquardt training technique is adopted to improve the robustness and convergence of the RNF predictor. Furthermore, the proposed smart predictor is implemented for material property testing. Investigation results show that the developed RNF predictor is a reliable forecasting tool for material property testing; it can capture and track the system's dynamic characteristics quickly and accurately. It is also a robust predictor to accommodate different system conditions

Predictors of quality of life among Chinese people with schizophrenia.

Science.gov (United States)

Wang, Xiao Qin; Petrini, Marcia A; Morisky, Donald E

2017-06-01

This study was designed to investigate the association of quality of life, perceived stigma, and medication adherence among Chinese patients with schizophrenia, and to ascertain the predictors of quality of life. A cross-sectional correlation study was conducted with 146 participants. All participants completed self-report scales: the Schizophrenia Quality of Life Scale, Link's Stigma Scale, and the Morisky Medication Adherence Scale. Pearson parametric correlations and stepwise multiple regressions were performed. The total quality of life score and psychosocial subscale was significantly positively correlated with perceived stigma, coping orientation of withdrawal, and feelings of stigma, and negatively correlated with age and medication adherence. The means of all subscale scores except perceived devaluation-discrimination and different/guilty feelings were significantly higher than the midpoint of 2.5. The best predictors of quality of life and psychosocial domains were stigma-related feelings: feeling misunderstood, feeling different/shame, and age. Our findings suggest that an individual's negative emotional response may strengthen internalized stigma and decrease quality of life. As the best predictor, age indicated that adaptation to mental illness may relieve perceived stigma and achieve favorable quality of life. © 2016 John Wiley & Sons Australia, Ltd.

Predictors of Hospitalization among Children on ART in Ethiopia: a Cohort study.

Science.gov (United States)

Haileamlak, Abraham; Hagos, Tesfalem; Abebe, Workeabeba; Abraham, Loko; Asefa, Henok; Teklu, Alula M

2017-02-01

Substantial progress has been made in the management of pediatric HIV infection in Ethiopia with the implementation of mother-to-child-prevention programs. Since the introduction of HAART in 2005, mortality among HIV-infected children has reduced while the rate of hospitalization was expected to rise. The purpose of this study, therefore, was to assess predictors of hospitalization in children on ART in seven university referral hospitals in Ethiopia. A prospective cohort study design was employed on children age 0-18 years as part of a multisite observational study. ART-experienced eligible and ART-naïve children with HIV/AIDS were enrolled into the Advanced Clinical Monitoring (ACM) till December 31, 2012 were included. From the database, information on hospitalization and other independent variables were extracted. Analysis was done using both SPSS for Windows version 16.0 and STATA. Descriptive analyses and modeling was done using logistic regression. Of the 405 children on ART (174 experienced, 231 naive), 86 (20.7%) were hospitalized for various reasons; two children were excluded since they were hospitalized for unrelated conditions (appendicitis and burn). Fifty one (60.7%) of the eighty four admitted children were hospitalized in the first six months of ART initiation. Of the independent variables, only the presence of opportunistic infections and duration on ART were significantly associated with hospitalization both on bi-variable and multivariable analyses (P-value ART increased by one month, the risk of hospitalization decreased by 5.4%, which is statistically significant (P hospitalized increased by 35.2% (P = 0.002). Of the individual opportunistic infections, pneumonia was found to be the only predictor of hospitalization (P-value = 0.002). This study showed that nearly two-third of the hospitalization was within 6 months of initiation of ART; and presence of OI and duration on ART were the only predictors of hospitalization.

Clinical Predictors of Intensive Care Unit Admission for Asthmatic Children

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Mohammad Hasan Kargar Maher

2015-07-01

Full Text Available IntroductionChildren with severe asthma attack are a challenging group of patients who could be difficult to treat and leading to significant morbidity and mortality. Asthma attack severity is qualitatively estimated as mild, moderate and severe attacks and respiratory failure based on conditions such as respiration status, feeling of dyspnea, and the degree of unconsciousness. part of which are subjective rather than objective. We investigated clinical findings as predictors of severe attack and probable requirement for Pediatric Intensive Care Unit (PICU admission.Materials and MethodsIn a cross sectional and analytical study 120 patients with asthma attack were enrolled from April 2010 to April 2014 (80 admitted in the ward and 40 in pediatric intensive care unit. Predictors of PICU admission were investigated regarding to initial heart rate(HR, respiratory rate (RR, Arterial Oxygen Saturation(SaO2 and PaCo2 and clinically evident cyanosis.ResultsInitial heart rate(p-value=0.02, respiratory rate (p-value=0.03, Arterial Oxygen Saturation(p-value=0.02 and PaCo2(p-value=0.03 and clinically evident cyanosis were significantly different in two groups(Ward admitted and PICU admittedConclusion There was a significant correlation between initial vital sign and blood gas analysis suggesting usefulness of these factors as predictors of severe asthma attack and subsequent clinical course.

Predictors of Longitudinal Quality of Life in Juvenile Localized Scleroderma.

Science.gov (United States)

Ardalan, Kaveh; Zigler, Christina K; Torok, Kathryn S

2017-07-01

Localized scleroderma can negatively affect children's quality of life (QoL), but predictors of impact have not been well described. We sought to identify predictors of QoL impact in juvenile localized scleroderma patients. We analyzed longitudinal data from a single-center cohort of juvenile localized scleroderma patients, using hierarchical generalized linear modeling (HGLM) to identify predictors of QoL impact. HGLM is useful for nested data and allows for evaluation of both time-variant and time-invariant predictors. The number of extracutaneous manifestations (ECMs; e.g., joint contracture and hemifacial atrophy) and female sex predicted negative QoL impact, defined as a Children's Dermatology Life Quality Index score >1 (P = 0.019 for ECMs and P = 0.002 for female sex). As the time since the initial visit increased, the odds of reporting a negative QoL impact decreased (P scleroderma than cutaneous features. Further study is required to determine which ECMs have the most impact on QoL, which factors underlie sex differences in QoL in localized scleroderma, and why increasing the time since the initial visit appears to be protective. An improved understanding of predictors of QoL impact may allow for the identification of patients at risk of poorer outcomes and for the tailoring of treatment and psychosocial support. © 2016, American College of Rheumatology.

Crowdsourcing novel childhood predictors of adult obesity.

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Bevelander, Kirsten E; Kaipainen, Kirsikka; Swain, Robert; Dohle, Simone; Bongard, Josh C; Hines, Paul D H; Wansink, Brian

2014-01-01

Effective and simple screening tools are needed to detect behaviors that are established early in life and have a significant influence on weight gain later in life. Crowdsourcing could be a novel and potentially useful tool to assess childhood predictors of adult obesity. This exploratory study examined whether crowdsourcing could generate well-documented predictors in obesity research and, moreover, whether new directions for future research could be uncovered. Participants were recruited through social media to a question-generation website, on which they answered questions and were able to pose new questions that they thought could predict obesity. During the two weeks of data collection, 532 participants (62% female; age  =  26.5±6.7; BMI  =  29.0±7.0) registered on the website and suggested a total of 56 unique questions. Nineteen of these questions correlated with body mass index (BMI) and covered several themes identified by prior research, such as parenting styles and healthy lifestyle. More importantly, participants were able to identify potential determinants that were related to a lower BMI, but have not been the subject of extensive research, such as parents packing their children's lunch to school or talking to them about nutrition. The findings indicate that crowdsourcing can reproduce already existing hypotheses and also generate ideas that are less well documented. The crowdsourced predictors discovered in this study emphasize the importance of family interventions to fight obesity. The questions generated by participants also suggest new ways to express known predictors.

Crowdsourcing novel childhood predictors of adult obesity.

Directory of Open Access Journals (Sweden)

Kirsten E Bevelander

Full Text Available Effective and simple screening tools are needed to detect behaviors that are established early in life and have a significant influence on weight gain later in life. Crowdsourcing could be a novel and potentially useful tool to assess childhood predictors of adult obesity. This exploratory study examined whether crowdsourcing could generate well-documented predictors in obesity research and, moreover, whether new directions for future research could be uncovered. Participants were recruited through social media to a question-generation website, on which they answered questions and were able to pose new questions that they thought could predict obesity. During the two weeks of data collection, 532 participants (62% female; age  =  26.5±6.7; BMI  =  29.0±7.0 registered on the website and suggested a total of 56 unique questions. Nineteen of these questions correlated with body mass index (BMI and covered several themes identified by prior research, such as parenting styles and healthy lifestyle. More importantly, participants were able to identify potential determinants that were related to a lower BMI, but have not been the subject of extensive research, such as parents packing their children's lunch to school or talking to them about nutrition. The findings indicate that crowdsourcing can reproduce already existing hypotheses and also generate ideas that are less well documented. The crowdsourced predictors discovered in this study emphasize the importance of family interventions to fight obesity. The questions generated by participants also suggest new ways to express known predictors.

Self-regulation and recall: growth curve modeling of intervention outcomes for older adults.

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West, Robin L; Hastings, Erin C

2011-12-01

Memory training has often been supported as a potential means to improve performance for older adults. Less often studied are the characteristics of trainees that benefit most from training. Using a self-regulatory perspective, the current project examined a latent growth curve model to predict training-related gains for middle-aged and older adult trainees from individual differences (e.g., education), information processing skills (strategy use) and self-regulatory factors such as self-efficacy, control, and active engagement in training. For name recall, a model including strategy usage and strategy change as predictors of memory gain, along with self-efficacy and self-efficacy change, showed comparable fit to a more parsimonious model including only self-efficacy variables as predictors. The best fit to the text recall data was a model focusing on self-efficacy change as the main predictor of memory change, and that model showed significantly better fit than a model also including strategy usage variables as predictors. In these models, overall performance was significantly predicted by age and memory self-efficacy, and subsequent training-related gains in performance were best predicted directly by change in self-efficacy (text recall), or indirectly through the impact of active engagement and self-efficacy on gains (name recall). These results underscore the benefits of targeting self-regulatory factors in intervention programs designed to improve memory skills.

Attachment representation as predictor of internalizing problems in middle childhood

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Mária Halamová

2015-01-01

Full Text Available Problem: The current study examines the relationship between the representation of attachment relationship with mother and internalizing problems in the developmental period of middle childhood. The purpose of the study was to analyze whether the quality of attachment predicts the intensity and seriousness of internalizing problems in middle childhood; and to examine whether the models are gender-specific. Methods: Participants in this study were 151 children aged 9-12 (M = 11.21, 77 boys and 74 girls, recruited from elementary schools in Nitra region. Children completed measures assessing the quality of attachment representation of the relationship with mother (selfreport questionnaire Security Scale, the tendency to react anxiously (self-report questionnaire Childen´s Manifest Anxiety Scale – CMAS, social anxiety (self-report questionnaire Scale of Classical Social Situational Anxiety – KSAT and depression (self-report questionnaire Children´s Depression Inventory – CDI. Results: Regression analysis indicated that secure attachment representation is a significant negative predictor of children's internalizing problems – manifest anxiety (ß = -.324, p 0.05 and ß = -.194, p > 0.05, respectively, but in the sample of girls, secure attachment representation was a significant negative predictor of both depressive symptoms (ß = -.296, p < .05 for Negative Mood; and ß = -.285, p < .05 for Anhedony. Other models, except for social anxiety, were statistically significant for both samples. In the sample of girls, the predictor accounted for 26.3% of variance in Negative Self Esteem (ß = -.512; p < .001, 18.9% of variance of the total of depression symptoms (ß = -.435; p < .001, 10.9% of variance in Ineffectiveness (ß = -.331; p < .05 and 10.5% of variance in manifest anxiety (ß = -.324; p < .05. The results were similar for the sample of boys. Attachment security accounted for 17.4% of variance in Negative Self Esteem (ß = -.435; p

Predictors of early infection in cerebral ischemic stroke.

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Ashour, Wmr; Al-Anwar, A D; Kamel, A E; Aidaros, M A

2016-01-01

Infection is the most common complication of stroke. To determine the risk factors and predictors of post-stroke infection (PSI), which developed within 7 days from the onset of acute ischemic stroke. The study included 60 ischemic stroke patients admitted in the Neurology Department of Zagazig University, Egypt, who were subdivided into: [Non Stroke Associated Infection group (nSAI); 30 patients having stroke without any criteria of infection within 7 days from the onset and Stroke Associated Infection group (SAI); 30 patients having stroke with respiratory tract infection (RTI) or urinary tract infection within 7 days], in addition to 30 healthy sex and age-matching subjects as control. All the patients had a detailed history taking, thorough clinical general and neurological examination, laboratory tests (Urine analysis & urine culture, blood sugar, lipid profile and serum tumor necrosis factor-alpha (TNF-α) and interleukin (IL)-10), a chest radiography to assess RTI and brain computed tomography (CT) to exclude the hemorrhagic stroke and to confirm the ischemic stroke. SAI patients were found to be significantly older with higher baseline blood glucose level. Also the number of patients with tube feeding, lower conscious level, more stroke severity and more large size infarcts were significantly higher in SAI patients. There was a significant elevation in the IL-10, a significant decrease in the TNF-α and a significant decrease in the TNF-α/ IL-10 ratio, in the SAI group. The baseline serum level of IL-10 ≥ 14.5 pg/ ml and size of infarct area > 3.5 cm3 were found to be the independent predictors of PSI. Patients with older age, tube feeding, lower conscious level, worse baseline stroke severity, large cerebral infarcts in CT scan, and increased IL-10 serum level were more susceptible to infection. The baseline serum level of IL-10 ≥ 14.5 pg/ ml and the size of infarct area > 3.5 cm3 were the independent predictors of PSI.

Predictors of condom use and refusal among the population of Free State province in South Africa.

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Chandran, Thoovakkunon Moorkoth; Berkvens, Dirk; Chikobvu, Perpetual; Nöstlinger, Christiana; Colebunders, Robert; Williams, Brian Gerard; Speybroeck, Niko

2012-05-28

This study investigated the extent and predictors of condom use and condom refusal in the Free State province in South Africa. Through a household survey conducted in the Free Sate province of South Africa, 5,837 adults were interviewed. Univariate and multivariate survey logistic regressions and classification trees (CT) were used for analysing two response variables 'ever used condom' and 'ever refused condom'. Eighty-three per cent of the respondents had ever used condoms, of which 38% always used them; 61% used them during the last sexual intercourse and 9% had ever refused to use them. The univariate logistic regression models and CT analysis indicated that a strong predictor of condom use was its perceived need. In the CT analysis, this variable was followed in importance by 'knowledge of correct use of condom', condom availability, young age, being single and higher education. 'Perceived need' for condoms did not remain significant in the multivariate analysis after controlling for other variables. The strongest predictor of condom refusal, as shown by the CT, was shame associated with condoms followed by the presence of sexual risk behaviour, knowing one's HIV status, older age and lacking knowledge of condoms (i.e., ability to prevent sexually transmitted diseases and pregnancy, availability, correct and consistent use and existence of female condoms). In the multivariate logistic regression, age was not significant for condom refusal while affordability and perceived need were additional significant variables. The use of complementary modelling techniques such as CT in addition to logistic regressions adds to a better understanding of condom use and refusal. Further improvement in correct and consistent use of condoms will require targeted interventions. In addition to existing social marketing campaigns, tailored approaches should focus on establishing the perceived need for condom-use and improving skills for correct use. They should also incorporate

Predictors of condom use and refusal among the population of Free State province in South Africa

Directory of Open Access Journals (Sweden)

Chandran Thoovakkunon

2012-05-01

Full Text Available Abstract Background This study investigated the extent and predictors of condom use and condom refusal in the Free State province in South Africa. Methods Through a household survey conducted in the Free Sate province of South Africa, 5,837 adults were interviewed. Univariate and multivariate survey logistic regressions and classification trees (CT were used for analysing two response variables ‘ever used condom’ and ‘ever refused condom’. Results Eighty-three per cent of the respondents had ever used condoms, of which 38% always used them; 61% used them during the last sexual intercourse and 9% had ever refused to use them. The univariate logistic regression models and CT analysis indicated that a strong predictor of condom use was its perceived need. In the CT analysis, this variable was followed in importance by ‘knowledge of correct use of condom’, condom availability, young age, being single and higher education. ‘Perceived need’ for condoms did not remain significant in the multivariate analysis after controlling for other variables. The strongest predictor of condom refusal, as shown by the CT, was shame associated with condoms followed by the presence of sexual risk behaviour, knowing one’s HIV status, older age and lacking knowledge of condoms (i.e., ability to prevent sexually transmitted diseases and pregnancy, availability, correct and consistent use and existence of female condoms. In the multivariate logistic regression, age was not significant for condom refusal while affordability and perceived need were additional significant variables. Conclusions The use of complementary modelling techniques such as CT in addition to logistic regressions adds to a better understanding of condom use and refusal. Further improvement in correct and consistent use of condoms will require targeted interventions. In addition to existing social marketing campaigns, tailored approaches should focus on establishing the perceived need

Predictors of posttreatment drinking outcomes in patients with alcohol dependence.

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Flórez, Gerardo; Saiz, Pilar A; García-Portilla, Paz; De Cos, Francisco J; Dapía, Sonia; Alvarez, Sandra; Nogueiras, Luis; Bobes, Julio

2015-01-01

This cohort study examined how predictors of alcohol dependence treatment outcomes work together over time by comparing pretreatment and posttreatment predictors. A sample of 274 alcohol-dependent patients was recruited and assessed at baseline, 6 months after treatment initiation (end of the active intervention phase), and 18 months after treatment initiation (end of the 12-month research follow-up phase). At each assessment point, the participants completed a battery of standardized tests [European Addiction Severity Index (EuropASI), Obsessive Compulsive Drinking Scale (OCDS), Alcohol Timeline Followback (TLFB), Fagerström, and International Personality Disorder Examination (IPDE)] that measured symptom severity and consequences; biological markers of alcohol consumption were also tested at each assessment point. A sequential strategy with univariate and multivariate analyses was used to identify how pretreatment and posttreatment predictors influence outcomes up to 1 year after treatment. Pretreatment variables had less predictive power than posttreatment ones. OCDS scores and biological markers of alcohol consumption were the most significant variables for the prediction of posttreatment outcomes. Prior pharmacotherapy treatment and relapse prevention interventions were also associated with posttreatment outcomes. The findings highlight the positive impact of pharmacotherapy during the first 6 months after treatment initiation and of relapse prevention during the first year after treatment and how posttreatment predictors are more important than pretreatment predictors.

Comparison of transform coding methods with an optimal predictor for the data compression of digital elevation models

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Lewis, Michael

1994-01-01

Statistical encoding techniques enable the reduction of the number of bits required to encode a set of symbols, and are derived from their probabilities. Huffman encoding is an example of statistical encoding that has been used for error-free data compression. The degree of compression given by Huffman encoding in this application can be improved by the use of prediction methods. These replace the set of elevations by a set of corrections that have a more advantageous probability distribution. In particular, the method of Lagrange Multipliers for minimization of the mean square error has been applied to local geometrical predictors. Using this technique, an 8-point predictor achieved about a 7 percent improvement over an existing simple triangular predictor.

Estimation Parameters And Modelling Zero Inflated Negative Binomial

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Cindy Cahyaning Astuti

2016-11-01

Full Text Available Regression analysis is used to determine relationship between one or several response variable (Y with one or several predictor variables (X. Regression model between predictor variables and the Poisson distributed response variable is called Poisson Regression Model. Since, Poisson Regression requires an equality between mean and variance, it is not appropriate to apply this model on overdispersion (variance is higher than mean. Poisson regression model is commonly used to analyze the count data. On the count data type, it is often to encounteredd some observations that have zero value with large proportion of zero value on the response variable (zero Inflation. Poisson regression can be used to analyze count data but it has not been able to solve problem of excess zero value on the response variable. An alternative model which is more suitable for overdispersion data and can solve the problem of excess zero value on the response variable is Zero Inflated Negative Binomial (ZINB. In this research, ZINB is applied on the case of Tetanus Neonatorum in East Java. The aim of this research is to examine the likelihood function and to form an algorithm to estimate the parameter of ZINB and also applying ZINB model in the case of Tetanus Neonatorum in East Java. Maximum Likelihood Estimation (MLE method is used to estimate the parameter on ZINB and the likelihood function is maximized using Expectation Maximization (EM algorithm. Test results of ZINB regression model showed that the predictor variable have a partial significant effect at negative binomial model is the percentage of pregnant women visits and the percentage of maternal health personnel assisted, while the predictor variables that have a partial significant effect at zero inflation model is the percentage of neonatus visits.

Money and Marriage: Couple's Choices and their Predictors

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Lina Coelho

2016-01-01

Full Text Available The ways in which couples in South Europe manage their money has received little attention. This study uses regression analysis to evaluate the allocative systems of Portuguese couples and their predictors. To do this we use a sample of 3,331 households in Portugal with at least one heterosexual couple. Couples' allocative systems were classified based on Pahl's typology. The results confirm what has been found in previous studies regarding the prevalence of joint pooling management and the predictors of the different models for managing money. However, some particularities have been found: decisions taken in multi-generational familes favour partial joint pooling, as the distinctive characteristics of households in South Europe play a role in assigning intra-family resources.

The behaviour of random forest permutation-based variable importance measures under predictor correlation.

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Nicodemus, Kristin K; Malley, James D; Strobl, Carolin; Ziegler, Andreas

2010-02-27

Random forests (RF) have been increasingly used in applications such as genome-wide association and microarray studies where predictor correlation is frequently observed. Recent works on permutation-based variable importance measures (VIMs) used in RF have come to apparently contradictory conclusions. We present an extended simulation study to synthesize results. In the case when both predictor correlation was present and predictors were associated with the outcome (HA), the unconditional RF VIM attributed a higher share of importance to correlated predictors, while under the null hypothesis that no predictors are associated with the outcome (H0) the unconditional RF VIM was unbiased. Conditional VIMs showed a decrease in VIM values for correlated predictors versus the unconditional VIMs under HA and was unbiased under H0. Scaled VIMs were clearly biased under HA and H0. Unconditional unscaled VIMs are a computationally tractable choice for large datasets and are unbiased under the null hypothesis. Whether the observed increased VIMs for correlated predictors may be considered a "bias" - because they do not directly reflect the coefficients in the generating model - or if it is a beneficial attribute of these VIMs is dependent on the application. For example, in genetic association studies, where correlation between markers may help to localize the functionally relevant variant, the increased importance of correlated predictors may be an advantage. On the other hand, we show examples where this increased importance may result in spurious signals.

Women with clomiphene citrate resistant polycystic ovarian disease: predictors of spontaneous ovulation after laparoscopic ovarian drilling.

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Abuelghar, Wessam M; Bayoumy, Hassan A; Ellaithy, Mohamed I; Khalil, Marian S

2014-04-01

To evaluate the role of different clinical, biochemical and sonographic factors as predictors of spontaneous ovulation after laparoscopic ovarian drilling (LOD) in women with clomiphene citrate resistant polycystic ovarian disease (CCR-PCOD). This prospective study recruited 251 infertile women with CCR-PCOD. Several clinical, biochemical and sonographic criteria were tested as possible predictors of spontaneous ovulation after LOD using multivariate analysis. Women with higher preoperative levels of LH, FSH and/or androstenedione had significantly higher rates of spontaneous ovulation within the first eight weeks after LOD, but only FSH and androstenedione were found to be independent predictors. Other factors including age, BMI, type of infertility, duration of infertility, menstrual pattern, testosterone level, ovarian volume and SHBG were insignificant predictors. Receiver-operating characteristic (ROC) curves derived from FSH, LH, androstenedione, and a logistic regression model showed that the best cut-off values were 4.1IU/l, 7.8IU/l, 1.2ng/ml, and 0.4897, respectively, with sensitivity of 91.18%, 100%, 73.53%, and 88.24% and specificity of 69.57%, 69.57%, 65.22%, and 73.91% for FSH, LH, androstenedione, and logistic regression model respectively. An extended follow up (9 months after LOD) was conducted for the anovulatory and the non-pregnant ovulatory women, who were treated individually according to their clinical situation. Of these women, 53.5% (69/129) got pregnant, resulting in a cumulative pregnancy rate of 48% (82/171). Of these pregnancies, 16/82 (19.5%) were spontaneous while 35.4% (29/82) and 45.1% (37/82) occurred after ovulation induction by CC and gonadotropins, respectively. This study supports the use of androstenedione, LH and FSH as a simple reliable tool in triaging patients with CCR-PCOD to select the ideal candidates for LOD. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Modelling tourists arrival using time varying parameter

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Suciptawati, P.; Sukarsa, K. G.; Kencana, Eka N.

2017-06-01

The importance of tourism and its related sectors to support economic development and poverty reduction in many countries increase researchers’ attentions to study and model tourists’ arrival. This work is aimed to demonstrate time varying parameter (TVP) technique to model the arrival of Korean’s tourists to Bali. The number of Korean tourists whom visiting Bali for period January 2010 to December 2015 were used to model the number of Korean’s tourists to Bali (KOR) as dependent variable. The predictors are the exchange rate of Won to IDR (WON), the inflation rate in Korea (INFKR), and the inflation rate in Indonesia (INFID). Observing tourists visit to Bali tend to fluctuate by their nationality, then the model was built by applying TVP and its parameters were approximated using Kalman Filter algorithm. The results showed all of predictor variables (WON, INFKR, INFID) significantly affect KOR. For in-sample and out-of-sample forecast with ARIMA’s forecasted values for the predictors, TVP model gave mean absolute percentage error (MAPE) as much as 11.24 percent and 12.86 percent, respectively.

Predictors of psychological resilience amongst medical students following major earthquakes.

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Carter, Frances; Bell, Caroline; Ali, Anthony; McKenzie, Janice; Boden, Joseph M; Wilkinson, Timothy; Bell, Caroline

2016-05-06

To identify predictors of self-reported psychological resilience amongst medical students following major earthquakes in Canterbury in 2010 and 2011. Two hundred and fifty-three medical students from the Christchurch campus, University of Otago, were invited to participate in an electronic survey seven months following the most severe earthquake. Students completed the Connor-Davidson Resilience Scale, the Depression, Anxiety and Stress Scale, the Post-traumatic Disorder Checklist, the Work and Adjustment Scale, and the Eysenck Personality Questionnaire. Likert scales and other questions were also used to assess a range of variables including demographic and historical variables (eg, self-rated resilience prior to the earthquakes), plus the impacts of the earthquakes. The response rate was 78%. Univariate analyses identified multiple variables that were significantly associated with higher resilience. Multiple linear regression analyses produced a fitted model that was able to explain 35% of the variance in resilience scores. The best predictors of higher resilience were: retrospectively-rated personality prior to the earthquakes (higher extroversion and lower neuroticism); higher self-rated resilience prior to the earthquakes; not being exposed to the most severe earthquake; and less psychological distress following the earthquakes. Psychological resilience amongst medical students following major earthquakes was able to be predicted to a moderate extent.

Predictors of hope among women with breast cancer during chemotherapy

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Alessandra Cristina Sartore Balsanelli

Full Text Available Abstract OBJECTIVE Identifying the predictors of hope in patients with breast cancer during chemotherapy treatment. METHOD A prospective longitudinal study. The sample was composed of 122 women who responded to the instruments of hope, anxiety and depression, coping, fatigue, religiosity and self-esteem in the first and last cycle of chemotherapy. These variables were used in adjusting the logistic regression model that characterized multivariate statistics, allowing identification of predictor variables. RESULT The increase of hope at the end of chemotherapy treatment was statistically significant (p = 0.012. The delay in undergoing treatment from the onset of breast cancer symptoms, Karnofsky Performance Status, depression, self-esteem and pain were characterized as factors being associated to hope by univariate analysis. Among the variables analyzed, pain was the only predicting factor of hope. CONCLUSION Pain was the predicting factor in this sample. Hope increased during treatment and revealed the following associated factors: Karnofsky Performance Status, delay in starting the treatment, depression, self-esteem and pain. This study brought forth a multidisciplinary contribution, allowing for understanding the factors that can influence hope and presenting support to nursing care. The data evidenced conditions of improvement or worsening of hope, which requires interdisciplinary attention in Oncology.

Predictors of Persistent Axial Neck Pain After Cervical Laminoplasty.

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Kimura, Atsushi; Shiraishi, Yasuyuki; Inoue, Hirokazu; Endo, Teruaki; Takeshita, Katsushi

2018-01-01

Retrospective analysis of prospective data. The aim of this study was to reveal baseline predictors of persistent postlaminoplasty neck pain. Axial neck pain is one of the most common complications after cervical laminoplasty; however, baseline predictors of persistent postlaminoplasty neck pain are unclear. We analyzed data from 156 patients who completed a 2-year follow-up after double-door laminoplasty for degenerative cervical myelopathy. Patients rated the average intensity of axial neck pain in the last month using an 11-point numerical rating scale preoperatively and at the 2-year follow-up. The dependent variable was the presence of moderate-to-severe neck pain (numerical rating scale ≥4) at the 2-year follow-up. The independent variables included patient characteristics, baseline radiological parameters, surgical variables, baseline axial neck pain intensity, and baseline functions, which were measured by the Japanese Orthopaedic Association score and the Short Form-36 survey (SF-36). Logistic regression analysis was performed to identify independent predictors of moderate-to-severe neck pain after laminoplasty. At the 2-year follow-up, 51 patients (32%) had moderate-to-severe neck pain, and 106 patients (68%) had no or mild pain. Univariate analysis revealed that the ratio of cervical anterolisthesis, ratio of current smoking, baseline neck pain intensity, and baseline SF-36 Mental Component Summary differed significantly between the groups. Multivariate logistic regression analysis showed that independent predictors of moderate-to-severe neck pain at the 2-year follow-up include the presence of anterolisthesis, current smoking, moderate-to-severe baseline neck pain, and lower SF-36 Mental Component Summary. The presence of anterolisthesis and moderate-to-severe baseline neck pain were also associated with significantly poorer physical function after surgery. The presence of anterolisthesis was associated not only with the highest odds ratio of

Predicting Performance in Higher Education Using Proximal Predictors

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Niessen, A. Susan M.; Meijer, Rob R.; Tendeiro, Jorge N.

2016-01-01

We studied the validity of two methods for predicting academic performance and student-program fit that were proximal to important study criteria. Applicants to an undergraduate psychology program participated in a selection procedure containing a trial-studying test based on a work sample approach, and specific skills tests in English and math. Test scores were used to predict academic achievement and progress after the first year, achievement in specific course types, enrollment, and dropout after the first year. All tests showed positive significant correlations with the criteria. The trial-studying test was consistently the best predictor in the admission procedure. We found no significant differences between the predictive validity of the trial-studying test and prior educational performance, and substantial shared explained variance between the two predictors. Only applicants with lower trial-studying scores were significantly less likely to enroll in the program. In conclusion, the trial-studying test yielded predictive validities similar to that of prior educational performance and possibly enabled self-selection. In admissions aimed at student-program fit, or in admissions in which past educational performance is difficult to use, a trial-studying test is a good instrument to predict academic performance. PMID:27073859

Sleep and Academic Performance in Undergraduates: A Multi-measure, Multi-predictor Approach

OpenAIRE

Gomes, Ana Allen; Tavares, José; de Azevedo, Maria Helena P.

2011-01-01

The present study examined the associations of sleep patterns with multiple measures of academic achievement of undergraduate university students and tested whether sleep variables emerged as significant predictors of subsequent academic performance when other potential predictors, such as class attendance, time devoted to study, and substance use are considered. A sample of 1654 (55% female) full-time undergraduates 17 to 25 yrs of age responded to a self-response questionnaire on sleep, aca...

Predictors of successful closure of patent ductus arteriosus with indomethacin.

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Ahamed, M F; Verma, P; Lee, S; Vega, M; Wang, D; Kim, M; Fuloria, M

2015-09-01

To determine whether platelet counts can predict the likelihood of successful closure of patent ductus arteriosus (PDA) with indomethacin. This was a retrospective cohort study of infants closure with indomethacin and those who failed were compared. Multivariable logistic regression was used to identify predictors of successful ductal closure. In infants with hemodynamically significant PDA, older GA (odds ratio=1.54; 95% confidence interval: 1.12 to 2.13), male gender (odds ratio=3.02; 95% confidence interval: 1.08 to 8.49) and higher platelet count (odds ratio=1.5; 95% confidence interval: 1.04 to 2.17) prior to indomethacin treatment were associated with successful ductal closure with indomethacin. Older GA, male gender and higher platelet count at time of treatment of hemodynamically significant PDA are predictors of successful ductal closure with indomethacin.

predictors of c-reactive protein response in children infected

African Journals Online (AJOL)

2014-01-01

Jan 1, 2014 ... Results: The predictors of the C-reactive protein response in malaria (CRP ≥ 10mg/l) were fever (t = 6.867; ..... The lack of a significant difference between the ... infections - A major cause of death among children in Africa.

Predictors of outcome among patients with obstructive jaundice at ...

African Journals Online (AJOL)

Despite recent advances both in preoperative diagnosis and postoperative care, obstructive jaundice still contributes significantly to high morbidity and mortality. A prospective study was undertaken to identify predictors of outcome among patients with obstructive jaundice at Bugando Medical Centre in north-western ...

To cross or not to cross: modeling wildlife road crossings as a binary response variable with contextual predictors

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Siers, Shane R.; Reed, Robert N.; Savidge, Julie A.

2016-01-01

Roads are significant barriers to landscape-scale movements of individuals or populations of many wildlife taxa. The decision by an animal near a road to either cross or not cross may be influenced by characteristics of the road, environmental conditions, traits of the individual animal, and other aspects of the context within which the decision is made. We considered such factors in a mixed-effects logistic regression model describing the nightly road crossing probabilities of invasive nocturnal Brown Treesnakes (Boiga irregularis) through short-term radiotracking of 691 snakes within close proximity to 50 road segments across the island of Guam. All measures of road magnitude (traffic volume, gap width, surface type, etc.) were significantly negatively correlated with crossing probabilities. Snake body size was the only intrinsic factor associated with crossing rates, with larger snakes crossing roads more frequently. Humidity was the only environmental variable affecting crossing rate. The distance of the snake from the road at the start of nightly movement trials was the most significant predictor of crossings. The presence of snake traps with live mouse lures during a portion of the trials indicated that localized prey cues reduced the probability of a snake crossing the road away from the traps, suggesting that a snake's decision to cross roads is influenced by local foraging opportunities. Per capita road crossing rates of Brown Treesnakes were very low, and comparisons to historical records suggest that crossing rates have declined in the 60+ yr since introduction to Guam. We report a simplified model that will allow managers to predict road crossing rates based on snake, road, and contextual characteristics. Road crossing simulations based on actual snake size distributions demonstrate that populations with size distributions skewed toward larger snakes will result in a higher number of road crossings. Our method of modeling per capita road crossing

Predictor-weighting strategies for probabilistic wind power forecasting with an analog ensemble

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Constantin Junk

2015-04-01

Full Text Available Unlike deterministic forecasts, probabilistic predictions provide estimates of uncertainty, which is an additional value for decision-making. Previous studies have proposed the analog ensemble (AnEn, which is a technique to generate uncertainty information from a purely deterministic forecast. The objective of this study is to improve the AnEn performance for wind power forecasts by developing static and dynamic weighting strategies, which optimize the predictor combination with a brute-force continuous ranked probability score (CRPS minimization and a principal component analysis (PCA of the predictors. Predictors are taken from the high-resolution deterministic forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF, including forecasts of wind at several heights, geopotential height, pressure, and temperature, among others. The weighting strategies are compared at five wind farms in Europe and the U.S. situated in regions with different terrain complexity, both on and offshore, and significantly improve the deterministic and probabilistic AnEn forecast performance compared to the AnEn with 10‑m wind speed and direction as predictors and compared to PCA-based approaches. The AnEn methodology also provides reliable estimation of the forecast uncertainty. The optimized predictor combinations are strongly dependent on terrain complexity, local wind regimes, and atmospheric stratification. Since the proposed predictor-weighting strategies can accomplish both the selection of relevant predictors as well as finding their optimal weights, the AnEn performance is improved by up to 20 % at on and offshore sites.

Predictors of depression stigma

Directory of Open Access Journals (Sweden)

Jorm Anthony F

2008-04-01

Full Text Available Abstract Background To investigate and compare the predictors of personal and perceived stigma associated with depression. Method Three samples were surveyed to investigate the predictors: a national sample of 1,001 Australian adults; a local community sample of 5,572 residents of the Australian Capital Territory and Queanbeyan aged 18 to 50 years; and a psychologically distressed subset (n = 487 of the latter sample. Personal and Perceived Stigma were measured using the two subscales of the Depression Stigma Scale. Potential predictors included demographic variables (age, gender, education, country of birth, remoteness of residence, psychological distress, awareness of Australia's national depression initiative beyondblue, depression literacy and level of exposure to depression. Not all predictors were used for all samples. Results Personal stigma was consistently higher among men, those with less education and those born overseas. It was also associated with greater current psychological distress, lower prior contact with depression, not having heard of a national awareness raising initiative, and lower depression literacy. These findings differed from those for perceived stigma except for psychological distress which was associated with both higher personal and higher perceived stigma. Remoteness of residence was not associated with either type of stigma. Conclusion The findings highlight the importance of treating the concepts of personal and perceived stigma separately in designing measures of stigma, in interpreting the pattern of findings in studies of the predictors of stigma, and in designing, interpreting the impact of and disseminating interventions for stigma.

Base Deficit as an Indicator of Significant Blunt Abdominal Trauma

African Journals Online (AJOL)

multiruka1

important cause of morbidity and mortality among trauma patients. ... the use of BD as an indicator of significant BAT. Methods: ... Key words: Base deficit, Blunt abdominal trauma,. Predictor. ..... Delineate Risk for Torso Injury in Stable Patients.

Third molar development: measurements versus scores as age predictor.

Science.gov (United States)

Thevissen, P W; Fieuws, S; Willems, G

2011-10-01

Human third molar development is widely used to predict chronological age of sub adult individuals with unknown or doubted age. For these predictions, classically, the radiologically observed third molar growth and maturation is registered using a staging and related scoring technique. Measures of lengths and widths of the developing wisdom tooth and its adjacent second molar can be considered as an alternative registration. The aim of this study was to verify relations between mandibular third molar developmental stages or measurements of mandibular second molar and third molars and age. Age related performance of stages and measurements were compared to assess if measurements added information to age predictions from third molar formation stage. The sample was 340 orthopantomograms (170 females, 170 males) of individuals homogenously distributed in age between 7 and 24 years. Mandibular lower right, third and second molars, were staged following Gleiser and Hunt, length and width measurements were registered, and various ratios of these measurements were calculated. Univariable regression models with age as response and third molar stage, measurements and ratios of second and third molars as predictors, were considered. Multivariable regression models assessed if measurements or ratios added information to age prediction from third molar stage. Coefficients of determination (R(2)) and root mean squared errors (RMSE) obtained from all regression models were compared. The univariable regression model using stages as predictor yielded most accurate age predictions (males: R(2) 0.85, RMSE between 0.85 and 1.22 year; females: R(2) 0.77, RMSE between 1.19 and 2.11 year) compared to all models including measurements and ratios. The multivariable regression models indicated that measurements and ratios added no clinical relevant information to the age prediction from third molar stage. Ratios and measurements of second and third molars are less accurate age predictors

Clinical predictors of central sleep apnea evoked by positive airway pressure titration.

Science.gov (United States)

Moro, Marilyn; Gannon, Karen; Lovell, Kathy; Merlino, Margaret; Mojica, James; Bianchi, Matt T

2016-01-01

Treatment-emergent central sleep apnea (TECSA), also called complex apnea, occurs in 5%-15% of sleep apnea patients during positive airway pressure (PAP) therapy, but the clinical predictors are not well understood. The goal of this study was to explore possible predictors in a clinical sleep laboratory cohort, which may highlight those at risk during clinical management. We retrospectively analyzed 728 patients who underwent PAP titration (n=422 split-night; n=306 two-night). Demographics and self-reported medical comorbidities, medications, and behaviors as well as standard physiological parameters from the polysomnography (PSG) data were analyzed. We used regression analysis to assess predictors of binary presence or absence of central apnea index (CAI) ≥5 during split-night PSG (SN-PSG) versus full-night PSG (FN-PSG) titrations. CAI ≥5 was present in 24.2% of SN-PSG and 11.4% of FN-PSG patients during titration. Male sex, maximum continuous positive airway pressure, and use of bilevel positive airway pressure were predictors of TECSA, and rapid eye movement dominance was a negative predictor, for both SN-PSG and FN-PSG patients. Self-reported narcotics were a positive predictor of TECSA, and the time spent in stage N2 sleep was a negative predictor only for SN-PSG patients. Self-reported history of stroke and the CAI during the diagnostic recording predicted TECSA only for FN-PSG patients. Clinical predictors of treatment-evoked central apnea spanned demographic, medical history, sleep physiology, and titration factors. Improved predictive models may be increasingly important as diagnostic and therapeutic modalities move away from the laboratory setting, even as PSG remains the gold standard for characterizing primary central apnea and TECSA.

Predictors of change in life skills in schizophrenia after cognitive remediation.

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Kurtz, Matthew M; Seltzer, James C; Fujimoto, Marco; Shagan, Dana S; Wexler, Bruce E

2009-02-01

Few studies have investigated predictors of response to cognitive remediation interventions in patients with schizophrenia. Predictor studies to date have selected treatment outcome measures that were either part of the remediation intervention itself or closely linked to the intervention with few studies investigating factors that predict generalization to measures of everyday life-skills as an index of treatment-related improvement. In the current study we investigated the relationship between four measures of neurocognitive function, crystallized verbal ability, auditory sustained attention and working memory, verbal learning and memory, and problem-solving, two measures of symptoms, total positive and negative symptoms, and the process variables of treatment intensity and duration, to change on a performance-based measure of everyday life-skills after a year of computer-assisted cognitive remediation offered as part of intensive outpatient rehabilitation treatment. Thirty-six patients with schizophrenia or schizoaffective disorder were studied. Results of a linear regression model revealed that auditory attention and working memory predicted a significant amount of the variance in change in performance-based measures of everyday life skills after cognitive remediation, even when variance for all other neurocognitive variables in the model was controlled. Stepwise regression revealed that auditory attention and working memory predicted change in everyday life-skills across the trial even when baseline life-skill scores, symptoms and treatment process variables were controlled. These findings emphasize the importance of sustained auditory attention and working memory for benefiting from extended programs of cognitive remediation.

Gambling Disorder: Exploring Pre-treatment and In-treatment Dropout Predictors. A UK Study.

Science.gov (United States)

Ronzitti, Silvia; Soldini, Emiliano; Smith, Neil; Clerici, Massimo; Bowden-Jones, Henrietta

2017-12-01

The aim of this study was to identify predictors of treatment dropout in a sample of gamblers attending a specialist clinic for gambling disorder. We analysed data on 846 treatment-seeking pathological gamblers. Firstly, we investigated differences in socio-demographic and clinical variables between treatment completers and pre-treatment dropouts, as well as between treatment completers and during-treatment dropouts. Subsequently, variables were entered into a multinomial logistic regression model to identify significant predictors of pre-treatment and in-treatment dropout. Overall, 44.8% of clients did not complete the treatment: 27.4% dropped out before starting it, while 17.4% dropped out during the treatment. Younger age and use of drugs were associated with pre-treatment dropout, while family history of gambling disorder, a lower PGSI score, and being a smoker were related with in-treatment dropout. Our findings suggest that pre-treatment dropouts differ from in-treatment dropouts, and, thus, further research will benefit from considering these groups separately. In addition, this newly gained knowledge will also be helpful in increasing treatment retention in specific subgroups of problem gamblers.

Electroconvulsive therapy: predictors and trends in utilization from 1976 to 2000

DEFF Research Database (Denmark)

Munk-Olsen, Trine; Laursen, Thomas Munk; Videbech, Poul

2006-01-01

with bipolar and schizoaffective disorders received the treatment in 2000 compared with 1976. CONCLUSIONS: Unipolar affective disorders, long duration of admissions, and no history of previous admissions are strong predictors of receiving first ECT. Despite a decrease in available inpatient beds, the treatment......BACKGROUND: Use of electroconvulsive therapy (ECT) may have changed during the last decades due to advances in psychopharmacology and organizational changes of psychiatric care. OBJECTIVES: To identify predictors for receiving ECT for the first time and to describe temporal trends in ECT...... utilization. METHODS: A register-based case-control study. The sample included 2010 cases treated with ECT between 1976 and 2000 and 148,284 controls. RESULTS: Predictors for receiving first ECT were unipolar affective disorders, long admissions, and no previous admissions. Significantly fewer patients...

Electroconvulsive therapy: predictors and trends in utilization from 1976 to 2000

DEFF Research Database (Denmark)

Munk-Olsen, Trine; Laursen, Thomas Munk; Videbech, Poul

2006-01-01

BACKGROUND: Use of electroconvulsive therapy (ECT) may have changed during the last decades due to advances in psychopharmacology and organizational changes of psychiatric care. OBJECTIVES: To identify predictors for receiving ECT for the first time and to describe temporal trends in ECT...... utilization. METHODS: A register-based case-control study. The sample included 2010 cases treated with ECT between 1976 and 2000 and 148,284 controls. RESULTS: Predictors for receiving first ECT were unipolar affective disorders, long admissions, and no previous admissions. Significantly fewer patients...... with bipolar and schizoaffective disorders received the treatment in 2000 compared with 1976. CONCLUSIONS: Unipolar affective disorders, long duration of admissions, and no history of previous admissions are strong predictors of receiving first ECT. Despite a decrease in available inpatient beds, the treatment...

Alcohol use as predictor for infertility in a representative population of Danish women

DEFF Research Database (Denmark)

Tolstrup, Janne Schurmann; Kjaer, Susanne Krüger; Holst, Claus

2003-01-01

and the Danish Infertility Cohort Register. Main outcome measures were hazard ratios of infertility according to alcohol intake at baseline estimated in a multivariate Cox proportional hazards model. RESULTS: During a mean follow-up of 4.9 years, 368 women had experienced infertility. Alcohol intake at baseline...... was unassociated with infertility among younger women, but was a significant predictor for infertility among women above age 30. In this age group, the adjusted hazard ratio for consuming seven or more drinks per week was 2.26 (95% confidence interval: 1.19-4.32) compared with women consuming less than one drink...

Radiologic Predictors for Clinical Stage IA Lung Adenocarcinoma with Ground Glass Components: A Multi-Center Study of Long-Term Outcomes.

Directory of Open Access Journals (Sweden)

Zhao Li

Full Text Available This study was to define preoperative predictors from radiologic findings for the pathologic risk groups based on long-term surgical outcomes, in the aim to help guide individualized patient management.We retrospectively reviewed 321 consecutive patients with clinical stage IA lung adenocarcinoma with ground glass component on computed tomography (CT scanning. Pathologic diagnosis for resection specimens was based on the 2011 IASLC/ATS/ERS classification of lung adenocarcinoma. Patients were classified into different pathologic risk grading groups based on their lymph node status, local regional recurrence and overall survival. Radiologic characteristics of the pulmonary nodules were re-evaluated by reconstructed three-dimension CT (3D-CT. Univariate and multivariate analysis identifies independent radiologic predictors from tumor diameter, total volume (TV, average CT value (AVG, and solid-to-tumor (S/T ratio. Receiver operating characteristic curves (ROC studies were carried out to determine the cutoff value(s for the predictor(s. Univariate cox regression model was used to determine the clinical significance of the above findings.A total of 321 patients with clinical stage IA lung adenocarcinoma with ground glass components were included in our study. Patients were classified into two pathologic low- and high- risk groups based on their distinguished surgical outcomes. A total of 134 patients fell into the low-risk group. Univariate and multivariate analyses identified AVG (HR: 32.210, 95% CI: 3.020-79.689, P<0.001 and S/T ratio (HR: 12.212, 95% CI: 5.441-27.408, P<0.001 as independent predictors for pathologic risk grading. ROC curves studies suggested the optimal cut-off values for AVG and S/T ratio were-198 (area under the curve [AUC] 0.921, 2.9 (AUC 0.996 and 54% (AUC 0.907, respectively. The tumor diameter and TV were excluded for the low AUCs (0.778 and 0.767. Both the cutoff values of AVG and S/T ratio were correlated with pathologic

Temporal predictors of health-related quality of life in elderly people with diabetes: results of a German cohort study.

Directory of Open Access Journals (Sweden)

Imad Maatouk

Full Text Available BACKGROUND: The aim of the study was to determine predictors that influence health-related quality of life (HRQOL in a large cohort of elderly diabetes patients from primary care over a follow-up period of five years. METHODS AND RESULTS: At the baseline measurement of the ESTHER cohort study (2000-2002, 1375 out of 9953 participants suffered from diabetes (13.8%. 1057 of these diabetes patients responded to the second-follow up (2005-2007. HRQOL at baseline and follow-up was measured using the SF-12; mental component scores (MCS and physical component scores (PCS were calculated; multiple linear regression models were used to determine predictors of HRQOL at follow-up. As possible predictors for HRQOL, the following baseline variables were examined: treatment with insulin, glycated hemoglobin (HbA1c, number of diabetes related complications, number of comorbid diseases, Body-Mass-Index (BMI, depression and HRQOL. Regression analyses were adjusted for sociodemographic variables and smoking status. 1034 patients (97.8% responded to the SF-12 both at baseline and after five years and were therefore included in the study. Regression analyses indicated that significant predictors of decreased MCS were a lower HRQOL, a higher number of diabetes related complications and a reported history of depression at baseline. Complications, BMI, smoking and HRQOL at baseline significantly predicted PCS at the five year follow-up. CONCLUSIONS: Our findings expand evidence from previous cross-sectional data indicating that in elderly diabetes patients, depression, diabetes related complications, smoking and BMI are temporally predictive for HRQOL.

Emotional Intelligence and Personality Traits as Predictors of Occupational Therapy students' Practice Education Performance: A Cross-Sectional Study.

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Brown, Ted; Williams, Brett; Etherington, Jamie

2016-12-01

This study investigated whether occupational therapy students' emotional intelligence and personality traits are predictive of specific aspects of their fieldwork performance. A total of 114 second and third year undergraduate occupational therapy students (86.6% response rate) completed the Genos Emotional Intelligence Inventory (Genos EI) and the Ten-Item Personality Inventory (TIPI). Fieldwork performance scores were obtained from the Student Practice Evaluation Form Revised (SPEF-R). Linear regressions were completed with the SPEF-R domains being the dependent variables and the Genos EI and TIPI factors being the independent variables. Regression analysis results revealed that the Genos EI subscales of Emotional Management of Others (EMO), Emotional Awareness of Others (EAO), Emotional Expression (EEX) and Emotional Reasoning (ERE) were significant predictors of various domains of students' fieldwork performance. EAO and ERE were significant predictors of students' Communication Skills accounting for 4.6% of its variance. EMO, EAO, EEX and ERE were significant predictors of students' Documentation Skills explaining 6.8% of its variance. EMO was a significant predictor of students' Professional Behaviour accounting for 3.2% of its variance. No TIPI factors were found to be significant predictors of the SPEF-R domains. Occupational therapy students' emotional intelligence was a significant predictor of components of their fieldwork performance while students' personality traits were not. The convenience sampling approach used, small sample size recruited and potential issue of social desirability of the self-reported Genos EI and TIPI data are acknowledged as study limitations. It is recommended that other studies be completed to investigate if any other relevant constructs or factors are predictive of occupational therapy students' fieldwork performance. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Predictors of outcome for cognitive behaviour therapy in binge eating disorder.

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Lammers, Mirjam W; Vroling, Maartje S; Ouwens, Machteld A; Engels, Rutger C M E; van Strien, Tatjana

2015-05-01

The aim of this naturalistic study was to identify pretreatment predictors of response to cognitive behaviour therapy in treatment-seeking patients with binge eating disorder (BED; N = 304). Furthermore, we examined end-of-treatment factors that predict treatment outcome 6 months later (N = 190). We assessed eating disorder psychopathology, general psychopathology, personality characteristics and demographic variables using self-report questionnaires. Treatment outcome was measured using the bulimia subscale of the Eating Disorder Inventory 1. Predictors were determined using hierarchical linear regression analyses. Several variables significantly predicted outcome, four of which were found to be both baseline predictors of treatment outcome and end-of-treatment predictors of follow-up: Higher levels of drive for thinness, higher levels of interoceptive awareness, lower levels of binge eating pathology and, in women, lower levels of body dissatisfaction predicted better outcome in the short and longer term. Based on these results, several suggestions are made to improve treatment outcome for BED patients. Copyright © 2015 John Wiley & Sons, Ltd and Eating Disorders Association.

Predictors of Racial Prejudice in White American Counseling Students

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Castillo, Linda G.; Conoley, Collie W.; King, Jennifer; Rollins, Dahl; Rivera, Saori; Veve, Mia

2006-01-01

This study extends the research on racial prejudice by combining previously identified predictors into 1 study to determine their relative importance in contributing to racial prejudice. Results revealed that White racial identity significantly predicted racial prejudice when demographic variables were controlled. Implications of reducing racial…

Predictors of tonic immobility during traumatic events

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Arturo Bados

2015-10-01

Full Text Available Tonic immobility (TI is a possible reaction to danger that is facilitated by intense fear, physical restraint and perceived inability to escape. Other variables that could affect TI, such as the type and characteristics of traumatic events and personal characteristics have been little or no studied. The present study evaluated the power of these variables to predict TI in a sample of 273 college students who had experienced at least one traumatic event. Of the sample, 7.7% and 13.2% responded with TI according to the two stricter definitions adopted. Most of the variables were significantly associated with TI in univariate analyses. However, in a multiple regression analysis, only certain features of the events (occurrence of physical/sexual abuse, number of different types of events experienced and certain reactions to them (perception of how traumatic were the events, severe fear response were significant predictors of TI. Since these predictors explained only 25% of the variance, the influence of other variables -such as neuroticism, negative affectivity and perceived lack of personal control or resources to cope with traumatic events- should be investigated.

Predictors of abnormal chest CT after blunt trauma: a critical appraisal of the literature

International Nuclear Information System (INIS)

Brink, M.; Kool, D.R.; Dekker, H.M.; Deunk, J.; Jager, G.J.; Kuijk, C. van; Edwards, M.J.R.; Blickman, J.G.

2009-01-01

Aim: To identify and to evaluate predictors that determine whether chest computed tomography (CT) is likely to reveal relevant injuries in adult blunt trauma patients. Methods: After a comprehensive literature search for original studies on blunt chest injury diagnosis, two independent observers included studies on the accuracy of parameters derived from history, physical examination, or diagnostic imaging that might predict injuries at (multidetector row) CT in adults and that allowed construction of 2 x 2 contingency tables. For each article, methodological quality was scored and relevant predictors for injuries at CT were extracted. For each predictor, sensitivity, specificity, positive and negative likelihood ratio and diagnostic odds ratio (DOR) including 95% confidence intervals were calculated. Results: Of 147 articles initially identified, the observers included 10 original studies in consensus. Abnormalities at physical examination (abnormal respiratory effort, need for assisted ventilation, reduced airentry, coma, chest wall tenderness) and pelvic fractures were significant predictors (DOR: 2.1-6.7). The presence of any injuries at conventional radiography of the chest (eight articles) was a more powerful significant predictor (DOR: 2.2-37). Abnormal chest ultrasonography (four articles) was the most accurate predictor for chest injury at CT (DOR: 491-infinite). Conclusion: The current literature indicates that in blunt trauma patients with abnormal physical examination, abnormal conventional radiography, or abnormal ultrasonography of the chest, CT was likely to reveal relevant chest injuries. However, there was no strong evidence to suggest that CT could be omitted in patients without these criteria, or whether these findings are beneficial for patients

Predictors of third and Higher order births in India

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Payal Singh

2015-12-01

Full Text Available Background: Total fertility rate (TFR reflecting population growth is closely related to higher order parity progression. Many Indian states reached replacement level of TFR, but still states constituting nearly 40% population are with TFR ≥ 3. The predictors are the desire of son’s, poor contraceptives practices, younger age at marriage, child loss and shorter birth spacing. Objective: This analysis assessed the degree of relation of 3rd and higher order parity progression with the above mentioned predictors. Material and Methods: State/Union Territories wise proportions of women: progressing to ≥3 births, more sons desire, birth spacing <24 months, adopting modern contraception and median marriage age <18 years along with infant mortality rate (IMR were taken from NFHS-III report. Correlation matrix and stepwise forward multiple regression carried. Significance was seen at 5%. Results: Hindi speaking states constituting 38.92% nation population recorded TFR ≥3. Positive correlation of mothers progressing ≥ 3 births was highest (0.746 with those desiring more sons followed by IMR (0.445; while maximum negative correlation with those practicing modern contraceptives (-0.565 followed by median age at marriage (-0.391. Multiple regression analysis in order identified desire of more sons, practicing modern contraception and shorter birth spacing as the significant predictors and jointly explained 77.9% of the total variation with gain of 15.5% by adding modern contraceptive practice and 8.3% by adding shorter birth spacing. Conclusions: Desire of more sons appeared the most important predictor to progress ≥3 births that is governed by society culture and educational attainment, require attitudinal change. Further, mothers need motivation to practice both spacing and terminal methods once family is complete.

Work engagement, burnout and related constructs as predictors of turnover intentions

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Janine du Plooy

2010-12-01

Research purpose: The main purpose of the study was to determine whether work engagement, burnout, organisational citizenship behaviour (OCB and work alienation are predictors of turnover intentions. Motivation for the study: Organisations operating within the 21st century face significant challenges in the management of talent and human capital. One in particular is voluntary employee turnover and the lack of appropriate business models to track this process. Research design, approach and method: A secondary data analysis (SDA was performed in a quantitative research tradition on the cross-sectional survey data collected from a large South African Information and Communication Technologies (ICT sector company (n = 2429. Main findings: The results of the study confirmed the predictive model (work engagement, burnout, OCB and work alienation of turnover intention. Specifically, work engagement and OCBs were significantly negatively related to turnover intention; whilst burnout and work alienation were significantly positively related to turnover intention. Several third-variable relationships, such as biographic and demographic variables, indicated statistical significance. Practical/managerial implications: Practical implications of the study could impact on human resource (HR value-chain activities in the form of evidence-based and improved recruitment and selection procedures, employee retention strategies and training and development interventions. Issues concerning talent management could also be addressed. Contribution/value-add: The study described in this article took Industrial/Organisational (I/O psychological concepts and linked them in unique combinations to establish better predictive validity of a new turnover intentions model.

Risk Prediction Models for Incident Heart Failure: A Systematic Review of Methodology and Model Performance.

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Sahle, Berhe W; Owen, Alice J; Chin, Ken Lee; Reid, Christopher M

2017-09-01

Numerous models predicting the risk of incident heart failure (HF) have been developed; however, evidence of their methodological rigor and reporting remains unclear. This study critically appraises the methods underpinning incident HF risk prediction models. EMBASE and PubMed were searched for articles published between 1990 and June 2016 that reported at least 1 multivariable model for prediction of HF. Model development information, including study design, variable coding, missing data, and predictor selection, was extracted. Nineteen studies reporting 40 risk prediction models were included. Existing models have acceptable discriminative ability (C-statistics > 0.70), although only 6 models were externally validated. Candidate variable selection was based on statistical significance from a univariate screening in 11 models, whereas it was unclear in 12 models. Continuous predictors were retained in 16 models, whereas it was unclear how continuous variables were handled in 16 models. Missing values were excluded in 19 of 23 models that reported missing data, and the number of events per variable was models. Only 2 models presented recommended regression equations. There was significant heterogeneity in discriminative ability of models with respect to age (P prediction models that had sufficient discriminative ability, although few are externally validated. Methods not recommended for the conduct and reporting of risk prediction modeling were frequently used, and resulting algorithms should be applied with caution. Copyright © 2017 Elsevier Inc. All rights reserved.

ATTACHMENT AS A PREDICTOR OF RISK FOR EATING DISORDERS ON A REPRESENTATIVE HUNGARIAN ADULT SAMPLE.

Science.gov (United States)

Szalai, Tamás Dömötör; Czeglédi, Edit

2015-11-30

Many studies confirm the relationship between attachment disturbances and (the severity of) eating disorders, however among them only one Hungarian study can be found. The exact predisposing traits of attachment and the strength of relationship is still uncleared. Our aim was to explore these aspects. Study was based on a cross-sectional nationally representative survey, called "Hungarostudy 2013" (N = 2000, 46.9% males, mean age 46.9 years, SD = 18.24 years). Measures: Sociodemographic and self-reported anthropometric data (weight and height), short Hungarian version of Relationship Scale Questionnaire, SCOFF questionnaire and short Hungarian version of Beck Depression Inventory. The frequency of risk for eating disorders (anorexia or bulimia nervosa) was 3.9% (N = 76) among the respondents (N = 1860). Attachment anxiety was significantly higher in the risk for eating disorders group (t (1888) = -3.939, p eating disorders after adjusting for the potential background variables (OR = 1.09, p = 0.040). Detachment was not a significant predictor of risk for eating disorders (OR = 0.98, p = 0.515). Younger age (OR = 0.97, p cross-sectional predictors of risk for eating disorders. The explained variance of the model was 10.7%. The study supported, that higher attachment anxiety is associated with the increased risk of eating disorders, with a possible therapeutic relevance. Assessment of attachment's further aspects and creating multivariable models are required for more thorough understanding and optimising of intervention points.

High Neutrophil-to-Lymphocyte Ratio is a Significant Predictor of Cardiovascular and All-Cause Mortality in Patients Undergoing Peritoneal Dialysis

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Xiangxue Lu

2018-03-01

Full Text Available Background/Aims: Chronic inflammation is associated with increased risk of cardiovascular death in patients with end-stage renal disease (ESRD. Although elevated neutrophil-to-lymphocyte ratio (NLR, a novel inflammatory marker, has been shown to predict cardiovascular disease and all-cause mortality in the general population, limited evidence is available for its role in ESRD. Methods: We enrolled 86 patients undergoing peritoneal dialysis (PD for a 36-month follow-up to investigate the association between the NLR and arterial stiffness markers, namely, carotid-femoral pulse wave velocity (cfPWV and carotid augmentation index (AIx, and mortality in PD patients. The primary endpoints were cardiovascular mortality and all-cause mortality. Kaplan–Meier curves were used to show the cumulative incidence of cardiovascular mortality and all-cause mortality. Results: High NLR was found to be a predictor of increased cfPWV (β = 1.150; P < 0.001 and AIx (β = 3.945; P < 0.001 in patients on PD. Patients with higher NLR had lower survival during follow-up. Kaplan–Meier curves showed that the cumulative incidences of both cardiovascular mortality and all-cause mortality were significantly higher in patients with NLR ≥ 4.5 (both P < 0.01. Conclusion: Our results suggest that high NLR is independently associated with arterial stiffness and predicts cardiovascular and all-cause mortality in PD patients.

Individual predictors of adolescents’ vocational interest stabilities

OpenAIRE

Hirschi, Andreas

2010-01-01

The study investigated the predictive utility of interest profile differentiation, coherence, elevation, congruence, and vocational identity commitment and career maturity (career planning and exploration) on the 10-month interest stability of 292 Swiss eighth-grade students: profile, rank, and level stabilities were assessed. Controlling for socio-demographic and vocational interest type variables, measures of differentiated and coherent vocational interests were significant predictors of pr...

Loneliness in old age: Psychosocial and health predictors

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Karen Kaasa

2009-10-01

Full Text Available  Study objectives  Design  Main results  17% (CI 12.5–23.0 of the respondents answered yes. A significant correlation was demonstratedbetween a feeling of loneliness and low self-perceived health, low vision and poor hearing, low activity of dailylife (ADL function, loss of a spouse, low social network, no hobbies and possession of a safety alarm. After amultiple regression analysis of the significant variables, the remaining variables as predictors for lonelinessincluded: number of social contacts, self-perceived health, using hearing aid and having a safety alarm.: : The information is obtained from a survey conducted among 232 inhabitants in this age group in the municipalityof Tønsberg, its Northern District. The interview data are composed of the responses from 202 elderlypeople living in a house or apartment (non-institutionalized to the question «do you generally feel lonely?».The purpose of this article is to study the prevalence of loneliness in a group of elderly peopleover 80 years old and the sociodemographic, health-related and social predictors for experiencing loneliness.ABSTRACT:

Seafood Spoilage Predictor - development and distribution of a product specific application software

DEFF Research Database (Denmark)

Dalgaard, Paw; Buch, P.; Silberg, Steen

2002-01-01

To allow shelf-life prediction of a range of products, the Seafood Spoilage Predictor (SSP) software has been developed to include both kinetic models for growth of specific spoilage microorganisms and empirical relative rates of spoilage models. SSP can read and evaluate temperature profile data...

Prevalence and predictors of physical exercise among nurses. A cross-sectional study

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Mohamad A. Al-Tannir

2017-02-01

Full Text Available Objectives: To identify the prevalence and predictors of physical exercise among nurses. Methods: This study was conducted at 2 hospitals selected randomly from tertiary hospitals in King Fahad Medical City, Riyadh, Kingdom of Saudi Arabia (KSA and Makassed General Hospital, Beirut, Lebanon in 2014. The study included nurses with at least one year of nursing experience. Data were collected using a self-administered questionnaire. The questionnaire was divided into 2 sections, one covering the respondents’ demographics, and the other one assessing the prevalence and the characteristics of physical exercise. Results: A total of 412 participants responded, of whom 248 (60.2% are engaged in physical exercise. On multivariate analysis, normal weight and smoking were independently associated with physical exercise. Most 66.1% of respondents reported practicing walking as the most common type of physical activity. One hundred eighty (72.6% respondents relied on their own motivation to perform physical activity and 64.6% reported the lack of availability of physical activity facilities. Conclusion: Smoking and obesity were the significant predictors associated with physical inactivity. Encouraging nurses to adopt a healthy lifestyle for their role modeling to patients as health promoters is recommended.

Predictors of Postpartum Depression in Dubai, a Rapidly Growing Multicultural Society in the United Arab Emirates.

Science.gov (United States)

Alhammadi, Salwa M; Hashem, Lien Abou; Abusbeih, Zainah R; Alzaabi, Fatima S; Alnuaimi, Salama N; Jalabi, Ala F; Nair, Satish C; Carrick, Frederick R; Abdulrahman, Mahera

2017-09-01

Postpartum depression (PPD) is a significant public health problem adversely affecting mothers, their newborns, and other members of the family. Although PPD is common and potentially dangerous, only a minority of the cases are identified in primary health care settings during routine care, and the majority of depressed mothers in the community lies unrecognized and therefore untreated. In this study, a total of 1500 mothers were approached randomly, 808 accepted to participate, and 504 were within the inclusion criteria (women who had a birth of a singleton full-term healthy infant, had an uncomplicated pregnancy, and were within their one week to six months postpartum). The participants completed the Edinburgh Postnatal Depression Scale. A total of 168 women had an EPDS score ≥10, yielding a crude prevalence rate of 33%. The prevalence of suicidal ideation was 14 out of 504 (3%), among which 11 (79%) had EPDS score of ≥10. We fitted multiple linear regression models to evaluate the predictors of variables measured on the EPDS scale. This model was statistically significant pemployment status, baby's birth weight, stressful life event and marital conflict were statistically significant predictors. The findings of this study are anticipated to entail the government and policy makers in the region to pay more attention to the apparently high prevalence of unrevealed PPD in the community. It is crucial to enhance screening mechanisms for early detection, providing interventions to manage symptoms, and at the same time mandating local guidelines to address the PPD pathology as a high priority for the UAE population.

Assessment of the impact of adherence and other predictors during HAART on various CD4 cell responses in resource-limited settings

Directory of Open Access Journals (Sweden)

Abrogoua DP

2012-03-01

Full Text Available Danho Pascal Abrogoua1,2, Brou Jerome Kablan1, Boua Alexis Thierry Kamenan1,3, Gilles Aulagner4, Konan N'Guessan1, Christian Zohoré11Laboratoire de Pharmacie Clinique, Pharmacologie et Therapeutique – UFR Sciences Pharmaceutiques et Biologiques, 2Laboratoire de Pharmacologie Clinique, CHU de Cocody, 3Service de Pharmacie, CHU de Cocody, Abidjan, Cote d'Ivoire, 4Service Pharmaceutique Hopital Louis Pradel, Lyon, FranceObjective: The aim of this study was to quantify, by modeling, the impact of significant predictors on CD4 cell response during antiretroviral therapy in a resource-limited setting.Methods: Modeling was used to determine which antiretroviral therapy response predictors (baseline CD4 cell count, clinical state, age, and adherence significantly influence immunological response in terms of CD4 cell gain compared to a reference value at different periods of monitoring.Results: At 6 months, CD4 cell response was significantly influenced by baseline CD4 count alone. The probability of no increase in CD4 cells was 2.6 higher in patients with a baseline CD4 cell count of ≥200/mm3. At 12 months, CD4 cell response was significantly influenced by both baseline CD4 cell count and adherence. The probability of no increase in CD4 cells was three times higher in patients with a baseline CD4 cell count of ≥200/mm3 and 0.15 times lower with adherent patients. At 18 months, CD4 cell response was also significantly influenced by both baseline CD4 cell count and adherence. The probability of no increase in CD4 cells was 5.1 times higher in patients with a baseline CD4 cell count of ≥200/mm3 and 0.28 times lower with adherent patients. At 24 months, optimal CD4 cell response was significantly influenced by adherence alone. Adherence increased the probability (by 5.8 of an optimal increase in CD4 cells. Age and baseline clinical state had no significant influence on immunological response.Conclusion: The relationship between adherence and CD4

Multilevel predictors of adolescent physical activity: a longitudinal analysis

Directory of Open Access Journals (Sweden)

Hearst Mary O

2012-02-01

Full Text Available Abstract Background To examine how factors from a social ecologic model predict physical activity (PA among adolescents using a longitudinal analysis. Methods Participants in this longitudinal study were adolescents (ages 10-16 at baseline and one parent enrolled in the Transdisciplinary Research on Energetics and Cancer-Identifying Determinants of Eating and Activity (TREC-IDEA and the Etiology of Childhood Obesity (ECHO. Both studies were designed to assess a socio-ecologic model of adolescent obesity risk. PA was collected using ActiGraph activity monitors at two time points 24 months apart. Other measures included objective height and weight, adolescent and parent questionnaires on multilevel psychological, behavioral and social determinants of PA, and a home PA equipment inventory. Analysis was conducted using SAS, including descriptive characteristics, bivariate and stepped multivariate mixed models, using baseline adjustment. Models were stratified by gender. Results There were 578 adolescents with complete data. Results suggest few statistically significant longitudinal associations with physical activity measured as minutes of MVPA or total counts from accelerometers. For boys, greater self-efficacy (B = 0.75, p = 0.01 and baseline MVPA (B = 0.55, p p = 0.01 and barriers (B = -0.32, p = 0.05 significantly predicted MVPA at follow-up in the full model. The full multilevel model explained 30% of the variance in PA among boys and 24% among girls. Conclusions PA change in adolescents is a complex issue that is not easily understood. Our findings suggest early PA habits are the most important predictor of PA levels in adolescence. Intervention may be necessary prior to middle school to maintain PA through adolescence.

Predictors of needs for community and financial resources for families of pre-school children with cerebral palsy

Directory of Open Access Journals (Sweden)

Bertule D.

2016-01-01

Full Text Available An understanding of predictors of family needs for the families of preschool children with cerebral palsy (CP is important for provision of efficient and cost-effective services. The aim of this study was to identify the characteristics of children, families and services that are risk factors to meeting family needs for community and financial resources. 234 parents of pre-school children with CP completed a modified version of the Family Needs Survey (FNS, the Measure of Processes of Care (MPOC-20, and a demographic questionnaire. The gross motor function level and communication function level of children were classified on the basis of the Gross Motor Function Classification System (GMFCS and the Communication Function Classification System (CFCS respectively. Two hierarchical multiple regression models were generated to determine the predictors of unmet family needs. The socialisation and communication skills of children, as well as caregiver employment and family income levels were significant predictors of family needs for community resources (adjusted R2=0.44. Significant risk factors in terms of family needs for financial resources included the child's gross motor limitations, caregiver employment, low levels of family income and no ability to receive services on the basis of enabling and partnership principles (adjusted R2=0.51. A child's limitations in terms of communication, gross motor functions and socialisation, as well as the socioeconomic status of the child's family, must be taken into account when planning services for families with preschool children with CP.

Predictors of smoking among male college students in Saudi Arabia.

Science.gov (United States)

Almogbel, Y S; Abughosh, S M; Almogbel, F S; Alhaidar, I A; Sansgiry, S S

2013-11-01

Identifying the predictors of smoking in one of the top cigarette-consuming countries in the world is a vital step in smoking prevention. A cross-sectional study assessed the predictors of smoking in a cohort of male students in 3 universities in Saudi Arabia. A pre-tested, validated questionnaire was used to determine sociodemographic characteristics, academic performance, peers' smoking, and presence of a smoker within the family. Of the 337 participants, 30.9% were current smokers (smoked 1 or more cigarettes within the last 30 days). Lower academic performance (OR = 2.29, 95% CI: 1.02-5.17), peer smoking (OR = 4.14, 95% CI: 1.53-11.3) and presence of other smokers in the family (OR = 2.77, 95% CI: 1.37-5.64) were the significant predictors of smoking status identified using multiple logistic regression analysis. These findings highlight the influence of family and peer pressure in initiating cigarette use among the youth of Saudi Arabia.

Explicit and Implicit Stigma of Mental Illness as Predictors of the Recovery Attitudes of Assertive Community Treatment Practitioners.

Science.gov (United States)

Stull, Laura G; McConnell, Haley; McGrew, John; Salyers, Michelle P

2017-01-01

While explicit negative stereotypes of mental illness are well established as barriers to recovery, implicit attitudes also may negatively impact outcomes. The current study is unique in its focus on both explicit and implicit stigma as predictors of recovery attitudes of mental health practitioners. Assertive Community Treatment practitioners (n = 154) from 55 teams completed online measures of stigma, recovery attitudes, and an Implicit Association Test (IAT). Three of four explicit stigma variables (perceptions of blameworthiness, helplessness, and dangerousness) and all three implicit stigma variables were associated with lower recovery attitudes. In a multivariate, hierarchical model, however, implicit stigma did not explain additional variance in recovery attitudes. In the overall model, perceptions of dangerousness and implicitly associating mental illness with "bad" were significant individual predictors of lower recovery attitudes. The current study demonstrates a need for interventions to lower explicit stigma, particularly perceptions of dangerousness, to increase mental health providers' expectations for recovery. The extent to which implicit and explicit stigma differentially predict outcomes, including recovery attitudes, needs further research.

Predictors of parenting stress among Malaysian mothers of children with Down syndrome.

Science.gov (United States)

Norizan, A; Shamsuddin, K

2010-11-01

Having children with intellectual disability can be stressful for most parents. Currently there are very few studies focusing on parenting stress among mothers of children with Down syndrome (DS) in Asia. The present study examined the level of parenting stress experienced by Malaysian mothers of children with DS and evaluated the child and maternal factors that contributed to parenting stress based on Hill's ABC-X Model (Hill 1949). We conducted a cross-sectional study of mothers of children with DS between the ages of 2-12 years during February-June 2008 in Kedah, a state in Peninsular Malaysia. We used self-administered questionnaires to gather data on parenting stress, child's birth history and current behavioural problems, as well as the maternal sociodemographic characteristics, coping styles and psychological well-being. Parental Stress Scale (PSS) was used to assess parenting stress. Measures of child's behavioural problem using Pediatric Symptom Checklist, mother's coping style using Carver et al. (1989) COPE inventory and their psychological well-being using Lovibond and Lovibond (1995) DASS21, a scale assessing depression, anxiety and stress were also carried out. The 147 mothers who participated in the study had an average age of 43.1 years (SD = 7.6 years), of whom 94.6% were married, 57.1% had secondary level education and 28.6% were working outside their home. Based on PSS, mean parenting stress was 37.6 (SD = 8.1). Parenting stress was significantly higher among mothers who reported having children with behavioural problems. However, parenting stress was modified by positive coping styles and negative maternal psychological well-being. The final model based on hierarchical regression analysis identified maternal depression and lack of acceptance as significant predictors of parenting stress rather than child's behavioural problems. Mean parenting stress among mothers of children with DS significantly differed by behavioural problems in their

Controlling confounding by frailty when estimating influenza vaccine effectiveness using predictors of dependency in activities of daily living.

Science.gov (United States)

Zhang, Henry T; McGrath, Leah J; Wyss, Richard; Ellis, Alan R; Stürmer, Til

2017-12-01

To improve control of confounding by frailty when estimating the effect of influenza vaccination on all-cause mortality by controlling for a published set of claims-based predictors of dependency in activities of daily living (ADL). Using Medicare claims data, a cohort of beneficiaries >65 years of age was followed from September 1, 2007, to April 12, 2008, with covariates assessed in the 6 months before follow-up. We estimated Cox proportional hazards models of all-cause mortality, with influenza vaccination as a time-varying exposure. We controlled for common demographics, comorbidities, and health care utilization variables and then added 20 ADL dependency predictors. To gauge residual confounding, we estimated pre-influenza season hazard ratios (HRs) between September 1, 2007 and January 5, 2008, which should be 1.0 in the absence of bias. A cohort of 2 235 140 beneficiaries was created, with a median follow-up of 224 days. Overall, 52% were vaccinated and 4% died during follow-up. During the pre-influenza season period, controlling for demographics, comorbidities, and health care use resulted in a HR of 0.66 (0.64, 0.67). Adding the ADL dependency predictors moved the HR to 0.68 (0.67, 0.70). Controlling for demographics and ADL dependency predictors alone resulted in a HR of 0.68 (0.66, 0.70). Results were consistent with those in the literature, with significant uncontrolled confounding after adjustment for demographics, comorbidities, and health care use. Adding ADL dependency predictors moved HRs slightly closer to the null. Of the comorbidities, health care use variables, and ADL dependency predictors, the last set reduced confounding most. However, substantial uncontrolled confounding remained. Copyright © 2017 John Wiley & Sons, Ltd.

Prevalence and predictors of sunburn among beachgoers.

Science.gov (United States)

de Troya-Martín, Magdalena; de Gálvez-Aranda, María Victoria; Rivas-Ruiz, Francisco; Blázquez-Sánchez, Nuria; Fernández-Morano, Maria Teresa; Padilla-España, Laura; Herrera-Ceballos, Enrique

2018-03-01

Painful sunburns at any age are one of the main risk factors for skin cancer. To determine the prevalence and predictors of sunburn among beachgoers. A cross-sectional health survey was conducted at the beach during the summer. Adults >18 years with an understanding of Spanish were interviewed using a questionnaire about behaviours, attitudes and knowledge related to sun exposure at the beach. A descriptive analysis was performed, and a log-binomial regression model was used to determine predictors of sunburn. The survey was completed by 1054 beachgoers, with a mean age of 43.8 (SD: 18.7) years, 61.2% women, skin phototypes i (13.6%), ii (22.3%), iii (34.0%) and iv (30.2%). 46.9% of responders reported at least one painful sunburn during the previous summer. Age, sex, education, skin phototype, midday sun exposure, sun protection habits, attitudes towards tanning and knowledge about skin cancer were identified as independent predictors of sunburn. It is necessary to develop photoprotection campaigns aimed at beachgoers, particularly in young people, men, those with skin phototypes I-III and secondary or university education. Educational strategies should be aimed at discouraging sun exposure at midday, changing attitudes towards tanning and improving knowledge about skin cancer. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Multilevel predictors of colorectal cancer testing modality among publicly and privately insured people turning 50.

Science.gov (United States)

Wheeler, Stephanie B; Kuo, Tzy-Mey; Meyer, Anne Marie; Martens, Christa E; Hassmiller Lich, Kristen M; Tangka, Florence K L; Richardson, Lisa C; Hall, Ingrid J; Smith, Judith Lee; Mayorga, Maria E; Brown, Paul; Crutchfield, Trisha M; Pignone, Michael P

2017-06-01

Understanding multilevel predictors of colorectal cancer (CRC) screening test modality can help inform screening program design and implementation. We used North Carolina Medicare, Medicaid, and private, commercially available, health plan insurance claims data from 2003 to 2008 to ascertain CRC test modality among people who received CRC screening around their 50th birthday, when guidelines recommend that screening should commence for normal risk individuals. We ascertained receipt of colonoscopy, fecal occult blood test (FOBT) and fecal immunochemical test (FIT) from billing codes. Person-level and county-level contextual variables were included in multilevel random intercepts models to understand predictors of CRC test modality, stratified by insurance type. Of 12,570 publicly-insured persons turning 50 during the study period who received CRC testing, 57% received colonoscopy, whereas 43% received FOBT/FIT, with significant regional variation. In multivariable models, females with public insurance had lower odds of colonoscopy than males (odds ratio [OR] = 0.68; p testing, 42% received colonoscopy, whereas 58% received FOBT/FIT, with significant regional variation. In multivariable models, females with private insurance had lower odds of colonoscopy than males (OR = 0.43; p < 0.05). People living 10-15 miles away from endoscopy facilities also had lower odds of colonoscopy than those living within 5 miles (OR = 0.91; p < 0.05). Both colonoscopy and FOBT/FIT are widely used in North Carolina among insured persons newly age-eligible for screening. The high level of FOBT/FIT use among privately insured persons and women suggests that renewed emphasis on FOBT/FIT as a viable screening alternative to colonoscopy may be important.

Predictors of Male Condom Utilization in Plateau State, Nigeria ...

African Journals Online (AJOL)

The dataset was analyzed using SPSS version 21.0 software (SPSS, IBM Corp, Armonk, NY, USA). Condom utilization prevalence rate was calculated for the 393 males, while predictors were determined by logistic regression. P ≤ 0.05 was considered statistically significant. Results: Mean age of the respondents was ...

Predictors of tanning dependence in white non-Hispanic females and males.

Science.gov (United States)

Cartmel, B; Bale, A E; Mayne, S T; Gelernter, J E; DeWan, A T; Spain, P; Leffell, D J; Pagoto, S; Ferrucci, L M

2017-07-01

Growing evidence suggests that some individuals may exhibit symptoms of dependence on ultraviolet (UV) light, a known carcinogen, in the context of tanning; however, few studies have investigated predictors of tanning dependence (TD). To identify predictors of TD. Non-Hispanics of European ancestry who had previously participated in a case-control study of early-onset basal cell carcinoma completed an online survey to ascertain TD and other behaviours (alcohol dependence, nicotine dependence, seasonal affective disorder (SAD), exercise 'addiction' and depression). Information on host factors, such as skin and eye colour and history of sunbathing and indoor tanning, was obtained from a study in which the participants were previously enrolled. Lifetime TD was assessed using the modified Cut down, Annoyed, Guilty, Eye-opener (mCAGE) and the modified Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (mDSM-IV-TR) questionnaires. Participants were classified as 'TD' if positive on both questionnaires and not TD if negative on both questionnaires. In total, 499 individuals completed the online survey (81.9% participation rate), and 24.4% were classified as 'TD'. In the multivariate model, women were more likely to be TD [odds ratio (OR) 6.93; 95% confidence intervals (95% CI) (3.36-14.27)] than men. Alcohol dependence (OR 6.55: 95% CI 3.19-13.42), SAD (OR 2.77; 95% CI 1.26-6.09) and exercise 'addiction' (OR 5.47; 95% CI 1.15-26.06) were all significant predictors for TD. Increased knowledge of those at risk for TD will allow appropriate interventions to be designed. © 2017 European Academy of Dermatology and Venereology.

Predictors of perceived importance and acceptance of digital delivery modes in higher education

Directory of Open Access Journals (Sweden)

Anne Mertens

2014-04-01

Full Text Available Teaching and assessment in higher education institutions are increasingly supported by digital tools and services. Students, however, perceive and value the importance of such e-learning offerings in very diverse ways. The goal of this article is to examine which predictors significantly influence students’ perceptions of the value of digital learning formats. Based on Küpper's acceptance model, we generate hypotheses that are subsequently tested using data from a German student survey. The results show that individual-related characteristics, especially motivation and orientation patterns of students, have a high impact on the perceived importance of digital learning formats. Our analyses indicate that besides individual performance and motivation, the practical orientation of a student is also a key predictor for a high rating of the importance of digital learning formats. An analysis of characteristics regarding the field of study shows that students who major in economic sciences, especially those who frequently work with digital learning formats in their classes, find them significantly more important than students who major in social science. Regarding innovation-based characteristics, students who express a need for flexible course offerings rate the use of digital learning formats as particularly important. The discussion provides an evaluation of the results of the student study based on the hypotheses and presents further implications.

Assessment of the assessment: Evaluation of the model quality estimates in CASP10

KAUST Repository

Kryshtafovych, Andriy

2013-08-31

The article presents an assessment of the ability of the thirty-seven model quality assessment (MQA) methods participating in CASP10 to provide an a priori estimation of the quality of structural models, and of the 67 tertiary structure prediction groups to provide confidence estimates for their predicted coordinates. The assessment of MQA predictors is based on the methods used in previous CASPs, such as correlation between the predicted and observed quality of the models (both at the global and local levels), accuracy of methods in distinguishing between good and bad models as well as good and bad regions within them, and ability to identify the best models in the decoy sets. Several numerical evaluations were used in our analysis for the first time, such as comparison of global and local quality predictors with reference (baseline) predictors and a ROC analysis of the predictors\\' ability to differentiate between the well and poorly modeled regions. For the evaluation of the reliability of self-assessment of the coordinate errors, we used the correlation between the predicted and observed deviations of the coordinates and a ROC analysis of correctly identified errors in the models. A modified two-stage procedure for testing MQA methods in CASP10 whereby a small number of models spanning the whole range of model accuracy was released first followed by the release of a larger number of models of more uniform quality, allowed a more thorough analysis of abilities and inabilities of different types of methods. Clustering methods were shown to have an advantage over the single- and quasi-single- model methods on the larger datasets. At the same time, the evaluation revealed that the size of the dataset has smaller influence on the global quality assessment scores (for both clustering and nonclustering methods), than its diversity. Narrowing the quality range of the assessed models caused significant decrease in accuracy of ranking for global quality predictors but

Cognitive behavioral therapy for compulsive buying behavior: Predictors of treatment outcome.

Science.gov (United States)

Granero, R; Fernández-Aranda, F; Mestre-Bach, G; Steward, T; Baño, M; Agüera, Z; Mallorquí-Bagué, N; Aymamí, N; Gómez-Peña, M; Sancho, M; Sánchez, I; Menchón, J M; Martín-Romera, V; Jiménez-Murcia, S

2017-01-01

Compulsive buying behavior (CBB) is receiving increasing consideration in both consumer and psychiatric-epidemiological research, yet empirical evidence on treatment interventions is scarce and mostly from small homogeneous clinical samples. To estimate the short-term effectiveness of a standardized, individual cognitive behavioral therapy intervention (CBT) in a sample of n=97 treatment-seeking patients diagnosed with CBB, and to identify the most relevant predictors of therapy outcome. The intervention consisted of 12 individual CBT weekly sessions, lasting approximately 45minutes each. Data on patients' personality traits, psychopathology, sociodemographic factors, and compulsive buying behavior were used in our analysis. The risk (cumulative incidence) of poor adherence to the CBT program was 27.8%. The presence of relapses during the CBT program was 47.4% and the dropout rate was 46.4%. Significant predictors of poor therapy adherence were being male, high levels of depression and obsessive-compulsive symptoms, low anxiety levels, high persistence, high harm avoidance and low self-transcendence. Cognitive behavioral models show promise in treating CBB, however future interventions for CBB should be designed via a multidimensional approach in which patients' sex, comorbid symptom levels and the personality-trait profiles play a central role. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Salivary protein levels as a predictor of perceived astringency in model systems and solid foods.

Science.gov (United States)

Fleming, Erin E; Ziegler, Gregory R; Hayes, John E

2016-09-01

Salivary protein difference value (SP D-value) is a quantitative measure of salivary protein replenishment, which reportedly relates to individual differences in perceived astringency. This in vitro measure is calculated as the difference in total salivary protein before (S1) and after (S2) stimulation with tannic acid, with a greater absolute value (S2-S1) indicating less protein replenishment. Others report that this measure predicts perceived astringency and liking of liquid model systems and beverages containing added polyphenols. Whether this relationship generalizes to astringent compounds other than polyphenols, or to solid foods is unknown. Here, the associations between SP D-values and perceived astringency and overall liking/disliking for alum and tannic acid (experiment 1) as well as solid chocolate-flavored compound coating with added tannic acid or grape seed extract (GSE) (experiment 2) were examined. In both experiments, participants (n=84 and 81, respectively) indicated perceived intensity of astringency, bitterness, sweetness, and sourness, and degree of liking of either aqueous solutions, or solid chocolate-flavored compound coating with added astringents. Data were analyzed via linear regression, and as discrete groups for comparison to prior work. Three discrete groups were formed based on first and third quartile splits of the SP D-value distribution: low (LR), medium (MR), and high responding (HR) individuals. In experiment 1, significantly higher mean astringency ratings were observed for the HR as compared to the LR/MR groups for alum and tannic acid, confirming and extending prior work. In experiment 2, significantly higher mean astringency ratings were also observed for HR as compared to LR groups in solid chocolate-flavored compound containing added tannic acid or GSE. Significant differences in liking were found between HR and LR groups for alum and tannic acid in water, but no significant differences in liking were observed for

Prevalence and Predictors of Depression and Anxiety among Korean Americans.

Science.gov (United States)

Koh, Eun

2018-01-01

Despite the significant growth of the Asian population in the United States, current knowledge on their mental health and service utilization behaviors is very limited. The study examined the prevalence and predictors of depression and anxiety among Korean Americans in the Washington, D.C. metropolitan area. A total of 602 Koreans completed a self-administered survey on physical and mental well-being, and the study found that 18.2% and 16.9% of the participants had severe symptoms of depression and anxiety, respectively. Acculturative stress and perceived social support were common predictors for depression and anxiety, and the effects of demographic factors were minimal.

Predictors of Readmission after Inpatient Plastic Surgery

Directory of Open Access Journals (Sweden)

Umang Jain

2014-03-01

Full Text Available Background Understanding risk factors that increase readmission rates may help enhance patient education and set system-wide expectations. We aimed to provide benchmark data on causes and predictors of readmission following inpatient plastic surgery. Methods The 2011 National Surgical Quality Improvement Program dataset was reviewed for patients with both "Plastics" as their recorded surgical specialty and inpatient status. Readmission was tracked through the "Unplanned Readmission" variable. Patient characteristics and outcomes were compared using chi-squared analysis and Student's t-tests for categorical and continuous variables, respectively. Multivariate regression analysis was used for identifying predictors of readmission. Results A total of 3,671 inpatient plastic surgery patients were included. The unplanned readmission rate was 7.11%. Multivariate regression analysis revealed a history of chronic obstructive pulmonary disease (COPD (odds ratio [OR], 2.01; confidence interval [CI], 1.12-3.60; P=0.020, previous percutaneous coronary intervention (PCI (OR, 2.69; CI, 1.21-5.97; P=0.015, hypertension requiring medication (OR, 1.65; CI, 1.22-2.24; P<0.001, bleeding disorders (OR, 1.70; CI, 1.01-2.87; P=0.046, American Society of Anesthesiologists (ASA class 3 or 4 (OR, 1.57; CI, 1.15-2.15; P=0.004, and obesity (body mass index ≥30 (OR, 1.43; CI, 1.09-1.88, P=0.011 to be significant predictors of readmission. Conclusions Inpatient plastic surgery has an associated 7.11% unplanned readmission rate. History of COPD, previous PCI, hypertension, ASA class 3 or 4, bleeding disorders, and obesity all proved to be significant risk factors for readmission. These findings will help to benchmark inpatient readmission rates and manage patient and hospital system expectations.

Publication of statistically significant research findings in prosthodontics & implant dentistry in the context of other dental specialties.

Science.gov (United States)

Papageorgiou, Spyridon N; Kloukos, Dimitrios; Petridis, Haralampos; Pandis, Nikolaos

2015-10-01

To assess the hypothesis that there is excessive reporting of statistically significant studies published in prosthodontic and implantology journals, which could indicate selective publication. The last 30 issues of 9 journals in prosthodontics and implant dentistry were hand-searched for articles with statistical analyses. The percentages of significant and non-significant results were tabulated by parameter of interest. Univariable/multivariable logistic regression analyses were applied to identify possible predictors of reporting statistically significance findings. The results of this study were compared with similar studies in dentistry with random-effects meta-analyses. From the 2323 included studies 71% of them reported statistically significant results, with the significant results ranging from 47% to 86%. Multivariable modeling identified that geographical area and involvement of statistician were predictors of statistically significant results. Compared to interventional studies, the odds that in vitro and observational studies would report statistically significant results was increased by 1.20 times (OR: 2.20, 95% CI: 1.66-2.92) and 0.35 times (OR: 1.35, 95% CI: 1.05-1.73), respectively. The probability of statistically significant results from randomized controlled trials was significantly lower compared to various study designs (difference: 30%, 95% CI: 11-49%). Likewise the probability of statistically significant results in prosthodontics and implant dentistry was lower compared to other dental specialties, but this result did not reach statistical significant (P>0.05). The majority of studies identified in the fields of prosthodontics and implant dentistry presented statistically significant results. The same trend existed in publications of other specialties in dentistry. Copyright © 2015 Elsevier Ltd. All rights reserved.

Interdependent Self-Construal, Self-Efficacy, and Community Involvement as Predictors of Perceived Knowledge Gain Among MMORPG Players.

Science.gov (United States)

Hopp, Toby; Barker, Valerie; Schmitz Weiss, Amy

2015-08-01

This study explored the relationship between interdependent self-construal, video game self-efficacy, massively multiplayer online role-playing game (MMORPG) community involvement, and self-reported learning outcomes. The results suggested that self-efficacy and interdependent self-construal were positive and significant predictors of MMORPG community involvement. For its part, MMORPG community involvement was a positive predictor of self-reported learning in both focused and incidental forms. Supplementary analyses suggested that self-efficacy was a comparatively more robust predictor of MMORPG community involvement when compared to self-construal. Moreover, the present data suggest that community involvement significantly facilitated indirect relationships between self-construal, game-relevant self-efficacy, and both focused and incidental learning.

Predictors of growth or attrition of the first language in Latino children with specific language impairment

Science.gov (United States)

Simon-Cereijido, Gabriela; Gutiérrez-Clellen, Vera F.; Sweet, Monica

2012-01-01

We investigated the factors that may help understand the differential rates of language development in the home language (i.e., Spanish) of Latino preschoolers with specific language impairment (SLI). Children were randomly assigned to either bilingual or English-only small group interventions and followed from preschool to kindergarten. Predictors of Spanish growth included the language of intervention, the child’s level of language development or severity, the child’s socio-emotional skills, and the child’s level of English use. Spanish performance outcomes were assessed over time using a series of longitudinal models with baseline and post-treatment measures nested within child. Children demonstrated growth on Spanish outcomes over time. The language of instruction and the child’s level of vocabulary and socio-emotional development at baseline were significant predictors of differences in rates of growth in the home language. Clinicians may need to take into consideration these factors when making clinical recommendations. PMID:24489415

Patient Characteristics and Patient Behavior as Predictors of Outcome in Cognitive Therapy and Exposure Therapy for Hypochondriasis.

Science.gov (United States)

Richtberg, Samantha; Jakob, Marion; Höfling, Volkmar; Weck, Florian

2017-06-01

Psychotherapy for hypochondriasis has greatly improved over the last decades and cognitive-behavioral treatments are most promising. However, research on predictors of treatment outcome for hypochondriasis is rare. Possible predictors of treatment outcome in cognitive therapy (CT) and exposure therapy (ET) for hypochondriasis were investigated. Characteristics and behaviors of 75 patients were considered as possible predictors: sociodemographic variables (sex, age, and cohabitation); psychopathology (pretreatment hypochondriacal symptoms, comorbid mental disorders, and levels of depression, anxiety, and somatic symptoms); and patient in-session interpersonal behavior. Severity of pretreatment hypochondriacal symptoms, comorbid mental disorders, and patient in-session interpersonal behavior were significant predictors in multiple hierarchical regression analyses. Interactions between the predictors and the treatment (CT or ET) were not found. In-session interpersonal behavior is an important predictor of outcome. Furthermore, there are no specific contraindications to treating hypochondriasis with CT or ET. © 2016 Wiley Periodicals, Inc.

Predictors of perceived male partner concurrency among women at risk for HIV and STI acquisition in Durban, South Africa.

Science.gov (United States)

Gaffoor, Zakir; Wand, Handan; Street, Renée A; Abbai, Nathlee; Ramjee, Gita

2016-01-01

Women in sub-Saharan Africa continue to be at greater risk for HIV acquisition than men. Concurrency, viz. multiple sexual partnerships that overlap over time, has been studied as a possible risk factor for HIV transmission. The aim of this study was to identify predictors of perceived male partner concurrency among sexually active, HIV negative women. Socio-demographic and behavioural data from women enrolled in a biomedical HIV prevention clinical trial were assessed in relation to perceived male partner concurrency using the Chi squared test. Univariate and multivariate logistic regression was performed to assess the independent predictors of perceived male partner concurrency. Kaplan-Meier survival estimates were obtained for HIV and STI incidence in relation to male partner concurrency. A Cox Proportional Hazards model was used to assess the association between perceived male partner concurrency and HIV and STI incidence. The results revealed that 29 % of women reported their male partners to be in concurrent sexual relationships, 22 % reported partners that were not engaging in concurrency, whilst 49 % reported not knowing their partners concurrency status. Older women, having never married, experiencing economic abuse, and women reporting individual concurrency, were found to be significant predictors of perceived male partner concurrency in the studied population. Perceived male partner concurrency was not found to be a significantly associated with incident HIV and STI infections in this analysis. The study provides insight into predictors of perceived male partner concurrency among women at high risk for STI and HIV acquisition. These results may inform the design of behavioural and biomedical interventions, to address the role of multiple sexual partnerships in HIV prevention.

Of Dutch courage and mobile chimneys: Pattern and predictors of ...

African Journals Online (AJOL)

Previous studies in Nigeria have associated alcohol and tobacco use among students with certain socioeconomic and educational achievement variables, albeit its determinants among university students remain largely unknown. This study examined current patterns and predictors of alcohol and tobacco use with a model ...

Inadequate Response to Therapy as a Predictor of Suicide.

Science.gov (United States)

Dahlsgaard, Katherine K.; Beck, Aaron T.; Brown, Gregory K.

1998-01-01

The role of response to cognitive therapy as a predictor of suicide was investigated by comparing 17 outpatients with mood disorders who committed suicide with 17 matched patients who did not commit suicide. Significant differences were found on several variables including higher levels of hopelessness at termination of therapy. (Author/EMK)

Predictors of utilisation of dental care services in a nationally representative sample of adults.

Science.gov (United States)

Guiney, H; Woods, N; Whelton, H; Morgan, K

2011-12-01

The objective of this study was to identify the predictors of utilisation of dental care services in Ireland. The 2007 Irish Survey of Lifestyle, Attitudes and Nutrition is a cross-sectional study, conducted in 2006/2007 (n = 10,364), by interviews at home to a representative sample of adults aged 18 years or over. Multivariate logistic regression was used to investigate the influence of socioeconomic, predisposing and enabling factors on the odds of males and females having a dental visit in the past year. The significant predictors of visiting the dentist in the past year were for males: having 3rd level education, employment status, earning 50,000 euros or more, location of residence, use of a car, brushing frequently, and dentition status. For females, the predictors were being between 25-34 or 55-64 years-old, education level, earning 50,000 euros or more, location of residence, use of a car, brushing frequently and dentition status. Predictors of the use of dental services vary by gender. Predictors common to both genders were education level, higher income, location of residence, use of a car, brushing frequently and dentition status. Many of the predictors of dental visiting in the past year are also related to social inequalities in health. These predictors may be useful markers of impact for policies designed to address inequalities in access to oral health services.

Demographics as predictors of suicidal thoughts and behaviors: A meta-analysis.

Directory of Open Access Journals (Sweden)

Xieyining Huang

Full Text Available Certain demographic factors have long been cited to confer risk or protection for suicidal thoughts and behaviors. However, many studies have found weak or non-significant effects. Determining the effect strength and clinical utility of demographics as predictors is crucial for suicide risk assessment and theory development. As such, we conducted a meta-analysis to determine the effect strength and clinical utility of demographics as predictors.We searched PsycInfo, PubMed, and GoogleScholar for studies published before January 1st, 2015. Inclusion criteria required that studies use at least one demographic factor to longitudinally predict suicide ideation, attempt, or death. The initial search yielded 2,541 studies, 159 of which were eligible. A total of 752 unique statistical tests were included in analysis.Suicide death was the most commonly studied outcome, followed by attempt and ideation. The average follow-up length was 9.4 years. The overall effects of demographic factors studied in the field as risk factors were significant but weak, and that of demographic factors studied as protective factors were non-significant. Adjusting for publication bias further reduced effect estimates. No specific demographic factors appeared to be strong predictors. The effects were consistent across multiple moderators.At least within the narrow methodological constraints of the existing literature, demographic factors were statistically significant risk factors, but not protective factors. Even as risk factors, demographics offer very little improvement in predictive accuracy. Future studies that go beyond the limitations of the existing literature are needed to further understand the effects of demographics.

Predictors of post-traumatic stress disorder following critical illness: A mixed methods study.

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Battle, Ceri E; James, Karen; Bromfield, Tom; Temblett, Paul

2017-11-01

Post-traumatic stress disorder has been reported in survivors of critical illness. The aim of this study was to investigate the predictors of post-traumatic stress disorder in survivors of critical illness. Patients attending the intensive care unit (ICU) follow-up clinic completed the UK-Post-Traumatic Stress Syndrome 14-Questions Inventory and data was collected from their medical records. Predictors investigated included age, gender, Apache II score, ICU length of stay, pre-illness psychopathology; delirium and benzodiazepine administration during ICU stay and delusional memories of the ICU stay following discharge. A total of 198 patients participated, with 54 (27%) patients suffering with post-traumatic stress disorder. On multivariable logistic regression, the significant predictors of post-traumatic stress disorder were younger age, lower Apache II score, pre-illness psychopathology and delirium during the ICU stay. The predictors of post-traumatic stress disorder in this study concur with previous research however a lower Apache II score has not been previously reported.

Nonstationary modeling of a long record of rainfall and temperature over Rome

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Villarini, Gabriele; Smith, James A.; Napolitano, Francesco

2010-10-01

A long record (1862-2004) of seasonal rainfall and temperature from the Rome observatory of Collegio Romano are modeled in a nonstationary framework by means of the Generalized Additive Models in Location, Scale and Shape (GAMLSS). Modeling analyses are used to characterize nonstationarities in rainfall and related climate variables. It is shown that the GAMLSS models are able to represent the magnitude and spread in the seasonal time series with parameters which are a smooth function of time. Covariate analyses highlight the role of seasonal and interannual variability of large-scale climate forcing, as reflected in three teleconnection indexes (Atlantic Multidecadal Oscillation, North Atlantic Oscillation, and Mediterranean Index), for modeling seasonal rainfall and temperature over Rome. In particular, the North Atlantic Oscillation is a significant predictor during the winter, while the Mediterranean Index is a significant predictor for almost all seasons.

The identity impairment model: a longitudinal study of self-schemas as predictors of disordered eating behaviors.

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Stein, Karen Farchaus; Corte, Colleen

2008-01-01

There is broad consensus that the eating disorders of anorexia nervosa and bulimia nervosa stem from fundamental disturbances in identity development, but theoretically based empirical support is lacking. To extend work on the identity impairment model by investigating the relationship between organizational properties of the self-concept and change in disordered eating behaviors (DEB) in an at-risk sample of college women transitioning between freshman and sophomore years. The number, valence, and organization of self-schemas; availability of a fat body weight self-schema; and DEB were measured at baseline in the freshman year and 6 and 12 months later in a community-based sample of college women engaged in subthreshold DEB (n = 77; control: n = 41). Repeated-measures analyses of variances were used to examine group differences, and hierarchical regression analyses were used to predict disordered eating behaviors. Women in the DEB group had more negative self-schemas at baseline and showed information-processing evidence of a fat self-schema compared with the controls. The groups did not differ in the number of positive self-schemas or interrelatedness. The number of negative self-schemas predicted increases in the level of DEB at 6- and 12-month follow-up, and these effects were mediated through the fat self-schema. The number of positive self-schemas predicted the fat self-schema score but was not predictive of increases in DEB. Interrelatedness of the self-concept was not a significant predictor in this model. Impairments in overall collection of identities are predictive of the availability in memory of a fat self-schema, which in turn is predictive of increases in DEB during the transition to college in a sample of women at risk for an eating disorder. Therefore, organizational properties of the self-concept may be an important focus for effective primary and secondary prevention.

Predictors of AIDS-preventive behavioral intentions among adult heterosexuals at risk for HIV-infection : Extending current models and measures

NARCIS (Netherlands)

Buunk, BP; Bakker, AB; Siero, FW; van den Eijnden, RJJM; Yzer, MC

This study examined the predictors of the intention to use condoms with new sexual partners. A sample of heterosexual adult females and males (n = 711) was recruited through various channels. A substantial part of the sample had engaged in risky sexual behavior. Predictors were based on various

Predictors of Exceptional Longevity: Effects of Early-Life Childhood Conditions, Midlife Environment and Parental Characteristics.

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Gavrilov, Leonid A; Gavrilova, Natalia S

Knowledge of strong predictors of mortality and longevity is very important for actuarial science and practice. Earlier studies found that parental characteristics as well as early-life conditions and midlife environment play a significant role in survival to advanced ages. However, little is known about the simultaneous effects of these three factors on longevity. This ongoing study attempts to fill this gap by comparing centenarians born in the United States in 1890-91 with peers born in the same years who died at age 65. The records for centenarians and controls were taken from computerized family histories, which were then linked to 1900 and 1930 U.S. censuses. As a result of this linkage procedure, 765 records of confirmed centenarians and 783 records of controls were obtained. Analysis with multivariate logistic regression found that parental longevity and some midlife characteristics proved to be significant predictors of longevity while the role of childhood conditions was less important. More centenarians were born in the second half of the year compared to controls, suggesting early origins of longevity. We found the existence of both general and gender-specific predictors of human longevity. General predictors common for men and women are paternal and maternal longevity. Gender-specific predictors of male longevity are the farmer occupation at age 40, Northeastern region of birth in the United States and birth in the second half of year. A gender-specific predictor of female longevity is surprisingly the availability of radio in the household according to the 1930 U.S. census. Given the importance of familial longevity as an independent predictor of survival to advanced ages, we conducted a comparative study of biological and nonbiological relatives of centenarians using a larger sample of 1,945 validated U.S. centenarians born in 1880-95. We found that male gender of centenarian has significant positive effect on survival of adult male relatives

Remarriage Beliefs as Predictors of Marital Quality and Positive Interaction in Stepcouples: An Actor-Partner Interdependence Model.

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Garneau, Chelsea L; Higginbotham, Brian; Adler-Baeder, Francesca

2015-12-01

Using an Actor-Partner Interdependence Model, we examined remarriage beliefs as predictors of marital quality and positive interaction in a sample of 179 stepcouples. Three beliefs were measured using subscales from the Remarriage Belief Inventory (RMBI) including success is slim, children are the priority, and finances should be pooled. Several significant actor and partner effects were found for both wives' and husbands' beliefs. Wives' marital quality was positively associated with their own beliefs that finances should be pooled and negatively associated with their own beliefs that success is slim. Wives' reports of their own and spouses' positive interaction were both positively associated with their beliefs that finances should be pooled. Their reports of spouses' positive interaction were also negatively associated with husbands' beliefs that success is slim. Husbands' marital quality was positively associated with wives' beliefs that children are the priority, positively associated with their own beliefs that finances should be pooled, and negatively with success is slim. Positive interaction for husbands was positively associated with wives' beliefs that finances should be pooled and negatively associated with their own beliefs that success is slim. Finally, husbands' reports of positive interaction for their spouses were positively associated with wives' beliefs that finances should be pooled. Implications for future research utilizing dyadic data analysis with stepcouples are addressed. © 2015 Family Process Institute.

Identifying rural-urban differences in the predictors of emergency ambulance service demand and misuse.

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Wong, Ho Ting; Lin, Teng-Kang; Lin, Jen-Jia

2018-06-13

This study aims to assess rural-urban differences in the predictors of emergency ambulance service (EAS) demand and misuse in New Taipei City. Identifying the predictors of EAS demand will help the EAS service managing authority in formulating focused policies to maintain service quality. Over 160,000 electronic EAS usage records were used with a negative binomial regression model to assess rural-urban differences in the predictors of EAS demand and misuse. The factors of 1) ln-transformed population density, 2) percentage of residents who completed up to junior high school education, 3) accessibility of hospitals without an emergency room, and 4) accessibility of EAS were found to be predictors of EAS demand in rural areas, whereas only the factor of percentage of people aged above 65 was found to predict EAS demand in urban areas. For EAS misuse, only the factor of percentage of low-income households was found to be a predictor in rural areas, whereas no predictor was found in the urban areas. Results showed that the factors predicting EAS demand and misuse in rural areas were more complicated compared to urban areas and, therefore, formulating EAS policies for rural areas based on the results of urban studies may not be appropriate. Copyright © 2018. Published by Elsevier B.V.

A longitudinal study of serum insulin and insulin resistance as predictors of weight and body fat gain in African American and Caucasian children.

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Sedaka, N M; Olsen, C H; Yannai, L E; Stutzman, W E; Krause, A J; Sherafat-Kazemzadeh, R; Condarco, T A; Brady, S M; Demidowich, A P; Reynolds, J C; Yanovski, S Z; Hubbard, V S; Yanovski, J A

2017-01-01

The influence of insulin and insulin resistance (IR) on children's weight and fat gain is unclear. To evaluate insulin and IR as predictors of weight and body fat gain in children at high risk for adult obesity. We hypothesized that baseline IR would be positively associated with follow-up body mass index (BMI) and fat mass. Two hundred and forty-nine healthy African American and Caucasian children aged 6-12 years at high risk for adult obesity because of early-onset childhood overweight and/or parental overweight were followed for up to 15 years with repeated BMI and fat mass measurements. We examined baseline serum insulin and homeostasis model of assessment-IR (HOMA-IR) as predictors of follow-up BMI Z-score and fat mass by dual-energy X-ray absorptiometry in mixed model longitudinal analyses accounting for baseline body composition, pubertal stage, sociodemographic factors and follow-up interval. At baseline, 39% were obese (BMI⩾95th percentile for age/sex). Data from 1335 annual visits were examined. Children were followed for an average of 7.2±4.3 years, with a maximum follow-up of 15 years. After accounting for covariates, neither baseline insulin nor HOMA-IR was significantly associated with follow-up BMI (Ps>0.26), BMIz score (Ps>0.22), fat mass (Ps>0.78) or fat mass percentage (Ps>0.71). In all models, baseline BMI (Pfat mass (Pfat (Pfat mass. In models restricted to children without obesity at baseline, some but not all models had significant interaction terms between body adiposity and insulinemia/HOMA-IR that suggested less gain in mass among those with greater insulin or IR. The opposite was found in some models restricted to children with obesity at baseline. In middle childhood, BMI and fat mass, but not insulin or IR, are strong predictors of children's gains in BMI and fat mass during adolescence.

Predictors of outcome after elective endovascular abdominal aortic aneurysm repair and external validation of a risk prediction model.

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Wisniowski, Brendan; Barnes, Mary; Jenkins, Jason; Boyne, Nicholas; Kruger, Allan; Walker, Philip J

2011-09-01

Endovascular abdominal aortic aneurysm (AAA) repair (EVAR) has been associated with lower operative mortality and morbidity than open surgery but comparable long-term mortality and higher delayed complication and reintervention rates. Attention has therefore been directed to identifying preoperative and operative variables that influence outcomes after EVAR. Risk-prediction models, such as the EVAR Risk Assessment (ERA) model, have also been developed to help surgeons plan EVAR procedures. The aims of this study were (1) to describe outcomes of elective EVAR at the Royal Brisbane and Women's Hospital (RBWH), (2) to identify preoperative and operative variables predictive of outcomes after EVAR, and (3) to externally validate the ERA model. All elective EVAR procedures at the RBWH before July 1, 2009, were reviewed. Descriptive analyses were performed to determine the outcomes. Univariate and multivariate analyses were performed to identify preoperative and operative variables predictive of outcomes after EVAR. Binomial logistic regression analyses were used to externally validate the ERA model. Before July 1, 2009, 197 patients (172 men), who were a mean age of 72.8 years, underwent elective EVAR at the RBWH. Operative mortality was 1.0%. Survival was 81.1% at 3 years and 63.2% at 5 years. Multivariate analysis showed predictors of survival were age (P = .0126), American Society of Anesthesiologists (ASA) score (P = .0180), and chronic obstructive pulmonary disease (P = .0348) at 3 years and age (P = .0103), ASA score (P = .0006), renal failure (P = .0048), and serum creatinine (P = .0022) at 5 years. Aortic branch vessel score was predictive of initial (30-day) type II endoleak (P = .0015). AAA tortuosity was predictive of midterm type I endoleak (P = .0251). Female sex was associated with lower rates of initial clinical success (P = .0406). The ERA model fitted RBWH data well for early death (C statistic = .906), 3-year survival (C statistic = .735), 5-year

Predictors of health-related quality of life in type II diabetic patients in Greece

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Frydas Aristidis

2007-07-01

Full Text Available Abstract Background Diabetes Mellitus (DM is a major cause of morbidity and mortality affecting millions of people worldwide, while placing a noteworthy strain on public health funding. The aim of this study was to assess health-related quality of life (HRQOL of Greek Type II DM patients and to identify significant predictors of the disease in this patient population. Methods The sample (N = 229, 52.8% female, 70.0 years mean age lived in a rural community of Lesvos, an island in the northeast of the Aegean Archipelagos. The generic SF-36 instrument, administered by trainee physicians, was used to measure HRQOL. Scale scores were compared with non-parametric Mann-Whitney and Kruskal-Wallis tests and multivariate stepwise linear regression analyses were used to investigate the effect of sociodemographic and diabetes-related variables on HRQOL. Results The most important predictors of impaired HRQOL were female gender, diabetic complications, non-diabetic comorbidity and years with diabetes. Older age, lower education, being unmarried, obesity, hypertension and hyperlipidaemia were also associated with impaired HRQOL in at least one SF-36 subscale. Multivariate regression analyses produced models explaining significant portions of the variance in SF-36 subscales, especially physical functioning (R2 = 42%, and also showed that diabetes-related indicators were more important disease predictors, compared to sociodemographic variables. Conclusion The findings could have implications for health promotion in rural medical practice in Greece. In order to preserve a good HRQOL, it is obviously important to prevent diabetes complications and properly manage concomitant chronic diseases. Furthermore, the gender difference is interesting and requires further elucidation. Modifying screening methods and medical interventions or formulating educational programs for the local population appear to be steps in the correct direction.

Epidemiology, Seasonality, and Predictors of Outcome of AIDS-Associated Penicillium marneffei Infection in Ho Chi Minh City, Viet Nam

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Wolbers, Marcel; Quang, Vo Minh; Chinh, Nguyen Tran; Huong Lan, Nguyen Phu; Lam, Pham Si; Kozal, Michael J.; Shikuma, Cecilia M.; Day, Jeremy N.; Farrar, Jeremy

2011-01-01

Background. Penicillium marneffei is an important human immunodeficiency virus (HIV)–associated opportunistic pathogen in Southeast Asia. The epidemiology and the predictors of penicilliosis outcome are poorly understood. Methods. We performed a retrospective study of culture-confirmed incident penicilliosis admissions during 1996–2009 at the Hospital for Tropical Diseases in Ho Chi Minh City, Viet Nam. Seasonality of penicilliosis was assessed using cosinor models. Logistic regression was used to assess predictors of death or worsening disease based on 10 predefined covariates, and Cox regression was performed to model time-to-antifungal initiation. Results. A total of 795 patients were identified; hospital charts were obtainable for 513 patients (65%). Cases increased exponentially and peaked in 2007 (156 cases), mirroring the trends in AIDS admissions during the study period. A highly significant seasonality for penicilliosis (P Viet nam. The number of cases increases during rainy months. Injection drug use, shorter history, absence of fever or skin lesions, respiratory difficulty, higher lymphocyte count, and lower platelet count predict poor in-hospital outcome. PMID:21427403

Predictors of job satisfaction and absenteeism in two samples of Hong Kong nurses.

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Siu, Oi-Ling

2002-10-01

Stress-related outcomes of job satisfaction and absenteeism among nurses should receive more attention in Hong Kong because absenteeism is costly. Many nurses' complaints are due to organizational change in privatization since the establishment of the Hong Kong Hospital Authority in 1991. Organizational climate is found to be an antecedent of job dissatisfaction and absenteeism in many studies in western societies. To investigate the role of organizational climate and psychological distress on job satisfaction; and the role of climate, distress and job satisfaction on absenteeism in Hong Kong nurses, while controlling for demographic variables. A self-administered questionnaire survey method was used to collect data from two samples of nurses within a 8-month period. They are, respectively, 144 (74 general nurses, 70 psychiatric nurses; 47 males, 97 females) and 114 (85 general nurses, 29 psychiatric nurses; 17 males, 97 females) nurses. Multiple regression analyses revealed that occupational type (psychiatric/general), environment (the physical conditions in the work area) and psychological distress were significant predictors of job satisfaction for sample 1; and well-being (social relations, welfare and health issues) was the only significant predictor of job satisfaction for sample 2. However, age, involvement (the degree of commitment displayed towards employees by the organization), psychological distress and job satisfaction were significant predictors of absenteeism for sample 1; and occupational type, organization (the interaction between the worker and the organization), and involvement were significant predictors of absenteeism for sample 2. The empirical findings provide support for the climate-job satisfaction and climate-absenteeism relationships. Psychological distress could be an antecedent of job satisfaction; and job satisfaction could be an antecedent of absenteeism. Certain climate dimensions should be improved to enhance job satisfaction and

Predictors of peer victimization among Peruvian adolescents in the young lives cohort.

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Lister, Cameron; Merrill, Ray M; Vance, David; West, Joshua H; Hall, P Cougar; Crookston, Benjamin T

2015-02-01

Bully-victimization is a widespread public health issue with significant negative effects on both social function and psychological well-being. Existing research in Peru shows high prevalence of bullying. However, researchers have yet to fully understand the phenomenon of victimization in developing regions. The purpose of this study was to characterize victimization patterns over time, along with the predictors of victimization from a cohort of Peruvian adolescents enrolled in the young lives (YL) study. This study examined data from YL, a longitudinal study of poverty, health, and development, which examined data from the older cohort of children in Peru across three rounds (ages 8, 12, and 15 years). The sample consisted of 714 children from 74 communities that represent 20 districts in Peru. After adjusting for urban/rural setting, there remained a significantly lower wealth index for children who were bullied at ages 8 and 12 years. Exploratory analysis showed that although those in the lowest quartile of body mass index (BMI) were significantly more likely to be bullied at age 8 years, this association waned over time. A worse caregiver assessment of child's health compared with others was associated with a significantly greater risk of bully-victimization. At age 8 years, caregiver education was significantly lower among those bullied compared with those who were not bullied. This study showed several factors as the predictors of victimization in the early years, including being male and having low BMI, low socioeconomic status, and low parental/caregiver education. Further longitudinal studies should be conducted to determine the extent to which these predictors vary in significance over time.

Predictors of Success in Dental Hygiene Education: A Six-Year Review.

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Downey, Mary C.; Collins, Marie A.; Browning, William D.

2002-01-01

Examined the predictive reliability of incoming grade point average (GPA), incoming math/science GPA, and Scholastic Aptitude Test (SAT) scores in predicting success in dental hygiene education. Found that GPA was the most significant predictor of success. (EV)

Significance of sarcopenia as a prognostic factor for metastatic urothelial carcinoma patients treated with systemic chemotherapy.

Science.gov (United States)

Abe, Hideyuki; Takei, Kohei; Uematsu, Toshitaka; Tokura, Yuumi; Suzuki, Issei; Sakamoto, Kazumasa; Nishihara, Daisaku; Yamaguchi, Yoshiyuki; Mizuno, Tomoya; Nukui, Akinori; Kobayashi, Minoru; Kamai, Takao

2018-04-01

Recently, numerous studies have reported an association between sarcopenia and poor outcomes in various kinds of malignancies. We investigated whether sarcopenia predicts the survival of patients with metastatic urothelial carcinoma who underwent systemic chemotherapy. We reviewed 87 metastatic urothelial carcinoma patients who underwent chemotherapy (gemcitabine plus cisplatin or gemcitabine plus carboplatin for cisplatin-unfit patients) between 2007 and 2015. A computed tomography scan prior to chemotherapy was used for evaluating sarcopenia, and we measured three cross-sectional areas of skeletal muscle at the third lumbar vertebra and calculated the skeletal muscle index (SMI), the paraspinal muscle index (PSMI), and the total psoas area (TPA) of each patient. Predictive values of survival were assessed using Cox regression analysis. The median overall survival (OS) was 16 months (95% CI 13.5-18). Although SMI alone was not a significant predictor of shorter OS (P = 0.117) in univariate analysis, SMI stratified by the value of the body mass index (BMI) was a significant predictor of shorter OS in univariate analysis (P = 0.037) and was also an independent predictor of shorter OS in multivariate analysis (P = 0.026). PSMI and TPA were not significant prognostic factors even when stratified by BMI (P = 0.294 and 0.448), respectively. Neither PSMI nor TPA could substitute SMI as a predictor for poor outcomes in metastatic urothelial carcinoma patients treated with systemic chemotherapy in our study. SMI stratified by BMI is a useful predictor of prognosis in these patients.

Survival and its predictors from age 75 to 85 in men and women belonging to cohorts with marked survival differences to age 75

DEFF Research Database (Denmark)

Heikkinen, E; Kauppinen, M; Schroll, M

2016-01-01

focusing on different domains of health, functional capacity, and physical and social activities. RESULTS: The proportion of survivors to age 75 was markedly smaller among the Finnish men and women than Danish or Swedish subjects. In the local population no marked differences in survival from age 75 to 85...... among three local Nordic populations using survival data on national cohorts as background information. METHODS: The data were derived from national registers and from samples of 75-year old living in Denmark, Sweden, and Finland. The subjects were invited to take part in interviews and examinations...... were observed between the groups of men, while women survived longer than men and longer in Göteborg than in Glostrup or Jyväskylä. Univariate models revealed 12 predictors of survival. In the multivariate models, the significant predictors among men related to physical fitness, whereas among women...

Fear of childbirth and obstetrical events as predictors of postnatal symptoms of depression and post-traumatic stress disorder.

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Fairbrother, Nichole; Woody, Sheila R

2007-12-01

This prospective study examined psychological and obstetrical predictors of enduring postpartum symptoms of depression and post-traumatic stress disorder. Contrary to prediction, prenatal fear of childbirth did not significantly predict symptoms of depression or post-traumatic stress disorder at one month postpartum, but anxiety sensitivity was an unexpected predictor that merits further investigation. Several obstetrical and neonatal variables significantly predicted symptoms of post-traumatic disorder, but not depression.

Age is no barrier: predictors of academic success in older learners

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Imlach, Abbie-Rose; Ward, David D.; Stuart, Kimberley E.; Summers, Mathew J.; Valenzuela, Michael J.; King, Anna E.; Saunders, Nichole L.; Summers, Jeffrey; Srikanth, Velandai K.; Robinson, Andrew; Vickers, James C.

2017-11-01

Although predictors of academic success have been identified in young adults, such predictors are unlikely to translate directly to an older student population, where such information is scarce. The current study aimed to examine cognitive, psychosocial, lifetime, and genetic predictors of university-level academic performance in older adults (50-79 years old). Participants were mostly female (71%) and had a greater than high school education level (M = 14.06 years, SD = 2.76), on average. Two multiple linear regression analyses were conducted. The first examined all potential predictors of grade point average (GPA) in the subset of participants who had volunteered samples for genetic analysis (N = 181). Significant predictors of GPA were then re-examined in a second multiple linear regression using the full sample (N = 329). Our data show that the cognitive domains of episodic memory and language processing, in conjunction with midlife engagement in cognitively stimulating activities, have a role in predicting academic performance as measured by GPA in the first year of study. In contrast, it was determined that age, IQ, gender, working memory, psychosocial factors, and common brain gene polymorphisms linked to brain function, plasticity and degeneration (APOE, BDNF, COMT, KIBRA, SERT) did not influence academic performance. These findings demonstrate that ageing does not impede academic achievement, and that discrete cognitive skills as well as lifetime engagement in cognitively stimulating activities can promote academic success in older adults.

Modelling the distribution of chickens, ducks, and geese in China

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Prosser, Diann J.; Wu, Junxi; Ellis, Erie C.; Gale, Fred; Van Boeckel, Thomas P.; Wint, William; Robinson, Tim; Xiao, Xiangming; Gilbert, Marius

2011-01-01

Global concerns over the emergence of zoonotic pandemics emphasize the need for high-resolution population distribution mapping and spatial modelling. Ongoing efforts to model disease risk in China have been hindered by a lack of available species level distribution maps for poultry. The goal of this study was to develop 1 km resolution population density models for China's chickens, ducks, and geese. We used an information theoretic approach to predict poultry densities based on statistical relationships between poultry census data and high-resolution agro-ecological predictor variables. Model predictions were validated by comparing goodness of fit measures (root mean square error and correlation coefficient) for observed and predicted values for 1/4 of the sample data which were not used for model training. Final output included mean and coefficient of variation maps for each species. We tested the quality of models produced using three predictor datasets and 4 regional stratification methods. For predictor variables, a combination of traditional predictors for livestock mapping and land use predictors produced the best goodness of fit scores. Comparison of regional stratifications indicated that for chickens and ducks, a stratification based on livestock production systems produced the best results; for geese, an agro-ecological stratification produced best results. However, for all species, each method of regional stratification produced significantly better goodness of fit scores than the global model. Here we provide descriptive methods, analytical comparisons, and model output for China's first high resolution, species level poultry distribution maps. Output will be made available to the scientific and public community for use in a wide range of applications from epidemiological studies to livestock policy and management initiatives.

Childhood Predictors of Adolescent Competence and Self-Worth in Rural Youth

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Rew, Lynn; Grady, Matthew W.; Spoden, Micajah

2012-01-01

Problem Urban children who become competent adults despite circumstances that place their development and mental health at risk are considered to be resilient. Less is known about the risk and protective factors that characterize resilience among Hispanic/Latinos living in rural areas. Methods Data for regression analyses were collected when children (N = 603; 54% Hispanic/Latino) enrolled in the study in fifth grade, (M=10.4 years of age) and again five years later when they were in high school (M=15 years of age). Findings Statistically significant predictors of competence and self-worth in high schoolers included gender, ethnicity, and mother’s education, as well as stress, temperament (task persistence), and competences measured in grade school. Conclusions Parents’ perceptions of child’s temperament is a significant predictor of future competence and self-worth among rural adolescents. PMID:23121139

Childhood predictors of adolescent competence and self-worth in rural youth.

Science.gov (United States)

Rew, Lynn; Grady, Matthew W; Spoden, Micajah

2012-11-01

Urban children who become competent adults despite circumstances that place their development and mental health at risk are considered to be resilient. Less is known about the risk and protective factors that characterize resilience among Hispanic/Latinos living in rural areas. Data for regression analyses were collected when children (n = 603; 54% Hispanic/Latino) enrolled in the study in fifth grade (M = 10.4 years of age), and again 5 years later when they were in high school (M = 15 years of age). Statistically significant predictors of competence and self-worth in high schoolers included gender, ethnicity, and mother's education, as well as stress, temperament (task persistence), and competences measured in grade school. Parents' perception of child's temperament is a significant predictor of future competence and self-worth among rural adolescents. © 2012 Wiley Periodicals, Inc.

Worsening heart failure in 'real-world' clinical practice: predictors and prognostic impact.

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AlFaleh, Hussam; Elasfar, Abdelfatah A; Ullah, Anhar; AlHabib, Khalid F; Hersi, Ahmad; Mimish, Layth; Almasood, Ali; Al Ghamdi, Saleh; Ghabashi, Abdullah; Malik, Asif; Hussein, Gamal A; Al-Murayeh, Mushabab; Abuosa, Ahmed; Al Habeeb, Waleed; Kashour, Tarek

2017-08-01

The aim of this study was to compare the clinical features, predictors, and clinical outcomes of patients hospitalized with acute heart failure (AHF), with and without worsening heart failure (WHF). We used data from a multicentre prospective registry of AHF patients created in Saudi Arabia. WHF was defined as recurrence of heart failure symptoms or signs-with or without cardiogenic shock. In-hospital short- and long-term outcomes, as well as predictors of WHF are described. Of the 2609 AHF patients enrolled, 33.8% developed WHF. WHF patients were more likely to have a history of heart failure and ischaemic heart disease. Use of intravenous vasodilators, inotropic agents, furosemide infusions, and discharge beta-blockers was significantly higher in WHF patients, while use of discharge ACE inhibitors was higher in patients without WHF. Length of hospital stay was significantly longer for WHF patients than for those without WHF [median (interquartile range) 13 (14) vs. 7 (7) days, P world clinical practice, WHF during hospitalization for AHF is a strong predictor for short- and intermediate-term mortality, and a cause for longer hospital stays. © 2016 The Authors. European Journal of Heart Failure © 2016 European Society of Cardiology.

Social-cognitive predictors of vocational outcomes in transition youth with epilepsy: Application of social cognitive career theory.

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Sung, Connie; Connor, Annemarie

2017-08-01

This study examined the utility of social-cognitive career theory (SCCT; Lent, Brown, & Hackett, 1994) as a framework to investigate career self-efficacy, outcome expectations, goals, and contextual supports and barriers as predictors of choice actions among transition-age individuals with epilepsy. Moreover, these SCCT constructs are offered as an operational definition of work participation in this population. Using a quantitative descriptive research design and hierarchical regression analysis (HRA), 90 transition-age individuals with epilepsy, age 18-25, were recruited from affiliates of the Epilepsy Foundation and invited to complete an online survey comprised of a series of self-report social-cognitive measures. The HRA findings indicated that self-efficacy, outcome expectations, and environmental supports were significant predictors of work participation in youth and young adults with epilepsy. The final model accounted for 58% of the variance in work participation, which is considered a large effect size. The research findings provide support for the use of the SCCT framework to identify predictors of work participation and to provide guidance for designing customized vocational rehabilitation services and career development interventions for individuals with epilepsy in the transition from adolescence to adulthood. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Predictors of dieting and non-dieting approaches among adults living in Australia

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Stuart Leske

2017-02-01

Full Text Available Abstract Background There is a dearth of research comparing why dieting and non-dieting approaches are adopted. A greater understanding of reasons underlying dieting and non-dieting attempts will help to identify target beliefs for interventions to support and motivate adults to attempt whatever approach they are willing and/or able to pursue. We investigated the predictors of dieting and non-dieting approaches in Australian adults using predictors that were identified in a previous qualitative study. Methods We conducted a prospective study, with two waves of data collection occurring 4 weeks apart. At baseline, participants completed a questionnaire assessing constructs drawn from the theory of planned behaviour (attitude, subjective norm, and self-efficacy, past behaviour, non-planning, attributions for dieting failure, weight control beliefs, and dieting and non-dieting intentions. We used path modelling to analyse responses. Results At baseline, 719 adults (52.2% male aged between 18 and 76 completed the questionnaire. Four weeks later, 64% of participants (n = 461 reported on their dieting and non-dieting behaviour in the past month. Past behaviour, attitude, subjective norm, and self-identity significantly predicted dieting intentions. Dieting intentions and past behaviour significantly predicted dieting behaviour, while non-planning and self-efficacy did not. The model explained 74.8% of the variance in intention and 52.9% of the variance in behaviour. While most findings were similar for the non-dieting model, subjective norms and self-identity did not predict intention, while self-efficacy and self-identity both predicted non-dieting behaviour directly. The non-dieting model explained 58.2% of the variance in intention and 37.5% of the variance in behaviour. Conclusions The findings from this study provide support for the application of TPB and identity theory constructs in the context of both dieting and non-dieting behaviour

Prevalence and predictors of depression and anxiety among the elderly population living in geriatric homes in Cairo, Egypt.

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Ahmed, Dalia; El Shair, Inas Helmi; Taher, Eman; Zyada, Fadia

2014-12-01

Anxiety and depression are common in the elderly and affect their quality of life. The rates of depression and anxiety are higher among those living in institutional settings and are usually undiagnosed. The aim of the study was to determine the prevalence and predictors of depression, anxiety and mixed form (i.e. depression and anxiety) in the elderly living at geriatric homes. A cross-sectional study was conducted on 240 elderly participants from four randomly selected geriatric homes in Cairo. A pretested interview questionnaire was used to collect data. A short version of the Geriatric Depression Scale (GDS-15), the Hamilton Anxiety Scale, the Katz scale for Activity of Daily living, the three-item loneliness scale and the Personal Wellbeing Index Scale were used. The prevalence of depression, anxiety and mixed disorder among the studied group were 37.5, 14.2 and 30%, respectively. Old age and the presence of comorbidities were predictors for depression and/or anxiety. Female sex, a lower social class, insufficient income, partial independence and loneliness feeling are significant predictors for depression. Being married and loneliness feeling are significant predictors for anxiety, whereas the functional status is a significant predictor for mixed depression and anxiety. Depression and/or anxiety were found in more than 80% of the studied group. An older age, female sex, insufficient income, a lower social class, a partially independent functional status, the presence of comorbidities, more frequent loneliness feeling and being married or divorced were found to be significant predictors for these problems. This study reflects the need for the screening of the elderly in geriatric homes for depression and/or anxiety, especially among high-risk groups, and developing interventions to prevent and control such problems.

Dysfunctional Career Thoughts and Attitudes as Predictors of Vocational Identity among Young Adults with Attention Deficit Hyperactivity Disorder

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Dipeolu, Abiola; Sniatecki, Jessica L.; Storlie, Cassandra A.; Hargrave, Stephanie

2013-01-01

This study examined dysfunctional career thoughts and attitudes as predictors of vocational identity among high school students with Attention Deficit Hyperactivity Disorder (ADHD). Regression analysis results indicated that dysfunctional career thoughts and attitudes were significant predictors of vocational identity, accounting for 42% of the…

Clinical predictors of central sleep apnea evoked by positive airway pressure titration

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Moro M

2016-07-01

Full Text Available Marilyn Moro,1 Karen Gannon,1 Kathy Lovell,1 Margaret Merlino,1 James Mojica,2 Matt T Bianchi,1,3 1Neurology Department, 2Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA; 3Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA Purpose: Treatment-emergent central sleep apnea (TECSA, also called complex apnea, occurs in 5%–15% of sleep apnea patients during positive airway pressure (PAP therapy, but the clinical predictors are not well understood. The goal of this study was to explore possible predictors in a clinical sleep laboratory cohort, which may highlight those at risk during clinical management.Methods: We retrospectively analyzed 728 patients who underwent PAP titration (n=422 split night; n=306 two-night. Demographics and self-reported medical comorbidities, medications, and behaviors as well as standard physiological parameters from the polysomnography (PSG data were analyzed. We used regression analysis to assess predictors of binary presence or absence of central apnea index (CAI ≥5 during split PSG (SN-PSG versus full-night PSG (FN-PSG titrations.Results: CAI ≥5 was present in 24.2% of SN-PSG and 11.4% of FN-PSG patients during titration. Male sex, maximum continuous positive airway pressure, and use of bilevel positive airway pressure were predictors of TECSA, and rapid eye movement dominance was a negative predictor, for both SN-PSG and FN-PSG patients. Self-reported narcotics were a positive predictor of TECSA, and the time spent in stage N2 sleep was a negative predictor only for SN-PSG patients. Self-reported history of stroke and the CAI during the diagnostic recording predicted TECSA only for FN-PSG patients.Conclusion: Clinical predictors of treatment-evoked central apnea spanned demographic, medical history, sleep physiology, and titration factors. Improved predictive models may be increasingly important as diagnostic and therapeutic modalities move away from the

Using Dominance Analysis to Determine Predictor Importance in Logistic Regression

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Azen, Razia; Traxel, Nicole

2009-01-01

This article proposes an extension of dominance analysis that allows researchers to determine the relative importance of predictors in logistic regression models. Criteria for choosing logistic regression R[superscript 2] analogues were determined and measures were selected that can be used to perform dominance analysis in logistic regression. A…

Predictors of Adolescent Breakfast Consumption: Longitudinal Findings from Project EAT

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Bruening, Meg; Larson, Nicole; Story, Mary; Neumark-Sztainer, Dianne; Hannan, Peter

2011-01-01

Objective: To identify predictors of breakfast consumption among adolescents. Methods: Five-year longitudinal study Project EAT (Eating Among Teens). Baseline surveys were completed in Minneapolis-St. Paul schools and by mail at follow-up by youth (n = 800) transitioning from middle to high school. Linear regression models examined associations…

Pubertal status, interaction with significant others, and self-esteem of adolescent girls.

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Lacković-Grgin, K; Dekovíc, M; Opacić, G

1994-01-01

The aim of this study was to examine the relationship between pubertal status, the quality of interactions with significant others, and the self-esteem of adolescent girls. The model which was tested, hypothesized that pubertal status affects self-esteem through girls' interactions with their parents and friends. Pubertal status was operationalized as the number of months between occurrence of the first menstrual periods and time of the investigation. The measure of self-esteem was the shortened form of the Coopersmith Self-Esteem Inventory. Analyses revealed that girls who begun menstruating six months before the investigation obtained higher scores on the measure of self-esteem than did girls who had been menstruating 13 months or more. The best predictor of self-esteem, however, was the quality of interaction with their mothers. The results support the theoretical view that stresses the importance of interaction with significant others for the development of self-esteem.

Teaching physical activities to students with significant disabilities using video modeling.

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Cannella-Malone, Helen I; Mizrachi, Sharona V; Sabielny, Linsey M; Jimenez, Eliseo D

2013-06-01

The objective of this study was to examine the effectiveness of video modeling on teaching physical activities to three adolescents with significant disabilities. The study implemented a multiple baseline across six physical activities (three per student): jumping rope, scooter board with cones, ladder drill (i.e., feet going in and out), ladder design (i.e., multiple steps), shuttle run, and disc ride. Additional prompt procedures (i.e., verbal, gestural, visual cues, and modeling) were implemented within the study. After the students mastered the physical activities, we tested to see if they would link the skills together (i.e., complete an obstacle course). All three students made progress learning the physical activities, but only one learned them with video modeling alone (i.e., without error correction). Video modeling can be an effective tool for teaching students with significant disabilities various physical activities, though additional prompting procedures may be needed.

Sex Differences in Predictors of Response to Multidisciplinary Treatment of Chronic Pain

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John W Burns

1996-01-01

Full Text Available BACKGROUND: Multidisciplinary programs for treatment of chronic pain are generally effective, yet many patients fail to show significant improvement. The search for predictors of outcome has not explicitly considered sex.

PhosphoRice: a meta-predictor of rice-specific phosphorylation sites

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Que Shufu

2012-02-01

Full Text Available Abstract Background As a result of the growing body of protein phosphorylation sites data, the number of phosphoprotein databases is constantly increasing, and dozens of tools are available for predicting protein phosphorylation sites to achieve fast automatic results. However, none of the existing tools has been developed to predict protein phosphorylation sites in rice. Results In this paper, the phosphorylation site predictors, NetPhos 2.0, NetPhosK, Kinasephos, Scansite, Disphos and Predphosphos, were integrated to construct meta-predictors of rice-specific phosphorylation sites using several methods, including unweighted voting, unreduced weighted voting, reduced unweighted voting and weighted voting strategies. PhosphoRice, the meta-predictor produced by using weighted voting strategy with parameters selected by restricted grid search and conditional random search, performed the best at predicting phosphorylation sites in rice. Its Matthew's Correlation Coefficient (MCC and Accuracy (ACC reached to 0.474 and 73.8%, respectively. Compared to the best individual element predictor (Disphos_default, PhosphoRice archieved a significant increase in MCC of 0.071 (P Conclusions PhosphoRice is a powerful tool for predicting unidentified phosphorylation sites in rice. Compared to the existing methods, we found that our tool showed greater robustness in ACC and MCC. PhosphoRice is available to the public at http://bioinformatics.fafu.edu.cn/PhosphoRice.

Stepwise latent class models for explaining group-level putcomes using discrete individual-level predictors

NARCIS (Netherlands)

Bennink, Margot; Croon, M.A.; Vermunt, J.K.

2015-01-01

Explaining group-level outcomes from individual-level predictors requires aggregating the individual-level scores to the group level and correcting the group-level estimates for measurement errors in the aggregated scores. However, for discrete variables it is not clear how to perform the

Respiratory sinus arrhythmia, effortful control, and parenting as predictors of children's sympathy across early childhood.

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Taylor, Zoe E; Eisenberg, Nancy; Spinrad, Tracy L

2015-01-01

The goal of this study was to examine physiological and environmental predictors of children's sympathy (an emotional response consisting of feelings of concern or sorrow for others who are distressed or in need) and whether temperamental effortful control mediated these relations. Specifically, in a study of 192 children (23% Hispanic; 54% male), respiratory sinus arrhythmia (RSA), a measure thought to reflect physiological regulation, and observed authoritative parenting (both at 42 months) were examined as predictors of children's effortful control (at 54 months) and, in turn, children's sympathy (at 72 and 84 months). Measures of both baseline RSA and RSA suppression were examined. In a structural equation model, observed parenting was positively related to children's subsequent sympathy through its positive relation to effortful control. Furthermore, the indirect path from baseline RSA to higher sympathy through effortful control was marginally significant. Authoritative parenting and baseline RSA uniquely predicted individual differences in children's effortful control. Findings highlight the potential role of both authoritative parenting and physiological regulation in the development of children's sympathy.

Predictors of self-rated health: a 12-month prospective study of IT and media workers.

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Hasson, Dan; Arnetz, Bengt B; Theorell, Töres; Anderberg, Ulla Maria

2006-07-31

The aim of the present study was to determine health-related risk and salutogenic factors and to use these to construct prediction models for future self-rated health (SRH), i.e. find possible characteristics predicting individuals improving or worsening in SRH over time (0-12 months). A prospective study was conducted with measurements (physiological markers and self-ratings) at 0, 6 and 12 months, involving 303 employees (187 men and 116 women, age 23-64) from four information technology and two media companies. There were a multitude of statistically significant cross-sectional correlations (Spearman's Rho) between SRH and other self-ratings as well as physiological markers. Predictors of future SRH were baseline ratings of SRH, self-esteem and social support (logistic regression), and SRH, sleep quality and sense of coherence (linear regression). The results of the present study indicate that baseline SRH and other self-ratings are predictive of future SRH. It is cautiously implied that SRH, self-esteem, social support, sleep quality and sense of coherence might be predictors of future SRH and therefore possibly also of various future health outcomes.

Incidence and predictors of surgical site infection in Ethiopia: prospective cohort.

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Legesse Laloto, Tamrat; Hiko Gemeda, Desta; Abdella, Sadikalmahdi Hussen

2017-02-03

Surgical site infections are commonest nosocomial infections and responsible for considerable morbidity and mortality as well as increased hospitalizations and treatment cost related to surgical operations. The aim of this study was to determine incidence and predictors of surgical site infections at surgical ward of Hawassa University Referral Hospital, Southern Ethiopia. We performed prospective study involving 105 patients that undergone major surgical procedure at Hawassa University Referral Hospital from March 2 to May 2, 2015. Data were extracted from paper based medical charts, operational and anesthesia note, by direct observation and patients' interview. All patients were followed daily before, during and after operation for 30 days starting from the date of operation. Data were analyzed using Statistical Package for Social Science (SPSS) for window version 20.0 software. Predictors of Surgical site infections were identified using multivariable logistic regression model. P-value less than 0.05 was considered to be statistically significant. We studied 105 patients. Sixty four patients (61%) were males. The mean age of the patients was 30.85 ± 17.72 years. The mean Body Mass Index (BMI) was 21.6 ± 4 kg/m 2 . Twenty patients (19.1%) developed surgical site infections. Age greater than 40 years, AOR = 7.7(95% CI [1.610-40.810 p = 0.016,]), preoperative hospital stay more than 7 days, AOR = 22.4(95% CI [4.544-110.780, p = 0.001]), duration of operation more than 1 hour, AOR = 8.01(95% CI [1.562-41.099, p = 0.013]) and administering antimicrobial prophylaxis before 1 hour of operation, AOR = 11.1 (95% CI [1.269-75.639, p = 0.014]) were independent predictors for surgical site infections. Surgical site infection is relatively high.

Predictors of myocardial injury in patients with acute upper gastrointestinal bleeding

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El-Sayed M Farag

2014-03-01

The most significant predictors for myocardial injury in patients with UGIB in descending order were hypertension, cigarette smoking, liver cirrhosis, body mass index > 25 kg/m2, and C-reactive protein level  > 5 mg/dl.

Pulmonary retransplantation : Predictors of graft function and survival in 230 patients

NARCIS (Netherlands)

Novick, RJ; Stitt, LW; Al-Kattan, K; Klepetko, W; Schafers, HJ; Duchatelle, JP; Khaghani, A; Hardesty, RL; Patterson, GA; Yacoub, MH

Background. Despite improving results in lung transplantation, a significant number of grafts fail early or late postoperatively. The pulmonary retransplant registry was founded in 1991 to determine the predictors of outcome after retransplantation. We hypothesized that ambulatory status of the

Newcomers to Social Categories: Longitudinal Predictors and Consequences of Ingroup Identification

NARCIS (Netherlands)

van Veelen, R.; Eisenbeiss, Kerstin; Otten, Sabine

In the present article, we propose a dynamic model of the longitudinal predictors and consequences of ingroup identification among newcomers to a social category. We hypothesize a shift in the relative importance of intragroup affiliation as compared with intergroup differentiation for ingroup

Newcomers to social categories : Longitudinal predictors and consequences of ingroup identification

NARCIS (Netherlands)

van Veelen, Ruth; Eisenbeiss, Kerstin Karen; Otten, Sabine

In the present article, we propose a dynamic model of the longitudinal predictors and consequences of ingroup identification among newcomers to a social category. We hypothesize a shift in the relative importance of intragroup affiliation as compared with intergroup differentiation for ingroup

Locus of Control, Self-Efficacy, and Task Value as Predictors of Learning Outcome in an Online University Context

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Joo, Young Ju; Lim, Kyu Yon; Kim, Jiyeon

2013-01-01

This study investigates the predictors of learner satisfaction, achievement and persistence in an online university located in South Korea. The specific predictors were learners' locus of control, self-efficacy, and task value, and the mediating effects of learner satisfaction and achievement were also tested. Structural equation modeling (SEM)…

Predictors of early arrival at the emergency department in acute ischaemic stroke.

LENUS (Irish Health Repository)

Curran, C

2012-01-31

BACKGROUND: A requirement of an effective acute stroke service is the early arrival of patients to the hospital emergency department (ED). This will allow the possible use of thrombolytic therapy or other acute interventions within a limited time window. AIMS: We investigated the predictors of early arrival in a single hospital serving a mixed urban and rural catchment area. METHODS: A retrospective review of all case notes for 1 year was performed. RESULTS: Of 105 acute strokes, 91 were cerebral infarcts and a total of 71 cases presenting initially to the ED had timing available for analysis. 39.4% presented within 3 h, and 12.7% were potentially suitable for thrombolysis. Those living closer to the hospital were not more likely to arrive within 3 h (Z = -0.411, p = 0.68). Presenting directly to the hospital by emergency services (or private transport) was significantly associated with early arrival in a univariate comparison (p < 0.001), and in a multivariate model. CONCLUSION: The only independent predictor of early arrival to the ED is direct presentation. Improved public education of the importance of recognition of stroke symptoms and rapid contact with the emergency services will improve the early attendance following acute stroke, allowing increased use of acute stroke treatments.

Assessing university students' sexual risk behaviors as predictors of human papillomavirus (HPV) vaccine uptake behavior.

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Rohde, Rebecca L; Adjei Boakye, Eric; Christopher, Kara M; Geneus, Christian J; Walker, Ronald J; Varvares, Mark A; Osazuwa-Peters, Nosayaba

2018-05-09

There exists a significant gap in vaccine coverage of the human papillomavirus (HPV) among college-aged students. This study assessed sexual risk-taking behavior among university students and analyzed predictors of HPV vaccine initiation and completion in this population. Data (n = 746) were from an anonymous online, cross-sectional survey distributed to university students, between the ages of 19-26 years, at a private Midwestern university. Both chi-square and multivariable logistics regression models estimated the association between sociodemographic characteristics and sexual risk factors (including number of vaginal sexual partners, number of oral sexual partners, initiation of oral sex, and initiation of vaginal sex), with HPV vaccine initiation and completion. A significant number of participants (40%) had not received a single dose of the HPV vaccine series. Of those who initiated the series, more than half (51%) did not achieve completion. Additionally, a greater number of participants have had multiple (4 or more) oral sexual partners than vaginal sexual partners (25.7% vs. 20.3%). After adjusting for covariates, it was found that sexual risk factors were not significantly associated with HPV vaccine initiation or completion. HPV vaccine initiation and completion rates are suboptimal among university students. High levels of sexual-risk taking behaviors associated with HPV infection persist, yet are not significant predictors of HPV vaccine behaviors in this age group. To increase uptake among 18-26-year-old students, future public health interventions should focus on HPV vaccine education and uptake across the entire population, irrespective of sexual risk profile. Copyright © 2018 Elsevier Ltd. All rights reserved.

Bayesian Subset Modeling for High-Dimensional Generalized Linear Models

KAUST Repository

Liang, Faming

2013-06-01

This article presents a new prior setting for high-dimensional generalized linear models, which leads to a Bayesian subset regression (BSR) with the maximum a posteriori model approximately equivalent to the minimum extended Bayesian information criterion model. The consistency of the resulting posterior is established under mild conditions. Further, a variable screening procedure is proposed based on the marginal inclusion probability, which shares the same properties of sure screening and consistency with the existing sure independence screening (SIS) and iterative sure independence screening (ISIS) procedures. However, since the proposed procedure makes use of joint information from all predictors, it generally outperforms SIS and ISIS in real applications. This article also makes extensive comparisons of BSR with the popular penalized likelihood methods, including Lasso, elastic net, SIS, and ISIS. The numerical results indicate that BSR can generally outperform the penalized likelihood methods. The models selected by BSR tend to be sparser and, more importantly, of higher prediction ability. In addition, the performance of the penalized likelihood methods tends to deteriorate as the number of predictors increases, while this is not significant for BSR. Supplementary materials for this article are available online. © 2013 American Statistical Association.

Predictors of nurse manager stress: a dominance analysis of potential work environment stressors.

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Kath, Lisa M; Stichler, Jaynelle F; Ehrhart, Mark G; Sievers, Andree

2013-11-01

Nurse managers have important but stressful jobs. Clinical or bedside nurse predictors of stress have been studied more frequently, but less has been done on work environment predictors for those in this first-line leadership role. Understanding the relative importance of those work environment predictors could be used to help identify the most fruitful areas for intervention, potentially improving recruitment and retention for nurse managers. Using Role Stress Theory and the Job Demands-Resources Theory, a model was tested examining the relative importance of five potential predictors of nurse manager stress (i.e., stressors). The work environment stressors included role ambiguity, role overload, role conflict, organizational constraints, and interpersonal conflict. A quantitative, cross-sectional survey study was conducted with a convenience sample of 36 hospitals in the Southwestern United States. All nurse managers working in these 36 hospitals were invited to participate. Of the 636 nurse managers invited, 480 responded, for a response rate of 75.5%. Questionnaires were distributed during nursing leadership meetings and were returned in person (in sealed envelopes) or by mail. Because work environment stressors were correlated, dominance analysis was conducted to examine which stressors were the most important predictors of nurse manager stress. Role overload was the most important predictor of stress, with an average of 13% increase in variance explained. The second- and third-most important predictors were organizational constraints and role conflict, with an average of 7% and 6% increase in variance explained, respectively. Because other research has shown deleterious effects of nurse manager stress, organizational leaders are encouraged to help nurse managers reduce their actual and/or perceived role overload and organizational constraints. Copyright © 2013 Elsevier Ltd. All rights reserved.

The predictors of absenteeism due to psychological disability: a longitudinal study in the education sector.

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Negrini, Alessia; Perron, Jacques; Corbière, Marc

2014-01-01

Being absent from work because of a psychological disability is costly for both individuals and organizations and frequent in employees working in the field of education. Absenteeism from work has been mostly studied as an organizational withdrawal behavior related to negative factors. The purpose of this longitudinal study is to define the predictors of absenteeism due to psychological disability by taking into account resources, such as Self-determined work motivation and Subjective well-being, as well as symptoms of Psychological distress. The sample consisted of 261 employees from a Canadian public school organization. Independent sample t-tests were conducted to compare the mean scores of participants who were not absent from work and participants who were absent due to psychological disability. Logistic regression analyses were computed for the dependent variable to assess the contribution of the three independent variables. Participants who were absent from work due to psychological disability in the year following the data collection scored significantly lower on resources, and higher on symptoms than those participants who were not absent. The three-predictor model was found to be significant. However, only Self-determined work motivation and Psychological distress significantly predicted absenteeism due to psychological disability. Results are discussed in terms of psychological processes regulating the relationships between the work-related factors (i.e., work motivation) and life-related factors (i.e., psychological distress and subjective well-being) of personal adjustment and accomplishment.

Predictors of outcomes in outpatients with anorexia nervosa - Results from the ANTOP study.

Science.gov (United States)

Wild, Beate; Friederich, Hans-Christoph; Zipfel, Stephan; Resmark, Gaby; Giel, Katrin; Teufel, Martin; Schellberg, Dieter; Löwe, Bernd; de Zwaan, Martina; Zeeck, Almut; Herpertz, Stephan; Burgmer, Markus; von Wietersheim, Jörn; Tagay, Sefik; Dinkel, Andreas; Herzog, Wolfgang

2016-10-30

This study aimed to determine predictors of BMI and recovery for outpatients with anorexia nervosa (AN). Patients were participants of the ANTOP (Anorexia Nervosa Treatment of Out-Patients) trial and randomized to focal psychodynamic therapy (FPT), enhanced cognitive behavior therapy (CBT-E), or optimized treatment as usual (TAU-O). N=169 patients participated in the one-year follow-up (T4). Outcomes were the BMI and global outcome (recovery/partial syndrome/full syndrome) at T4. We examined the following baseline variables as possible predictors: age, BMI, duration of illness, subtype of AN, various axis I diagnoses, quality of life, self-esteem, and psychological characteristics relevant to AN. Linear and logistic regression analyses were conducted to identify the predictors of the BMI and global outcome. The strongest positive predictor for BMI and recovery at T4 was a higher baseline BMI of the patients. Negative predictors for BMI and recovery were a duration of illness >6 years and a lifetime depression diagnosis at baseline. Additionally, higher bodily pain was significantly associated with a lower BMI and self-esteem was a positive predictor for recovery at T4. A higher baseline BMI and shorter illness duration led to a better outcome. Further research is necessary to investigate whether or not AN patients with lifetime depression, higher bodily pain, and lower self-esteem may benefit from specific treatment approaches. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Longitudinal predictors of colorectal cancer screening among participants in a randomized controlled trial.

Science.gov (United States)

Murphy, Caitlin C; Vernon, Sally W; Haddock, Nicole M; Anderson, Melissa L; Chubak, Jessica; Green, Beverly B

2014-09-01

Few studies use longitudinal data to identify predictors of colorectal cancer screening (CRCS). We examined predictors of (1) initial CRCS during the first year of a randomized trial, and (2) repeat CRCS during the second year of the trial among those that completed FOBT in Year 1. The sample comprised 1247 participants of the Systems of Support to Increase Colorectal Cancer Screening (SOS) Trial (Group Health Cooperative, August 2008 to November 2011). Potential predictors of CRCS were identified with logistic regression and included sociodemographics, health history, and validated scales of psychosocial constructs. Prior CRCS (OR 2.64, 95% CI 1.99-3.52) and intervention group (Automated: OR 2.06 95% CI 1.43-2.95; Assisted: OR 4.03, 95% CI 2.69-6.03; Navigated: OR 5.64, 95% CI 3.74-8.49) were predictors of CRCS completion at Year 1. For repeat CRCS at Year 2, prior CRCS at baseline (OR 1.97, 95% CI 1.25-3.11), intervention group (Automated: OR 9.27, 95% CI 4.56-18.82; Assisted: OR 11.17, 95% CI 5.44-22.94; Navigated: OR 13.10, 95% CI 6.33-27.08), and self-efficacy (OR 1.32, 95% CI 1.00-1.73) were significant predictors. Self-efficacy and prior CRCS are important predictors of future screening behavior. CRCS completion increased when access barriers were removed through interventions. Copyright © 2014 Elsevier Inc. All rights reserved.

Distal and proximal predictors of snacking at work: A daily-survey study.

Science.gov (United States)

Sonnentag, Sabine; Pundt, Alexander; Venz, Laura

2017-02-01

This study aimed at examining predictors of healthy and unhealthy snacking at work. As proximal predictors we looked at food-choice motives (health motive, affect-regulation motive); as distal predictors we included organizational eating climate, emotional eating, and self-control demands at work. We collected daily survey data from 247 employees, over a period of 2 workweeks. Multilevel structural equation modeling showed that organizational eating climate predicted health as food-choice motive, whereas emotional eating and self-control demands predicted affect regulation as food-choice motive. The health motive, in turn, predicted consuming more fruits and more cereal bars and less sweet snacks; the affect-regulation motive predicted consuming more sweet snacks. Findings highlight the importance of a health-promoting eating climate within the organization and point to the potential harm of high self-control demands at work. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

DRREP: deep ridge regressed epitope predictor.

Science.gov (United States)

Sher, Gene; Zhi, Degui; Zhang, Shaojie

2017-10-03

The ability to predict epitopes plays an enormous role in vaccine development in terms of our ability to zero in on where to do a more thorough in-vivo analysis of the protein in question. Though for the past decade there have been numerous advancements and improvements in epitope prediction, on average the best benchmark prediction accuracies are still only around 60%. New machine learning algorithms have arisen within the domain of deep learning, text mining, and convolutional networks. This paper presents a novel analytically trained and string kernel using deep neural network, which is tailored for continuous epitope prediction, called: Deep Ridge Regressed Epitope Predictor (DRREP). DRREP was tested on long protein sequences from the following datasets: SARS, Pellequer, HIV, AntiJen, and SEQ194. DRREP was compared to numerous state of the art epitope predictors, including the most recently published predictors called LBtope and DMNLBE. Using area under ROC curve (AUC), DRREP achieved a performance improvement over the best performing predictors on SARS (13.7%), HIV (8.9%), Pellequer (1.5%), and SEQ194 (3.1%), with its performance being matched only on the AntiJen dataset, by the LBtope predictor, where both DRREP and LBtope achieved an AUC of 0.702. DRREP is an analytically trained deep neural network, thus capable of learning in a single step through regression. By combining the features of deep learning, string kernels, and convolutional networks, the system is able to perform residue-by-residue prediction of continues epitopes with higher accuracy than the current state of the art predictors.

[Predictors of nurses' professional burnout: a study in a university hospital].

Science.gov (United States)

Stordeur, S; Vandenberghe, C; D'hoore, W

1999-12-01

This study was designed to examine the level of burnout and to identify stressor among nurses in a teaching hospital. Based on a sample of 625 nurses, results show that burnout levels are moderate (M. = 24.3, SD = 9.3) and comparable to those observed in physicians (M. = 26.6, SD = 9.8) and in the administrative staff of the same hospital (M. = 25.1, SD = 11.9). Multiple regression analyses selected 11 predictors significantly associated with burnout. Some contributed positively to burnout (job strain, lack of social support, conflicts with other nurses, conflicts with physicians, presence of stressors related to private life, feeling that the job is threatened, full-time vs. part-time status), whereas others contributed negatively (perceived job control, hierarchical level, death and dying of patients, feeling protected against occupational hazards). It is worthy of noting that leadership dimensions were not significantly related to burnout, once stressors were included in the regression model. We also tested Karasek's (1979) model, according to which job demands interact with perceived job control in influencing burnout. For example, the worst situation is one in which job demands are high and perceived control is low. This is defined as a high-strain job. The results from this study confirm that perceived control reduces the effect of job strain on burnout. This suggests that if job strain is high, managers can reduce its effect by providing nurses with opportunities to control their work environment and relations with patients. Results also demonstrate that burnout is negatively correlated with job satisfaction and perceived unit effectiveness. Managers should invest in prevention programs, since burnout is as deleterious to individuals as to the organization. A limitation of this study is its focus on emotional exhaustion which is known to be the first step of the burnout process. Future research should examine whether the predictors identified here would also

Predictors of Exceptional Longevity: Effects of Early-Life and Midlife Conditions, and Familial Longevity.

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Gavrilov, Leonid A; Gavrilova, Natalia S

Knowledge of strong predictors of mortality and longevity is very important for actuarial science and practice. Earlier studies found that parental characteristics as well as early-life conditions and midlife environment play a significant role in survival to advanced ages. However, little is known about the simultaneous effects of these three factors on longevity. This ongoing study attempts to fill this gap by comparing centenarians born in the United States in 1890-1891 with peers born in the same years who died at age 65. The records for centenarians and controls were taken from computerized family histories, which were then linked to 1900 and 1930 U.S. censuses. As a result of this linkage procedure, 765 records of confirmed centenarians and 783 records of controls were obtained. Analysis with multivariate logistic regression found the existence of both general and gender-specific predictors of human longevity. General predictors common for men and women are paternal and maternal longevity. Gender-specific predictors of male longevity are occupation as a farmer at age 40, Northeastern region of birth in the United States, and birth in the second half of year. A gender-specific predictor of female longevity is the availability of radio in the household according to the 1930 U.S. census. Given the importance of familial longevity as an independent predictor of survival to advanced ages, we conducted a comparative study of biological and nonbiological relatives of centenarians using a larger sample of 1,945 validated U.S. centenarians born in 1880-1895. We found that male gender of centenarian has a significant positive effect on survival of adult male relatives (brothers and fathers) but not female blood relatives. Life span of centenarian siblings-in-law is lower compared to life span of centenarian siblings and does not depend on centenarian gender. Wives of male centenarians (who share lifestyle and living conditions) have a significantly better survival

Predictors of Sensitivity in Mothers of 8-Month-Old Infants

Directory of Open Access Journals (Sweden)

Patricia Alvarenga

2013-09-01

Full Text Available This longitudinal study investigated the impact of maternal mental health, including postpartum depression, and of maternal-fetal attachment, on maternal sensitivity when babies were eight months old. The study included 38 mother-infant dyads. The women answered the SRQ-20 and the Maternal-Fetal Attachment Scale in the third trimester of pregnancy, and the BDI, for evaluation of postpartum depression in the first month following birth. Maternal sensitivity was examined through an observation of mother-child interaction when babies were eight months old. The multiple regression model considering the three factors explained 18.6% of the variance in sensitivity, and only maternal-fetal attachment was a significant predictor. The results indicate the importance of interventions to promote the bond of pregnant women with their babies, which may even minimize possible harmful effects of postpartum depression on mother-child interaction.

Clinical Predictors of Response to Cognitive-Behavioral Therapy in Pediatric Anxiety Disorders: The Genes for Treatment (GxT) Study.

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Hudson, Jennifer L; Keers, Robert; Roberts, Susanna; Coleman, Jonathan R I; Breen, Gerome; Arendt, Kristian; Bögels, Susan; Cooper, Peter; Creswell, Cathy; Hartman, Catharina; Heiervang, Einar R; Hötzel, Katrin; In-Albon, Tina; Lavallee, Kristen; Lyneham, Heidi J; Marin, Carla E; McKinnon, Anna; Meiser-Stedman, Richard; Morris, Talia; Nauta, Maaike; Rapee, Ronald M; Schneider, Silvia; Schneider, Sophie C; Silverman, Wendy K; Thastum, Mikael; Thirlwall, Kerstin; Waite, Polly; Wergeland, Gro Janne; Lester, Kathryn J; Eley, Thalia C

2015-06-01

The Genes for Treatment study is an international, multisite collaboration exploring the role of genetic, demographic, and clinical predictors in response to cognitive-behavioral therapy (CBT) in pediatric anxiety disorders. The current article, the first from the study, examined demographic and clinical predictors of response to CBT. We hypothesized that the child's gender, type of anxiety disorder, initial severity and comorbidity, and parents' psychopathology would significantly predict outcome. A sample of 1,519 children 5 to 18 years of age with a primary anxiety diagnosis received CBT across 11 sites. Outcome was defined as response (change in diagnostic severity) and remission (absence of the primary diagnosis) at each time point (posttreatment, 3-, 6-, and/or 12-month follow-up) and analyzed using linear and logistic mixed models. Separate analyses were conducted using data from posttreatment and follow-up assessments to explore the relative importance of predictors at these time points. Individuals with social anxiety disorder (SoAD) had significantly poorer outcomes (poorer response and lower rates of remission) than those with generalized anxiety disorder (GAD). Although individuals with specific phobia (SP) also had poorer outcomes than those with GAD at posttreatment, these differences were not maintained at follow-up. Both comorbid mood and externalizing disorders significantly predicted poorer outcomes at posttreatment and follow-up, whereas self-reported parental psychopathology had little effect on posttreatment outcomes but significantly predicted response (although not remission) at follow-up. SoAD, nonanxiety comorbidity, and parental psychopathology were associated with poorer outcomes after CBT. The results highlight the need for enhanced treatments for children at risk for poorer outcomes. Copyright © 2015 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Plant Water Content is the Best Predictor of Drought-induced Mortality

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Sapes, G.; Roskilly, B.; Dobrowski, S.; Sala, A.

2017-12-01

Predicting drought-induced forest mortality remains extremely challenging. Recent research has shown that both plant hydraulics and stored non-structural carbohydrates (NSC) interact during drought-induced mortality. The strong interaction between these two variables and the fact that they are both difficult to measure render drought-induced plant mortality extremely difficult to monitor and predict. A variable that is easier to measure and that integrates hydraulic transport and carbohydrate dynamics may, therefore, improve our ability to monitor and predict mortality. Here, we tested whether plant water content is such an integrator variable and, therefore, a better predictor of mortality under drought. We subjected 250 two-year-old ponderosa pine seedlings to drought until they died in a greenhouse experiment. Periodically during the dry down, we measured percent loss of hydraulic conductivity (PLC), NSC concentration (starch and soluble sugars), and tissue volumetric water content (VWC) in roots, stems and leaves. At each measurement time, a separate set of seedlings were re-watered to estimate the probability of mortality at the population level. Linear models were used to explore whether PLC and NSC were linked to VWC and to determine which of the three variables predicted mortality the best. As expected, plants lost hydraulic conductivity in stems and roots during the dry down. Starch concentrations also decreased in all organs as the drought proceeded. In contrast, soluble sugars increased in stems and roots, consistent with the conversion of stored NSCs into osmotically active compounds. Models containing both PLC and NSC concentrations as predictors of VWC were highly significant in all organs and at the whole plant level, indicating that water content is influenced by both PLC and NSCs. PLC, NSC, and VWC explained mortality across organs and at the whole plant level, but VWC was the best predictor (R2 = 0.99). Our results indicate that plant water

Significant uncertainty in global scale hydrological modeling from precipitation data erros

NARCIS (Netherlands)

Sperna Weiland, F.; Vrugt, J.A.; Beek, van P.H.; Weerts, A.H.; Bierkens, M.F.P.

2015-01-01

In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we

Significant uncertainty in global scale hydrological modeling from precipitation data errors

NARCIS (Netherlands)

Weiland, Frederiek C. Sperna; Vrugt, Jasper A.; van Beek, Rens (L. ) P. H.; Weerts, Albrecht H.; Bierkens, Marc F. P.

2015-01-01

In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we

Predictors of comorbid personality disorders in patients with panic disorder with agoraphobia.

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Latas, M; Starcevic, V; Trajkovic, G; Bogojevic, G

2000-01-01

The aim of this study was to ascertain predictors of comorbid personality disorders in patients with panic disorder with agoraphobia (PDAG). Sixty consecutive outpatients with PDAG were administered the Structured Clinical Interview for DSM-IV Axis II Personality Disorders (SCID-II) for the purpose of diagnosing personality disorders. Logistic regressions were used to identify predictors of any comorbid personality disorder, any DSM-IV cluster A, cluster B, and cluster C personality disorder. Independent variables in these regressions were gender, age, duration of panic disorder (PD), severity of PDAG, and scores on self-report instruments that assess the patient's perception of their parents, childhood separation anxiety, and traumatic experiences. High levels of parental protection on the Parental Bonding Instrument (PBI), indicating a perception of the parents as overprotective and controlling, emerged as the only statistically significant predictor of any comorbid personality disorder. This finding was attributed to the association between parental overprotection and cluster B personality disorders, particularly borderline personality disorder. The duration of PD was a significant predictor of any cluster B and any cluster C personality disorder, suggesting that some of the cluster B and cluster C personality disorders may be a consequence of the long-lasting PDAG. Any cluster B personality disorder was also associated with younger age. In conclusion, despite a generally nonspecific nature of the relationship between parental overprotection in childhood and adult psychopathology, the findings of this study suggest some specificity for the association between parental overprotection in childhood and personality disturbance in PDAG patients, particularly cluster B personality disorders.

PPM-One: a static protein structure based chemical shift predictor

International Nuclear Information System (INIS)

Li, Dawei; Brüschweiler, Rafael

2015-01-01

We mined the most recent editions of the BioMagResDataBank and the protein data bank to parametrize a new empirical knowledge-based chemical shift predictor of protein backbone atoms using either a linear or an artificial neural network model. The resulting chemical shift predictor PPM-One accepts a single static 3D structure as input and emulates the effect of local protein dynamics via interatomic steric contacts. Furthermore, the chemical shift prediction was extended to most side-chain protons and it is found that the prediction accuracy is at a level allowing an independent assessment of stereospecific assignments. For a previously established set of test proteins some overall improvement was achieved over current top-performing chemical shift prediction programs