The double-edged sword of genetic accounts of criminality: causal attributions from genetic ascriptions affect legal decision making.

Science.gov (United States)

Cheung, Benjamin Y; Heine, Steven J

2015-12-01

Much debate exists surrounding the applicability of genetic information in the courtroom, making the psychological processes underlying how people consider this information important to explore. This article addresses how people think about different kinds of causal explanations in legal decision-making contexts. Three studies involving a total of 600 Mechanical Turk and university participants found that genetic, versus environmental, explanations of criminal behavior lead people to view the applicability of various defense claims differently, perceive the perpetrator's mental state differently, and draw different causal attributions. Moreover, mediation and path analyses highlight the double-edged nature of genetic attributions-they simultaneously reduce people's perception of the perpetrator's sense of control while increasing people's tendencies to attribute the cause to internal factors and to expect the perpetrator to reoffend. These countervailing relations, in turn, predict sentencing in opposite directions, although no overall differences in sentencing or ultimate verdicts were found. © 2015 by the Society for Personality and Social Psychology, Inc.

The genomic era and serious mental illness: a potential application for psychiatric genetic counseling.

Science.gov (United States)

Austin, Jehannine C; Honer, William G

2007-02-01

Genetic counseling is an important clinical service that is routinely offered to families affected by genetic disorders or by complex disorders for which genetic testing is available. It is not yet routinely offered to individuals with serious mental illnesses and their families, but recent findings that beliefs about the cause of mental illness can affect an individual's adaptation to the illness suggest that genetic counseling may be a useful intervention for this population. In a genetic counseling session the counselor discusses genetic and environmental contributors to disease pathogenesis; helps individuals explore conceptions, fears, and adaptive strategies; and provides nondirective support for decision making. Expected outcomes may include reductions in fear, stigma, and guilt associated with a psychiatric diagnosis; improvements in adherence to prescribed medications; declines in risk behaviors; and reductions in misconceptions about the illness. The authors endorse a multidisciplinary approach in which a psychiatrist and genetic counselor collaborate to provide comprehensive psychiatric genetic counseling.

Genetic causal beliefs about obesity, self-efficacy for weight control, and obesity-related behaviours in a middle-aged female cohort.

Science.gov (United States)

Knerr, Sarah; Bowen, Deborah J; Beresford, Shirley A A; Wang, Catharine

2016-01-01

Obesity is a heritable condition with well-established risk-reducing behaviours. Studies have shown that beliefs about the causes of obesity are associated with diet and exercise behaviour. Identifying mechanisms linking causal beliefs and behaviours is important for obesity prevention and control. Cross-sectional multi-level regression analyses of self-efficacy for weight control as a possible mediator of obesity attributions (diet, physical activity, genetic) and preventive behaviours in 487 non-Hispanic White women from South King County, Washington. Self-reported daily fruit and vegetable intake and weekly leisure-time physical activity. Diet causal beliefs were positively associated with fruit and vegetable intake, with self-efficacy for weight control partially accounting for this association. Self-efficacy for weight control also indirectly linked physical activity attributions and physical activity behaviour. Relationships between genetic causal beliefs, self-efficacy for weight control, and obesity-related behaviours differed by obesity status. Self-efficacy for weight control contributed to negative associations between genetic causal attributions and obesity-related behaviours in non-obese, but not obese, women. Self-efficacy is an important construct to include in studies of genetic causal beliefs and behavioural self-regulation. Theoretical and longitudinal work is needed to clarify the causal nature of these relationships and other mediating and moderating factors.

Images of illness: how causal claims and racial associations influence public preferences toward diabetes research spending.

Science.gov (United States)

Gollust, Sarah E; Lantz, Paula M; Ubel, Peter A

2010-12-01

Despite the salience of health disparities in media and policy discourse, little previous research has investigated if imagery associating an illness with a certain racial group influences public perceptions. This study evaluated the influence of the media's presentation of the causes of type 2 diabetes and its implicit racial associations on attitudes toward people with diabetes and preferences toward research spending. Survey participants who viewed an article on genetic causation or social determinants of diabetes were more likely to support increased government spending on research than those viewing an article with no causal language, while participants viewing an article on behavioral choices were more likely to attribute negative stereotypes to people with diabetes. Participants who viewed a photo of a black woman accompanying the article were less likely to endorse negative stereotypes than those viewing a photo of a white woman, but those who viewed a photo of a glucose-testing device expressed the lowest negative stereotypes. The effect of social determinants language was significantly different for blacks and whites, lowering stereotypes only among blacks. Emphasizing the behavioral causes of diabetes, as is common in media coverage, may perpetuate negative stereotypes. While drawing attention to the social determinants that shape these behaviors could mitigate stereotypes, this strategy is unlikely to influence the public uniformly.

Genetic evidence for causal relationships between maternal obesity-related traits and birth weight

NARCIS (Netherlands)

A.W.R. Tyrrell; R.C. Richmond (Rebecca C.); T.M. Palmer (Tom); B. Feenstra (Bjarke); J. Rangarajan (Janani); S. Metrustry (Sarah); A. Cavadino (Alana); L. Paternoster (Lavinia); L.L. Armstrong (Loren L.); N.M.G. De Silva (N. Maneka G.); A.R. Wood (Andrew); M. Horikoshi (Momoko); F. Geller (Frank); R. Myhre (Ronny); J.P. Bradfield (Jonathan); E. Kreiner-Møller (Eskil); I. Huikari (Ille); J.N. Painter (Jodie N.); J.J. Hottenga (Jouke Jan); C. Allard (Catherine); D. Berry (Diane); L. Bouchard (Luigi); S. Das (Shikta); D.M. Evans (David); H. Hakonarson (Hakon); M.G. Hayes (M. Geoffrey); J. Heikkinen (Jani); A. Hofman (Albert); B.A. Knight (Bridget); P.A. Lind (Penelope); M.I. McCarthy (Mark); G. Mcmahon (George); S.E. Medland (Sarah Elizabeth); M. Melbye (Mads); A.P. Morris (Andrew); M. Nodzenski (Michael); C. Reichetzeder (Christoph); S.M. Ring (Susan); S. Sebert (Sylvain); V. Sengpiel (Verena); T.I.A. Sørensen (Thorkild); G.A.H.M. Willemsen (Gonneke); E.J.C. de Geus (Eco); N.G. Martin (Nicholas); T.D. Spector (Timothy); C. Power (Christine); M.-R. Jarvelin (Marjo-Riitta); H. Bisgaard (Hans); S.F.A. Grant (Struan); C. Nohr (Christian); V.W.V. Jaddoe (Vincent); B. Jacobsson (Bo); J.C. Murray (Jeffrey C.); B. Hocher (Berthold); A.T. Hattersley (Andrew); D.M. Scholtens (Denise M.); G.D. Smith; M.-F. Hivert (Marie-France); J.F. Felix (Janine); E. Hypponen (Elina); W.L. Lowe Jr. (William); T.M. Frayling (Timothy); D.A. Lawlor (Debbie); R.M. Freathy (Rachel)

2016-01-01

textabstractIMPORTANCE Neonates born to overweight or obese women are larger and at higher risk of birth complications. Many maternal obesity-related traits are observationally associated with birth weight, but the causal nature of these associations is uncertain. OBJECTIVE To test for genetic

Bayesian methods for meta-analysis of causal relationships estimated using genetic instrumental variables

DEFF Research Database (Denmark)

Burgess, Stephen; Thompson, Simon G; Thompson, Grahame

2010-01-01

Genetic markers can be used as instrumental variables, in an analogous way to randomization in a clinical trial, to estimate the causal relationship between a phenotype and an outcome variable. Our purpose is to extend the existing methods for such Mendelian randomization studies to the context o...

IQ and schizophrenia in a Swedish national sample: their causal relationship and the interaction of IQ with genetic risk.

Science.gov (United States)

Kendler, Kenneth S; Ohlsson, Henrik; Sundquist, Jan; Sundquist, Kristina

2015-03-01

The authors sought to clarify the relationship between IQ and subsequent risk for schizophrenia. IQ was assessed at ages 18-20 in 1,204,983 Swedish males born between 1951 and 1975. Schizophrenia was assessed by hospital diagnosis through 2010. Cox proportional hazards models were used to investigate future risk for schizophrenia in individuals as a function of their IQ score, and then stratified models using pairs of relatives were used to adjust for familial cluster. Finally, regression models were used to examine the interaction between IQ and genetic liability on risk for schizophrenia. IQ had a monotonic relationship with schizophrenia risk across the IQ range, with a mean increase in risk of 3.8% per 1-point decrease in IQ; this association was stronger in the lower than the higher IQ range. Co-relative control analyses showed a similar association between IQ and schizophrenia in the general population and in cousin, half-sibling, and full-sibling pairs. A robust interaction was seen between genetic liability to schizophrenia and IQ in predicting schizophrenia risk. Genetic susceptibility for schizophrenia had a much stronger impact on risk of illness for those with low than high intelligence. The IQ-genetic liability interaction arose largely from IQ differences between close relatives. IQ assessed in late adolescence is a robust risk factor for subsequent onset of schizophrenia. This association is not the result of a declining IQ associated with insidious onset. In this large, representative sample, we found no evidence for a link between genius and schizophrenia. Co-relative control analyses showed that the association between lower IQ and schizophrenia is not the result of shared familial risk factors and may be causal. The strongest effect was seen with IQ differences within families. High intelligence substantially attenuates the impact of genetic liability on the risk for schizophrenia.

Rhinovirus Wheezing Illness and Genetic Risk of Childhood-Onset Asthma

DEFF Research Database (Denmark)

Calışkan, Minal; Bochkov, Yury A; Kreiner-Møller, Eskil

2013-01-01

Background Both genetic variation at the 17q21 locus and virus-induced respiratory wheezing illnesses are associated with the development of asthma. Our aim was to determine the effects of these two factors on the risk of asthma in the Childhood Origins of Asthma (COAST) and the Copenhagen...... Prospective Study on Asthma in Childhood (COPSAC) birth cohorts. Methods We tested genotypes at the 17q21 locus for associations with asthma and with human rhinovirus (HRV) and respiratory syncytial virus (RSV) wheezing illnesses and tested for interactions between 17q21 genotypes and HRV and RSV wheezing...... illnesses with respect to the risk of asthma. Finally, we examined genotype-specific expression of 17q21 genes in unstimulated and HRV-stimulated peripheral-blood mononuclear cells (PBMCs). Results The 17q21 variants were associated with HRV wheezing illnesses in early life, but not with RSV wheezing...

Is an Early Age at Illness Onset in Schizophrenia Associated With Increased Genetic Susceptibility?

DEFF Research Database (Denmark)

Hilker, Rikke; Helenius, Dorte; Fagerlund, Birgitte

2017-01-01

with schizophrenia spectrum) and a subsample of N = 448 (affected with schizophrenia). Survival analysis was applied to investigate the effect of age at illness onset. Findings We found that early age at illness onset compared to later onset in the first diagnosed twin can be considered a major risk factor......Background Early age at illness onset has been viewed as an important liability marker for schizophrenia, which may be associated with an increased genetic vulnerability. A twin approach can be valuable, because it allows for the investigation of specific illness markers in individuals...... with a shared genetic background. Methods We linked nationwide registers to identify a cohort of twin pairs born in Denmark from 1951 to 2000 (N = 31,524 pairs), where one or both twins had a diagnosis in the schizophrenia spectrum. We defined two groups consisting of; N = 788 twin pairs (affected...

Causal Attributions about Disease-Onset and Relapse in Patients with Systemic Vasculitis

Science.gov (United States)

Grayson, Peter C.; Amudala, Naomi A.; McAlear, Carol A.; Leduc, Renée L.; Shereff, Denise; Richesson, Rachel; Fraenkel, Liana; Merkel, Peter A.

2014-01-01

Objectives Patients vary in their beliefs related to the cause of serious illness. The impact of these beliefs among patients with systemic vasculitis is not known. This study aimed to describe causal attributions about disease-onset and relapse in systemic vasculitis and to examine whether causal beliefs a) differ by type of vasculitis; and b) are associated with negative health outcomes. Methods Patients with vasculitis were recruited to complete an online questionnaire. Categories of causal beliefs were assessed with the Revised Illness Perception Questionnaire (IPQ-R). Differences in beliefs about disease-onset versus relapse were compared across different forms of vasculitis. Causal beliefs were assessed in association with several health outcomes including fatigue, functional impairments, and personal understanding of the condition. Results 692 patients representing 9 forms of vasculitis completed the questionnaire. The majority (90%) of patients had beliefs about the cause of their illness. Causal attributions were highly variable, but altered immunity and stress were the most commonly agreed upon causal beliefs. Frequencies of causal beliefs were strikingly similar across different forms of vasculitis, with few notable exceptions primarily in Behçet’s disease. Beliefs differed about causes of disease-onset versus relapse. Specific beliefs about disease-onset and relapse were weakly associated with fatigue, functional impairments, and understanding of the condition. Conclusion Patient beliefs related to the cause of systemic vasculitis are highly variable. Patterns of causal beliefs are associated with important negative health outcomes. Clinicians who care for patients with vasculitis should be mindful of these associations and consider asking about patients’ causal beliefs. PMID:24634202

A putative causal relationship between genetically determined female body shape and posttraumatic stress disorder.

Science.gov (United States)

Polimanti, Renato; Amstadter, Ananda B; Stein, Murray B; Almli, Lynn M; Baker, Dewleen G; Bierut, Laura J; Bradley, Bekh; Farrer, Lindsay A; Johnson, Eric O; King, Anthony; Kranzler, Henry R; Maihofer, Adam X; Rice, John P; Roberts, Andrea L; Saccone, Nancy L; Zhao, Hongyu; Liberzon, Israel; Ressler, Kerry J; Nievergelt, Caroline M; Koenen, Karestan C; Gelernter, Joel

2017-11-27

The nature and underlying mechanisms of the observed increased vulnerability to posttraumatic stress disorder (PTSD) in women are unclear. We investigated the genetic overlap of PTSD with anthropometric traits and reproductive behaviors and functions in women. The analysis was conducted using female-specific summary statistics from large genome-wide association studies (GWAS) and a cohort of 3577 European American women (966 PTSD cases and 2611 trauma-exposed controls). We applied a high-resolution polygenic score approach and Mendelian randomization analysis to investigate genetic correlations and causal relationships. We observed an inverse association of PTSD with genetically determined anthropometric traits related to body shape, independent of body mass index (BMI). The top association was related to BMI-adjusted waist circumference (WC adj ; R = -0.079, P body shape and PTSD, which could be mediated by evolutionary mechanisms involved in human sexual behaviors.

Investigating cognitive transfer within the framework of music practice: genetic pleiotropy rather than causality.

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Mosing, Miriam A; Madison, Guy; Pedersen, Nancy L; Ullén, Fredrik

2016-05-01

The idea of far transfer effects in the cognitive sciences has received much attention in recent years. One domain where far transfer effects have frequently been reported is music education, with the prevailing idea that music practice entails an increase in cognitive ability (IQ). While cross-sectional studies consistently find significant associations between music practice and IQ, randomized controlled trials, however, report mixed results. An alternative to the hypothesis of cognitive transfer effects is that some underlying factors, such as shared genes, influence practice behaviour and IQ causing associations on the phenotypic level. Here we explored the hypothesis of far transfer within the framework of music practice. A co-twin control design combined with classical twin-modelling based on a sample of more than 10,500 twins was used to explore causal associations between music practice and IQ as well as underlying genetic and environmental influences. As expected, phenotypic associations were moderate (r = 0.11 and r = 0.10 for males and females, respectively). However, the relationship disappeared when controlling for genetic and shared environmental influences using the co-twin control method, indicating that a highly practiced twin did not have higher IQ than the untrained co-twin. In line with that finding, the relationship between practice and IQ was mostly due to shared genetic influences. Findings strongly suggest that associations between music practice and IQ in the general population are non-causal in nature. The implications of the present findings for research on plasticity, modularity, and transfer are discussed. © 2015 John Wiley & Sons Ltd.

Psychogenic Explanations of Physical Illness: Time to Examine the Evidence.

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Wilshire, Carolyn E; Ward, Tony

2016-09-01

In some patients with chronic physical complaints, detailed examination fails to reveal a well-recognized underlying disease process. In this situation, the physician may suspect a psychological cause. In this review, we critically evaluated the evidence for this causal claim, focusing on complaints presenting as neurological disorders. There were four main conclusions. First, patients with these complaints frequently exhibit psychopathology but not consistently more often than patients with a comparable "organic" diagnosis, so a causal role cannot be inferred. Second, these patients report a high incidence of adverse life experiences, but again, there is insufficient evidence to indicate a causal role for any particular type of experience. Third, although psychogenic illnesses are believed to be more responsive to psychological interventions than comparable "organic" illnesses, there is currently no evidence to support this claim. Finally, recent evidence suggests that biological and physical factors play a much greater causal role in these illnesses than previously believed. We conclude that there is currently little evidential support for psychogenic theories of illness in the neurological domain. In future research, researchers need to take a wider view concerning the etiology of these illnesses. © The Author(s) 2016.

Genetic Causal Attribution of Epilepsy and its Implications for Felt Stigma

Science.gov (United States)

Sabatello, Maya; Phelan, Jo C.; Hesdorffer, Dale C.; Shostak, Sara; Goldsmith, Jeff; Sorge, Shawn T.; Winawer, Melodie R.; Chung, Wendy K.; Ottman, Ruth

2015-01-01

Summary Objective Research in other disorders suggests that genetic causal attribution of epilepsy might be associated with increased stigma. We investigated this hypothesis in a unique sample of families containing multiple individuals with epilepsy. Methods 181 people with epilepsy and 178 biological relatives without epilepsy completed a self-administered survey. In people with epilepsy, felt stigma was assessed through the Epilepsy Stigma Scale (ESS), scored 1 to 7 with higher scores indicating more stigma and >4 indicating some felt stigma. Felt stigma related to having epilepsy in the family was assessed through the Family Epilepsy Stigma Scale (FESS), created by replacing “epilepsy” with “epilepsy in my family” in each ESS item. Genetic attribution was assessed through participants’ perceptions of the (1) role of genetics in causing epilepsy in the family, (2) chance they had an epilepsy-related mutation, and (3) (in people with epilepsy) influence of genetics in causing their epilepsy. Results Among people with epilepsy, 22% met criteria for felt stigma (ESS score >4). Scores were increased among individuals who were aged ≥60 years, were unemployed, reported epilepsy-related discrimination, or had seizures within the last year or >100 seizures in their lifetime. Adjusting for other variables, ESS scores in people with epilepsy were significantly higher among those who perceived genetics played a “medium” or “big” role in causing epilepsy in the family than in others (3.4 vs. 2.7, p=0.025). Only 4% of relatives without epilepsy had felt stigma. Scores in relatives were unrelated to genetic attribution. Significance In these unusual families, predictors of felt stigma in individuals with epilepsy are similar to those in other studies, and stigma levels are low in relatives without epilepsy. Felt stigma may be increased in people with epilepsy who believe epilepsy in the family has a genetic cause, emphasizing the need for sensitive

Famous people and genetic disorders: from monarchs to geniuses--a portrait of their genetic illnesses.

Science.gov (United States)

Ho, Nicola C; Park, Susan S; Maragh, Kevin D; Gutter, Emily M

2003-04-15

Famous people with genetic disorders have always been a subject of interest because such news feeds the curiosity the public has for celebrities. It gives further insight into their lives and provides a medical basis for any unexplained or idiosyncratic feature or behavior they exhibit. It draws admiration from society of those who excel in their specialized fields despite the impositions of their genetic illnesses and also elicits sympathy even in the most casual observer. Such news certainly catapults a rare genetic disorder into the realm of public awareness. We hereby present six famous figures: King George III, Toulouse-Lautrec, Queen Victoria, Nicolo Paganini, Abraham Lincoln, and Vincent van Gogh, all of whom made a huge indelible mark in either the history of politics or that of the arts. Copyright 2003 Wiley-Liss, Inc.

Molecular genetics in affective illness

Energy Technology Data Exchange (ETDEWEB)

Mendlewicz, J.; Sevy, S.; Mendelbaum, K. (Erasme Univ. Hospital, Brussels (Belgium))

1993-01-01

Genetic transmission in manic depressive illness (MDI) has been explored in twins, adoption, association, and linkage studies. The X-linked transmission hypothesis has been tested by using several markers on chromosome X: Xg blood group, color blindness, glucose-6-phosphate dehydrogenase (G6PD), factor IX (hemophilia B), and DNA probes such as DXS15, DXS52, F8C, ST14. The hypothesis of autosomal transmission has been tested by association studies with the O blood group located on chromosome 9, as well as linkage studies on chromosome 6 with the Human Leucocyte Antigens (HLA) haplotypes and on Chromosome 11 with DNA markers for the following genes: D2 dopamine receptor, tyrosinase, C-Harvey-Ras-A (HRAS) oncogene, insuline (ins), and tyrosine hydroxylase (TH). Although linkage studies support the hypothesis of a major locus for the transmission of MDI in the Xq27-28 region, several factors are limiting the results, and are discussed in the present review. 105 refs., 1 fig., 2 tabs.

Surrogate receptivity to participation in critical illness genetic research: aligning research oversight and stakeholder concerns.

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Freeman, Bradley D; Butler, Kevin; Bolcic-Jankovic, Dragana; Clarridge, Brian R; Kennedy, Carie R; LeBlanc, Jessica; Chandros Hull, Sara

2015-04-01

Collection of genetic biospecimens as part of critical illness investigations is increasingly commonplace. Oversight bodies vary in restrictions imposed on genetic research, introducing inconsistencies in study design, potential for sampling bias, and the possibility of being overly prohibitive of this type of research altogether. We undertook this study to better understand whether restrictions on genetic data collection beyond those governing research on cognitively intact subjects reflect the concerns of surrogates for critically ill patients. We analyzed survey data collected from 1,176 patients in nonurgent settings and 437 surrogates representing critically ill adults. Attitudes pertaining to genetic data (familiarity, perceptions, interest in participation, concerns) and demographic information were examined using univariate and multivariate techniques. We explored differences among respondents who were receptive (1,333) and nonreceptive (280) to genetic sample collection. Whereas factors positively associated with receptivity to research participation were "complete trust" in health-care providers (OR, 2.091; 95% CI, 1.544-2.833), upper income strata (OR, 2.319; 95% CI, 1.308-4.114), viewing genetic research "very positively" (OR, 3.524; 95% CI, 2.122-5.852), and expressing "no worry at all" regarding disclosure of results (OR, 2.505; 95% CI, 1.436-4.369), black race was negatively associated with research participation (OR, 0.410; 95% CI, 0.288-0.585). We could detect no difference in receptivity to genetic sample collection comparing ambulatory patients and surrogates (OR, 0.738; 95% CI, 0.511-1.066). Expressing trust in health-care providers and viewing genetic research favorably were associated with increased willingness for study enrollment, while concern regarding breach of confidentiality and black race had the opposite effect. Study setting had no bearing on willingness to participate.

Analysis of genetic diversity of Fusarium tupiense, the main causal agent of mango malformation disease in southern Spain

Science.gov (United States)

Mango malformation disease (MMD) has become an important global disease affecting this crop. The aim of this study was to identify the main causal agents of MMD in the Axarquía region of southern Spain and determine their genetic diversity. Fusarium mangiferae was previously described in the Axarquí...

Rhinovirus Wheezing Illness and Genetic Risk of Childhood-Onset Asthma

Science.gov (United States)

Çalışkan, Minal; Bochkov, Yury A.; Kreiner-Møller, Eskil; Bønnelykke, Klaus; Stein, Michelle M.; Du, Gaixin; Bisgaard, Hans; Jackson, Daniel J.; Gern, James E.; Lemanske, Robert F.; Nicolae, Dan L.; Ober, Carole

2013-01-01

BACKGROUND Both genetic variation at the 17q21 locus and virus-induced respiratory wheezing illnesses are associated with the development of asthma. Our aim was to determine the effects of these two factors on the risk of asthma in the Childhood Origins of Asthma (COAST) and the Copenhagen Prospective Study on Asthma in Childhood (COPSAC) birth cohorts. METHODS We tested genotypes at the 17q21 locus for associations with asthma and with human rhinovirus (HRV) and respiratory syncytial virus (RSV) wheezing illnesses and tested for interactions between 17q21 genotypes and HRV and RSV wheezing illnesses with respect to the risk of asthma. Finally, we examined genotype-specific expression of 17q21 genes in unstimulated and HRV-stimulated peripheral-blood mononuclear cells (PBMCs). RESULTS The 17q21 variants were associated with HRV wheezing illnesses in early life, but not with RSV wheezing illnesses. The associations of 17q21 variants with asthma were restricted to children who had had HRV wheezing illnesses, resulting in a significant interaction effect with respect to the risk of asthma. Moreover, the expression levels of ORMDL3 and of GSDMB were significantly increased in HRV-stimulated PBMCs, as compared with unstimulated PBMCs. The expression of these genes was associated with 17q21 variants in both conditions, although the increase with exposure to HRV was not genotype-specific. CONCLUSIONS Variants at the 17q21 locus were associated with asthma in children who had had HRV wheezing illnesses and with expression of two genes at this locus. The expression levels of both genes increased in response to HRV stimulation, although the relative increase was not associated with the 17q21 genotypes. (Funded by the National Institutes of Health.) PMID:23534543

Mind and Meaning: Piaget and Vygotsky on Causal Explanation.

Science.gov (United States)

Beilin, Harry

1996-01-01

Piaget's theory has been characterized as descriptive and not explanatory, not qualifying as causal explanation. Piaget was consistent in showing how his theory was both explanatory and causal. Vygotsky also endorsed causal-genetic explanation but, on the basis of knowledge of only Piaget's earliest works, he claimed that Piaget's theory was not…

Early Prediction of Sepsis Incidence in Critically Ill Patients Using Specific Genetic Polymorphisms.

Science.gov (United States)

David, Vlad Laurentiu; Ercisli, Muhammed Furkan; Rogobete, Alexandru Florin; Boia, Eugen S; Horhat, Razvan; Nitu, Razvan; Diaconu, Mircea M; Pirtea, Laurentiu; Ciuca, Ioana; Horhat, Delia; Horhat, Florin George; Licker, Monica; Popovici, Sonia Elena; Tanasescu, Sonia; Tataru, Calin

2017-06-01

Several diagnostic methods for the evaluation and monitoring were used to find out the pro-inflammatory status, as well as incidence of sepsis in critically ill patients. One such recent method is based on investigating the genetic polymorphisms and determining the molecular and genetic links between them, as well as other sepsis-associated pathophysiologies. Identification of genetic polymorphisms in critical patients with sepsis can become a revolutionary method for evaluating and monitoring these patients. Similarly, the complications, as well as the high costs associated with the management of patients with sepsis, can be significantly reduced by early initiation of intensive care.

What Do Patients Think about the Cause of Their Mental Disorder? A Qualitative and Quantitative Analysis of Causal Beliefs of Mental Disorder in Inpatients in Psychosomatic Rehabilitation.

Directory of Open Access Journals (Sweden)

Julia Luise Magaard

Full Text Available Patients' causal beliefs about their mental disorders are important for treatment because they affect illness-related behaviours. However, there are few studies exploring patients' causal beliefs about their mental disorder.(a To qualitatively explore patients' causal beliefs of their mental disorder, (b to explore frequencies of patients stating causal beliefs, and (c to investigate differences of causal beliefs according to patients' primary diagnoses.Inpatients in psychosomatic rehabilitation were asked an open-ended question about their three most important causal beliefs about their mental illness. Answers were obtained from 678 patients, with primary diagnoses of depression (N = 341, adjustment disorder (N = 75, reaction to severe stress (N = 57 and anxiety disorders (N = 40. Two researchers developed a category system inductively and categorised the reported causal beliefs. Qualitative analysis has been supplemented by logistic regression analyses.The causal beliefs were organized into twelve content-related categories. Causal beliefs referring to "problems at work" (47% and "problems in social environment" (46% were most frequently mentioned by patients with mental disorders. 35% of patients indicate causal beliefs related to "self/internal states". Patients with depression and patients with anxiety disorders stated similar causal beliefs, whereas patients with reactions to severe stress and adjustment disorders stated different causal beliefs in comparison to patients with depression.There was no opportunity for further exploration, because we analysed written documents.These results add a detailed insight to mentally ill patients' causal beliefs to illness perception literature. Additionally, evidence about differences in frequencies of causal beliefs between different illness groups complement previous findings. For future research it is important to clarify the relation between patients' causal beliefs and the chosen treatment.

What Do Patients Think about the Cause of Their Mental Disorder? A Qualitative and Quantitative Analysis of Causal Beliefs of Mental Disorder in Inpatients in Psychosomatic Rehabilitation.

Science.gov (United States)

Magaard, Julia Luise; Schulz, Holger; Brütt, Anna Levke

2017-01-01

Patients' causal beliefs about their mental disorders are important for treatment because they affect illness-related behaviours. However, there are few studies exploring patients' causal beliefs about their mental disorder. (a) To qualitatively explore patients' causal beliefs of their mental disorder, (b) to explore frequencies of patients stating causal beliefs, and (c) to investigate differences of causal beliefs according to patients' primary diagnoses. Inpatients in psychosomatic rehabilitation were asked an open-ended question about their three most important causal beliefs about their mental illness. Answers were obtained from 678 patients, with primary diagnoses of depression (N = 341), adjustment disorder (N = 75), reaction to severe stress (N = 57) and anxiety disorders (N = 40). Two researchers developed a category system inductively and categorised the reported causal beliefs. Qualitative analysis has been supplemented by logistic regression analyses. The causal beliefs were organized into twelve content-related categories. Causal beliefs referring to "problems at work" (47%) and "problems in social environment" (46%) were most frequently mentioned by patients with mental disorders. 35% of patients indicate causal beliefs related to "self/internal states". Patients with depression and patients with anxiety disorders stated similar causal beliefs, whereas patients with reactions to severe stress and adjustment disorders stated different causal beliefs in comparison to patients with depression. There was no opportunity for further exploration, because we analysed written documents. These results add a detailed insight to mentally ill patients' causal beliefs to illness perception literature. Additionally, evidence about differences in frequencies of causal beliefs between different illness groups complement previous findings. For future research it is important to clarify the relation between patients' causal beliefs and the chosen treatment.

Genetic and environmental multidimensionality of well- and ill-being in middle aged twin men.

Science.gov (United States)

Franz, Carol E; Panizzon, Matthew S; Eaves, Lindon J; Thompson, Wesley; Lyons, Michael J; Jacobson, Kristen C; Tsuang, Ming; Glatt, Stephen J; Kremen, William S

2012-07-01

The goals of the study were to determine the extent to which the underlying structure of different types of well-being was multidimensional and whether well- and ill-being were influenced by similar or different genetic and environmental factors. Participants were 1226 male twins ages 51-60, from the Vietnam Era Twin Study of Aging. Measures included: psychological well-being, Multidimensional Personality Questionnaire Well-Being scale (MPQWB), life satisfaction, self-esteem, and depressive symptoms. A two-orthogonal-factor common pathway model fit the data well. Psychological well-being and self-esteem loaded most strongly on Factor 1, which was highly heritable (h(2) = .79). Life satisfaction loaded most strongly on Factor 2, which was only moderately heritable (h(2) = .32). Only MPQWB had measure-specific genetic influences. Depressive symptoms loaded on both factors, and only depressive symptoms had measure-specific common environmental influences. All measures had specific unique environmental influences. Results indicate that well-being is genetically and environmentally multidimensional and that ill-being has partial overlap with both latent factors.

The role of secure attachment, empathic self-efficacy, and stress perception in causal beliefs related to mental illness – a cross-cultural study: Italy versus Israel

Directory of Open Access Journals (Sweden)

Mannarini S

2017-10-01

Full Text Available Stefania Mannarini,1 Alisa Reikher,1 Sharon Shani,1 Inbal Shani-Zinovich2 1Department of Philosophy, Sociology, Education and Applied Psychology, Interdepartmental Center for Family Research, University of Padova, Padova, Italy; 2Department of Counseling and Human Development, Faculty of Education, University of Haifa, Mount Carmel, Haifa, Israel Background: Research suggests that “mental illness etiological beliefs” and attitudes toward mentally ill people are significantly related; it has also been demonstrated that adult attachment style and empathic self-efficacy affect such attitudes. Moreover, community or regional culture has a significant impact on etiology beliefs and attitudes toward the mentally sick. Materials and methods: We carried out this study in Italy and Israel among psychology students to compare two cultures in regards to causal beliefs of mental disorders and the roles that specific variables, such as secure attachment, empathic self-efficacy, and stress, play in etiological beliefs. The participants (N=305 were students who belonged to two universities: Padua (N=183 and Haifa (N=122. The Many Facet Rasch Model (MFRM was applied in a cross-cultural perspective to analyze the differential functioning of specific etiological beliefs in relation to the above mentioned variables; the effect of gender and religious beliefs was also entered in the MFRM. Results: The two cultures reacted differently to the biogenetic and psychosocial causal explanations of mental disorders: Israeli students endorsed the biogenetic causal beliefs model more frequently than the Italians. Among other findings, concerning the biogenetic model, the Italian students were predominantly males, who declared to be religious and reported lower levels of secure attachment than Israelis. On the other hand, the Israeli students who manifested a preference toward the biogenetic explanation were mostly females, who declared not to be religious and who

Can chance cause cancer? A causal consideration.

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Stensrud, Mats Julius; Strohmaier, Susanne; Valberg, Morten; Aalen, Odd Olai

2017-04-01

The role of randomness, environment and genetics in cancer development is debated. We approach the discussion by using the potential outcomes framework for causal inference. By briefly considering the underlying assumptions, we suggest that the antagonising views arise due to estimation of substantially different causal effects. These effects may be hard to interpret, and the results cannot be immediately compared. Indeed, it is not clear whether it is possible to define a causal effect of chance at all. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Causal Theory of Mnemonic Confabulation

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Sven Bernecker

2017-07-01

Full Text Available This paper attempts to answer the question of what defines mnemonic confabulation vis-à-vis genuine memory. The two extant accounts of mnemonic confabulation as “false memory” and as ill-grounded memory are shown to be problematic, for they cannot account for the possibility of veridical confabulation, ill-grounded memory, and well-grounded confabulation. This paper argues that the defining characteristic of mnemonic confabulation is that it lacks the appropriate causal history. In the confabulation case, there is no proper counterfactual dependence of the state of seeming to remember on the corresponding past representation.

Moving towards causality in attention-deficit hyperactivity disorder: overview of neural and genetic mechanisms

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Gallo, Eduardo F; Posner, Jonathan

2016-01-01

Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterised by developmentally inappropriate levels of inattention and hyperactivity or impulsivity. The heterogeneity of its clinical manifestations and the differential responses to treatment and varied prognoses have long suggested myriad underlying causes. Over the past decade, clinical and basic research efforts have uncovered many behavioural and neurobiological alterations associated with ADHD, from genes to higher order neural networks. Here, we review the neurobiology of ADHD by focusing on neural circuits implicated in the disorder and discuss how abnormalities in circuitry relate to symptom presentation and treatment. We summarise the literature on genetic variants that are potentially related to the development of ADHD, and how these, in turn, might affect circuit function and relevant behaviours. Whether these underlying neurobiological factors are causally related to symptom presentation remains unresolved. Therefore, we assess efforts aimed at disentangling issues of causality, and showcase the shifting research landscape towards endophenotype refinement in clinical and preclinical settings. Furthermore, we review approaches being developed to understand the neurobiological underpinnings of this complex disorder including the use of animal models, neuromodulation, and pharmaco-imaging studies. PMID:27183902

Causal correlations between genes and linguistic features: The mechanism of gradual language evolution

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Dediu, D.

2008-01-01

The causal correlations between human genetic variants and linguistic (typological) features could represent the mechanism required for gradual, accretionary models of language evolution. The causal link is mediated by the process of cultural transmission of language across generations in a population of genetically biased individuals. The particular case of Tone, ASPM and Microcephalin is discussed as an illustration. It is proposed that this type of genetically-influenced linguistic bias, c...

Genetic evidence of a causal effect of insulin resistance on branched-chain amino acid levels.

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Mahendran, Yuvaraj; Jonsson, Anna; Have, Christian T; Allin, Kristine H; Witte, Daniel R; Jørgensen, Marit E; Grarup, Niels; Pedersen, Oluf; Kilpeläinen, Tuomas O; Hansen, Torben

2017-05-01

Fasting plasma levels of branched-chain amino acids (BCAAs) are associated with insulin resistance, but it remains unclear whether there is a causal relation between the two. We aimed to disentangle the causal relations by performing a Mendelian randomisation study using genetic variants associated with circulating BCAA levels and insulin resistance as instrumental variables. We measured circulating BCAA levels in blood plasma by NMR spectroscopy in 1,321 individuals from the ADDITION-PRO cohort. We complemented our analyses by using previously published genome-wide association study (GWAS) results from the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) (n = 46,186) and from a GWAS of serum BCAA levels (n = 24,925). We used a genetic risk score (GRS), calculated using ten established fasting serum insulin associated variants, as an instrumental variable for insulin resistance. A GRS of three variants increasing circulating BCAA levels was used as an instrumental variable for circulating BCAA levels. Fasting plasma BCAA levels were associated with higher HOMA-IR in ADDITION-PRO (β 0.137 [95% CI 0.08, 0.19] p = 6 × 10 -7 ). However, the GRS for circulating BCAA levels was not associated with fasting insulin levels or HOMA-IR in ADDITION-PRO (β -0.011 [95% CI -0.053, 0.032] p = 0.6 and β -0.011 [95% CI -0.054, 0.031] p = 0.6, respectively) or in GWAS results for HOMA-IR from MAGIC (β for valine-increasing GRS -0.012 [95% CI -0.069, 0.045] p = 0.7). By contrast, the insulin-resistance-increasing GRS was significantly associated with increased BCAA levels in ADDITION-PRO (β 0.027 [95% CI 0.005, 0.048] p = 0.01) and in GWAS results for serum BCAA levels (β 1.22 [95% CI 0.71, 1.73] p = 4 × 10 -6 , β 0.96 [95% CI 0.45, 1.47] p = 3 × 10 -4 , and β 0.67 [95% CI 0.16, 1.18] p = 0.01 for isoleucine, leucine and valine levels, respectively) and instrumental variable analyses in ADDITION

Explaining quantum correlations through evolution of causal models

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Harper, Robin; Chapman, Robert J.; Ferrie, Christopher; Granade, Christopher; Kueng, Richard; Naoumenko, Daniel; Flammia, Steven T.; Peruzzo, Alberto

2017-04-01

We propose a framework for the systematic and quantitative generalization of Bell's theorem using causal networks. We first consider the multiobjective optimization problem of matching observed data while minimizing the causal effect of nonlocal variables and prove an inequality for the optimal region that both strengthens and generalizes Bell's theorem. To solve the optimization problem (rather than simply bound it), we develop a genetic algorithm treating as individuals causal networks. By applying our algorithm to a photonic Bell experiment, we demonstrate the trade-off between the quantitative relaxation of one or more local causality assumptions and the ability of data to match quantum correlations.

Causal Genetic Variation Underlying Metabolome Differences.

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Swain-Lenz, Devjanee; Nikolskiy, Igor; Cheng, Jiye; Sudarsanam, Priya; Nayler, Darcy; Staller, Max V; Cohen, Barak A

2017-08-01

An ongoing challenge in biology is to predict the phenotypes of individuals from their genotypes. Genetic variants that cause disease often change an individual's total metabolite profile, or metabolome. In light of our extensive knowledge of metabolic pathways, genetic variants that alter the metabolome may help predict novel phenotypes. To link genetic variants to changes in the metabolome, we studied natural variation in the yeast Saccharomyces cerevisiae We used an untargeted mass spectrometry method to identify dozens of metabolite Quantitative Trait Loci (mQTL), genomic regions containing genetic variation that control differences in metabolite levels between individuals. We mapped differences in urea cycle metabolites to genetic variation in specific genes known to regulate amino acid biosynthesis. Our functional assays reveal that genetic variation in two genes, AUA1 and ARG81 , cause the differences in the abundance of several urea cycle metabolites. Based on knowledge of the urea cycle, we predicted and then validated a new phenotype: sensitivity to a particular class of amino acid isomers. Our results are a proof-of-concept that untargeted mass spectrometry can reveal links between natural genetic variants and metabolome diversity. The interpretability of our results demonstrates the promise of using genetic variants underlying natural differences in the metabolome to predict novel phenotypes from genotype. Copyright © 2017 by the Genetics Society of America.

The children of mentally ill parents.

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Mattejat, Fritz; Remschmidt, Helmut

2008-06-01

The children of mentally ill parents have a higher risk of developing mental illnesses themselves over the course of their lives. This known risk must be taken into account in the practical provision of health care. Selective literature review. The increased psychiatric risk for children of mentally ill parents is due partly to genetic influences and partly to an impairment of the parent-child interaction because of the parent's illness. Furthermore, adverse factors are more frequent in these families, as well as a higher risk for child abuse. Genetic and psychosocial factors interact with one another. For example, genetic factors moderate environmental effects; that is, the effect of adverse environmental factors depends on the genetic substrate. Preventive measures for children of mentally ill parents urgently need improvement. In this article, positively evaluated programs of preventive measures are discussed. Essential prerequisites for success include appropriate, specialized treatment of the parental illness, psychoeducative measures, and special support (e.g. self-help groups) as indicated by the family's particular needs.

A Hierarchical Causal Taxonomy of Psychopathology across the Life Span

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Lahey, Benjamin B.; Krueger, Robert F.; Rathouz, Paul J.; Waldman, Irwin D.; Zald, David H.

2016-01-01

We propose a taxonomy of psychopathology based on patterns of shared causal influences identified in a review of multivariate behavior genetic studies that distinguish genetic and environmental influences that are either common to multiple dimensions of psychopathology or unique to each dimension. At the phenotypic level, first-order dimensions are defined by correlations among symptoms; correlations among first-order dimensions similarly define higher-order domains (e.g., internalizing or externalizing psychopathology). We hypothesize that the robust phenotypic correlations among first-order dimensions reflect a hierarchy of increasingly specific etiologic influences. Some nonspecific etiologic factors increase risk for all first-order dimensions of psychopathology to varying degrees through a general factor of psychopathology. Other nonspecific etiologic factors increase risk only for all first-order dimensions within a more specific higher-order domain. Furthermore, each first-order dimension has its own unique causal influences. Genetic and environmental influences common to family members tend to be nonspecific, whereas environmental influences unique to each individual are more dimension-specific. We posit that these causal influences on psychopathology are moderated by sex and developmental processes. This causal taxonomy also provides a novel framework for understanding the heterogeneity of each first-order dimension: Different persons exhibiting similar symptoms may be influenced by different combinations of etiologic influences from each of the three levels of the etiologic hierarchy. Furthermore, we relate the proposed causal taxonomy to transdimensional psychobiological processes, which also impact the heterogeneity of each psychopathology dimension. This causal taxonomy implies the need for changes in strategies for studying the etiology, psychobiology, prevention, and treatment of psychopathology. PMID:28004947

Women's caregiving and paid work: causal relationships in late midlife.

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Pavalko, E K; Artis, J E

1997-07-01

Care of an ill or disabled family member or friend is disproportionately done by women and typically is done in late midlife. Because this is-also a time in the life course when women's labor force participation peaks, many women faced with caregiving demands have to decide how to balance them with their employment. In this study we use the National Longitudinal Survey (NLS) of Mature Women to examine the causal relationship between employment and caring for an ill or disabled friend or relative over a three-year period. We find that employment does not affect whether or not women start caregiving, but that women who do start are more likely to reduce employment hours or stop work. Thus, the causal relationship between employment and caregiving in late midlife is largely unidirectional, with women reducing hours to meet caregiving demands.

Causal and causally separable processes

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Oreshkov, Ognyan; Giarmatzi, Christina

2016-09-01

The idea that events are equipped with a partial causal order is central to our understanding of physics in the tested regimes: given two pointlike events A and B, either A is in the causal past of B, B is in the causal past of A, or A and B are space-like separated. Operationally, the meaning of these order relations corresponds to constraints on the possible correlations between experiments performed in the vicinities of the respective events: if A is in the causal past of B, an experimenter at A could signal to an experimenter at B but not the other way around, while if A and B are space-like separated, no signaling is possible in either direction. In the context of a concrete physical theory, the correlations compatible with a given causal configuration may obey further constraints. For instance, space-like correlations in quantum mechanics arise from local measurements on joint quantum states, while time-like correlations are established via quantum channels. Similarly to other variables, however, the causal order of a set of events could be random, and little is understood about the constraints that causality implies in this case. A main difficulty concerns the fact that the order of events can now generally depend on the operations performed at the locations of these events, since, for instance, an operation at A could influence the order in which B and C occur in A’s future. So far, no formal theory of causality compatible with such dynamical causal order has been developed. Apart from being of fundamental interest in the context of inferring causal relations, such a theory is imperative for understanding recent suggestions that the causal order of events in quantum mechanics can be indefinite. Here, we develop such a theory in the general multipartite case. Starting from a background-independent definition of causality, we derive an iteratively formulated canonical decomposition of multipartite causal correlations. For a fixed number of settings and

Causal and causally separable processes

International Nuclear Information System (INIS)

Oreshkov, Ognyan; Giarmatzi, Christina

2016-01-01

The idea that events are equipped with a partial causal order is central to our understanding of physics in the tested regimes: given two pointlike events A and B , either A is in the causal past of B , B is in the causal past of A , or A and B are space-like separated. Operationally, the meaning of these order relations corresponds to constraints on the possible correlations between experiments performed in the vicinities of the respective events: if A is in the causal past of B , an experimenter at A could signal to an experimenter at B but not the other way around, while if A and B are space-like separated, no signaling is possible in either direction. In the context of a concrete physical theory, the correlations compatible with a given causal configuration may obey further constraints. For instance, space-like correlations in quantum mechanics arise from local measurements on joint quantum states, while time-like correlations are established via quantum channels. Similarly to other variables, however, the causal order of a set of events could be random, and little is understood about the constraints that causality implies in this case. A main difficulty concerns the fact that the order of events can now generally depend on the operations performed at the locations of these events, since, for instance, an operation at A could influence the order in which B and C occur in A ’s future. So far, no formal theory of causality compatible with such dynamical causal order has been developed. Apart from being of fundamental interest in the context of inferring causal relations, such a theory is imperative for understanding recent suggestions that the causal order of events in quantum mechanics can be indefinite. Here, we develop such a theory in the general multipartite case. Starting from a background-independent definition of causality, we derive an iteratively formulated canonical decomposition of multipartite causal correlations. For a fixed number of settings and

Children's Moral Reasoning about Illness in Chhattisgarh, Central India

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Froerer, Peggy

2011-01-01

This article is about children's moral reasoning about illness and supernatural retribution in a rural tribal community in Chhattisgarh, central India. Detailed ethnographic analysis is devoted to the norms and experiences within which conceptions about illness causality and morality are formed. The author is principally interested in the…

Genetics and intelligence differences: five special findings

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Plomin, R; Deary, I J

2015-01-01

Intelligence is a core construct in differential psychology and behavioural genetics, and should be so in cognitive neuroscience. It is one of the best predictors of important life outcomes such as education, occupation, mental and physical health and illness, and mortality. Intelligence is one of the most heritable behavioural traits. Here, we highlight five genetic findings that are special to intelligence differences and that have important implications for its genetic architecture and for gene-hunting expeditions. (i) The heritability of intelligence increases from about 20% in infancy to perhaps 80% in later adulthood. (ii) Intelligence captures genetic effects on diverse cognitive and learning abilities, which correlate phenotypically about 0.30 on average but correlate genetically about 0.60 or higher. (iii) Assortative mating is greater for intelligence (spouse correlations ~0.40) than for other behavioural traits such as personality and psychopathology (~0.10) or physical traits such as height and weight (~0.20). Assortative mating pumps additive genetic variance into the population every generation, contributing to the high narrow heritability (additive genetic variance) of intelligence. (iv) Unlike psychiatric disorders, intelligence is normally distributed with a positive end of exceptional performance that is a model for ‘positive genetics'. (v) Intelligence is associated with education and social class and broadens the causal perspectives on how these three inter-correlated variables contribute to social mobility, and health, illness and mortality differences. These five findings arose primarily from twin studies. They are being confirmed by the first new quantitative genetic technique in a century—Genome-wide Complex Trait Analysis (GCTA)—which estimates genetic influence using genome-wide genotypes in large samples of unrelated individuals. Comparing GCTA results to the results of twin studies reveals important insights into the genetic

Causal Reasoning with Mental Models

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2014-08-08

The initial rubric is equivalent to an exclusive disjunction between the two causal assertions. It 488 yields the following two mental models: 489...are 575 important, whereas the functions of artifacts are important (Ahn, 1998). A genetic code is 576 accordingly more critical to being a goat than

Association Between Maternal Smoking During Pregnancy and Severe Mental Illness in Offspring.

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Quinn, Patrick D; Rickert, Martin E; Weibull, Caroline E; Johansson, Anna L V; Lichtenstein, Paul; Almqvist, Catarina; Larsson, Henrik; Iliadou, Anastasia N; D'Onofrio, Brian M

2017-06-01

Several recent population-based studies have linked exposure to maternal smoking during pregnancy to increased risk of severe mental illness in offspring (eg, bipolar disorder, schizophrenia). It is not yet clear, however, whether this association results from causal teratogenic effects or from confounding influences shared by smoking and severe mental illness. To examine the association between smoking during pregnancy and severe mental illness in offspring, adjusting for measured covariates and unmeasured confounding using family-based designs. This study analyzed population register data through December 31, 2013, for a cohort of 1 680 219 individuals born in Sweden from January 1, 1983, to December 31, 2001. Associations between smoking during pregnancy and severe mental illness in offspring were estimated with adjustment for measured covariates. Cousins and siblings who were discordant on smoking during pregnancy and severe mental illness were then compared, which helped to account for unmeasured genetic and environmental confounding by design. Maternal self-reported smoking during pregnancy, obtained from antenatal visits. Severe mental illness, with clinical diagnosis obtained from inpatient and outpatient visits and defined using International Classification of Diseases codes for bipolar disorder and schizophrenia spectrum disorders. Of the 1 680 219 offspring included in the analysis, 816 775 (48.61%) were female. At the population level, offspring exposed to moderate and high levels of smoking during pregnancy had greater severe mental illness rates than did unexposed offspring (moderate smoking during pregnancy: hazard ratio [HR], 1.25; 95% CI, 1.19-1.30; high smoking during pregnancy: HR, 1.51; 95% CI, 1.44-1.59). These associations decreased in strength with increasing statistical and methodologic controls for familial confounding. In sibling comparisons with within-family covariates, associations were substantially weaker and nonsignificant (moderate

Causal attributions in Brazilian children's reasoning about health and illness Atribuições de causalidade referentes à saúde e à doença de crianças brasileiras

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Evely Boruchovitch

2000-10-01

Full Text Available INTRODUCTION: At a time when a great number of diseases can be prevented by changing one's habits and life style, investigations have focused on understanding what adults and children believe to be desirable health practices and uncovering the factors associated with successful adherence to such practices. For these, causal attributions for health and illness were investigated among 96 Brazilian elementary school students. METHODS: Ninety six subjects, aged 6 to 14, were interviewed individually and their causal attributions were assessed through 14 true-false items (e.g. people stay well [healthy] because they are lucky. The relationship between the children's causal attributions and demographic characteristics were also examined. RESULTS: Overall, the results were consistent with previous researches. "Taking care of oneself" was considered the most important cause of good health. "Viruses and germs" and "lack of self-care" were the most selected causes of illness. Analyses revealed significant relationship between subjects' causal attribution and their age, school grade level, socioeconomic status and gender. CONCLUSIONS: The study findings suggest that there may be more cross-cultural similarities than differences in children's causal attributions for health and illness. Finding ways to help individuals engage in appropriate preventive-maintenance health practices without developing an exaggerated notion that the individuals can control their own health and illness is a challenge which remains to be addressed by further research.INTRODUÇÃO: Num momento histórico no qual um grande número de doenças podem ser prevenidas pelas mudanças de hábitos e comportamentos, investigações vêm se desenvolvendo no sentido de, não só compreender o que adultos e crianças consideram como práticas saudáveis desejáveis, mas também na tentativa de identificar fatores associados ao engajamento em comportamentos saudáveis por parte do indiv

Genetic insights into age-related macular degeneration: Controversies addressing Risk, Causality, and Therapeutics

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Gorin, Michael B.

2012-01-01

Age-related macular degeneration (AMD) is a common condition among the elderly population that leads to the progressive central vision loss and serious compromise of quality of life for its sufferers. It is also one of the few disorders for whom the investigation of its genetics has yielded rich insights into its diversity and causality and holds the promise of enabling clinicians to provide better risk assessments for individuals as well as to develop and selectively deploy new therapeutics to either prevent or slow the development of disease and lessen the threat of vision loss. The genetics of AMD began initially with the appreciation of familial aggregation and increase risk and expanded with the initial association of APOE variants with the disease. The first major breakthroughs came with family-based linkage studies of affected (and discordant) sibs, which identified a number of genetic loci and led to the targeted search of the 1q31 and 10q26 loci for associated variants. Three of the initial four reports for the CFH variant, Y402H, were based on regional candidate searches, as were the two initial reports of the ARMS2/HTRA1 locus variants. Case-control association studies initially also played a role in discovering the major genetic variants for AMD, and the success of those early studies have been used to fuel enthusiasm for the methodology for a number of diseases. Until 2010, all of the subsequent genetic variants associated with AMD came from candidate gene testing based on the complement factor pathway. In 2010, several large-scale genome-wide association studies (GWAS) identified genes that had not been previously identified. Much of this historical information is available in a number of recent reviews.(Chen et al., 2010b; Deangelis et al., 2011; Fafowora and Gorin, 2012b; Francis and Klein, 2011; Kokotas et al., 2011) Large meta analysis of AMD GWAS has added new loci and variants to this collection.(Chen et al., 2010a; Kopplin et al., 2010; Yu et

Genetic variations of PIP4K2A confer vulnerability to poor antipsychotic response in severely ill schizophrenia patients.

Directory of Open Access Journals (Sweden)

Harpreet Kaur

incomplete responders with low severity (OR = 4.09, 95%-CI = 2.09-8.02. Our findings provide strong evidence that diplotype ATTGCT/ATTGCT of PIP4K2A gene conferred approximately three-times higher incomplete responsiveness towards antipsychotics in severely ill patients. These results are consistent with the known role of phosphatidyl-inositol-signaling elements in antipsychotic action and outcome. Findings have implication for future molecular genetic studies as well as personalized medicine. However more work is warranted to elucidate underlying causal biological pathway.

Causally nonseparable processes admitting a causal model

International Nuclear Information System (INIS)

Feix, Adrien; Araújo, Mateus; Brukner, Caslav

2016-01-01

A recent framework of quantum theory with no global causal order predicts the existence of ‘causally nonseparable’ processes. Some of these processes produce correlations incompatible with any causal order (they violate so-called ‘causal inequalities’ analogous to Bell inequalities ) while others do not (they admit a ‘causal model’ analogous to a local model ). Here we show for the first time that bipartite causally nonseparable processes with a causal model exist, and give evidence that they have no clear physical interpretation. We also provide an algorithm to generate processes of this kind and show that they have nonzero measure in the set of all processes. We demonstrate the existence of processes which stop violating causal inequalities but are still causally nonseparable when mixed with a certain amount of ‘white noise’. This is reminiscent of the behavior of Werner states in the context of entanglement and nonlocality. Finally, we provide numerical evidence for the existence of causally nonseparable processes which have a causal model even when extended with an entangled state shared among the parties. (paper)

Seventy-five genetic loci influencing the human red blood cell.

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van der Harst, Pim; Zhang, Weihua; Mateo Leach, Irene; Rendon, Augusto; Verweij, Niek; Sehmi, Joban; Paul, Dirk S; Elling, Ulrich; Allayee, Hooman; Li, Xinzhong; Radhakrishnan, Aparna; Tan, Sian-Tsung; Voss, Katrin; Weichenberger, Christian X; Albers, Cornelis A; Al-Hussani, Abtehale; Asselbergs, Folkert W; Ciullo, Marina; Danjou, Fabrice; Dina, Christian; Esko, Tõnu; Evans, David M; Franke, Lude; Gögele, Martin; Hartiala, Jaana; Hersch, Micha; Holm, Hilma; Hottenga, Jouke-Jan; Kanoni, Stavroula; Kleber, Marcus E; Lagou, Vasiliki; Langenberg, Claudia; Lopez, Lorna M; Lyytikäinen, Leo-Pekka; Melander, Olle; Murgia, Federico; Nolte, Ilja M; O'Reilly, Paul F; Padmanabhan, Sandosh; Parsa, Afshin; Pirastu, Nicola; Porcu, Eleonora; Portas, Laura; Prokopenko, Inga; Ried, Janina S; Shin, So-Youn; Tang, Clara S; Teumer, Alexander; Traglia, Michela; Ulivi, Sheila; Westra, Harm-Jan; Yang, Jian; Zhao, Jing Hua; Anni, Franco; Abdellaoui, Abdel; Attwood, Antony; Balkau, Beverley; Bandinelli, Stefania; Bastardot, François; Benyamin, Beben; Boehm, Bernhard O; Cookson, William O; Das, Debashish; de Bakker, Paul I W; de Boer, Rudolf A; de Geus, Eco J C; de Moor, Marleen H; Dimitriou, Maria; Domingues, Francisco S; Döring, Angela; Engström, Gunnar; Eyjolfsson, Gudmundur Ingi; Ferrucci, Luigi; Fischer, Krista; Galanello, Renzo; Garner, Stephen F; Genser, Bernd; Gibson, Quince D; Girotto, Giorgia; Gudbjartsson, Daniel Fannar; Harris, Sarah E; Hartikainen, Anna-Liisa; Hastie, Claire E; Hedblad, Bo; Illig, Thomas; Jolley, Jennifer; Kähönen, Mika; Kema, Ido P; Kemp, John P; Liang, Liming; Lloyd-Jones, Heather; Loos, Ruth J F; Meacham, Stuart; Medland, Sarah E; Meisinger, Christa; Memari, Yasin; Mihailov, Evelin; Miller, Kathy; Moffatt, Miriam F; Nauck, Matthias; Novatchkova, Maria; Nutile, Teresa; Olafsson, Isleifur; Onundarson, Pall T; Parracciani, Debora; Penninx, Brenda W; Perseu, Lucia; Piga, Antonio; Pistis, Giorgio; Pouta, Anneli; Puc, Ursula; Raitakari, Olli; Ring, Susan M; Robino, Antonietta; Ruggiero, Daniela; Ruokonen, Aimo; Saint-Pierre, Aude; Sala, Cinzia; Salumets, Andres; Sambrook, Jennifer; Schepers, Hein; Schmidt, Carsten Oliver; Silljé, Herman H W; Sladek, Rob; Smit, Johannes H; Starr, John M; Stephens, Jonathan; Sulem, Patrick; Tanaka, Toshiko; Thorsteinsdottir, Unnur; Tragante, Vinicius; van Gilst, Wiek H; van Pelt, L Joost; van Veldhuisen, Dirk J; Völker, Uwe; Whitfield, John B; Willemsen, Gonneke; Winkelmann, Bernhard R; Wirnsberger, Gerald; Algra, Ale; Cucca, Francesco; d'Adamo, Adamo Pio; Danesh, John; Deary, Ian J; Dominiczak, Anna F; Elliott, Paul; Fortina, Paolo; Froguel, Philippe; Gasparini, Paolo; Greinacher, Andreas; Hazen, Stanley L; Jarvelin, Marjo-Riitta; Khaw, Kay Tee; Lehtimäki, Terho; Maerz, Winfried; Martin, Nicholas G; Metspalu, Andres; Mitchell, Braxton D; Montgomery, Grant W; Moore, Carmel; Navis, Gerjan; Pirastu, Mario; Pramstaller, Peter P; Ramirez-Solis, Ramiro; Schadt, Eric; Scott, James; Shuldiner, Alan R; Smith, George Davey; Smith, J Gustav; Snieder, Harold; Sorice, Rossella; Spector, Tim D; Stefansson, Kari; Stumvoll, Michael; Tang, W H Wilson; Toniolo, Daniela; Tönjes, Anke; Visscher, Peter M; Vollenweider, Peter; Wareham, Nicholas J; Wolffenbuttel, Bruce H R; Boomsma, Dorret I; Beckmann, Jacques S; Dedoussis, George V; Deloukas, Panos; Ferreira, Manuel A; Sanna, Serena; Uda, Manuela; Hicks, Andrew A; Penninger, Josef Martin; Gieger, Christian; Kooner, Jaspal S; Ouwehand, Willem H; Soranzo, Nicole; Chambers, John C

2012-12-20

Anaemia is a chief determinant of global ill health, contributing to cognitive impairment, growth retardation and impaired physical capacity. To understand further the genetic factors influencing red blood cells, we carried out a genome-wide association study of haemoglobin concentration and related parameters in up to 135,367 individuals. Here we identify 75 independent genetic loci associated with one or more red blood cell phenotypes at P < 10(-8), which together explain 4-9% of the phenotypic variance per trait. Using expression quantitative trait loci and bioinformatic strategies, we identify 121 candidate genes enriched in functions relevant to red blood cell biology. The candidate genes are expressed preferentially in red blood cell precursors, and 43 have haematopoietic phenotypes in Mus musculus or Drosophila melanogaster. Through open-chromatin and coding-variant analyses we identify potential causal genetic variants at 41 loci. Our findings provide extensive new insights into genetic mechanisms and biological pathways controlling red blood cell formation and function.

Causal gene identification using combinatorial V-structure search.

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Cai, Ruichu; Zhang, Zhenjie; Hao, Zhifeng

2013-07-01

With the advances of biomedical techniques in the last decade, the costs of human genomic sequencing and genomic activity monitoring are coming down rapidly. To support the huge genome-based business in the near future, researchers are eager to find killer applications based on human genome information. Causal gene identification is one of the most promising applications, which may help the potential patients to estimate the risk of certain genetic diseases and locate the target gene for further genetic therapy. Unfortunately, existing pattern recognition techniques, such as Bayesian networks, cannot be directly applied to find the accurate causal relationship between genes and diseases. This is mainly due to the insufficient number of samples and the extremely high dimensionality of the gene space. In this paper, we present the first practical solution to causal gene identification, utilizing a new combinatorial formulation over V-Structures commonly used in conventional Bayesian networks, by exploring the combinations of significant V-Structures. We prove the NP-hardness of the combinatorial search problem under a general settings on the significance measure on the V-Structures, and present a greedy algorithm to find sub-optimal results. Extensive experiments show that our proposal is both scalable and effective, particularly with interesting findings on the causal genes over real human genome data. Copyright © 2013 Elsevier Ltd. All rights reserved.

Illness Among Persian Gulf War Veterans: Case Validation Studies

National Research Council Canada - National Science Library

Doebbeling, Bradley

1999-01-01

..., and fibromyalgia were particularly elevated. The existence of a causal relationship between either military exposures or other risk factors and documented illness for most symptomatic PGW veterans remains to be demonstrated...

Comparison of individuals opting for BRCA1/2 or HNPCC genetic susceptibility testing with regard to coping, illness perceptions, illness experiences, family system characteristics and hereditary cancer distress

NARCIS (Netherlands)

van Oostrom, Iris; Meijers-Heijboer, Hanne; Duivenvoorden, Hugo J.; Brocker-Vriends, Annette H. J. T.; van Asperen, Christi J.; Sijmons, Rolf H.; Seynaeve, Caroline; Van Gool, Arthur R.; Klijn, Jan G. M.; Tibben, Aad

Objective: To study differences between individuals opting for genetic cancer susceptibility testing of a known familial BRCA1/2 and HNPCC related germline mutation. Methods: Coping, illness perceptions, experiences with cancer in relatives and family system characteristics were assessed in 271

Genetic explanations, discrimination and chronic illness: A qualitative study on hereditary haemochromatosis in Germany.

Science.gov (United States)

Manz, Ulrike

2016-12-01

The objective of this study is to explore the discriminatory impacts of genetic diagnosis for people living with the chronic illness of hereditary haemochromatosis in Germany. Semi-structured interviews with 15 patients; all had tested positive for a genetic mutation associated with haemochromatosis and already displayed symptoms of the disease. Inductive approach, with interviews collaboratively interpreted by the research group in a vertical and horizontal analysis informed by a multi-person perspective. First, as the genetic diagnosis of the disease holds the promise of therapeutic intervention, the interviewees perceived it as leading to relief. Second, the interviewees felt stigmatized by their family members, they complained of social isolation and a lack of acknowledgement of their health problems. Third, they feared disadvantages for themselves or their children at their place of work, when buying insurance coverage, and when attempting to donate blood. The findings point to the need for an expanded view on genetic discrimination. Besides institutional discrimination, it appears necessary to systematically address interactional stigmatization and take anxieties and fears into account. Here we see starting points for providing essential support through specialist and self-help groups to those faced with the genetic diagnosis of haemochromatosis in addition to and beyond the legal protection against genetic discrimination that already exists. © The Author(s) 2016.

Mental illness from the perspective of theoretical neuroscience.

Science.gov (United States)

Thagard, Paul

2008-01-01

Theoretical neuroscience, which characterizes neural mechanisms using mathematical and computational models, is highly relevant to central problems in the philosophy of psychiatry. These models can help to solve the explanation problem of causally connecting neural processes with the behaviors and experiences found in mental illnesses. Such explanations will also be useful for generating better classifications and treatments of psychiatric disorders. The result should help to eliminate concerns that mental illnesses such as depression and schizophrenia are not objectively real. A philosophical approach to mental illness based on neuroscience need not neglect the inherently social and historical nature of mental phenomena.

Alexithymia and illness behaviour among female Indian outpatients with multiple somatic symptoms

OpenAIRE

Sarkar, Jaydip; Chandra, Prabha

2003-01-01

Sixty Indian muslim women outpatients with multiple somatic complaints of nonorganic origin were assessed for alexithymia and abnormal illness behavior using the Toronto Alexithymia Scale (TAS) and the Illness Behaviour Assessment Schedule (IBAS). Alexithymia represented by TAS scores correlated best with the IBAS variables of communication of affect, somatic illness causal beliefs and denial. Correlation with other IBAS variables was modest to poor.There was no correlation of IBAS variables ...

Who deserves health care? The effects of causal attributions and group cues on public attitudes about responsibility for health care costs.

Science.gov (United States)

Gollust, Sarah E; Lynch, Julia

2011-12-01

This research investigates the impact of cues about ascriptive group characteristics (race, class, gender) and the causes of ill health (health behaviors, inborn biological traits, social systemic factors) on beliefs about who deserves society's help in paying for the costs of medical treatment. Drawing on data from three original vignette experiments embedded in a nationally representative survey of American adults, we find that respondents are reluctant to blame or deny societal support in response to explicit cues about racial attributes--but equally explicit cues about the causal impact of individual behaviors on health have large effects on expressed attitudes. Across all three experiments, a focus on individual behavioral causes of illness is associated with increased support for individual responsibility for health care costs and lower support for government-financed health insurance. Beliefs about social groups and causal attributions are, however, tightly intertwined. We find that when groups suffering ill health are defined in racial, class, or gender terms, Americans differ in their attribution of health disparities to individual behaviors versus biological or systemic factors. Because causal attributions also affect health policy opinions, varying patterns of causal attribution may reinforce group stereotypes and undermine support for universal access to health care.

Investigating causal associations between use of nicotine, alcohol, caffeine and cannabis: a two-sample bidirectional Mendelian randomization study.

Science.gov (United States)

Verweij, Karin J H; Treur, Jorien L; Vink, Jacqueline M

2018-07-01

Epidemiological studies consistently show co-occurrence of use of different addictive substances. Whether these associations are causal or due to overlapping underlying influences remains an important question in addiction research. Methodological advances have made it possible to use published genetic associations to infer causal relationships between phenotypes. In this exploratory study, we used Mendelian randomization (MR) to examine the causality of well-established associations between nicotine, alcohol, caffeine and cannabis use. Two-sample MR was employed to estimate bidirectional causal effects between four addictive substances: nicotine (smoking initiation and cigarettes smoked per day), caffeine (cups of coffee per day), alcohol (units per week) and cannabis (initiation). Based on existing genome-wide association results we selected genetic variants associated with the exposure measure as an instrument to estimate causal effects. Where possible we applied sensitivity analyses (MR-Egger and weighted median) more robust to horizontal pleiotropy. Most MR tests did not reveal causal associations. There was some weak evidence for a causal positive effect of genetically instrumented alcohol use on smoking initiation and of cigarettes per day on caffeine use, but these were not supported by the sensitivity analyses. There was also some suggestive evidence for a positive effect of alcohol use on caffeine use (only with MR-Egger) and smoking initiation on cannabis initiation (only with weighted median). None of the suggestive causal associations survived corrections for multiple testing. Two-sample Mendelian randomization analyses found little evidence for causal relationships between nicotine, alcohol, caffeine and cannabis use. © 2018 Society for the Study of Addiction.

Influence of Factor V Leiden on susceptibility to and outcome from critical illness: a genetic association study

DEFF Research Database (Denmark)

Benfield, Thomas; Ejrnæs, Karen; Juul, Klaus

2010-01-01

ABSTRACT: INTRODUCTION: Disturbance of the pro-coagulatant and anti-coagulant balance is associated with a poor outcome from critical illness. The objective of this study is to determine whether the Factor V Leiden (FVL) mutation is associated with susceptibility to or death from critical illness....... METHODS: A genetic association study involving four case cohorts comprising two Gram negative sepsis, one invasive pneumococcal disease and one intensive care unit cohort with a total of 1,249 patients. Controls were derived from a population-based cohort study (N = 8,147). DNA from patients and controls...... not appear to increase the risk of admission due to severe invasive infections. Nevertheless, in the subgroup of patients admitted to intensive care an increased risk and a poorer long-term outcome for individuals with critical illness were observed for FVL mutation carriers....

Causal relationship between obesity and vitamin D status

DEFF Research Database (Denmark)

Vimaleswaran, Karani S; Berry, Diane J; Lu, Chen

2013-01-01

Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional ...

Temporal expression profiling identifies pathways mediating effect of causal variant on phenotype.

Directory of Open Access Journals (Sweden)

Saumya Gupta

2015-06-01

Full Text Available Even with identification of multiple causal genetic variants for common human diseases, understanding the molecular processes mediating the causal variants' effect on the disease remains a challenge. This understanding is crucial for the development of therapeutic strategies to prevent and treat disease. While static profiling of gene expression is primarily used to get insights into the biological bases of diseases, it makes differentiating the causative from the correlative effects difficult, as the dynamics of the underlying biological processes are not monitored. Using yeast as a model, we studied genome-wide gene expression dynamics in the presence of a causal variant as the sole genetic determinant, and performed allele-specific functional validation to delineate the causal effects of the genetic variant on the phenotype. Here, we characterized the precise genetic effects of a functional MKT1 allelic variant in sporulation efficiency variation. A mathematical model describing meiotic landmark events and conditional activation of MKT1 expression during sporulation specified an early meiotic role of this variant. By analyzing the early meiotic genome-wide transcriptional response, we demonstrate an MKT1-dependent role of novel modulators, namely, RTG1/3, regulators of mitochondrial retrograde signaling, and DAL82, regulator of nitrogen starvation, in additively effecting sporulation efficiency. In the presence of functional MKT1 allele, better respiration during early sporulation was observed, which was dependent on the mitochondrial retrograde regulator, RTG3. Furthermore, our approach showed that MKT1 contributes to sporulation independent of Puf3, an RNA-binding protein that steady-state transcription profiling studies have suggested to mediate MKT1-pleiotropic effects during mitotic growth. These results uncover interesting regulatory links between meiosis and mitochondrial retrograde signaling. In this study, we highlight the advantage

Causal imprinting in causal structure learning.

Science.gov (United States)

Taylor, Eric G; Ahn, Woo-Kyoung

2012-11-01

Suppose one observes a correlation between two events, B and C, and infers that B causes C. Later one discovers that event A explains away the correlation between B and C. Normatively, one should now dismiss or weaken the belief that B causes C. Nonetheless, participants in the current study who observed a positive contingency between B and C followed by evidence that B and C were independent given A, persisted in believing that B causes C. The authors term this difficulty in revising initially learned causal structures "causal imprinting." Throughout four experiments, causal imprinting was obtained using multiple dependent measures and control conditions. A Bayesian analysis showed that causal imprinting may be normative under some conditions, but causal imprinting also occurred in the current study when it was clearly non-normative. It is suggested that causal imprinting occurs due to the influence of prior knowledge on how reasoners interpret later evidence. Consistent with this view, when participants first viewed the evidence showing that B and C are independent given A, later evidence with only B and C did not lead to the belief that B causes C. Copyright © 2012 Elsevier Inc. All rights reserved.

Causal Beliefs and Effects upon Mental Illness Identification Among Chinese Immigrant Relatives of Individuals with Psychosis

OpenAIRE

Yang, Lawrence H.; Wonpat-Borja, Ahtoy J.

2011-01-01

Identifying factors that facilitate treatment for psychotic disorders among Chinese-immigrants is crucial due to delayed treatment use. Identifying causal beliefs held by relatives that might predict identification of ‘mental illness’ as opposed to other ‘indigenous labels’ may promote more effective mental health service use. We examine what effects beliefs of ‘physical causes’ and other non-biomedical causal beliefs (‘general social causes’, and ‘indigenous Chinese beliefs’ or culture-speci...

Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors.

Science.gov (United States)

Burgess, Stephen; Scott, Robert A; Timpson, Nicholas J; Davey Smith, George; Thompson, Simon G

2015-07-01

Finding individual-level data for adequately-powered Mendelian randomization analyses may be problematic. As publicly-available summarized data on genetic associations with disease outcomes from large consortia are becoming more abundant, use of published data is an attractive analysis strategy for obtaining precise estimates of the causal effects of risk factors on outcomes. We detail the necessary steps for conducting Mendelian randomization investigations using published data, and present novel statistical methods for combining data on the associations of multiple (correlated or uncorrelated) genetic variants with the risk factor and outcome into a single causal effect estimate. A two-sample analysis strategy may be employed, in which evidence on the gene-risk factor and gene-outcome associations are taken from different data sources. These approaches allow the efficient identification of risk factors that are suitable targets for clinical intervention from published data, although the ability to assess the assumptions necessary for causal inference is diminished. Methods and guidance are illustrated using the example of the causal effect of serum calcium levels on fasting glucose concentrations. The estimated causal effect of a 1 standard deviation (0.13 mmol/L) increase in calcium levels on fasting glucose (mM) using a single lead variant from the CASR gene region is 0.044 (95 % credible interval -0.002, 0.100). In contrast, using our method to account for the correlation between variants, the corresponding estimate using 17 genetic variants is 0.022 (95 % credible interval 0.009, 0.035), a more clearly positive causal effect.

Legionnaire's disease - a puzzling pneumonic illness

International Nuclear Information System (INIS)

Stark, P.; Harvard Medical School, Boston, MA

1981-01-01

Three cases of a pneumonic illness are described, produced by a newly discovered causal organism. This is the weakly gram negative bacterium Legionelle pneumophila. The organisms is found intracellularly and can be recognised by direct or indirect immunofluorescence or the Dieterle staining. The clinical picture is characterised by a fulminating pneumonia with accompanying diarrhoea. Treatment of choice is intravenous erythromycin. (orig.) [de

Optimal causal inference: estimating stored information and approximating causal architecture.

Science.gov (United States)

Still, Susanne; Crutchfield, James P; Ellison, Christopher J

2010-09-01

We introduce an approach to inferring the causal architecture of stochastic dynamical systems that extends rate-distortion theory to use causal shielding--a natural principle of learning. We study two distinct cases of causal inference: optimal causal filtering and optimal causal estimation. Filtering corresponds to the ideal case in which the probability distribution of measurement sequences is known, giving a principled method to approximate a system's causal structure at a desired level of representation. We show that in the limit in which a model-complexity constraint is relaxed, filtering finds the exact causal architecture of a stochastic dynamical system, known as the causal-state partition. From this, one can estimate the amount of historical information the process stores. More generally, causal filtering finds a graded model-complexity hierarchy of approximations to the causal architecture. Abrupt changes in the hierarchy, as a function of approximation, capture distinct scales of structural organization. For nonideal cases with finite data, we show how the correct number of the underlying causal states can be found by optimal causal estimation. A previously derived model-complexity control term allows us to correct for the effect of statistical fluctuations in probability estimates and thereby avoid overfitting.

Capture Hi-C identifies a novel causal gene, IL20RA, in the pan-autoimmune genetic susceptibility region 6q23.

Science.gov (United States)

McGovern, Amanda; Schoenfelder, Stefan; Martin, Paul; Massey, Jonathan; Duffus, Kate; Plant, Darren; Yarwood, Annie; Pratt, Arthur G; Anderson, Amy E; Isaacs, John D; Diboll, Julie; Thalayasingam, Nishanthi; Ospelt, Caroline; Barton, Anne; Worthington, Jane; Fraser, Peter; Eyre, Stephen; Orozco, Gisela

2016-11-01

The identification of causal genes from genome-wide association studies (GWAS) is the next important step for the translation of genetic findings into biologically meaningful mechanisms of disease and potential therapeutic targets. Using novel chromatin interaction detection techniques and allele specific assays in T and B cell lines, we provide compelling evidence that redefines causal genes at the 6q23 locus, one of the most important loci that confers autoimmunity risk. Although the function of disease-associated non-coding single nucleotide polymorphisms (SNPs) at 6q23 is unknown, the association is generally assigned to TNFAIP3, the closest gene. However, the DNA fragment containing the associated SNPs interacts through chromatin looping not only with TNFAIP3, but also with IL20RA, located 680 kb upstream. The risk allele of the most likely causal SNP, rs6927172, is correlated with both a higher frequency of interactions and increased expression of IL20RA, along with a stronger binding of both the NFκB transcription factor and chromatin marks characteristic of active enhancers in T-cells. Our results highlight the importance of gene assignment for translating GWAS findings into biologically meaningful mechanisms of disease and potential therapeutic targets; indeed, monoclonal antibody therapy targeting IL-20 is effective in the treatment of rheumatoid arthritis and psoriasis, both with strong GWAS associations to this region.

Causality

Science.gov (United States)

Pearl, Judea

2000-03-01

Written by one of the pre-eminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artifical intelligence, business, epidemiology, social science and economics. Students in these areas will find natural models, simple identification procedures, and precise mathematical definitions of causal concepts that traditional texts have tended to evade or make unduly complicated. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable.

Gene-environment interplay in depressive symptoms: moderation by age, sex, and physical illness.

Science.gov (United States)

Petkus, A J; Beam, C R; Johnson, W; Kaprio, J; Korhonen, T; McGue, M; Neiderhiser, J M; Pedersen, N L; Reynolds, C A; Gatz, M

2017-07-01

Numerous factors influence late-life depressive symptoms in adults, many not thoroughly characterized. We addressed whether genetic and environmental influences on depressive symptoms differed by age, sex, and physical illness. The analysis sample included 24 436 twins aged 40-90 years drawn from the Interplay of Genes and Environment across Multiple Studies (IGEMS) Consortium. Biometric analyses tested age, sex, and physical illness moderation of genetic and environmental variance in depressive symptoms. Women reported greater depressive symptoms than men. After age 60, there was an accelerating increase in depressive symptom scores with age, but this did not appreciably affect genetic and environmental variances. Overlap in genetic influences between physical illness and depressive symptoms was greater in men than in women. Additionally, in men extent of overlap was greater with worse physical illness (the genetic correlation ranged from near 0.00 for the least physical illness to nearly 0.60 with physical illness 2 s.d. above the mean). For men and women, the same environmental factors that influenced depressive symptoms also influenced physical illness. Findings suggested that genetic factors play a larger part in the association between depressive symptoms and physical illness for men than for women. For both sexes, across all ages, physical illness may similarly trigger social and health limitations that contribute to depressive symptoms.

Causal events enter awareness faster than non-causal events

Directory of Open Access Journals (Sweden)

Pieter Moors

2017-01-01

Full Text Available Philosophers have long argued that causality cannot be directly observed but requires a conscious inference (Hume, 1967. Albert Michotte however developed numerous visual phenomena in which people seemed to perceive causality akin to primary visual properties like colour or motion (Michotte, 1946. Michotte claimed that the perception of causality did not require a conscious, deliberate inference but, working over 70 years ago, he did not have access to the experimental methods to test this claim. Here we employ Continuous Flash Suppression (CFS—an interocular suppression technique to render stimuli invisible (Tsuchiya & Koch, 2005—to test whether causal events enter awareness faster than non-causal events. We presented observers with ‘causal’ and ‘non-causal’ events, and found consistent evidence that participants become aware of causal events more rapidly than non-causal events. Our results suggest that, whilst causality must be inferred from sensory evidence, this inference might be computed at low levels of perceptual processing, and does not depend on a deliberative conscious evaluation of the stimulus. This work therefore supports Michotte’s contention that, like colour or motion, causality is an immediate property of our perception of the world.

Theories of Causality

Science.gov (United States)

Jones, Robert

2010-03-01

There are a wide range of views on causality. To some (e.g. Karl Popper) causality is superfluous. Bertrand Russell said ``In advanced science the word cause never occurs. Causality is a relic of a bygone age.'' At the other extreme Rafael Sorkin and L. Bombelli suggest that space and time do not exist but are only an approximation to a reality that is simply a discrete ordered set, a ``causal set.'' For them causality IS reality. Others, like Judea Pearl and Nancy Cartwright are seaking to build a complex fundamental theory of causality (Causality, Cambridge Univ. Press, 2000) Or perhaps a theory of causality is simply the theory of functions. This is more or less my take on causality.

Different biogenetic causal explanations and attitudes towards persons with major depression, schizophrenia and alcohol dependence: is the concept of a chemical imbalance beneficial?

Science.gov (United States)

Speerforck, Sven; Schomerus, Georg; Pruess, Susanne; Angermeyer, Matthias C

2014-10-01

It is unclear whether different biogenetic causal beliefs affect stigmatization of mentally-ill patients differently. It has been argued that in particular believing in a 'chemical imbalance' as a cause of mental disorder might be associated with more tolerant attitudes. In a representative population survey in Germany (n=3642), using unlabelled case vignettes of persons with depression, schizophrenia, or alcohol dependence, we elicited agreement with three different biogenetic explanations of the illness: 'Chemical imbalance of the brain', 'brain disease' and 'heredity'. We further investigated emotional reactions as well as the desire for social distance. For each vignette condition we calculated linear regressions with each biogenetic explanation as independent and emotional reactions as well as social distance as dependent variable controlling for socio-demographic variables. Our cross-sectional study does not allow statements regarding causality and the explanatory power of our statistical models was low. 'Chemical imbalance of the brain' and 'brain disease' were both associated with a stronger desire for social distance in schizophrenia and depression, and with more social acceptance in alcohol dependence, whereas 'heredity' was not significantly associated with social distance in any of the investigated illnesses. All three biogenetic causal beliefs were associated with more fear in all three illnesses. Our study corroborates findings that biogenetic explanations have different effects in different disorders, and seem to be harmful in depression and schizophrenia. A particular de-stigmatizing potential of the causal belief 'chemical imbalance' could not be found. Implications for useful anti-stigma messages are discussed. Copyright © 2014 Elsevier B.V. All rights reserved.

Using genetics to test the causal relationship of total adiposity and periodontitis: Mendelian randomization analyses in the Gene-Lifestyle Interactions and Dental Endpoints (GLIDE) Consortium

Science.gov (United States)

Shungin, Dmitry; Cornelis, Marilyn C; Divaris, Kimon; Holtfreter, Birte; Shaffer, John R; Yu, Yau-Hua; Barros, Silvana P; Beck, James D; Biffar, Reiner; Boerwinkle, Eric A; Crout, Richard J.; Ganna, Andrea; Hallmans, Goran; Hindy, George; Hu, Frank B; Kraft, Peter; McNeil, Daniel W; Melander, Olle; Moss, Kevin L; North, Kari E; Orho-Melander, Marju; Pedersen, Nancy L; Ridker, Paul M; Rimm, Eric B; Rose, Lynda M; Rukh, Gull; Teumer, Alexander; Weyant, Robert J; Chasman, Daniel I; Joshipura, Kaumudi; Kocher, Thomas; Magnusson, Patrik KE; Marazita, Mary L; Nilsson, Peter; Offenbacher, Steve; Davey Smith, George; Lundberg, Pernilla; Palmer, Tom M; Timpson, Nicholas J; Johansson, Ingegerd; Franks, Paul W

2015-01-01

Background: The observational relationship between obesity and periodontitis is widely known, yet causal evidence is lacking. Our objective was to investigate causal associations between periodontitis and body mass index (BMI). Methods: We performed Mendelian randomization analyses with BMI-associated loci combined in a genetic risk score (GRS) as the instrument for BMI. All analyses were conducted within the Gene-Lifestyle Interactions and Dental Endpoints (GLIDE) Consortium in 13 studies from Europe and the USA, including 49 066 participants with clinically assessed (seven studies, 42.1% of participants) and self-reported (six studies, 57.9% of participants) periodontitis and genotype data (17 672/31 394 with/without periodontitis); 68 761 participants with BMI and genotype data; and 57 871 participants (18 881/38 990 with/without periodontitis) with data on BMI and periodontitis. Results: In the observational meta-analysis of all participants, the pooled crude observational odds ratio (OR) for periodontitis was 1.13 [95% confidence interval (CI): 1.03, 1.24] per standard deviation increase of BMI. Controlling for potential confounders attenuated this estimate (OR = 1.08; 95% CI:1.03, 1.12). For clinically assessed periodontitis, corresponding ORs were 1.25 (95% CI: 1.10, 1.42) and 1.13 (95% CI: 1.10, 1.17), respectively. In the genetic association meta-analysis, the OR for periodontitis was 1.01 (95% CI: 0.99, 1.03) per GRS unit (per one effect allele) in all participants and 1.00 (95% CI: 0.97, 1.03) in participants with clinically assessed periodontitis. The instrumental variable meta-analysis of all participants yielded an OR of 1.05 (95% CI: 0.80, 1.38) per BMI standard deviation, and 0.90 (95% CI: 0.56, 1.46) in participants with clinical data. Conclusions: Our study does not support total adiposity as a causal risk factor for periodontitis, as the point estimate is very close to the null in the causal inference analysis, with wide

Of arrows and flows. Causality, determination, and specificity in the Central Dogma of molecular biology.

Science.gov (United States)

Fantini, Bernardino

2006-01-01

From its first proposal, the Central Dogma had a graphical form, complete with arrows of different types, and this form quickly became its standard presentation. In different scientific contexts, arrows have different meanings and in this particular case the arrows indicated the flow of information among different macromolecules. A deeper analysis illustrates that the arrows also imply a causal statement, directly connected to the causal role of genetic information. The author suggests a distinction between two different kinds of causal links, defined as 'physical causality' and 'biological determination', both implied in the production of biological specificity.

Investigating the possible causal role of coffee consumption with prostate cancer risk and progression using Mendelian randomization analysis

DEFF Research Database (Denmark)

Taylor, Amy E; Martin, Richard M; Geybels, Milan S

2017-01-01

Coffee consumption has been shown in some studies to be associated with lower risk of prostate cancer. However, it is unclear if this association is causal or due to confounding or reverse causality. We conducted a Mendelian randomisation analysis to investigate the causal effects of coffee...... consumption on prostate cancer risk and progression. We used two genetic variants robustly associated with caffeine intake (rs4410790 and rs2472297) as proxies for coffee consumption in a sample of 46,687 men of European ancestry from 25 studies in the PRACTICAL consortium. Associations between genetic...... variants and prostate cancer case status, stage and grade were assessed by logistic regression and with all-cause and prostate cancer-specific mortality using Cox proportional hazards regression. There was no clear evidence that a genetic risk score combining rs4410790 and rs2472297 was associated...

Causal boundary for stably causal space-times

International Nuclear Information System (INIS)

Racz, I.

1987-12-01

The usual boundary constructions for space-times often yield an unsatisfactory boundary set. This problem is reviewed and a new solution is proposed. An explicit identification rule is given on the set of the ideal points of the space-time. This construction leads to a satisfactory boundary point set structure for stably causal space-times. The topological properties of the resulting causal boundary construction are examined. For the stably causal space-times each causal curve has a unique endpoint on the boundary set according to the extended Alexandrov topology. The extension of the space-time through the boundary is discussed. To describe the singularities the defined boundary sets have to be separated into two disjoint sets. (D.Gy.) 8 refs

"It's often liberating": consumers discuss causal beliefs in the treatment process.

Science.gov (United States)

Larkings, Josephine S; Brown, Patricia M; Scholz, Brett

2017-12-19

Causal beliefs are thought to influence consumers' perceptions of their mental illness and self-stigma, and may impact treatment and recovery. Understanding consumers' perspective on causes being addressed in treatment is vital to help guide future research and improve services. This study aimed to explore consumers' views on causes of mental illness being addressed in treatment, along with their subjective experiences of how causes were focused on in their treatment. Using a qualitative approach, semi-structured interviews were conducted with 23 consumers who self-identified as having a mental illness. A thematic analytic framework was used to identify and analyse themes that emerged within the data. Consumers believed that causes were important and should be addressed in treatment, and identified several associated benefits including increased insight/personal understanding of their illness, symptom management and relapse prevention and reduced self-blame. Negative consequences and considerations were also identified. Causes help consumers make sense of their illness, and consumers would like causes to be addressed in treatment. More research is needed on how mental health professionals can address causes effectively as consumers are currently dissatisfied with how causes were discussed in their treatment.

Causal universe

CERN Document Server

Ellis, George FR; Pabjan, Tadeusz

2013-01-01

Written by philosophers, cosmologists, and physicists, this collection of essays deals with causality, which is a core issue for both science and philosophy. Readers will learn about different types of causality in complex systems and about new perspectives on this issue based on physical and cosmological considerations. In addition, the book includes essays pertaining to the problem of causality in ancient Greek philosophy, and to the problem of God's relation to the causal structures of nature viewed in the light of contemporary physics and cosmology.

Local Genetic Correlation Gives Insights into the Shared Genetic Architecture of Complex Traits.

Science.gov (United States)

Shi, Huwenbo; Mancuso, Nicholas; Spendlove, Sarah; Pasaniuc, Bogdan

2017-11-02

Although genetic correlations between complex traits provide valuable insights into epidemiological and etiological studies, a precise quantification of which genomic regions disproportionately contribute to the genome-wide correlation is currently lacking. Here, we introduce ρ-HESS, a technique to quantify the correlation between pairs of traits due to genetic variation at a small region in the genome. Our approach requires GWAS summary data only and makes no distributional assumption on the causal variant effect sizes while accounting for linkage disequilibrium (LD) and overlapping GWAS samples. We analyzed large-scale GWAS summary data across 36 quantitative traits, and identified 25 genomic regions that contribute significantly to the genetic correlation among these traits. Notably, we find 6 genomic regions that contribute to the genetic correlation of 10 pairs of traits that show negligible genome-wide correlation, further showcasing the power of local genetic correlation analyses. Finally, we report the distribution of local genetic correlations across the genome for 55 pairs of traits that show putative causal relationships. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Causal relationship: a new tool for the causal characterization of Lorentzian manifolds

International Nuclear Information System (INIS)

Garcia-Parrado, Alfonso; Senovilla, Jose M M

2003-01-01

We define and study a new kind of relation between two diffeomorphic Lorentzian manifolds called a causal relation, which is any diffeomorphism characterized by mapping every causal vector of the first manifold onto a causal vector of the second. We perform a thorough study of the mathematical properties of causal relations and prove in particular that two given Lorentzian manifolds (say V and W) may be causally related only in one direction (say from V to W, but not from W to V). This leads us to the concept of causally equivalent (or isocausal in short) Lorentzian manifolds as those mutually causally related and to a definition of causal structure over a differentiable manifold as the equivalence class formed by isocausal Lorentzian metrics upon it. Isocausality is a more general concept than the conformal relationship, because we prove the remarkable result that a conformal relation φ is characterized by the fact of being a causal relation of the particular kind in which both φ and φ -1 are causal relations. Isocausal Lorentzian manifolds are mutually causally compatible, they share some important causal properties, and there are one-to-one correspondences, which are sometimes non-trivial, between several classes of their respective future (and past) objects. A more important feature is that they satisfy the same standard causality constraints. We also introduce a partial order for the equivalence classes of isocausal Lorentzian manifolds providing a classification of all the causal structures that a given fixed manifold can have. By introducing the concept of causal extension we put forward a new definition of causal boundary for Lorentzian manifolds based on the concept of isocausality, and thereby we generalize the traditional Penrose constructions of conformal infinity, diagrams and embeddings. In particular, the concept of causal diagram is given. Many explicit clarifying examples are presented throughout the paper

Investigating causality in the association between 25(OH)D and schizophrenia.

Science.gov (United States)

Taylor, Amy E; Burgess, Stephen; Ware, Jennifer J; Gage, Suzanne H; Richards, J Brent; Davey Smith, George; Munafò, Marcus R

2016-05-24

Vitamin D deficiency is associated with increased risk of schizophrenia. However, it is not known whether this association is causal or what the direction of causality is. We performed two sample bidirectional Mendelian randomization analysis using single nucleotide polymorphisms (SNPs) robustly associated with serum 25(OH)D to investigate the causal effect of 25(OH)D on risk of schizophrenia, and SNPs robustly associated with schizophrenia to investigate the causal effect of schizophrenia on 25(OH)D. We used summary data from genome-wide association studies and meta-analyses of schizophrenia and 25(OH)D to obtain betas and standard errors for the SNP-exposure and SNP-outcome associations. These were combined using inverse variance weighted fixed effects meta-analyses. In 34,241 schizophrenia cases and 45,604 controls, there was no clear evidence for a causal effect of 25(OH)D on schizophrenia risk. The odds ratio for schizophrenia per 10% increase in 25(OH)D conferred by the four 25(OH)D increasing SNPs was 0.992 (95% CI: 0.969 to 1.015). In up to 16,125 individuals with measured serum 25(OH)D, there was no clear evidence that genetic risk for schizophrenia causally lowers serum 25(OH)D. These findings suggest that associations between schizophrenia and serum 25(OH)D may not be causal. Therefore, vitamin D supplementation may not prevent schizophrenia.

Rethinking platelet function: thrombocytopenia induced immunodeficiency in critical illness

DEFF Research Database (Denmark)

Ostrowski, Sisse R; Johansson, Per Ingemar

2011-01-01

Thrombocytopenia in critical illness predicts a poor clinical outcome. Apart from its role in microvascular thrombus formation, it is widely anticipated that this association is indirect rather than causal. Emerging evidence however indicates that platelets are also immune competent cells. Like...... per se results in immunodeficiency through loss of platelet-mediated immune functions, and propose that thrombocytopenia induced immunodeficiency in critical illness in part explain the negative predictive value of low or declining platelet count. We propose that rethinking the risks...... of thrombocytopenia to include not only bleeding but also immunodeficiency and immune dysregulation along with the conduct of studies investigating mechanisms contributing to thrombocytopenia induced poor non-hemorrhagic outcome in critical illness, may be means to improve outcome in these patients through...

Illness beliefs and psychological outcome in people with Parkinson's disease.

Science.gov (United States)

Simpson, Jane; Lekwuwa, Godwin; Crawford, Trevor

2013-06-01

Illness beliefs are important predictors of psychological outcome in people with chronic illness and evidence suggests these could also be significant in furthering our understanding of psychological functioning in people with Parkinson's disease. Illness beliefs are specific, dynamic representations of an illness and cover dimensions such as cause, identity, consequences and controllability. Eighty-one people with Parkinson's disease completed a series of questionnaires to provide demographic, clinical and psychosocial data, which were then used to assess the relative impact of illness beliefs on their psychological functioning. Psychological functioning was assessed by measuring levels of depression, anxiety, stress, positive affect and emotional well-being. Hierarchical block regression indicated that illness beliefs were important independent predictors across some but not all outcomes and the results emphasised the importance of testing new predictors against more established predictors of outcome such as physical functioning and self-esteem. The illness beliefs most important in psychological outcome in people with PD were causal beliefs (particularly in psychosocial causes) and illness coherence (the level of understanding of the illness). The therapeutic potential of psychosocial variables was discussed given that these can be modified during therapy and this change can positively influence psychological outcome.

Experiencing the genetic body: parents' encounters with pediatric clinical genetics.

Science.gov (United States)

Raspberry, Kelly; Skinner, Debra

2007-01-01

Because of advancements in genetic research and technologies, the clinical practice of genetics is becoming a prevalent component of biomedicine. As the genetic basis for more and more diseases are found, it is possible that ways of experiencing health, illness, identity, kin relations, and the body are becoming geneticized, or understood within a genetic model of disease. Yet, other models and relations that go beyond genetic explanations also shape interpretations of health and disease. This article explores how one group of individuals for whom genetic disorder is highly relevant formulates their views of the body in light of genetic knowledge. Using data from an ethnographic study of 106 parents or potential parents of children with known or suspected genetic disorders who were referred to a pediatric genetic counseling and evaluation clinic in the southeastern United States, we find that these parents do, to some degree, perceive of their children's disorders in terms of a genetic body that encompasses two principal qualities: a sense of predetermined health and illness and an awareness of a profound historicity that reaches into the past and extends into the present and future. They experience this genetic body as both fixed and historical, but they also express ideas of a genetic body made less deterministic by their own efforts and future possibilities. This account of parents' experiences with genetics and clinical practice contributes to a growing body of work on the ways in which genetic information and technologies are transforming popular and medical notions of the body, and with it, health, illness, kinship relations, and personal and social identities.

The dappled nature of causes of psychiatric illness: replacing the organic-functional/hardware-software dichotomy with empirically based pluralism.

Science.gov (United States)

Kendler, K S

2012-04-01

Our tendency to see the world of psychiatric illness in dichotomous and opposing terms has three major sources: the philosophy of Descartes, the state of neuropathology in late nineteenth century Europe (when disorders were divided into those with and without demonstrable pathology and labeled, respectively, organic and functional), and the influential concept of computer functionalism wherein the computer is viewed as a model for the human mind-brain system (brain=hardware, mind=software). These mutually re-enforcing dichotomies, which have had a pernicious influence on our field, make a clear prediction about how 'difference-makers' (aka causal risk factors) for psychiatric disorders should be distributed in nature. In particular, are psychiatric disorders like our laptops, which when they dysfunction, can be cleanly divided into those with software versus hardware problems? I propose 11 categories of difference-makers for psychiatric illness from molecular genetics through culture and review their distribution in schizophrenia, major depression and alcohol dependence. In no case do these distributions resemble that predicted by the organic-functional/hardware-software dichotomy. Instead, the causes of psychiatric illness are dappled, distributed widely across multiple categories. We should abandon Cartesian and computer-functionalism-based dichotomies as scientifically inadequate and an impediment to our ability to integrate the diverse information about psychiatric illness our research has produced. Empirically based pluralism provides a rigorous but dappled view of the etiology of psychiatric illness. Critically, it is based not on how we wish the world to be but how the difference-makers for psychiatric illness are in fact distributed.

Genetics, mental illness, and complex disease: development and distribution of an interactive CD-ROM for genetic counselors. Final report for period 15 August 2000 - 31 December 2002

Energy Technology Data Exchange (ETDEWEB)

McInerney, Joseph D.

2003-03-31

"Genetics and Major Psychiatric Disorders: A Program for Genetic Counselors" provides an introduction to psychiatric genetics, with a focus on the genetics of common complex disease, for genetics professionals. The program is available as a CD-ROM and an online educational resource. The on-line version requires a direct internet connection. Each educational module begins with an interactive case study that raises significant issues addressed in each module. In addition, case studies provided throughout the educational materials support teaching of major concepts. Incorporated throughout the content are expert video clips, video clips from individuals affected by psychiatric illness, and optional "learn more" materials that offer greater depth about a particular topic. The structure of the CD-ROM permits self-navigation, but we have suggested a sequence that allows materials to build upon each other. At any point in the materials, users may pause and look up terms in the glossary or review the DSM-IV criteria for selected psychiatric disorders. A detailed site map is available for those who choose to self navigate through the content.

Causal ubiquity in quantum physics. A superluminal and local-causal physical ontology

International Nuclear Information System (INIS)

Neelamkavil, Raphael

2014-01-01

A fixed highest criterial velocity (of light) in STR (special theory of relativity) is a convention for a layer of physical inquiry. QM (Quantum Mechanics) avoids action-at-a-distance using this concept, but accepts non-causality and action-at-a-distance in EPR (Einstein-Podolsky-Rosen-Paradox) entanglement experiments. Even in such allegedly [non-causal] processes, something exists processually in extension-motion, between the causal and the [non-causal]. If STR theoretically allows real-valued superluminal communication between EPR entangled particles, quantum processes become fully causal. That is, the QM world is sub-luminally, luminally and superluminally local-causal throughout, and the Law of Causality is ubiquitous in the micro-world. Thus, ''probabilistic causality'' is a merely epistemic term.

Causal ubiquity in quantum physics. A superluminal and local-causal physical ontology

Energy Technology Data Exchange (ETDEWEB)

Neelamkavil, Raphael

2014-07-01

A fixed highest criterial velocity (of light) in STR (special theory of relativity) is a convention for a layer of physical inquiry. QM (Quantum Mechanics) avoids action-at-a-distance using this concept, but accepts non-causality and action-at-a-distance in EPR (Einstein-Podolsky-Rosen-Paradox) entanglement experiments. Even in such allegedly [non-causal] processes, something exists processually in extension-motion, between the causal and the [non-causal]. If STR theoretically allows real-valued superluminal communication between EPR entangled particles, quantum processes become fully causal. That is, the QM world is sub-luminally, luminally and superluminally local-causal throughout, and the Law of Causality is ubiquitous in the micro-world. Thus, ''probabilistic causality'' is a merely epistemic term.

Causality in Science

Directory of Open Access Journals (Sweden)

Cristina Puente Águeda

2011-10-01

Full Text Available Causality is a fundamental notion in every field of science. Since the times of Aristotle, causal relationships have been a matter of study as a way to generate knowledge and provide for explanations. In this paper I review the notion of causality through different scientific areas such as physics, biology, engineering, etc. In the scientific area, causality is usually seen as a precise relation: the same cause provokes always the same effect. But in the everyday world, the links between cause and effect are frequently imprecise or imperfect in nature. Fuzzy logic offers an adequate framework for dealing with imperfect causality, so a few notions of fuzzy causality are introduced.

Causal Association of Overall Obesity and Abdominal Obesity with Type 2 Diabetes: A Mendelian Randomization Analysis.

Science.gov (United States)

Wang, Tao; Zhang, Rong; Ma, Xiaojing; Wang, Shiyun; He, Zhen; Huang, Yeping; Xu, Bo; Li, Yangyang; Zhang, Hong; Jiang, Feng; Bao, Yuqian; Hu, Cheng; Jia, Weiping

2018-05-01

This study aimed to compare the causal effect of overall obesity and abdominal obesity on type 2 diabetes among Chinese Han individuals. The causal relationship of BMI and waist-to-hip ratio (WHR) with the risk of glucose deterioration and glycemic traits was compared using two different genetic instruments based on 30 BMI loci and 6 WHR loci with Mendelian randomization (MR) in three prospective cohorts (n = 6,476). Each 1-SD genetically instrumented higher WHR was associated with a 65.7% higher risk of glucose deterioration (95% CI = 1.069-2.569, P = 0.024), whereas no significant association of BMI with glucose deterioration was observed. Furthermore, a causal relationship was found only between BMI and homeostatic model assessment β-cell function (HOMA-B) (β = 0.143, P = 0.001), and there was a nominal association with Stumvoll second-phase insulin secretion traits (β = 0.074, P = 0.022). The significance level did not persist in sensitivity analyses, except in the causal estimate of WHR on the Gutt index in MR-Egger (β = -0.379, P = 0.022) and the causal estimate of BMI on homeostatic model assessment β-cell function in weighted median MR (β = 0.128, P = 0.017). The data from this study support the potential causal relationship between abdominal obesity and hyperglycemia, which may be driven by aggravated insulin resistance, in contrast with the potential causal relationship between overall obesity and insulin secretion. © 2018 The Obesity Society.

A theory of causal learning in children: causal maps and Bayes nets.

Science.gov (United States)

Gopnik, Alison; Glymour, Clark; Sobel, David M; Schulz, Laura E; Kushnir, Tamar; Danks, David

2004-01-01

The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or Bayes nets. Children's causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest that 2- to 4-year-old children construct new causal maps and that their learning is consistent with the Bayes net formalism.

Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression.

Science.gov (United States)

Wray, Naomi R; Ripke, Stephan; Mattheisen, Manuel; Trzaskowski, Maciej; Byrne, Enda M; Abdellaoui, Abdel; Adams, Mark J; Agerbo, Esben; Air, Tracy M; Andlauer, Till M F; Bacanu, Silviu-Alin; Bækvad-Hansen, Marie; Beekman, Aartjan F T; Bigdeli, Tim B; Binder, Elisabeth B; Blackwood, Douglas R H; Bryois, Julien; Buttenschøn, Henriette N; Bybjerg-Grauholm, Jonas; Cai, Na; Castelao, Enrique; Christensen, Jane Hvarregaard; Clarke, Toni-Kim; Coleman, Jonathan I R; Colodro-Conde, Lucía; Couvy-Duchesne, Baptiste; Craddock, Nick; Crawford, Gregory E; Crowley, Cheynna A; Dashti, Hassan S; Davies, Gail; Deary, Ian J; Degenhardt, Franziska; Derks, Eske M; Direk, Nese; Dolan, Conor V; Dunn, Erin C; Eley, Thalia C; Eriksson, Nicholas; Escott-Price, Valentina; Kiadeh, Farnush Hassan Farhadi; Finucane, Hilary K; Forstner, Andreas J; Frank, Josef; Gaspar, Héléna A; Gill, Michael; Giusti-Rodríguez, Paola; Goes, Fernando S; Gordon, Scott D; Grove, Jakob; Hall, Lynsey S; Hannon, Eilis; Hansen, Christine Søholm; Hansen, Thomas F; Herms, Stefan; Hickie, Ian B; Hoffmann, Per; Homuth, Georg; Horn, Carsten; Hottenga, Jouke-Jan; Hougaard, David M; Hu, Ming; Hyde, Craig L; Ising, Marcus; Jansen, Rick; Jin, Fulai; Jorgenson, Eric; Knowles, James A; Kohane, Isaac S; Kraft, Julia; Kretzschmar, Warren W; Krogh, Jesper; Kutalik, Zoltán; Lane, Jacqueline M; Li, Yihan; Li, Yun; Lind, Penelope A; Liu, Xiaoxiao; Lu, Leina; MacIntyre, Donald J; MacKinnon, Dean F; Maier, Robert M; Maier, Wolfgang; Marchini, Jonathan; Mbarek, Hamdi; McGrath, Patrick; McGuffin, Peter; Medland, Sarah E; Mehta, Divya; Middeldorp, Christel M; Mihailov, Evelin; Milaneschi, Yuri; Milani, Lili; Mill, Jonathan; Mondimore, Francis M; Montgomery, Grant W; Mostafavi, Sara; Mullins, Niamh; Nauck, Matthias; Ng, Bernard; Nivard, Michel G; Nyholt, Dale R; O'Reilly, Paul F; Oskarsson, Hogni; Owen, Michael J; Painter, Jodie N; Pedersen, Carsten Bøcker; Pedersen, Marianne Giørtz; Peterson, Roseann E; Pettersson, Erik; Peyrot, Wouter J; Pistis, Giorgio; Posthuma, Danielle; Purcell, Shaun M; Quiroz, Jorge A; Qvist, Per; Rice, John P; Riley, Brien P; Rivera, Margarita; Saeed Mirza, Saira; Saxena, Richa; Schoevers, Robert; Schulte, Eva C; Shen, Ling; Shi, Jianxin; Shyn, Stanley I; Sigurdsson, Engilbert; Sinnamon, Grant B C; Smit, Johannes H; Smith, Daniel J; Stefansson, Hreinn; Steinberg, Stacy; Stockmeier, Craig A; Streit, Fabian; Strohmaier, Jana; Tansey, Katherine E; Teismann, Henning; Teumer, Alexander; Thompson, Wesley; Thomson, Pippa A; Thorgeirsson, Thorgeir E; Tian, Chao; Traylor, Matthew; Treutlein, Jens; Trubetskoy, Vassily; Uitterlinden, André G; Umbricht, Daniel; Van der Auwera, Sandra; van Hemert, Albert M; Viktorin, Alexander; Visscher, Peter M; Wang, Yunpeng; Webb, Bradley T; Weinsheimer, Shantel Marie; Wellmann, Jürgen; Willemsen, Gonneke; Witt, Stephanie H; Wu, Yang; Xi, Hualin S; Yang, Jian; Zhang, Futao; Arolt, Volker; Baune, Bernhard T; Berger, Klaus; Boomsma, Dorret I; Cichon, Sven; Dannlowski, Udo; de Geus, E C J; DePaulo, J Raymond; Domenici, Enrico; Domschke, Katharina; Esko, Tõnu; Grabe, Hans J; Hamilton, Steven P; Hayward, Caroline; Heath, Andrew C; Hinds, David A; Kendler, Kenneth S; Kloiber, Stefan; Lewis, Glyn; Li, Qingqin S; Lucae, Susanne; Madden, Pamela F A; Magnusson, Patrik K; Martin, Nicholas G; McIntosh, Andrew M; Metspalu, Andres; Mors, Ole; Mortensen, Preben Bo; Müller-Myhsok, Bertram; Nordentoft, Merete; Nöthen, Markus M; O'Donovan, Michael C; Paciga, Sara A; Pedersen, Nancy L; Penninx, Brenda W J H; Perlis, Roy H; Porteous, David J; Potash, James B; Preisig, Martin; Rietschel, Marcella; Schaefer, Catherine; Schulze, Thomas G; Smoller, Jordan W; Stefansson, Kari; Tiemeier, Henning; Uher, Rudolf; Völzke, Henry; Weissman, Myrna M; Werge, Thomas; Winslow, Ashley R; Lewis, Cathryn M; Levinson, Douglas F; Breen, Gerome; Børglum, Anders D; Sullivan, Patrick F

2018-05-01

Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.

Work overload, burnout, and psychological ill-health symptoms: a three-wave mediation model of the employee health impairment process.

Science.gov (United States)

de Beer, Leon T; Pienaar, Jaco; Rothmann, Sebastiaan

2016-07-01

The study reported here investigated the causal relationships in the health impairment process of employee well-being, and the mediating role of burnout in the relationship between work overload and psychological ill-health symptoms, over time. The research is deemed important due to the need for longitudinal evidence of the health impairment process of employee well-being over three waves of data. A quantitative survey design was followed. Participants constituted a longitudinal sample of 370 participants, at three time points, after attrition. Descriptive statistics and structural equation modeling methods were implemented. Work overload at time one predicted burnout at time two, and burnout at time two predicted psychological ill-health symptoms at time three. Indirect effects were found between work overload time one and psychological ill-health symptoms time three via burnout time two, and also between burnout time one and psychological ill-health symptoms time three, via burnout time two. The results provided supportive evidence for an "indirect-only" mediation effect, for burnout's causal mediation mechanism in the health impairment process between work overload and psychological ill-health symptoms.

An implicit measure of associations with mental illness versus physical illness: response latency decomposition and stimuli differential functioning in relation to IAT order of associative conditions and accuracy.

Science.gov (United States)

Mannarini, Stefania; Boffo, Marilisa

2014-01-01

The present study aimed at the definition of a latent measurement dimension underlying an implicit measure of automatic associations between the concept of mental illness and the psychosocial and biogenetic causal explanatory attributes. To this end, an Implicit Association Test (IAT) assessing the association between the Mental Illness and Physical Illness target categories to the Psychological and Biologic attribute categories, representative of the causal explanation domains, was developed. The IAT presented 22 stimuli (words and pictures) to be categorized into the four categories. After 360 university students completed the IAT, a Many-Facet Rasch Measurement (MFRM) modelling approach was applied. The model specified a person latency parameter and a stimulus latency parameter. Two additional parameters were introduced to denote the order of presentation of the task associative conditions and the general response accuracy. Beyond the overall definition of the latent measurement dimension, the MFRM was also applied to disentangle the effect of the task block order and the general response accuracy on the stimuli response latency. Further, the MFRM allowed detecting any differential functioning of each stimulus in relation to both block ordering and accuracy. The results evidenced: a) the existence of a latency measurement dimension underlying the Mental Illness versus Physical Illness - Implicit Association Test; b) significant effects of block order and accuracy on the overall latency; c) a differential functioning of specific stimuli. The results of the present study can contribute to a better understanding of the functioning of an implicit measure of semantic associations with mental illness and give a first blueprint for the examination of relevant issues in the development of an IAT.

Lipoprotein(a) and ischemic heart disease-A causal association? A review

DEFF Research Database (Denmark)

Kamstrup, P.R.

2010-01-01

association of LPA copy number variants, influencing levels of lipoprotein(a), with risk of IHD. In conclusion, results from epidemiologic, in vitro, animal, and genetic epidemiologic studies support a causal association of lipoprotein(a) with risk of IHD, while results from randomized clinical trials...

Children's conceptions of mental illness: a naïve theory approach.

Science.gov (United States)

Fox, Claudine; Buchanan-Barrow, Eithne; Barrett, Martyn

2010-09-01

This paper reports two studies that investigated children's conceptions of mental illness using a naïve theory approach, drawing upon a conceptual framework for analysing illness representations which distinguishes between the identity, causes, consequences, curability, and timeline of an illness. The studies utilized semi-structured interviewing and card selection tasks to assess 6- to 11-year-old children's conceptions of the causes and consequences (Study 1) and the curability and timeline (Study 2) of different mental and physical illnesses/ailments. The studies revealed that, at all ages, the children held coherent causal-explanatory ideas about the causes, consequences, curability, and timeline of both mental and physical illnesses/ailments. However, while younger children tended to rely on their knowledge of common physical illnesses when thinking about mental illnesses, providing contagion and contamination explanations of cause, older children demonstrated differences in their thinking about mental and physical illnesses. No substantial gender differences were found in the children's thinking. It is argued that children hold coherent conceptions of mental illness at all ages, but that mental illness only emerges as an ontologically distinct conceptual domain by the end of middle childhood.

Gene-Environment Interactions in Severe Mental Illness

Directory of Open Access Journals (Sweden)

Rudolf eUher

2014-05-01

Full Text Available Severe mental illness is a broad category that includes schizophrenia, bipolar disorder and severe depression. Both genetic disposition and environmental exposures play important roles in the development of severe mental illness. Multiple lines of evidence suggest that the roles of genetic and environmental depend on each other. Gene-environment interactions may underlie the paradox of strong environmental factors for highly heritable disorders, the low estimates of shared environmental influences in twin studies of severe mental illness and the heritability gap between twin and molecular heritability estimates. Sons and daughters of parents with severe mental illness are more vulnerable to the effects of prenatal and postnatal environmental exposures, suggesting that the expression of genetic liability depends on environment. In the last decade, gene-environment interactions involving specific molecular variants in candidate genes have been identified. Replicated findings include an interaction between a polymorphism in the AKT1 gene and cannabis use in the development of psychosis and an interaction between the length polymorphism of the serotonin transporter gene and childhood maltreatment in the development of persistent depressive disorder. Bipolar disorder has been underinvestigated, with only a single study showing an interaction between a functional polymorphism in BDNF and stressful life events triggering bipolar depressive episodes. The first systematic search for gene-environment interactions has found that a polymorphism in CTNNA3 may sensitise the developing brain to the pathogenic effect of cytomegalovirus in utero, leading to schizophrenia in adulthood. Strategies for genome-wide investigations will likely include coordination between epidemiological and genetic research efforts, systematic assessment of multiple environmental factors in large samples, and prioritization of genetic variants.

Exploring Relationships Among Belief in Genetic Determinism, Genetics Knowledge, and Social Factors

Science.gov (United States)

Gericke, Niklas; Carver, Rebecca; Castéra, Jérémy; Evangelista, Neima Alice Menezes; Marre, Claire Coiffard; El-Hani, Charbel N.

2017-12-01

Genetic determinism can be described as the attribution of the formation of traits to genes, where genes are ascribed more causal power than what scientific consensus suggests. Belief in genetic determinism is an educational problem because it contradicts scientific knowledge, and is a societal problem because it has the potential to foster intolerant attitudes such as racism and prejudice against sexual orientation. In this article, we begin by investigating the very nature of belief in genetic determinism. Then, we investigate whether knowledge of genetics and genomics is associated with beliefs in genetic determinism. Finally, we explore the extent to which social factors such as gender, education, and religiosity are associated with genetic determinism. Methodologically, we gathered and analyzed data on beliefs in genetic determinism, knowledge of genetics and genomics, and social variables using the "Public Understanding and Attitudes towards Genetics and Genomics" (PUGGS) instrument. Our analyses of PUGGS responses from a sample of Brazilian university freshmen undergraduates indicated that (1) belief in genetic determinism was best characterized as a construct built up by two dimensions or belief systems: beliefs concerning social traits and beliefs concerning biological traits; (2) levels of belief in genetic determination of social traits were low, which contradicts prior work; (3) associations between knowledge of genetics and genomics and levels of belief in genetic determinism were low; and (4) social factors such as age and religiosity had stronger associations with beliefs in genetic determinism than knowledge. Although our study design precludes causal inferences, our results raise questions about whether enhancing genetic literacy will decrease or prevent beliefs in genetic determinism.

Genetics of Adverse Reactions to Haloperidol in a Mouse Diallel: A Drug–Placebo Experiment and Bayesian Causal Analysis

Science.gov (United States)

Crowley, James J.; Kim, Yunjung; Lenarcic, Alan B.; Quackenbush, Corey R.; Barrick, Cordelia J.; Adkins, Daniel E.; Shaw, Ginger S.; Miller, Darla R.; de Villena, Fernando Pardo-Manuel; Sullivan, Patrick F.; Valdar, William

2014-01-01

Haloperidol is an efficacious antipsychotic drug that has serious, unpredictable motor side effects that limit its utility and cause noncompliance in many patients. Using a drug–placebo diallel of the eight founder strains of the Collaborative Cross and their F1 hybrids, we characterized aggregate effects of genetics, sex, parent of origin, and their combinations on haloperidol response. Treating matched pairs of both sexes with drug or placebo, we measured changes in the following: open field activity, inclined screen rigidity, orofacial movements, prepulse inhibition of the acoustic startle response, plasma and brain drug level measurements, and body weight. To understand the genetic architecture of haloperidol response we introduce new statistical methodology linking heritable variation with causal effect of drug treatment. Our new estimators, “difference of models” and “multiple-impute matched pairs”, are motivated by the Neyman–Rubin potential outcomes framework and extend our existing Bayesian hierarchical model for the diallel (Lenarcic et al. 2012). Drug-induced rigidity after chronic treatment was affected by mainly additive genetics and parent-of-origin effects (accounting for 28% and 14.8% of the variance), with NZO/HILtJ and 129S1/SvlmJ contributions tending to increase this side effect. Locomotor activity after acute treatment, by contrast, was more affected by strain-specific inbreeding (12.8%). In addition to drug response phenotypes, we examined diallel effects on behavior before treatment and found not only effects of additive genetics (10.2–53.2%) but also strong effects of epistasis (10.64–25.2%). In particular: prepulse inhibition showed additivity and epistasis in about equal proportions (26.1% and 23.7%); there was evidence of nonreciprocal epistasis in pretreatment activity and rigidity; and we estimated a range of effects on body weight that replicate those found in our previous work. Our results provide the first

Causal reasoning in physics

CERN Document Server

Frisch, Mathias

2014-01-01

Much has been written on the role of causal notions and causal reasoning in the so-called 'special sciences' and in common sense. But does causal reasoning also play a role in physics? Mathias Frisch argues that, contrary to what influential philosophical arguments purport to show, the answer is yes. Time-asymmetric causal structures are as integral a part of the representational toolkit of physics as a theory's dynamical equations. Frisch develops his argument partly through a critique of anti-causal arguments and partly through a detailed examination of actual examples of causal notions in physics, including causal principles invoked in linear response theory and in representations of radiation phenomena. Offering a new perspective on the nature of scientific theories and causal reasoning, this book will be of interest to professional philosophers, graduate students, and anyone interested in the role of causal thinking in science.

Assessment of explanatory models of mental illness: effects of patient and interviewer characteristics

NARCIS (Netherlands)

Ghane, S.; Kolk, A.M.; Emmelkamp, P.M.G.

2010-01-01

Background: Explanatory models (EMs) refer to patients’ causal attributions of illness and have been shown to affect treatment preference and outcome. Reliable and valid assessment of EMs may be hindered by interviewer and respondent disparities on certain demographic characteristics, such as

A theory of causal learning in children: Causal maps and Bayes nets

OpenAIRE

Gopnik, A; Glymour, C; Sobel, D M; Schulz, L E; Kushnir, T; Danks, D

2004-01-01

The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or Bayes nets. Children's causal learning and inference may involve computatio...

Illness Causation and Interpretation in a Newar Town

Directory of Open Access Journals (Sweden)

Madhusudan Subedi

2012-06-01

Full Text Available One of the core concerns of medical anthropology is to explore how people in different cultures and social groups explain the causes of ill health, the type of treatment they believe in, and to whom they turn if they do become ill. This article focuses on the understanding of illness causation by the Newars in Kirtipur and their concern about biological and socio-cultural aspects of healthy behavior, and particularly with the ways in which they have been coping in everyday life. The basic method of data collection for this study was formal and informal discussions with the elderly Newar males and females, followed by discussions with youths to explore the variations in their perceptions. The findings show that the understanding of illness etiology is multi-causal. The individual, natural, social, and supernatural causes are not mutually exclusive but are usually linked together in a particular case. In any specific case of illness, moreover, people’s explanatory model varies in how they explain its etiology.DOI: http://dx.doi.org/10.3126/dsaj.v5i0.6358 Dhaulagiri Journal of Sociology and Anthropology Vol. 5, 2011: 101-120    

Repeated causal decision making.

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Hagmayer, York; Meder, Björn

2013-01-01

Many of our decisions refer to actions that have a causal impact on the external environment. Such actions may not only allow for the mere learning of expected values or utilities but also for acquiring knowledge about the causal structure of our world. We used a repeated decision-making paradigm to examine what kind of knowledge people acquire in such situations and how they use their knowledge to adapt to changes in the decision context. Our studies show that decision makers' behavior is strongly contingent on their causal beliefs and that people exploit their causal knowledge to assess the consequences of changes in the decision problem. A high consistency between hypotheses about causal structure, causally expected values, and actual choices was observed. The experiments show that (a) existing causal hypotheses guide the interpretation of decision feedback, (b) consequences of decisions are used to revise existing causal beliefs, and (c) decision makers use the experienced feedback to induce a causal model of the choice situation even when they have no initial causal hypotheses, which (d) enables them to adapt their choices to changes of the decision problem. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Exploring Relationships among Belief in Genetic Determinism, Genetics Knowledge, and Social Factors

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Gericke, Niklas; Carver, Rebecca; Castéra, Jérémy; Evangelista, Neima Alice Menezes; Marre, Claire Coiffard; El-Hani, Charbel N.

2017-01-01

Genetic determinism can be described as the attribution of the formation of traits to genes, where genes are ascribed more causal power than what scientific consensus suggests. Belief in genetic determinism is an educational problem because it contradicts scientific knowledge, and is a societal problem because it has the potential to foster…

Causal beliefs about intellectual disability and schizophrenia and their relationship with awareness of the condition and social distance.

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Scior, Katrina; Furnham, Adrian

2016-09-30

Evidence on mental illness stigma abounds yet little is known about public perceptions of intellectual disability. This study examined causal beliefs about intellectual disability and schizophrenia and how these relate to awareness of the condition and social distance. UK lay people aged 16+(N=1752), in response to vignettes depicting intellectual disability and schizophrenia, noted their interpretation of the difficulties, and rated their agreement with 22 causal and four social distance items. They were most likely to endorse environmental causes for intellectual disability, and biomedical factors, trauma and early disadvantage for schizophrenia. Accurate identification of both vignettes was associated with stronger endorsement of biomedical causes, alongside weaker endorsement of adversity, environmental and supernatural causes. Biomedical causal beliefs and social distance were negatively correlated for intellectual disability, but not for schizophrenia. Causal beliefs mediated the relationship between identification of the condition and social distance for both conditions. While all four types of causal beliefs acted as mediators for intellectual disability, for schizophrenia only supernatural causal beliefs did. Educating the public and promoting certain causal beliefs may be of benefit in tackling intellectual disability stigma, but for schizophrenia, other than tackling supernatural attributions, may be of little benefit in reducing stigma. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Celiac disease : moving from genetic associations to causal variants

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Hrdlickova, B.; Westra, H-J; Franke, L.; Wijmenga, C.

Genome-wide association studies are providing insight into the genetic basis of common complex diseases: more than 1150 genetic loci [2165 unique single nucleotide polymorphisms (SNPs)] have recently been associated to 159 complex diseases. The hunt for genes contributing to immune-related diseases

Causal ubiquity in quantum physics a superluminal and local-causal physical ontology

CERN Document Server

Neelamkavil, Raphael

2014-01-01

A fixed highest criterial velocity (of light) in STR (special theory of relativity) is a convention for a layer of physical inquiry. QM (Quantum Mechanics) avoids action-at-a-distance using this concept, but accepts non-causality and action-at-a-distance in EPR (Einstein-Podolsky-Rosen-Paradox) entanglement experiments. Even in such allegedly non-causal processes, something exists processually in extension-motion, between the causal and the non-causal. If STR theoretically allows real-valued superluminal communication between EPR entangled particles, quantum processes become fully causal. That

Mendelian Randomisation Studies Do Not Support a Causal Role for Reduced Circulating Adiponectin Levels in Insulin Resistance and Type 2 Diabetes

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Yaghootkar, Hanieh; Lamina, Claudia; Scott, Robert A

2013-01-01

Adiponectin is strongly inversely associated with insulin resistance and type 2 diabetes but its causal role remains controversial. We used a Mendelian randomisation approach to test the hypothesis that adiponectin causally influences insulin resistance and type 2 diabetes. We used genetic varian...

Non-Causal Computation

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Ämin Baumeler

2017-07-01

Full Text Available Computation models such as circuits describe sequences of computation steps that are carried out one after the other. In other words, algorithm design is traditionally subject to the restriction imposed by a fixed causal order. We address a novel computing paradigm beyond quantum computing, replacing this assumption by mere logical consistency: We study non-causal circuits, where a fixed time structure within a gate is locally assumed whilst the global causal structure between the gates is dropped. We present examples of logically consistent non-causal circuits outperforming all causal ones; they imply that suppressing loops entirely is more restrictive than just avoiding the contradictions they can give rise to. That fact is already known for correlations as well as for communication, and we here extend it to computation.

Causality re-established.

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D'Ariano, Giacomo Mauro

2018-07-13

Causality has never gained the status of a 'law' or 'principle' in physics. Some recent literature has even popularized the false idea that causality is a notion that should be banned from theory. Such misconception relies on an alleged universality of the reversibility of the laws of physics, based either on the determinism of classical theory, or on the multiverse interpretation of quantum theory, in both cases motivated by mere interpretational requirements for realism of the theory. Here, I will show that a properly defined unambiguous notion of causality is a theorem of quantum theory, which is also a falsifiable proposition of the theory. Such a notion of causality appeared in the literature within the framework of operational probabilistic theories. It is a genuinely theoretical notion, corresponding to establishing a definite partial order among events, in the same way as we do by using the future causal cone on Minkowski space. The notion of causality is logically completely independent of the misidentified concept of 'determinism', and, being a consequence of quantum theory, is ubiquitous in physics. In addition, as classical theory can be regarded as a restriction of quantum theory, causality holds also in the classical case, although the determinism of the theory trivializes it. I then conclude by arguing that causality naturally establishes an arrow of time. This implies that the scenario of the 'block Universe' and the connected 'past hypothesis' are incompatible with causality, and thus with quantum theory: they are both doomed to remain mere interpretations and, as such, are not falsifiable, similar to the hypothesis of 'super-determinism'.This article is part of a discussion meeting issue 'Foundations of quantum mechanics and their impact on contemporary society'. © 2018 The Author(s).

Model selection approach suggests causal association between 25-hydroxyvitamin D and colorectal cancer.

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Lina Zgaga

Full Text Available Vitamin D deficiency has been associated with increased risk of colorectal cancer (CRC, but causal relationship has not yet been confirmed. We investigate the direction of causation between vitamin D and CRC by extending the conventional approaches to allow pleiotropic relationships and by explicitly modelling unmeasured confounders.Plasma 25-hydroxyvitamin D (25-OHD, genetic variants associated with 25-OHD and CRC, and other relevant information was available for 2645 individuals (1057 CRC cases and 1588 controls and included in the model. We investigate whether 25-OHD is likely to be causally associated with CRC, or vice versa, by selecting the best modelling hypothesis according to Bayesian predictive scores. We examine consistency for a range of prior assumptions.Model comparison showed preference for the causal association between low 25-OHD and CRC over the reverse causal hypothesis. This was confirmed for posterior mean deviances obtained for both models (11.5 natural log units in favour of the causal model, and also for deviance information criteria (DIC computed for a range of prior distributions. Overall, models ignoring hidden confounding or pleiotropy had significantly poorer DIC scores.Results suggest causal association between 25-OHD and colorectal cancer, and support the need for randomised clinical trials for further confirmations.

Causal beliefs about obesity and associated health behaviors: results from a population-based survey

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Coups Elliot J

2010-03-01

Full Text Available Abstract Background Several genetic variants are associated with obesity risk. Promoting the notion of genes as a cause for obesity may increase genetically deterministic beliefs and decrease motivation to engage in healthy lifestyle behaviors. Little is known about whether causal beliefs about obesity are associated with lifestyle behaviors. Study objectives were as follows: 1 to document the prevalence of various causal beliefs about obesity (i.e., genes versus lifestyle behaviors, and 2 to determine the association between obesity causal beliefs and self-reported dietary and physical activity behaviors. Methods The study data were drawn from the 2007 Health Information National Trends Survey (HINTS. A total of 3,534 individuals were included in the present study. Results Overall, 72% of respondents endorsed the belief that lifestyle behaviors have 'a lot' to do with causing obesity, whereas 19% indicated that inheritance has 'a lot' to do with causing obesity. Multinomial logistic regression analyses indicated that the belief that obesity is inherited was associated with lower reported levels of physical activity (OR = 0.87, 95% CI: 0.77-0.99 and fruit and vegetable consumption (OR = 0.87, 95% CI: 0.76-0.99. In contrast, the belief that obesity is caused by lifestyle behaviors was associated with greater reported levels of physical activity (OR = 1.29, 95% CI: 1.03-1.62, but was not associated with fruit and vegetable intake (OR = 1.07, 95% CI: 0.90-1.28. Conclusions Causal beliefs about obesity are associated with some lifestyle behaviors. Additional research is needed to determine whether promoting awareness of the genetic determinants of obesity will decrease the extent to which individuals will engage in the lifestyle behaviors essential to healthy weight management.

Further properties of causal relationship: causal structure stability, new criteria for isocausality and counterexamples

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Garcia-Parrado, Alfonso; Sanchez, Miguel

2005-01-01

Recently (Garcia-Parrado and Senovilla 2003 Class. Quantum Grav. 20 625-64) the concept of causal mapping between spacetimes, essentially equivalent in this context to the chronological map defined in abstract chronological spaces, and the related notion of causal structure, have been introduced as new tools to study causality in Lorentzian geometry. In the present paper, these tools are further developed in several directions such as (i) causal mappings-and, thus, abstract chronological ones-do not preserve two levels of the standard hierarchy of causality conditions (however, they preserve the remaining levels as shown in the above reference), (ii) even though global hyperbolicity is a stable property (in the set of all time-oriented Lorentzian metrics on a fixed manifold), the causal structure of a globally hyperbolic spacetime can be unstable against perturbations; in fact, we show that the causal structures of Minkowski and Einstein static spacetimes remain stable, whereas that of de Sitter becomes unstable, (iii) general criteria allow us to discriminate different causal structures in some general spacetimes (e.g. globally hyperbolic, stationary standard); in particular, there are infinitely many different globally hyperbolic causal structures (and thus, different conformal ones) on R 2 (iv) plane waves with the same number of positive eigenvalues in the frequency matrix share the same causal structure and, thus, they have equal causal extensions and causal boundaries

A quantum causal discovery algorithm

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Giarmatzi, Christina; Costa, Fabio

2018-03-01

Finding a causal model for a set of classical variables is now a well-established task—but what about the quantum equivalent? Even the notion of a quantum causal model is controversial. Here, we present a causal discovery algorithm for quantum systems. The input to the algorithm is a process matrix describing correlations between quantum events. Its output consists of different levels of information about the underlying causal model. Our algorithm determines whether the process is causally ordered by grouping the events into causally ordered non-signaling sets. It detects if all relevant common causes are included in the process, which we label Markovian, or alternatively if some causal relations are mediated through some external memory. For a Markovian process, it outputs a causal model, namely the causal relations and the corresponding mechanisms, represented as quantum states and channels. Our algorithm opens the route to more general quantum causal discovery methods.

Epidemiological causality.

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Morabia, Alfredo

2005-01-01

Epidemiological methods, which combine population thinking and group comparisons, can primarily identify causes of disease in populations. There is therefore a tension between our intuitive notion of a cause, which we want to be deterministic and invariant at the individual level, and the epidemiological notion of causes, which are invariant only at the population level. Epidemiologists have given heretofore a pragmatic solution to this tension. Causal inference in epidemiology consists in checking the logical coherence of a causality statement and determining whether what has been found grossly contradicts what we think we already know: how strong is the association? Is there a dose-response relationship? Does the cause precede the effect? Is the effect biologically plausible? Etc. This approach to causal inference can be traced back to the English philosophers David Hume and John Stuart Mill. On the other hand, the mode of establishing causality, devised by Jakob Henle and Robert Koch, which has been fruitful in bacteriology, requires that in every instance the effect invariably follows the cause (e.g., inoculation of Koch bacillus and tuberculosis). This is incompatible with epidemiological causality which has to deal with probabilistic effects (e.g., smoking and lung cancer), and is therefore invariant only for the population.

Serum total bilirubin levels and coronary heart disease--Causal association or epiphenomenon?

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Kunutsor, Setor K

2015-12-01

Observational epidemiological evidence supports a linear inverse and independent association between serum total bilirubin levels and coronary heart disease (CHD) risk, but whether this association is causal remains to be ascertained. A Mendelian randomization approach was employed to test whether serum total bilirubin is causally linked to CHD. The genetic variant rs6742078--well known to specifically modify levels of serum total bilirubin and accounting for up to 20% of the variance in circulating serum total bilirubin levels--was used as an instrumental variable. In pooled analysis of estimates reported from published genome-wide association studies, every copy of the T allele of rs6742078 was associated with 0.42 standard deviation (SD) higher levels of serum total bilirubin (95% confidence interval, 0.40 to 0.43). Based on combined data from the Coronary Artery Disease Genome wide Replication and Meta-analyses and the Coronary Artery Disease (C4D) Genetics Consortium involving a total of 36,763 CHD cases and 76,997 controls, the odds ratio for CHD per copy of the T allele was 1.01 (95% confidence interval, 0.99 to 1.04). The odds ratio of CHD for a 1 SD genetically elevated serum total bilirubin level was 1.03 (95% confidence interval, 0.98 to 1.09). The current findings casts doubt on a strong causal association of serum total bilirubin levels with CHD. The inverse associations demonstrated in observational studies may be driven by biases such as unmeasured confounding and/or reverse causation. However, further research in large-scale consortia is needed. Copyright © 2015 Elsevier Inc. All rights reserved.

Discrete causal theory emergent spacetime and the causal metric hypothesis

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Dribus, Benjamin F

2017-01-01

This book evaluates and suggests potentially critical improvements to causal set theory, one of the best-motivated approaches to the outstanding problems of fundamental physics. Spacetime structure is of central importance to physics beyond general relativity and the standard model. The causal metric hypothesis treats causal relations as the basis of this structure. The book develops the consequences of this hypothesis under the assumption of a fundamental scale, with smooth spacetime geometry viewed as emergent. This approach resembles causal set theory, but differs in important ways; for example, the relative viewpoint, emphasizing relations between pairs of events, and relationships between pairs of histories, is central. The book culminates in a dynamical law for quantum spacetime, derived via generalized path summation.

Causal Analysis After Haavelmo

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Heckman, James; Pinto, Rodrigo

2014-01-01

Haavelmo's seminal 1943 and 1944 papers are the first rigorous treatment of causality. In them, he distinguished the definition of causal parameters from their identification. He showed that causal parameters are defined using hypothetical models that assign variation to some of the inputs determining outcomes while holding all other inputs fixed. He thus formalized and made operational Marshall's (1890) ceteris paribus analysis. We embed Haavelmo's framework into the recursive framework of Directed Acyclic Graphs (DAGs) used in one influential recent approach to causality (Pearl, 2000) and in the related literature on Bayesian nets (Lauritzen, 1996). We compare the simplicity of an analysis of causality based on Haavelmo's methodology with the complex and nonintuitive approach used in the causal literature of DAGs—the “do-calculus” of Pearl (2009). We discuss the severe limitations of DAGs and in particular of the do-calculus of Pearl in securing identification of economic models. We extend our framework to consider models for simultaneous causality, a central contribution of Haavelmo. In general cases, DAGs cannot be used to analyze models for simultaneous causality, but Haavelmo's approach naturally generalizes to cover them. PMID:25729123

Phenotypic and Causal Structure of Conduct Disorder in the Broader Context of Prevalent Forms of Psychopathology

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Lahey, Benjamin B.; Waldman, Irwin D.

2011-01-01

Background A better understanding of the nature and etiology of conduct disorder (CD) can inform nosology and vice-versa. We posit that any prevalent form of psychopathology, including CD, can be best understood if it is studied in the context of other correlated forms of child and adolescent psychopathology using formal models to guide inquiry. Methods Review of both cross-sectional and longitudinal studies of the place of CD in the phenotypic and causal structure of prevalent psychopathology, with an emphasis on similarities and differences between CD and oppositional defiant disorder (ODD). Papers were located using Web of Science by topic searches with no restriction on year of publication. Results Although some important nosologic questions remain unanswered, the dimensional phenotype of CD is well defined. CD differs from other disorders in its correlates, associated impairment, and course. Nonetheless, it is robustly correlated with many other prevalent dimensions of psychopathology both concurrently and predictively, including both other “externalizing” disorders and some “internalizing” disorders. Based on emerging evidence, we hypothesize that these concurrent and predictive correlations result primarily from widespread genetic pleiotropy, with some genetic factors nonspecifically influencing risk for multiple correlated dimensions of psychopathology. In contrast, environmental influences mostly act to differentiate dimensions of psychopathology from one another both concurrently and over time. CD and ODD share half of their genetic influences, but their genetic etiologies are distinct in other ways. Unlike most other dimensions of psychopathology, half of the genetic influences on CD appear to be unique to CD. In contrast, ODD broadly shares nearly all of its genetic influences with other disorders and has little unique genetic variance. Conclusions CD is a relatively distinct syndrome at both phenotypic and etiologic levels, but much is revealed

A Theory of Causal Learning in Children: Causal Maps and Bayes Nets

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Gopnik, Alison; Glymour, Clark; Sobel, David M.; Schulz, Laura E.; Kushnir, Tamar; Danks, David

2004-01-01

The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously…

Cultural influences on causal beliefs about depression among Latino immigrants.

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Caplan, Susan; Escobar, Javier; Paris, Manuel; Alvidrez, Jennifer; Dixon, Jane K; Desai, Mayur M; Scahill, Lawrence D; Whittemore, Robin

2013-01-01

This study describes causal beliefs about depression among Dominican, Colombian, and Ecuadorian immigrants. The authors describe participants' narratives about how particular supernatural or religious beliefs may contribute to or alleviate depression. Latino primary care patients (n = 177) were interviewed with the Beliefs About Causes of Depression Scale, a list of 35 items rated from not at all important to extremely important. Participants had the option of expanding on responses using an informal conversational approach. Underlying themes of these explanatory comments were derived from narrative and content analysis. Major themes that emerged were Psychosocial and Religious and Supernatural causal beliefs. A third theme emerged that represented the integration of these categories in the context of the immigrant experience. This article adds to the understanding of cross-cultural beliefs about depression. Psychosocial stressors related to the immigrant experience and adverse life events were highly endorsed, but the meaning of these stressors was construed in terms of religious and cultural values. To provide culturally appropriate services, nurses should be aware of and discuss the patient's belief systems, illness interpretations, and expectations of treatment.

Geneticization of deviant behavior and consequences for stigma: the case of mental illness.

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Phelan, Jo C

2005-12-01

One likely consequence of the genetics revolution is an increased tendency to understand human behavior in genetic terms. How might this "geneticization" affect stigma? Attribution theory predicts a reduction in stigma via reduced blame, anger, and punishment and increased sympathy and help. According to "genetic essentialist" thinking, genes are the basis of human identity and strongly deterministic of behavior. If such ideas are commonly accepted, geneticization should exacerbate stigma by increasing perceptions of differentness, persistence, seriousness, and transmissibility, which in turn should increase social distance and reproductive restrictiveness. I test these predictions using the case of mental illness and a vignette experiment embedded in a nationally representative survey. There was little support for attribution theory predictions. Consistent with genetic essentialism, genetic attributions increased the perceived seriousness and persistence of the mental illness and the belief that siblings and children would develop the same problem. Genetic attribution did not affect reproductive restrictiveness or social distance from the ill person but did increase social distance from the person's sibling, particularly regarding intimate forms of contact involving dating, marriage, and having children.

Neural Correlates of Causal Power Judgments

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Denise Dellarosa Cummins

2014-12-01

Full Text Available Causal inference is a fundamental component of cognition and perception. Probabilistic theories of causal judgment (most notably causal Bayes networks derive causal judgments using metrics that integrate contingency information. But human estimates typically diverge from these normative predictions. This is because human causal power judgments are typically strongly influenced by beliefs concerning underlying causal mechanisms, and because of the way knowledge is retrieved from human memory during the judgment process. Neuroimaging studies indicate that the brain distinguishes causal events from mere covariation, and between perceived and inferred causality. Areas involved in error prediction are also activated, implying automatic activation of possible exception cases during causal decision-making.

Healthcare disparities in critical illness.

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Soto, Graciela J; Martin, Greg S; Gong, Michelle Ng

2013-12-01

To summarize the current literature on racial and gender disparities in critical care and the mechanisms underlying these disparities in the course of acute critical illness. MEDLINE search on the published literature addressing racial, ethnic, or gender disparities in acute critical illness, such as sepsis, acute lung injury, pneumonia, venous thromboembolism, and cardiac arrest. Clinical studies that evaluated general critically ill patient populations in the United States as well as specific critical care conditions were reviewed with a focus on studies evaluating factors and contributors to health disparities. Study findings are presented according to their association with the prevalence, clinical presentation, management, and outcomes in acute critical illness. This review presents potential contributors for racial and gender disparities related to genetic susceptibility, comorbidities, preventive health services, socioeconomic factors, cultural differences, and access to care. The data are organized along the course of acute critical illness. The literature to date shows that disparities in critical care are most likely multifactorial involving individual, community, and hospital-level factors at several points in the continuum of acute critical illness. The data presented identify potential targets as interventions to reduce disparities in critical care and future avenues for research.

Agency, time and causality

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Thomas eWidlok

2014-11-01

Full Text Available Cognitive Scientists interested in causal cognition increasingly search for evidence from non-WEIRD people but find only very few cross-cultural studies that specifically target causal cognition. This article suggests how information about causality can be retrieved from ethnographic monographs, specifically from ethnographies that discuss agency and concepts of time. Many apparent cultural differences with regard to causal cognition dissolve when cultural extensions of agency and personhood to non-humans are taken into account. At the same time considerable variability remains when we include notions of time, linearity and sequence. The article focuses on ethnographic case studies from Africa but provides a more general perspective on the role of ethnography in research on the diversity and universality of causal cognition.

Causal boundary for strongly causal spacetimes: Pt. 1

International Nuclear Information System (INIS)

Szabados, L.B.

1989-01-01

In a previous paper an analysis of the general structure of the causal boundary constructions and a new explicit identification rule, built up from elementary TIP-TIF gluings, were presented. In the present paper we complete our identification by incorporating TIP-TIP and TIF-TIF gluings as well. An asymptotic causality condition is found which, for physically important cases, ensures the uniqueness of the endpoints of the non-spacelike curves in the completed spacetime. (author)

Structural Equations and Causal Explanations: Some Challenges for Causal SEM

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Markus, Keith A.

2010-01-01

One common application of structural equation modeling (SEM) involves expressing and empirically investigating causal explanations. Nonetheless, several aspects of causal explanation that have an impact on behavioral science methodology remain poorly understood. It remains unclear whether applications of SEM should attempt to provide complete…

Perception of the etiology of illness: causal attributions in a heart patient population.

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Koslowsky, M; Croog, S H; La Voie, L

1978-10-01

This study examined perceived causes of myocardial infarction in a patient population of 345 men previously free from significant medical problems. Investigation of their perceptions following the life-threatening illness crisis indicated that stress and tension factors were the causes most commonly cited. Possible social and psychological correlates are analyzed using an attribution theory framework, and their implications are discussed.

Investigating the Causal Relationship of C-Reactive Protein with 32 Complex Somatic and Psychiatric Outcomes

DEFF Research Database (Denmark)

Prins, Bram P; Abbasi, Ali; Wong, Anson

2016-01-01

BACKGROUND: C-reactive protein (CRP) is associated with immune, cardiometabolic, and psychiatric traits and diseases. Yet it is inconclusive whether these associations are causal. METHODS AND FINDINGS: We performed Mendelian randomization (MR) analyses using two genetic risk scores (GRSs) as inst...

Maternal age at first birth and offspring criminality: using the children of twins design to test causal hypotheses.

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Coyne, Claire A; Långström, Niklas; Rickert, Martin E; Lichtenstein, Paul; D'Onofrio, Brian M

2013-02-01

Teenage childbirth is a risk factor for poor offspring outcomes, particularly offspring antisocial behavior. It is not clear, however, if maternal age at first birth (MAFB) is causally associated with offspring antisocial behavior or if this association is due to selection factors that influence both the likelihood that a young woman gives birth early and that her offspring engage in antisocial behavior. The current study addresses the limitations of previous research by using longitudinal data from Swedish national registries and children of siblings and children of twins comparisons to identify the extent to which the association between MAFB and offspring criminal convictions is consistent with a causal influence and confounded by genetic or environmental factors that make cousins similar. We found offspring born to mothers who began childbearing earlier were more likely to be convicted of a crime than offspring born to mothers who delayed childbearing. The results from comparisons of differentially exposed cousins, especially born to discordant monozygotic twin sisters, provide support for a causal association between MAFB and offspring criminal convictions. The analyses also found little evidence for genetic confounding due to passive gene-environment correlation. Future studies are needed to replicate these findings and to identify environmental risk factors that mediate this causal association.

Maternal age at first birth and offspring criminality: Using the children-of-twins design to test causal hypotheses

Science.gov (United States)

Coyne, Claire A; Långström, Niklas; Rickert, Martin E; Lichtenstein, Paul; D’Onofrio, Brian M

2013-01-01

Teenage childbirth is a risk factor for poor offspring outcomes, particularly offspring antisocial behaviour. It is not clear if maternal age at first birth (MAFB) is causally associated with offspring antisocial behavior or if this association is due to selection factors that influence both the likelihood that a young woman gives birth early and that her offspring engage in antisocial behavior. The current study addresses the limitations of previous research by using longitudinal data from Swedish national registries and children-of-siblings and children-of-twins comparisons to identify the extent to which the association between MAFB and offspring criminal convictions is consistent with a causal influence and confounded by genetic or environmental factors that make cousins similar. We found offspring born to mothers who began childbearing earlier were more likely to be convicted of a crime than offspring born to mothers who delayed childbearing. The results from comparisons of differentially exposed cousins, especially born to discordant MZ twin sisters, provide support for a causal association between MAFB and offspring criminal convictions. The analyses also found little evidence for genetic confounding due to passive gene-environment correlation. Future studies are needed to replicate these findings and to identify environmental risk factors that mediate this causal association. PMID:23398750

Causality discovery technology

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Chen, M.; Ertl, T.; Jirotka, M.; Trefethen, A.; Schmidt, A.; Coecke, B.; Bañares-Alcántara, R.

2012-11-01

Causality is the fabric of our dynamic world. We all make frequent attempts to reason causation relationships of everyday events (e.g., what was the cause of my headache, or what has upset Alice?). We attempt to manage causality all the time through planning and scheduling. The greatest scientific discoveries are usually about causality (e.g., Newton found the cause for an apple to fall, and Darwin discovered natural selection). Meanwhile, we continue to seek a comprehensive understanding about the causes of numerous complex phenomena, such as social divisions, economic crisis, global warming, home-grown terrorism, etc. Humans analyse and reason causality based on observation, experimentation and acquired a priori knowledge. Today's technologies enable us to make observations and carry out experiments in an unprecedented scale that has created data mountains everywhere. Whereas there are exciting opportunities to discover new causation relationships, there are also unparalleled challenges to benefit from such data mountains. In this article, we present a case for developing a new piece of ICT, called Causality Discovery Technology. We reason about the necessity, feasibility and potential impact of such a technology.

Reasoning with Causal Cycles

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Rehder, Bob

2017-01-01

This article assesses how people reason with categories whose features are related in causal cycles. Whereas models based on causal graphical models (CGMs) have enjoyed success modeling category-based judgments as well as a number of other cognitive phenomena, CGMs are only able to represent causal structures that are acyclic. A number of new…

Beyond attributions: Understanding public stigma of mental illness with the common sense model.

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Mak, Winnie W S; Chong, Eddie S K; Wong, Celia C Y

2014-03-01

The present study applied the common sense model (i.e., cause, controllability, timeline, consequences, and illness coherence) to understand public attitudes toward mental illness and help-seeking intention and to examine the mediating role of perceived controllability between causal attributions with public attitudes and help seeking. Based on a randomized household sample of 941 Chinese community adults in Hong Kong, results of the structural equation modeling demonstrated that people who endorsed cultural lay beliefs tended to perceive the course of mental illness as less controllable, whereas those with psychosocial attributions see its course as more controllable. The more people perceived the course of mental illness as less controllable, more chronic, and incomprehensible, the lower was their acceptance and the greater was mental illness stigma. Furthermore, those who perceived mental illness with dire consequences were more likely to feel greater stigma and social distance. Conversely, when people were more accepting, they were more likely to seek help for psychological services and felt a shorter social distance. The common sense model provides a multidimensional framework in understanding public's mental illness perceptions and stigma. Not only should biopsychosocial determinants of mental illness be advocated to the public, cultural myths toward mental illness must be debunked.

The Impact of Relative Poverty on Norwegian Adolescents’ Subjective Health: A Causal Analysis with Propensity Score Matching

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Jon Ivar Elstad

2012-12-01

Full Text Available Studies have revealed that relative poverty is associated with ill health, but the interpretations of this correlation vary. This article asks whether relative poverty among Norwegian adolescents is causally related to poor subjective health, i.e., self-reported somatic and mental symptoms. Data consist of interview responses from a sample of adolescents (N = 510 and their parents, combined with register data on the family’s economic situation. Relatively poor adolescents had significantly worse subjective health than non-poor adolescents. Relatively poor adolescents also experienced many other social disadvantages, such as parental unemployment and parental ill health. Comparisons between the relatively poor and the non-poor adolescents, using propensity score matching, indicated a negative impact of relative poverty on the subjective health among those adolescents who lived in families with relatively few economic resources. The results suggest that there is a causal component in the association between relative poverty and the symptom burden of disadvantaged adolescents. Relative poverty is only one of many determinants of adolescents’ subjective health, but its role should be acknowledged when policies for promoting adolescent health are designed.

Association of physicians' illness perception of fibromyalgia with frustration and resistance to accepting patients: a cross-sectional study.

Science.gov (United States)

Homma, Mieko; Ishikawa, Hirono; Kiuchi, Takahiro

2016-04-01

The aim of this study was to elucidate whether physicians' illness perceptions correlate with their frustration or resistance to accepting patients with fibromyalgia (FM). In this cross-sectional postal survey, questionnaires were sent to member physicians of the Japan College of Rheumatology and Japan Rheumatism Foundation. Measures collected included the Brief Illness Perception Questionnaire with Causal Attribution, the Illness Invalidation Inventory, and the Difficult Doctor-Patient Relationship Questionnaire (DDPRQ-10). Multiple logistic regression was performed to examine associations between the DDPRQ-10 and resistance to accepting patients with FM for treatment. We analyzed data from 233 physicians who had experience in consulting with patients with FM. Only 44.2 % answered that they wanted to accept additional patients with FM. Physicians' frustration was associated with difficulty controlling symptoms, patients' emotional responses, and causal attribution of FM to patient internal factors. Conversely, lower levels of frustration were associated with causal attributions to biological factors and uncontrollable external factors. However, the "difficult patient" perception did not correlate with resistance to accepting patients with FM. Difficulty controlling symptoms with treatment was the one factor common to both physicians' frustration and resistance to accepting patients with FM. Physicians may hesitate to accept patients with FM not because of the stigmatic image of the "difficult patient," but instead because of the difficulty in controlling the symptoms of FM. Thus, to improve the quality of consultation, physicians must continuously receive new information about the treatments and causes of FM.

Structure and Strength in Causal Induction

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Griffiths, Thomas L.; Tenenbaum, Joshua B.

2005-01-01

We present a framework for the rational analysis of elemental causal induction--learning about the existence of a relationship between a single cause and effect--based upon causal graphical models. This framework makes precise the distinction between causal structure and causal strength: the difference between asking whether a causal relationship…

Regression to Causality : Regression-style presentation influences causal attribution

DEFF Research Database (Denmark)

Bordacconi, Mats Joe; Larsen, Martin Vinæs

2014-01-01

of equivalent results presented as either regression models or as a test of two sample means. Our experiment shows that the subjects who were presented with results as estimates from a regression model were more inclined to interpret these results causally. Our experiment implies that scholars using regression...... models – one of the primary vehicles for analyzing statistical results in political science – encourage causal interpretation. Specifically, we demonstrate that presenting observational results in a regression model, rather than as a simple comparison of means, makes causal interpretation of the results...... more likely. Our experiment drew on a sample of 235 university students from three different social science degree programs (political science, sociology and economics), all of whom had received substantial training in statistics. The subjects were asked to compare and evaluate the validity...

In vitro evidence for sexual reproduction in Venturia effusa, causal agent of pecan scab

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Venturia effusa is the causal agent of pecan scab, the most prevalent disease of pecan in the southeastern US. Venturia effusa is currently only known to reproduce asexually, yet the genetic diversity among populations of pecan scab suggest it is a sexually reproducing pathogen. Analysis of the mati...

Assessing Causal Pathways between Physical Formidability and Aggression in Human Males

DEFF Research Database (Denmark)

Petersen, Michael Bang; Dawes, Christopher T.

2017-01-01

Studies suggest the existence of an association between the physical formidability of human males and their level of aggression. This association is theoretically predictable from animal models of conflict behavior but could emerge from multiple different causal pathways. Previous studies have...... not been able to tease apart these paths, as they have almost exclusively relied on bivariate correlations and cross-sectional data. Here, we apply longitudinal twin data from two different samples to (1) estimate the direction of causality between formidability and aggression by means of quasi......-experimental methods and (2) estimate the relative contribution of genetic and environmental factors by means of twin modeling. Importantly, the results suggest, on the one hand, that the association between formidability and aggression is less reliable than previously thought. On the other hand, the results also...

Causality in Europeanization Research

DEFF Research Database (Denmark)

Lynggaard, Kennet

2012-01-01

to develop discursive institutional analytical frameworks and something that comes close to the formulation of hypothesis on the effects of European Union (EU) policies and institutions on domestic change. Even if these efforts so far do not necessarily amount to substantive theories or claims of causality......Discourse analysis as a methodology is perhaps not readily associated with substantive causality claims. At the same time the study of discourses is very much the study of conceptions of causal relations among a set, or sets, of agents. Within Europeanization research we have seen endeavours......, it suggests that discourse analysis and the study of causality are by no means opposites. The study of Europeanization discourses may even be seen as an essential step in the move towards claims of causality in Europeanization research. This chapter deals with the question of how we may move from the study...

Transitions Study of predictors of illness progression in young people with mental ill health: study methodology.

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Purcell, R; Jorm, A F; Hickie, I B; Yung, A R; Pantelis, C; Amminger, G P; Glozier, N; Killackey, E; Phillips, L; Wood, S J; Mackinnon, A; Scott, E; Kenyon, A; Mundy, L; Nichles, A; Scaffidi, A; Spiliotacopoulos, D; Taylor, L; Tong, J P Y; Wiltink, S; Zmicerevska, N; Hermens, Daniel; Guastella, Adam; McGorry, P D

2015-02-01

An estimated 75% of mental disorders begin before the age of 24 and approximately 25% of 13-24-year-olds are affected by mental disorders at any one time. To better understand and ideally prevent the onset of post-pubertal mental disorders, a clinical staging model has been proposed that provides a longitudinal perspective of illness development. This heuristic model takes account of the differential effects of both genetic and environmental risk factors, as well as markers relevant to the stage of illness, course or prognosis. The aim of the Transitions Study is to test empirically the assumptions that underpin the clinical staging model. Additionally, it will permit investigation of a range of psychological, social and genetic markers in terms of their capacity to define current clinical stage or predict transition from less severe or enduring to more severe and persistent stages of mental disorder. This paper describes the study methodology, which involves a longitudinal cohort design implemented within four headspace youth mental health services in Australia. Participants are young people aged 12-25 years who have sought help at headspace and consented to complete a comprehensive assessment of clinical state and psychosocial risk factors. A total of 802 young people (66% female) completed baseline assessments. Annual follow-up assessments have commenced. The results of this study may have implications for the way mental disorders are diagnosed and treated, and progress our understanding of the pathophysiologies of complex mental disorders by identifying genetic or psychosocial markers of illness stage or progression. © 2013 Wiley Publishing Asia Pty Ltd.

Causality and headache triggers

Science.gov (United States)

Turner, Dana P.; Smitherman, Todd A.; Martin, Vincent T.; Penzien, Donald B.; Houle, Timothy T.

2013-01-01

Objective The objective of this study was to explore the conditions necessary to assign causal status to headache triggers. Background The term “headache trigger” is commonly used to label any stimulus that is assumed to cause headaches. However, the assumptions required for determining if a given stimulus in fact has a causal-type relationship in eliciting headaches have not been explicated. Methods A synthesis and application of Rubin’s Causal Model is applied to the context of headache causes. From this application the conditions necessary to infer that one event (trigger) causes another (headache) are outlined using basic assumptions and examples from relevant literature. Results Although many conditions must be satisfied for a causal attribution, three basic assumptions are identified for determining causality in headache triggers: 1) constancy of the sufferer; 2) constancy of the trigger effect; and 3) constancy of the trigger presentation. A valid evaluation of a potential trigger’s effect can only be undertaken once these three basic assumptions are satisfied during formal or informal studies of headache triggers. Conclusions Evaluating these assumptions is extremely difficult or infeasible in clinical practice, and satisfying them during natural experimentation is unlikely. Researchers, practitioners, and headache sufferers are encouraged to avoid natural experimentation to determine the causal effects of headache triggers. Instead, formal experimental designs or retrospective diary studies using advanced statistical modeling techniques provide the best approaches to satisfy the required assumptions and inform causal statements about headache triggers. PMID:23534872

Viscous causal cosmologies

International Nuclear Information System (INIS)

Novello, M.; Salim, J.M.; Torres, J.; Oliveira, H.P. de

1989-01-01

A set of spatially homogeneous and isotropic cosmological geometries generated by a class of non-perfect is investigated fluids. The irreversibility if this system is studied in the context of causal thermodynamics which provides a useful mechanism to conform to the non-violation of the causal principle. (author) [pt

Dynamics of Quantum Causal Structures

Science.gov (United States)

Castro-Ruiz, Esteban; Giacomini, Flaminia; Brukner, Časlav

2018-01-01

It was recently suggested that causal structures are both dynamical, because of general relativity, and indefinite, because of quantum theory. The process matrix formalism furnishes a framework for quantum mechanics on indefinite causal structures, where the order between operations of local laboratories is not definite (e.g., one cannot say whether operation in laboratory A occurs before or after operation in laboratory B ). Here, we develop a framework for "dynamics of causal structures," i.e., for transformations of process matrices into process matrices. We show that, under continuous and reversible transformations, the causal order between operations is always preserved. However, the causal order between a subset of operations can be changed under continuous yet nonreversible transformations. An explicit example is that of the quantum switch, where a party in the past affects the causal order of operations of future parties, leading to a transition from a channel from A to B , via superposition of causal orders, to a channel from B to A . We generalize our framework to construct a hierarchy of quantum maps based on transformations of process matrices and transformations thereof.

Causal inference based on counterfactuals

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Höfler M

2005-09-01

Full Text Available Abstract Background The counterfactual or potential outcome model has become increasingly standard for causal inference in epidemiological and medical studies. Discussion This paper provides an overview on the counterfactual and related approaches. A variety of conceptual as well as practical issues when estimating causal effects are reviewed. These include causal interactions, imperfect experiments, adjustment for confounding, time-varying exposures, competing risks and the probability of causation. It is argued that the counterfactual model of causal effects captures the main aspects of causality in health sciences and relates to many statistical procedures. Summary Counterfactuals are the basis of causal inference in medicine and epidemiology. Nevertheless, the estimation of counterfactual differences pose several difficulties, primarily in observational studies. These problems, however, reflect fundamental barriers only when learning from observations, and this does not invalidate the counterfactual concept.

The causal effect of family income on child health in the U.K.

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Kuehnle, Daniel

2014-07-01

Recent studies examining the effect of family income on child health have been unable to account for the endogeneity of income. Using data from a British cohort study, we address this gap by exploiting exogenous variation in local labour market characteristics to instrument for family income. We estimate the causal effect of family income on different measures of child health and explore the role of potential transmission mechanisms. We find that income has a very small but significant causal effect on subjective child health and no significant effect on chronic health conditions, apart from respiratory illnesses. Using the panel structure, we show that the timing of income does not matter for young children. Moreover, our results provide further evidence that parental health does not drive a spurious relationship between family income and child health. Our study implies that financial transfers are unlikely to deliver substantial improvements in child health. Copyright © 2014 Elsevier B.V. All rights reserved.

The argumentative impact of causal relations

DEFF Research Database (Denmark)

Nielsen, Anne Ellerup

1996-01-01

such as causality, explanation and justification. In certain types of discourse, causal relations also imply an intentional element. This paper describes the way in which the semantic and pragmatic functions of causal markers can be accounted for in terms of linguistic and rhetorical theories of argumentation.......The semantic relations between and within utterances are marked by the use of connectors and adverbials. One type of semantic relations is causal relations expressed by causal markers such as because, therefore, so, for, etc. Some of these markers cover different types of causal relations...

Associations between causal attributions and personal stigmatizing attitudes in untreated persons with current mental health problems.

Science.gov (United States)

Stolzenburg, Susanne; Freitag, Simone; Schmidt, Silke; Schomerus, Georg

2018-02-01

Past research has shown that among the general public, certain causal explanations like biomedical causes are associated with stronger desire for social distance from persons with mental illness. Aim of this study was to find out how different causal attributions of persons with untreated mental health problems regarding their own complaints are associated with stigmatizing attitudes, anticipated self-stigma when seeking help and perceived stigma-stress. Altogether, 207 untreated persons with a current depressive syndrome were interviewed. Biomedical causes, but also belief in childhood trauma or unhealthy behavior as a cause of the problem, were associated with stronger personal stigma and with more stigma-stress. Similarities and differences to findings among the general population and implications for future research are discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

Entropy for theories with indefinite causal structure

International Nuclear Information System (INIS)

Markes, Sonia; Hardy, Lucien

2011-01-01

Any theory with definite causal structure has a defined past and future, be it defined by light cones or an absolute time scale. Entropy is a concept that has traditionally been reliant on a definite notion of causality. However, without a definite notion of causality, the concept of entropy is not all lost. Indefinite causal structure results from combining probabilistic predictions and dynamical space-time. The causaloid framework lays the mathematical groundwork to be able to treat indefinite causal structure. In this paper, we build on the causaloid mathematics and define a causally-unbiased entropy for an indefinite causal structure. In defining a causally-unbiased entropy, there comes about an emergent idea of causality in the form of a measure of causal connectedness, termed the Q factor.

Causality analysis detects the regulatory role of maternal effect genes in the early Drosophila embryo

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Zara Ghodsi

2017-03-01

Full Text Available In developmental studies, inferring regulatory interactions of segmentation genetic network play a vital role in unveiling the mechanism of pattern formation. As such, there exists an opportune demand for theoretical developments and new mathematical models which can result in a more accurate illustration of this genetic network. Accordingly, this paper seeks to extract the meaningful regulatory role of the maternal effect genes using a variety of causality detection techniques and to explore whether these methods can suggest a new analytical view to the gene regulatory networks. We evaluate the use of three different powerful and widely-used models representing time and frequency domain Granger causality and convergent cross mapping technique with the results being thoroughly evaluated for statistical significance. Our findings show that the regulatory role of maternal effect genes is detectable in different time classes and thereby the method is applicable to infer the possible regulatory interactions present among the other genes of this network.

Inferring causation from cross-sectional data: Examination of the causal relationship between hyperactivity-impulsivity and novelty seeking

Directory of Open Access Journals (Sweden)

Alexis Caroline Wood

2011-03-01

Full Text Available Previous research suggests an association between hyperactivity-impulsivity – one of the two behavioural dimensions that form attention deficit hyperactivity disorder – and the temperament characteristic of novelty seeking. We aimed to examine etiological links underlying the co-occurrence between these behaviours using a general population sample of 668 twin pairs, ages 7-10, for whom we obtained parent ratings in middle childhood; and pilot longitudinal data on 76 children. Structural equation modelling confirmed a shared genetic etiology (genetic correlation, rD=.81; 95% confidence intervals [CI]= .34-1.00 and showed that much (64% of the covariation can be accounted for by shared genetic effects. In addition, causal paths were modelled between the two behaviours; 12% of the variance in novelty seeking at age 7 was accounted for by hyperactive-impulsive behaviors at the same age. The causal effects model fits with the current characterization of hyperactive-impulsive behaviors reflecting a heightened need for stimulation. This has important implications for the management of hyperactive-impulsive behaviors in clinical settings.

Dynamics of Quantum Causal Structures

Directory of Open Access Journals (Sweden)

Esteban Castro-Ruiz

2018-03-01

Full Text Available It was recently suggested that causal structures are both dynamical, because of general relativity, and indefinite, because of quantum theory. The process matrix formalism furnishes a framework for quantum mechanics on indefinite causal structures, where the order between operations of local laboratories is not definite (e.g., one cannot say whether operation in laboratory A occurs before or after operation in laboratory B. Here, we develop a framework for “dynamics of causal structures,” i.e., for transformations of process matrices into process matrices. We show that, under continuous and reversible transformations, the causal order between operations is always preserved. However, the causal order between a subset of operations can be changed under continuous yet nonreversible transformations. An explicit example is that of the quantum switch, where a party in the past affects the causal order of operations of future parties, leading to a transition from a channel from A to B, via superposition of causal orders, to a channel from B to A. We generalize our framework to construct a hierarchy of quantum maps based on transformations of process matrices and transformations thereof.

Causal inference in public health.

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Glass, Thomas A; Goodman, Steven N; Hernán, Miguel A; Samet, Jonathan M

2013-01-01

Causal inference has a central role in public health; the determination that an association is causal indicates the possibility for intervention. We review and comment on the long-used guidelines for interpreting evidence as supporting a causal association and contrast them with the potential outcomes framework that encourages thinking in terms of causes that are interventions. We argue that in public health this framework is more suitable, providing an estimate of an action's consequences rather than the less precise notion of a risk factor's causal effect. A variety of modern statistical methods adopt this approach. When an intervention cannot be specified, causal relations can still exist, but how to intervene to change the outcome will be unclear. In application, the often-complex structure of causal processes needs to be acknowledged and appropriate data collected to study them. These newer approaches need to be brought to bear on the increasingly complex public health challenges of our globalized world.

Putting a cap on causality violations in causal dynamical triangulations

International Nuclear Information System (INIS)

Ambjoern, Jan; Loll, Renate; Westra, Willem; Zohren, Stefan

2007-01-01

The formalism of causal dynamical triangulations (CDT) provides us with a non-perturbatively defined model of quantum gravity, where the sum over histories includes only causal space-time histories. Path integrals of CDT and their continuum limits have been studied in two, three and four dimensions. Here we investigate a generalization of the two-dimensional CDT model, where the causality constraint is partially lifted by introducing branching points with a weight g s , and demonstrate that the system can be solved analytically in the genus-zero sector. The solution is analytic in a neighborhood around weight g s = 0 and cannot be analytically continued to g s = ∞, where the branching is entirely geometric and where one would formally recover standard Euclidean two-dimensional quantum gravity defined via dynamical triangulations or Liouville theory

Scientific evidence of dockworker illness to nursing clinical reasoning

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Marlise Capa Verde de Almeida

2016-04-01

Full Text Available Abstract OBJECTIVE To identify scientific evidence of occupational illness of dockworkers published in the literature. METHOD systematic review of the literature, developed according to the Cochrane method. The databases searched were: Cochrane, LILACS, MEDLINE/PubMed, CINAHL and SciELO. Studies from 1988 to 2014 were selected. The data were analyzed according to the level of evidence and Strengthening the Reporting of Observational Studies in Epidemiology. RESULTS We included 14 studies, in which 11 (78.6% were from international journals. The year of 2012 showed greater number of studies. All studies were classified as: Level of Evidence 4, highlighting lung cancer, musculoskeletal and ischemic diseases, causal link in chemical risks. CONCLUSION The development of preventive measures should especially include chemical exposure of workers applying the clinical reasoning of nurses' environmental knowledge to care for illnesses.

Comprehensive analysis of schizophrenia-associated loci highlights ion channel pathways and biologically plausible candidate causal genes

DEFF Research Database (Denmark)

Pers, Tune H; Timshel, Pascal; Ripke, Stephan

2016-01-01

Over 100 associated genetic loci have been robustly associated with schizophrenia. Gene prioritization and pathway analysis have focused on a priori hypotheses and thus may have been unduly influenced by prior assumptions and missed important causal genes and pathways. Using a data-driven approac...

Causality Statistical Perspectives and Applications

CERN Document Server

Berzuini, Carlo; Bernardinell, Luisa

2012-01-01

A state of the art volume on statistical causality Causality: Statistical Perspectives and Applications presents a wide-ranging collection of seminal contributions by renowned experts in the field, providing a thorough treatment of all aspects of statistical causality. It covers the various formalisms in current use, methods for applying them to specific problems, and the special requirements of a range of examples from medicine, biology and economics to political science. This book:Provides a clear account and comparison of formal languages, concepts and models for statistical causality. Addr

A frequency domain subspace algorithm for mixed causal, anti-causal LTI systems

NARCIS (Netherlands)

Fraanje, Rufus; Verhaegen, Michel; Verdult, Vincent; Pintelon, Rik

2003-01-01

The paper extends the subspacc identification method to estimate state-space models from frequency response function (FRF) samples, proposed by McKelvey et al. (1996) for mixed causal/anti-causal systems, and shows that other frequency domain subspace algorithms can be extended similarly. The method

How effects of chemicals might differ from those of radiations in giving rise to genetic ill-health in man

International Nuclear Information System (INIS)

Evans, H.J.

1980-01-01

Possible differences between the effects of the two groups of agents are considered. Two types of genetic damage are discussed. The first type involves mutational changes induced in germ cells or germ cell precursors which are then transmitted to the products of conception and to any resultant offspring and their descendants. The second kind is that damage sustained by the genome in somatic cells which is transmitted to daughter cells. Such somatic mutations are not heritable in the familiar sense, but they are transmitted to descendant cells within the body. It is concluded that a greater heterogeneity is expected in mutagenic response to chemical mutagens than to radiations in human populations, that the spectrum of mutations following chemical exposure may be quite different from that following radiation exposure, and that for many chemical agents, and in contrast to ionising radiations, one might expect a greater burden of genetic ill-health due to increased frequencies of mildly deleterious recessive and polygenic mutations. (Auth.)

Biomarkers of brain function in psychosis and their genetic basis

OpenAIRE

Ranlund, S. M.

2016-01-01

Psychotic disorders, including schizophrenia and bipolar disorder, are amongst the most severe and enduring mental illnesses. Recent research has identified several genetic variants associated with an increased risk of developing psychosis; however, it remains largely unknown how these lead to the illness. This is where endophenotypes – heritable traits associated with the illness and observed in unaffected family members of patients – could be valuable. Endophenotypes are linked to the genet...

The Functions of Danish Causal Conjunctions

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Rita Therkelsen

2004-01-01

Full Text Available In the article I propose an analysis of the Danish causal conjunctions fordi, siden and for based on the framework of Danish Functional Grammar. As conjunctions they relate two clauses, and their semantics have in common that it indicates a causal relationship between the clauses. The causal conjunctions are different as far as their distribution is concerned; siden conjoins a subordinate clause and a main clause, for conjoins two main clauses, and fordi is able to do both. Methodologically I have based my analysis on these distributional properties comparing siden and fordi conjoining a subordinate and a main clause, and comparing for and fordi conjoining two main clauses, following the thesis that they would establish a causal relationship between different kinds of content. My main findings are that fordi establishes a causal relationship between the events referred to by the two clauses, and the whole utterance functions as a statement of this causal relationship. Siden presupposes such a general causal relationship between the two events and puts forward the causing event as a reason for assuming or wishing or ordering the caused event, siden thus establishes a causal relationship between an event and a speech act. For equally presupposes a general causal relationship between two events and it establishes a causal relationship between speech acts, and fordi conjoining two main clauses is able to do this too, but in this position it also maintains its event-relating ability, the interpretation depending on contextual factors.

Space and time in perceptual causality

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Benjamin Straube

2010-04-01

Full Text Available Inferring causality is a fundamental feature of human cognition that allows us to theorize about and predict future states of the world. Michotte suggested that humans automatically perceive causality based on certain perceptual features of events. However, individual differences in judgments of perceptual causality cast doubt on Michotte’s view. To gain insights in the neural basis of individual difference in the perception of causality, our participants judged causal relationships in animations of a blue ball colliding with a red ball (a launching event while fMRI-data were acquired. Spatial continuity and temporal contiguity were varied parametrically in these stimuli. We did not find consistent brain activation differences between trials judged as caused and those judged as non-caused, making it unlikely that humans have universal instantiation of perceptual causality in the brain. However, participants were slower to respond to and showed greater neural activity for violations of causality, suggesting that humans are biased to expect causal relationships when moving objects appear to interact. Our participants demonstrated considerable individual differences in their sensitivity to spatial and temporal characteristics in perceiving causality. These qualitative differences in sensitivity to time or space in perceiving causality were instantiated in individual differences in activation of the left basal ganglia or right parietal lobe, respectively. Thus, the perception that the movement of one object causes the movement of another is triggered by elemental spatial and temporal sensitivities, which themselves are instantiated in specific distinct neural networks.

Causal relationship between obesity and vitamin D status: bi-directional Mendelian randomization analysis of multiple cohorts

NARCIS (Netherlands)

Vimaleswaran, K.S.; Berry, D.J.; Lu, C.; Tikkanen, E.; Pilz, S.; Hiraki, L.T.; Cooper, J.D.; Dastani, Z.; Li, R.; Houston, D.K.; Wood, A.R.; Michaelsson, K.; Vandenput, L.; Zgaga, L.; Yerges-Armstrong, L.M.; McCarthy, M.I.; Dupuis, J.; Kaakinen, M.; Kleber, M.E.; Jameson, K.; Arden, N.; Raitakari, O.; Viikari, J.; Lohman, K.K.; Ferrucci, L.; Melhus, H.; Ingelsson, E.; Byberg, L.; Lind, L.; Lorentzon, M.; Salomaa, V.; Campbell, H.; Dunlop, M.; Mitchell, B.D.; Herzig, K.H.; Pouta, A.; Hartikainen, A.L.; Streeten, E.A.; Theodoratou, E.; Jula, A.; Wareham, N.J.; Ohlsson, C.; Frayling, T.M.; Kritchevsky, S.B.; Spector, T.D.; Richards, J.B.; Lehtimaki, T.; Ouwehand, W.H.; Kraft, P.; Cooper, C.; Marz, W.; Power, C.; Loos, R.J.; Wang, T.J.; Jarvelin, M.R.; Whittaker, J.C.; Hingorani, A.D.; Hypponen, E.; Kiemeney, L.A.L.M.; et al.,

2013-01-01

BACKGROUND: Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in

Causal relationship between obesity and vitamin D status: bi-directional Mendelian randomization analysis of multiple cohorts

NARCIS (Netherlands)

Vimaleswaran, K.S.; Berry, D.J.; Lu, C.; Tikkanen, E.; Pilz, S.; Hiraki, L.T.; Cooper, J.D.; Dastani, Z.; Li, R.; Houston, D.K.; Wood, A.R.; Michaëlsson, K.; Vandenput, L.; Zgaga, L.; Yerges-Armstrong, L.M.; McCarthy, M.I.; Dupuis, J.; Kaakinen, M.; Kleber, M.E.; Jameson, K.; Arden, N.; Raitakari, O.; Viikari, J.; Lohman, K.K.; Ferrucci, L.; Melhus, H.; Ingelsson, E.; Byberg, L.; Lind, L.; Lorentzon, M.; Salomaa, V.; Campbell, H.; Dunlop, M.; Mitchell, B.D.; Herzig, K.H.; Pouta, A.; Hartikainen, A.L.; Hottenga, J.J.; de Geus, E.J.C.; Willemsen, G.; Boomsma, D.I.; Penninx, B.W.J.H.; Uitterlinden, A.G.; Visscher, P.M.; van Duijn, C.M.; Streeten, E.A.; Theodoratou, E.; Jula, A.; Wareham, N.J.; Ohlsson, C.; Frayling, T.M.; Kritchevsky, S.B.; Spector, T.D.; Richards, J.B.; Lehtimäki, T.; Ouwehand, W.H.; Kraft, P.; Cooper, C.; März, W.; Power, C.; Loos, R.J.; Wang, T.J.; Järvelin, M.R.; Whittaker, J.C.; Hingorani, A.D.; Hyppönen, E.

2013-01-01

Background: Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in

An atlas of genetic correlations across human diseases and traits

DEFF Research Database (Denmark)

Bulik-Sullivan, Brendan; Finucane, Hilary K; Anttila, Verneri

2015-01-01

Identifying genetic correlations between complex traits and diseases can provide useful etiological insights and help prioritize likely causal relationships. The major challenges preventing estimation of genetic correlation from genome-wide association study (GWAS) data with current methods are t...

Causal inference in nonlinear systems: Granger causality versus time-delayed mutual information

Science.gov (United States)

Li, Songting; Xiao, Yanyang; Zhou, Douglas; Cai, David

2018-05-01

The Granger causality (GC) analysis has been extensively applied to infer causal interactions in dynamical systems arising from economy and finance, physics, bioinformatics, neuroscience, social science, and many other fields. In the presence of potential nonlinearity in these systems, the validity of the GC analysis in general is questionable. To illustrate this, here we first construct minimal nonlinear systems and show that the GC analysis fails to infer causal relations in these systems—it gives rise to all types of incorrect causal directions. In contrast, we show that the time-delayed mutual information (TDMI) analysis is able to successfully identify the direction of interactions underlying these nonlinear systems. We then apply both methods to neuroscience data collected from experiments and demonstrate that the TDMI analysis but not the GC analysis can identify the direction of interactions among neuronal signals. Our work exemplifies inference hazards in the GC analysis in nonlinear systems and suggests that the TDMI analysis can be an appropriate tool in such a case.

The Impact of Mental Illness on Uptake of Genetic Counseling for Hereditary Breast Cancer and Ovarian Cancer in a Multiethnic Cohort of Breast Cancer Patients.

Science.gov (United States)

Ackerman, Marra G; Shapiro, Peter A; Coe, Austin; Trivedi, Meghna S; Crew, Katherine D

2017-09-01

We evaluated whether mental illness is a barrier to genetic counseling for hereditary breast and ovarian cancer (HBOC) in multiethnic breast cancer patients. We conducted a retrospective analysis of 308 women with newly diagnosed breast cancer and eligible for HBOC genetic testing seen in the breast clinic of an academic, urban medical center from 2007 to 2015. Uptake of genetic services and history of mental health disorder (MHD), defined as a psychiatric diagnosis or treatment with an antidepressant, mood stabilizer, anxiolytic, or antipsychotic medication, were ascertained by medical chart review. The mean age at breast cancer diagnosis was 56 years, with 44% non-Hispanic whites, 37% Hispanics, and 15% non-Hispanic blacks. Ninety-nine (32%) women met study criteria for MHD, 73% had a genetics referral, 57% had genetic counseling, and 54% completed BRCA testing. Uptake of genetic counseling services did not differ by race/ethnicity or presence of MHD. In multivariable analysis, younger age at diagnosis, Ashkenazi Jewish heritage, and family history of breast cancer were associated with HBOC genetic counseling. A relatively high proportion of breast cancer patients eligible for HBOC genetic testing were referred to a genetic counselor and referral status did not vary by MHD or race/ethnicity. © 2017 Wiley Periodicals, Inc.

Significance of functional disease-causal/susceptible variants identified by whole-genome analyses for the understanding of human diseases.

Science.gov (United States)

Hitomi, Yuki; Tokunaga, Katsushi

2017-01-01

Human genome variation may cause differences in traits and disease risks. Disease-causal/susceptible genes and variants for both common and rare diseases can be detected by comprehensive whole-genome analyses, such as whole-genome sequencing (WGS), using next-generation sequencing (NGS) technology and genome-wide association studies (GWAS). Here, in addition to the application of an NGS as a whole-genome analysis method, we summarize approaches for the identification of functional disease-causal/susceptible variants from abundant genetic variants in the human genome and methods for evaluating their functional effects in human diseases, using an NGS and in silico and in vitro functional analyses. We also discuss the clinical applications of the functional disease causal/susceptible variants to personalized medicine.

Dairy consumption and body mass index among adults: Mendelian randomization analysis of 184802 individuals from 25 studies

Science.gov (United States)

Associations between dairy intake and body mass index (BMI) have been inconsistently observed in epidemiological studies, and the causal relationship remains ill defined. We performed Mendelian randomization (MR) analysis using an established dairy intake-associated genetic polymorphism located upst...

Biological causal links on physiological and evolutionary time scales.

Science.gov (United States)

Karmon, Amit; Pilpel, Yitzhak

2016-04-26

Correlation does not imply causation. If two variables, say A and B, are correlated, it could be because A causes B, or that B causes A, or because a third factor affects them both. We suggest that in many cases in biology, the causal link might be bi-directional: A causes B through a fast-acting physiological process, while B causes A through a slowly accumulating evolutionary process. Furthermore, many trained biologists tend to consistently focus at first on the fast-acting direction, and overlook the slower process in the opposite direction. We analyse several examples from modern biology that demonstrate this bias (codon usage optimality and gene expression, gene duplication and genetic dispensability, stem cell division and cancer risk, and the microbiome and host metabolism) and also discuss an example from linguistics. These examples demonstrate mutual effects between the fast physiological processes and the slow evolutionary ones. We believe that building awareness of inference biases among biologists who tend to prefer one causal direction over another could improve scientific reasoning.

Paradoxical Behavior of Granger Causality

Science.gov (United States)

Witt, Annette; Battaglia, Demian; Gail, Alexander

2013-03-01

Granger causality is a standard tool for the description of directed interaction of network components and is popular in many scientific fields including econometrics, neuroscience and climate science. For time series that can be modeled as bivariate auto-regressive processes we analytically derive an expression for spectrally decomposed Granger Causality (SDGC) and show that this quantity depends only on two out of four groups of model parameters. Then we present examples of such processes whose SDGC expose paradoxical behavior in the sense that causality is high for frequency ranges with low spectral power. For avoiding misinterpretations of Granger causality analysis we propose to complement it by partial spectral analysis. Our findings are illustrated by an example from brain electrophysiology. Finally, we draw implications for the conventional definition of Granger causality. Bernstein Center for Computational Neuroscience Goettingen

On causality of extreme events

Directory of Open Access Journals (Sweden)

Massimiliano Zanin

2016-06-01

Full Text Available Multiple metrics have been developed to detect causality relations between data describing the elements constituting complex systems, all of them considering their evolution through time. Here we propose a metric able to detect causality within static data sets, by analysing how extreme events in one element correspond to the appearance of extreme events in a second one. The metric is able to detect non-linear causalities; to analyse both cross-sectional and longitudinal data sets; and to discriminate between real causalities and correlations caused by confounding factors. We validate the metric through synthetic data, dynamical and chaotic systems, and data representing the human brain activity in a cognitive task. We further show how the proposed metric is able to outperform classical causality metrics, provided non-linear relationships are present and large enough data sets are available.

Smoking and caffeine consumption: a genetic analysis of their association.

Science.gov (United States)

Treur, Jorien L; Taylor, Amy E; Ware, Jennifer J; Nivard, Michel G; Neale, Michael C; McMahon, George; Hottenga, Jouke-Jan; Baselmans, Bart M L; Boomsma, Dorret I; Munafò, Marcus R; Vink, Jacqueline M

2017-07-01

Smoking and caffeine consumption show a strong positive correlation, but the mechanism underlying this association is unclear. Explanations include shared genetic/environmental factors or causal effects. This study employed three methods to investigate the association between smoking and caffeine. First, bivariate genetic models were applied to data of 10 368 twins from the Netherlands Twin Register in order to estimate genetic and environmental correlations between smoking and caffeine use. Second, from the summary statistics of meta-analyses of genome-wide association studies on smoking and caffeine, the genetic correlation was calculated by LD-score regression. Third, causal effects were tested using Mendelian randomization analysis in 6605 Netherlands Twin Register participants and 5714 women from the Avon Longitudinal Study of Parents and Children. Through twin modelling, a genetic correlation of r0.47 and an environmental correlation of r0.30 were estimated between current smoking (yes/no) and coffee use (high/low). Between current smoking and total caffeine use, this was r0.44 and r0.00, respectively. LD-score regression also indicated sizeable genetic correlations between smoking and coffee use (r0.44 between smoking heaviness and cups of coffee per day, r0.28 between smoking initiation and coffee use and r0.25 between smoking persistence and coffee use). Consistent with the relatively high genetic correlations and lower environmental correlations, Mendelian randomization provided no evidence for causal effects of smoking on caffeine or vice versa. Genetic factors thus explain most of the association between smoking and caffeine consumption. These findings suggest that quitting smoking may be more difficult for heavy caffeine consumers, given their genetic susceptibility. © 2016 The Authors.Addiction Biology published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction.

Causal symmetric spaces

CERN Document Server

Olafsson, Gestur; Helgason, Sigurdur

1996-01-01

This book is intended to introduce researchers and graduate students to the concepts of causal symmetric spaces. To date, results of recent studies considered standard by specialists have not been widely published. This book seeks to bring this information to students and researchers in geometry and analysis on causal symmetric spaces.Includes the newest results in harmonic analysis including Spherical functions on ordered symmetric space and the holmorphic discrete series and Hardy spaces on compactly casual symmetric spacesDeals with the infinitesimal situation, coverings of symmetric spaces, classification of causal symmetric pairs and invariant cone fieldsPresents basic geometric properties of semi-simple symmetric spacesIncludes appendices on Lie algebras and Lie groups, Bounded symmetric domains (Cayley transforms), Antiholomorphic Involutions on Bounded Domains and Para-Hermitian Symmetric Spaces

Predicting Causal Relationships from Biological Data: Applying Automated Causal Discovery on Mass Cytometry Data of Human Immune Cells

KAUST Repository

Triantafillou, Sofia; Lagani, Vincenzo; Heinze-Deml, Christina; Schmidt, Angelika; Tegner, Jesper; Tsamardinos, Ioannis

2017-01-01

Learning the causal relationships that define a molecular system allows us to predict how the system will respond to different interventions. Distinguishing causality from mere association typically requires randomized experiments. Methods for automated  causal discovery from limited experiments exist, but have so far rarely been tested in systems biology applications. In this work, we apply state-of-the art causal discovery methods on a large collection of public mass cytometry data sets, measuring intra-cellular signaling proteins of the human immune system and their response to several perturbations. We show how different experimental conditions can be used to facilitate causal discovery, and apply two fundamental methods that produce context-specific causal predictions. Causal predictions were reproducible across independent data sets from two different studies, but often disagree with the KEGG pathway databases. Within this context, we discuss the caveats we need to overcome for automated causal discovery to become a part of the routine data analysis in systems biology.

Predicting Causal Relationships from Biological Data: Applying Automated Causal Discovery on Mass Cytometry Data of Human Immune Cells

KAUST Repository

Triantafillou, Sofia

2017-09-29

Learning the causal relationships that define a molecular system allows us to predict how the system will respond to different interventions. Distinguishing causality from mere association typically requires randomized experiments. Methods for automated  causal discovery from limited experiments exist, but have so far rarely been tested in systems biology applications. In this work, we apply state-of-the art causal discovery methods on a large collection of public mass cytometry data sets, measuring intra-cellular signaling proteins of the human immune system and their response to several perturbations. We show how different experimental conditions can be used to facilitate causal discovery, and apply two fundamental methods that produce context-specific causal predictions. Causal predictions were reproducible across independent data sets from two different studies, but often disagree with the KEGG pathway databases. Within this context, we discuss the caveats we need to overcome for automated causal discovery to become a part of the routine data analysis in systems biology.

Genetics of dioecy and causal sex chromosomes in plants

Indian Academy of Sciences (India)

2014-04-15

chromosome evolution; sex-ratio variation ...... interaction between the two genes, Cm ACS7 and Cm W1P1, ... son of low pollinator density seed formation will be scanty ...... Kaltz O. and Bell G. 2002 The ecology and genetics of fitness in.

Causal effects on child language development: A review of studies in communication sciences and disorders.

Science.gov (United States)

Rogers, Clare R; Nulty, Karissa L; Betancourt, Mariana Aparicio; DeThorne, Laura S

2015-01-01

We reviewed recent studies published across key journals within the field of communication sciences and disorders (CSD) to survey what causal influences on child language development were being considered. Specifically, we reviewed a total of 2921 abstracts published within the following journals between 2003 and 2013: Language, Speech, and Hearing Services in Schools (LSHSS); American Journal of Speech-Language Pathology (AJSLP); Journal of Speech, Language, and Hearing Research (JSLHR); Journal of Communication Disorders (JCD); and the International Journal of Language and Communication Disorders (IJLCD). Of the 346 eligible articles that addressed causal factors on child language development across the five journals, 11% were categorized as Genetic (37/346), 83% (287/346) were categorized as Environmental, and 6% (22/346) were categorized as Mixed. The bulk of studies addressing environmental influences focused on therapist intervention (154/296=52%), family/caregiver linguistic input (65/296=22%), or family/caregiver qualities (39/296=13%). A more in-depth review of all eligible studies published in 2013 (n=34) revealed that family/caregiver qualities served as the most commonly controlled environmental factor (e.g., SES) and only 3 studies explicitly noted the possibility of gene-environment interplay. This review highlighted the need to expand the research base for the field of CSD to include a broader range of environmental influences on child language development (e.g., diet, toxin exposure, stress) and to consider more directly the complex and dynamic interplay between genetic and environmental effects. Readers will be able to highlight causal factors on child language development that have been studied over the past decade in CSD and recognize additional influences worthy of consideration. In addition, readers will become familiar with basic tenets of developmental systems theory, including the complex interplay between genetic and environmental factors

Investigating the multi-causal and complex nature of the accident causal influence of construction project features.

Science.gov (United States)

Manu, Patrick A; Ankrah, Nii A; Proverbs, David G; Suresh, Subashini

2012-09-01

Construction project features (CPFs) are organisational, physical and operational attributes that characterise construction projects. Although previous studies have examined the accident causal influence of CPFs, the multi-causal attribute of this causal phenomenon still remain elusive and thus requires further investigation. Aiming to shed light on this facet of the accident causal phenomenon of CPFs, this study examines relevant literature and crystallises the attained insight of the multi-causal attribute by a graphical model which is subsequently operationalised by a derived mathematical risk expression that offers a systematic approach for evaluating the potential of CPFs to cause harm and consequently their health and safety (H&S) risk implications. The graphical model and the risk expression put forth by the study thus advance current understanding of the accident causal phenomenon of CPFs and they present an opportunity for project participants to manage the H&S risk associated with CPFs from the early stages of project procurement. Copyright © 2011 Elsevier Ltd. All rights reserved.

The relationship between the belief in a genetic cause for breast cancer and bilateral mastectomy.

Science.gov (United States)

Petrie, Keith J; Myrtveit, Solbjørg Makalani; Partridge, Ann H; Stephens, Melika; Stanton, Annette L

2015-05-01

Most women develop causal beliefs following diagnosis with breast cancer and these beliefs can guide decisions around their care and management. Bilateral mastectomy rates are increasing, although the benefits of this surgery are only established in a small percentage of women. In this study we investigated the relationship between causal beliefs and the decision to have a bilateral mastectomy. Women (N = 2,269) from the Army of Women's breast cancer research registry completed an online survey. Women were asked what they believed caused their cancer and responses were coded into 8 causal categories. Participants were also asked about the type of surgery they underwent following their breast cancer diagnosis. The odds ratios for having a double mastectomy were calculated for each causal category using random/bad luck as a referent category. Hormonal factors (22%) and genetics (19%) were the most common causal belief, followed by don't know (19%), environmental toxins (11%), negative emotions (9%), poor health behavior (8%), other (6%) and random/bad luck (6%). Compared with the referent category, the odds ratio of having a bilateral mastectomy was significantly higher in both the genetics and hormonal causal belief groups (OR = 2.36, 95% CI [1.38, 4.02] and OR = 1.98, 95% CI [1.16, 3.38], respectively). Beliefs in a genetic cause for breast cancer are common and are associated with high rates of bilateral mastectomy. This is despite evidence that the actual genetic contribution to breast cancer is much lower than perceived and that bilateral mastectomy is, in most cases, unlikely to improve survival. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Principal stratification in causal inference.

Science.gov (United States)

Frangakis, Constantine E; Rubin, Donald B

2002-03-01

Many scientific problems require that treatment comparisons be adjusted for posttreatment variables, but the estimands underlying standard methods are not causal effects. To address this deficiency, we propose a general framework for comparing treatments adjusting for posttreatment variables that yields principal effects based on principal stratification. Principal stratification with respect to a posttreatment variable is a cross-classification of subjects defined by the joint potential values of that posttreatment variable tinder each of the treatments being compared. Principal effects are causal effects within a principal stratum. The key property of principal strata is that they are not affected by treatment assignment and therefore can be used just as any pretreatment covariate. such as age category. As a result, the central property of our principal effects is that they are always causal effects and do not suffer from the complications of standard posttreatment-adjusted estimands. We discuss briefly that such principal causal effects are the link between three recent applications with adjustment for posttreatment variables: (i) treatment noncompliance, (ii) missing outcomes (dropout) following treatment noncompliance. and (iii) censoring by death. We then attack the problem of surrogate or biomarker endpoints, where we show, using principal causal effects, that all current definitions of surrogacy, even when perfectly true, do not generally have the desired interpretation as causal effects of treatment on outcome. We go on to forrmulate estimands based on principal stratification and principal causal effects and show their superiority.

Causal Set Generator and Action Computer

OpenAIRE

Cunningham, William; Krioukov, Dmitri

2017-01-01

The causal set approach to quantum gravity has gained traction over the past three decades, but numerical experiments involving causal sets have been limited to relatively small scales. The software suite presented here provides a new framework for the generation and study of causal sets. Its efficiency surpasses previous implementations by several orders of magnitude. We highlight several important features of the code, including the compact data structures, the $O(N^2)$ causal set generatio...

Spectral dimension in causal set quantum gravity

International Nuclear Information System (INIS)

Eichhorn, Astrid; Mizera, Sebastian

2014-01-01

We evaluate the spectral dimension in causal set quantum gravity by simulating random walks on causal sets. In contrast to other approaches to quantum gravity, we find an increasing spectral dimension at small scales. This observation can be connected to the nonlocality of causal set theory that is deeply rooted in its fundamentally Lorentzian nature. Based on its large-scale behaviour, we conjecture that the spectral dimension can serve as a tool to distinguish causal sets that approximate manifolds from those that do not. As a new tool to probe quantum spacetime in different quantum gravity approaches, we introduce a novel dimensional estimator, the causal spectral dimension, based on the meeting probability of two random walkers, which respect the causal structure of the quantum spacetime. We discuss a causal-set example, where the spectral dimension and the causal spectral dimension differ, due to the existence of a preferred foliation. (paper)

The causal link between energy and output growth: Evidence from Markov switching Granger causality

International Nuclear Information System (INIS)

Kandemir Kocaaslan, Ozge

2013-01-01

In this paper we empirically investigate the causal link between energy consumption and economic growth employing a Markov switching Granger causality analysis. We carry out our investigation using annual U.S. real GDP, total final energy consumption and total primary energy consumption data which cover the period between 1968 and 2010. We find that there are significant changes in the causal relation between energy consumption and economic growth over the sample period under investigation. Our results show that total final energy consumption and total primary energy consumption have significant predictive content for real economic activity in the U.S. economy. Furthermore, the causality running from energy consumption to output growth seems to be strongly apparent particularly during the periods of economic downturn and energy crisis. We also document that output growth has predictive power in explaining total energy consumption. Furthermore, the power of output growth in predicting total energy consumption is found to diminish after the mid of 1980s. - Highlights: • Total energy consumption has predictive content for real economic activity. • The causality from energy to output growth is apparent in the periods of recession. • The causality from energy to output growth is strong in the periods of energy crisis. • Output growth has predictive power in explaining total energy consumption. • The power of output growth in explaining energy diminishes after the mid of 1980s

The illness/non-illness model: hypnotherapy for physically ill patients.

Science.gov (United States)

Navon, Shaul

2014-07-01

This article proposes a focused, novel sub-set of the cognitive behavioral therapy approach to hypnotherapy for physically ill patients, based upon the illness/non-illness psychotherapeutic model for physically ill patients. The model is based on three logical rules used in differentiating illness from non-illness: duality, contradiction, and complementarity. The article discusses the use of hypnotic interventions to help physically ill and/or disabled patients distinguish between illness and non-illness in their psychotherapeutic themes and attitudes. Two case studies illustrate that patients in this special population group can be taught to learn the language of change and to use this language to overcome difficult situations. The model suggests a new clinical mode of treatment in which individuals who are physically ill and/or disabled are helped in coping with actual motifs and thoughts related to non-illness or non-disability.

¿CONFIEREN PODERES CAUSALES LOS UNIVERSALES TRASCENDENTES?

Directory of Open Access Journals (Sweden)

José Tomás Alvarado Marambio

2013-11-01

Full Text Available This work discusses the so-called ‘Eleatic’ argument against the existence of transcendent universals, i. e. universals which does not require instantiation for its existence. The Eleatic Principle states that everything produces a difference in the causal powers of something. As transcendent universals seem not to produce such a difference, transcendent universals seem not to exist. The argument depends crucially on the justification and the interpretation of the Eleatic Principle. It is argued, first, that it is not very clear that the principle is justified, and, second, that there are several alternatives for its interpretation, in relation with the different theories one can endorse about modality or causality. Anti-realist theories of modality or causality are not very appropriate for the understanding of what should be a ‘causal power’. Neither does a realist theory of causality conjoined with a combinatorial theory of possible worlds. A ‘causal power’ seems to be better understood in connection with a realist –non-reductionist– theory of causality and a causal theory of modality. Taken in this way the Eleatic Principle, nonetheless, it is argued that transcendent universals do ‘produce’ a difference in causal powers, for every causal connection requires such universals for its existence.

Therapeutic Targets of Triglyceride Metabolism as Informed by Human Genetics.

Science.gov (United States)

Bauer, Robert C; Khetarpal, Sumeet A; Hand, Nicholas J; Rader, Daniel J

2016-04-01

Human genetics has contributed to the development of multiple drugs to treat hyperlipidemia and coronary artery disease (CAD), most recently including antibodies targeting PCSK9 to reduce LDL cholesterol. Despite these successes, a large burden of CAD remains. Genetic and epidemiological studies have suggested that circulating triglyceride (TG)-rich lipoproteins (TRLs) are a causal risk factor for CAD, presenting an opportunity for novel therapeutic strategies. We discuss recent unbiased human genetics testing, including genome-wide association studies (GWAS) and whole-genome or -exome sequencing, that have identified the lipoprotein lipase (LPL) and hepatic lipogenesis pathways as important mechanisms in the regulation of circulating TRLs. Further strengthening the causal relationship between TRLs and CAD, findings such as these may provide novel targets for much-needed potential therapeutic interventions. Copyright © 2016. Published by Elsevier Ltd.

Spiritual beliefs in bipolar affective disorder: their relevance for illness management.

Science.gov (United States)

Mitchell, Logan; Romans, Sarah

2003-08-01

There has been growing interest in investigating religion as a relevant element in illness outcome. Having religious beliefs has been shown repeatedly to be associated with lessened rates of depression. Most of the limited published research has been restricted to elderly samples. Religious coping is thought to play a key role in religion's effects. Strangely, psychiatric research has neglected this area. A questionnaire covering religious, spiritual and philosophical beliefs and religious practice was given to a sample of patients with bipolar affective disorder in remission. Most patients often held strong religious or spiritual beliefs (78%) and practised their religion frequently (81.5%). Most saw a direct link between their beliefs and the management of their illness. Many used religious coping, and often religio-spiritual beliefs and practice put them in conflict with illness models (24%) and advice (19%) used by their medical advisors. This was a cross-sectional design without a control group and thus it is not possible to determine causal associations from the data set. Religio-spiritual ideas are of great salience to many patients with bipolar disorder and shape the ways in which they think about their illness. Many reported experiencing significant paradigm conflict in understanding and managing their illness between medical and their spiritual advisors. These data suggest that the whole area of religion and spirituality is directly relevant to people living with a chronic psychiatric illness and should be firmly on the discussion agenda of clinicians working with patients with bipolar disorder.

Re-thinking local causality

NARCIS (Netherlands)

Friederich, Simon

There is widespread belief in a tension between quantum theory and special relativity, motivated by the idea that quantum theory violates J. S. Bell's criterion of local causality, which is meant to implement the causal structure of relativistic space-time. This paper argues that if one takes the

mediation: R package for causal mediation analysis

OpenAIRE

Tingley, Dustin; Yamamoto, Teppei; Hirose, Kentaro; Keele, Luke; Imai, Kosuke

2012-01-01

In this paper, we describe the R package mediation for conducting causal mediation analysis in applied empirical research. In many scientific disciplines, the goal of researchers is not only estimating causal effects of a treatment but also understanding the process in which the treatment causally affects the outcome. Causal mediation analysis is frequently used to assess potential causal mechanisms. The mediation package implements a comprehensive suite of statistical tools for conducting su...

Culturally prescribed beliefs about mental illness among the Akan of Ghana.

Science.gov (United States)

Opare-Henaku, Annabella; Utsey, Shawn O

2017-08-01

Mental illness is a culturally laden phenomenon, and different cultures have unique ways of constructing mental illness. In this study, conceptions of mental illness were explored among 30 participants of Akan descent in Ghana through individual and group interviews. Participants demonstrated a wide range of knowledge on mental illness indicating that poor self-care, deficits in social functioning, and disordered behaviors are the cardinal features of mental illness. The data revealed that Akan cultural beliefs influenced notions of etiology of mental illness and care of the mentally ill. While participants recognized the role of multiple factors such as genetics, substance abuse, daily hassles (for example, concerns about basic needs such as food, clothing, and shelter), and trauma in the cause of mental illness, the predominant belief was that mental illness is a retributive and/or a spiritual illness. This belief encourages pluralistic health-seeking behaviors: use of hospitals, prayer camps, herbalists, and traditional healers. The implications of these findings for public health education on mental illness, and clinical training and practice are discussed.

Annual research review: phenotypic and causal structure of conduct disorder in the broader context of prevalent forms of psychopathology.

Science.gov (United States)

Lahey, Benjamin B; Waldman, Irwin D

2012-05-01

A better understanding of the nature and etiology of conduct disorder (CD) can inform nosology and vice versa. We posit that any prevalent form of psychopathology, including CD, can be best understood if it is studied in the context of other correlated forms of child and adolescent psychopathology using formal models to guide inquiry. Review of both cross-sectional and longitudinal studies of the place of CD in the phenotypic and causal structure of prevalent psychopathology, with an emphasis on similarities and differences between CD and oppositional defiant disorder (ODD). Papers were located using Web of Science by topic searches with no restriction on year of publication. Although some important nosologic questions remain unanswered, the dimensional phenotype of CD is well defined. CD differs from other disorders in its correlates, associated impairment, and course. Nonetheless, it is robustly correlated with many other prevalent dimensions of psychopathology both concurrently and predictively, including both other 'externalizing' disorders and some 'internalizing' disorders. Based on emerging evidence, we hypothesize that these concurrent and predictive correlations result primarily from widespread genetic pleiotropy, with some genetic factors nonspecifically influencing risk for multiple correlated dimensions of psychopathology. In contrast, environmental influences mostly act to differentiate dimensions of psychopathology from one another both concurrently and over time. CD and ODD share half of their genetic influences, but their genetic etiologies are distinct in other ways. Unlike most other dimensions of psychopathology, half of the genetic influences on CD appear to be unique to CD. In contrast, ODD broadly shares nearly all of its genetic influences with other disorders and has little unique genetic variance. Conduct disorder is a relatively distinct syndrome at both phenotypic and etiologic levels, but much is revealed by studying CD in the context of

Causal knowledge and the development of inductive reasoning.

Science.gov (United States)

Bright, Aimée K; Feeney, Aidan

2014-06-01

We explored the development of sensitivity to causal relations in children's inductive reasoning. Children (5-, 8-, and 12-year-olds) and adults were given trials in which they decided whether a property known to be possessed by members of one category was also possessed by members of (a) a taxonomically related category or (b) a causally related category. The direction of the causal link was either predictive (prey→predator) or diagnostic (predator→prey), and the property that participants reasoned about established either a taxonomic or causal context. There was a causal asymmetry effect across all age groups, with more causal choices when the causal link was predictive than when it was diagnostic. Furthermore, context-sensitive causal reasoning showed a curvilinear development, with causal choices being most frequent for 8-year-olds regardless of context. Causal inductions decreased thereafter because 12-year-olds and adults made more taxonomic choices when reasoning in the taxonomic context. These findings suggest that simple causal relations may often be the default knowledge structure in young children's inductive reasoning, that sensitivity to causal direction is present early on, and that children over-generalize their causal knowledge when reasoning. Copyright © 2013 Elsevier Inc. All rights reserved.

Causal Diagrams for Empirical Research

OpenAIRE

Pearl, Judea

1994-01-01

The primary aim of this paper is to show how graphical models can be used as a mathematical language for integrating statistical and subject-matter information. In particular, the paper develops a principled, nonparametric framework for causal inference, in which diagrams are queried to determine if the assumptions available are sufficient for identifiying causal effects from non-experimental data. If so the diagrams can be queried to produce mathematical expressions for causal effects in ter...

Cadherin-related Family Member 3 Genetics and Rhinovirus C Respiratory Illnesses

DEFF Research Database (Denmark)

Bønnelykke, Klaus; Coleman, Amaziah T; Evans, Michael D

2018-01-01

Background Experimental evidence suggests that CDHR3 is a receptor for rhinovirus-C (RV-C), and a missense variant in this gene (rs6967330) is associated with childhood asthma with severe exacerbations. Objective To determine whether rs6967330 influences RV-C infections and illnesses in early...... childhood. Methods We studied associations between rs6967330 and respiratory infections and illnesses in the COPSAC2010 and COAST birth cohorts, where respiratory infections were monitored prospectively for the first 3 years of life. Nasal samples were collected during acute infections in both cohorts...

Inference of Causal Relationships between Biomarkers and Outcomes in High Dimensions

Directory of Open Access Journals (Sweden)

Felix Agakov

2011-12-01

Full Text Available We describe a unified computational framework for learning causal dependencies between genotypes, biomarkers, and phenotypic outcomes from large-scale data. In contrast to previous studies, our framework allows for noisy measurements, hidden confounders, missing data, and pleiotropic effects of genotypes on outcomes. The method exploits the use of genotypes as “instrumental variables” to infer causal associations between phenotypic biomarkers and outcomes, without requiring the assumption that genotypic effects are mediated only through the observed biomarkers. The framework builds on sparse linear methods developed in statistics and machine learning and modified here for inferring structures of richer networks with latent variables. Where the biomarkers are gene transcripts, the method can be used for fine mapping of quantitative trait loci (QTLs detected in genetic linkage studies. To demonstrate our method, we examined effects of gene transcript levels in the liver on plasma HDL cholesterol levels in a sample of 260 mice from a heterogeneous stock.

A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis

Directory of Open Access Journals (Sweden)

Akira Ishikawa

2017-11-01

Full Text Available Large numbers of quantitative trait loci (QTL affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis.

Science.gov (United States)

Ishikawa, Akira

2017-11-27

Large numbers of quantitative trait loci (QTL) affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs) for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

Mapping Determinants of Gene Expression Plasticity by Genetical Genomics in C. elegans

NARCIS (Netherlands)

Li, Y.; Alda Alvarez, O.; Gutteling, E.W.; Tijsterman, M.; Fu, J.; Riksen, J.A.G.; Hazendonk, E.; Prins, J.C.P.; Plasterk, R.H.A.; Jansen, R.C.; Breitling, R.; Kammenga, J.E.

2006-01-01

Recent genetical genomics studies have provided intimate views on gene regulatory networks. Gene expression variations between genetically different individuals have been mapped to the causal regulatory regions, termed expression quantitative trait loci. Whether the environment-induced plastic

Mapping determinants of gene expression plasticity by genetical genomics in C. elegans.

NARCIS (Netherlands)

Li, Y.; Alvarez, O.A.; Gutteling, E.W.; Tijsterman, M.; Fu, J.; Riksen, J.A.; Hazendonk, M.G.A.; Prins, P.; Plasterk, R.H.A.; Jansen, R.C.; Breitling, R.; Kammenga, J.E.

2006-01-01

Recent genetical genomics studies have provided intimate views on gene regulatory networks. Gene expression variations between genetically different individuals have been mapped to the causal regulatory regions, termed expression quantitative trait loci. Whether the environment-induced plastic

The selective power of causality on memory errors.

Science.gov (United States)

Marsh, Jessecae K; Kulkofsky, Sarah

2015-01-01

We tested the influence of causal links on the production of memory errors in a misinformation paradigm. Participants studied a set of statements about a person, which were presented as either individual statements or pairs of causally linked statements. Participants were then provided with causally plausible and causally implausible misinformation. We hypothesised that studying information connected with causal links would promote representing information in a more abstract manner. As such, we predicted that causal information would not provide an overall protection against memory errors, but rather would preferentially help in the rejection of misinformation that was causally implausible, given the learned causal links. In two experiments, we measured whether the causal linkage of information would be generally protective against all memory errors or only selectively protective against certain types of memory errors. Causal links helped participants reject implausible memory lures, but did not protect against plausible lures. Our results suggest that causal information may promote an abstract storage of information that helps prevent only specific types of memory errors.

Rate-Agnostic (Causal) Structure Learning.

Science.gov (United States)

Plis, Sergey; Danks, David; Freeman, Cynthia; Calhoun, Vince

2015-12-01

Causal structure learning from time series data is a major scientific challenge. Extant algorithms assume that measurements occur sufficiently quickly; more precisely, they assume approximately equal system and measurement timescales. In many domains, however, measurements occur at a significantly slower rate than the underlying system changes, but the size of the timescale mismatch is often unknown. This paper develops three causal structure learning algorithms, each of which discovers all dynamic causal graphs that explain the observed measurement data, perhaps given undersampling. That is, these algorithms all learn causal structure in a "rate-agnostic" manner: they do not assume any particular relation between the measurement and system timescales. We apply these algorithms to data from simulations to gain insight into the challenge of undersampling.

Employees' perspectives on ethically important aspects of genetic research participation: a pilot study.

Science.gov (United States)

Roberts, Laura Weiss; Warner, Teddy D; Geppert, Cynthia M A; Rogers, Melinda; Green Hammond, Katherine A

2005-01-01

Insights from genetic research may greatly improve our understanding of physical and mental illnesses and assist in the prevention of disease. Early experience with genetic information suggests that it may lead to stigma, discrimination, and other psychosocial harms, however, and this may be particularly salient in some settings, such as the workplace. Despite the importance of these issues, little is known about how healthy adults, including workers, perceive and understand ethically important issues in genetic research pertaining to physical and mental illness. We developed, pilot tested, and administered a written survey and structured interview to 63 healthy working adults in 2 settings. For this paper, we analyzed a subset of items that assessed attitudes toward ethically relevant issues related to participation in genetic research on physical and mental illness, such as its perceived importance, its acceptability for various populations, and appropriate motivations for participation. Our respondents strongly endorsed the importance of physical and mental illness genetic research. They viewed participation as somewhat to very acceptable for all 12 special population groups we asked about, including persons with mental illness. They perceived more positives than negatives in genetic research participation, giving neutral responses regarding potential risks. They affirmed many motivations for participation to varying degrees. Men tended to affirm genetic research participation importance, acceptability, and motivations more strongly than women. Healthy working persons may be willing partners in genetic research related to physical and mental illnesses in coming years. This project suggests the feasibility and value of evidence-based ethics inquiry, although further study is necessary. Evidence regarding stakeholders' perspectives on ethically important issues in science may help in the development of research practices and policy.

Causality and analyticity in optics

International Nuclear Information System (INIS)

Nussenzveig, H.M.

In order to provide an overall picture of the broad range of optical phenomena that are directly linked with the concepts of causality and analyticity, the following topics are briefly reviewed, emphasizing recent developments: 1) Derivation of dispersion relations for the optical constants of general linear media from causality. Application to the theory of natural optical activity. 2) Derivation of sum rules for the optical constants from causality and from the short-time response function (asymptotic high-frequency behavior). Average spectral behavior of optical media. Applications. 3) Role of spectral conditions. Analytic properties of coherence functions in quantum optics. Reconstruction theorem.4) Phase retrieval problems. 5) Inverse scattering problems. 6) Solution of nonlinear evolution equations in optics by inverse scattering methods. Application to self-induced transparency. Causality in nonlinear wave propagation. 7) Analytic continuation in frequency and angular momentum. Complex singularities. Resonances and natural-mode expansions. Regge poles. 8) Wigner's causal inequality. Time delay. Spatial displacements in total reflection. 9) Analyticity in diffraction theory. Complex angular momentum theory of Mie scattering. Diffraction as a barrier tunnelling effect. Complex trajectories in optics. (Author) [pt

mediation: R Package for Causal Mediation Analysis

Directory of Open Access Journals (Sweden)

Dustin Tingley

2014-09-01

Full Text Available In this paper, we describe the R package mediation for conducting causal mediation analysis in applied empirical research. In many scientific disciplines, the goal of researchers is not only estimating causal effects of a treatment but also understanding the process in which the treatment causally affects the outcome. Causal mediation analysis is frequently used to assess potential causal mechanisms. The mediation package implements a comprehensive suite of statistical tools for conducting such an analysis. The package is organized into two distinct approaches. Using the model-based approach, researchers can estimate causal mediation effects and conduct sensitivity analysis under the standard research design. Furthermore, the design-based approach provides several analysis tools that are applicable under different experimental designs. This approach requires weaker assumptions than the model-based approach. We also implement a statistical method for dealing with multiple (causally dependent mediators, which are often encountered in practice. Finally, the package also offers a methodology for assessing causal mediation in the presence of treatment noncompliance, a common problem in randomized trials.

Attributions of Mental Illness: An Ethnically Diverse Community Perspective.

Science.gov (United States)

Bignall, Whitney J Raglin; Jacquez, Farrah; Vaughn, Lisa M

2015-07-01

Although the prevalence of mental illness is similar across ethnic groups, a large disparity exists in the utilization of services. Mental health attributions, causal beliefs regarding the etiology of mental illness, may contribute to this disparity. To understand mental health attributions across diverse ethnic backgrounds, we conducted focus groups with African American (n = 8; 24 %), Asian American (n = 6; 18 %), Latino/Hispanic (n = 9; 26 %), and White (n = 11; 32 %) participants. We solicited attributions about 19 mental health disorders, each representing major sub-categories of the DSM-IV. Using a grounded theory approach, participant responses were categorized into 12 themes: Biological, Normalization, Personal Characteristic, Personal Choice, Just World, Spiritual, Family, Social Other, Environment, Trauma, Stress, and Diagnosis. Results indicate that ethnic minorities are more likely than Whites to mention spirituality and normalization causes. Understanding ethnic minority mental health attributions is critical to promote treatment-seeking behaviors and inform culturally responsive community-based mental health services.

Causal asymmetry across cultures: Assigning causal roles in symmetric physical settings

Directory of Open Access Journals (Sweden)

Andrea eBender

2011-09-01

Full Text Available In the cognitive sciences, causal cognition in the physical domain has featured as a core research topic, but the impact of culture has been rarely ever explored. One case in point for a topic on which this neglect is pronounced is the pervasive tendency of people to consider one of two (equally important entities as more important for bringing about an effect. In order to scrutinize how robust such tendencies are across cultures, we asked German and Tongan participants to assign prime causality in nine symmetric settings. For most settings, strong asymmetries in both cultures were found, but not always in the same direction, depending on the task content. This indicates that causal asymmetries, while indeed being a robust phenomenon across cultures, are also subject to culture-specific concepts. Moreover, the asymmetries were found to be modulated by figure-ground relations, but not by marking agency.

Entanglement, non-Markovianity, and causal non-separability

Science.gov (United States)

Milz, Simon; Pollock, Felix A.; Le, Thao P.; Chiribella, Giulio; Modi, Kavan

2018-03-01

Quantum mechanics, in principle, allows for processes with indefinite causal order. However, most of these causal anomalies have not yet been detected experimentally. We show that every such process can be simulated experimentally by means of non-Markovian dynamics with a measurement on additional degrees of freedom. In detail, we provide an explicit construction to implement arbitrary a causal processes. Furthermore, we give necessary and sufficient conditions for open system dynamics with measurement to yield processes that respect causality locally, and find that tripartite entanglement and nonlocal unitary transformations are crucial requirements for the simulation of causally indefinite processes. These results show a direct connection between three counter-intuitive concepts: entanglement, non-Markovianity, and causal non-separability.

Amodal causal capture in the tunnel effect.

Science.gov (United States)

Bae, Gi Yeul; Flombaum, Jonathan I

2011-01-01

In addition to identifying individual objects in the world, the visual system must also characterize the relationships between objects, for instance when objects occlude one another or cause one another to move. Here we explored the relationship between perceived causality and occlusion. Can one perceive causality in an occluded location? In several experiments, observers judged whether a centrally presented event involved a single object passing behind an occluder, or one object causally launching another (out of view and behind the occluder). With no additional context, the centrally presented event was typically judged as a non-causal pass, even when the occluding and disoccluding objects were different colors--an illusion known as the 'tunnel effect' that results from spatiotemporal continuity. However, when a synchronized context event involved an unambiguous causal launch, participants perceived a causal launch behind the occluder. This percept of an occluded causal interaction could also be driven by grouping and synchrony cues in the absence of any explicitly causal interaction. These results reinforce the hypothesis that causality is an aspect of perception. It is among the interpretations of the world that are independently available to vision when resolving ambiguity, and that the visual system can 'fill in' amodally.

Space-time as a causal set

International Nuclear Information System (INIS)

Bombelli, L.; Lee, J.; Meyer, D.; Sorkin, R.D.

1987-01-01

We propose that space-time at the smallest scales is in reality a causal set: a locally finite set of elements endowed with a partial order corresponding to the macroscopic relation that defines past and future. We explore how a Lorentzian manifold can approximate a causal set, noting in particular that the thereby defined effective dimensionality of a given causal set can vary with length scale. Finally, we speculate briefly on the quantum dynamics of causal sets, indicating why an appropriate choice of action can reproduce general relativity in the classical limit

Carcinogenesis. Genetics and circumstances

International Nuclear Information System (INIS)

Hino, Okio

2005-01-01

Described are the author's study and aspect concerning carcinogenesis and radiation carcinogenesis, where he thinks cancer is not automatic, has a process and takes time. For radiation carcinogenic studies, he has used a model of the rat with genetically determined kidney cancer which is highly radiosensitive. That is, mutation by the so-called 2nd-hit of the causal gene (tumor suppressing gene Tsc2) is studied in the animal where the 1st-hit has been done by retrotransposon insertion, with and without exposure to radiations (X-ray, heavy particle beam and cosmic ray) for elucidating the mutation spectrum of the causal gene, the carcinogenic target, for the ultimate aim to prevent human cancer. He discusses the drama-type molecular mechanisms leading to cancer, gene abnormality and disease crisis, discontinuity in continuity in cancer formation, and importance of the timely diagnosis and appropriate therapy, and concludes the present age is becoming such one as that the nature of cancer even if genetic can be controlled by circumstances like timely and appropriate intervention. (S.I.)

Representing Personal Determinants in Causal Structures.

Science.gov (United States)

Bandura, Albert

1984-01-01

Responds to Staddon's critique of the author's earlier article and addresses issues raised by Staddon's (1984) alternative models of causality. The author argues that it is not the formalizability of causal processes that is the issue but whether cognitive determinants of behavior are reducible to past stimulus inputs in causal structures.…

[Causal analysis approaches in epidemiology].

Science.gov (United States)

Dumas, O; Siroux, V; Le Moual, N; Varraso, R

2014-02-01

Epidemiological research is mostly based on observational studies. Whether such studies can provide evidence of causation remains discussed. Several causal analysis methods have been developed in epidemiology. This paper aims at presenting an overview of these methods: graphical models, path analysis and its extensions, and models based on the counterfactual approach, with a special emphasis on marginal structural models. Graphical approaches have been developed to allow synthetic representations of supposed causal relationships in a given problem. They serve as qualitative support in the study of causal relationships. The sufficient-component cause model has been developed to deal with the issue of multicausality raised by the emergence of chronic multifactorial diseases. Directed acyclic graphs are mostly used as a visual tool to identify possible confounding sources in a study. Structural equations models, the main extension of path analysis, combine a system of equations and a path diagram, representing a set of possible causal relationships. They allow quantifying direct and indirect effects in a general model in which several relationships can be tested simultaneously. Dynamic path analysis further takes into account the role of time. The counterfactual approach defines causality by comparing the observed event and the counterfactual event (the event that would have been observed if, contrary to the fact, the subject had received a different exposure than the one he actually received). This theoretical approach has shown limits of traditional methods to address some causality questions. In particular, in longitudinal studies, when there is time-varying confounding, classical methods (regressions) may be biased. Marginal structural models have been developed to address this issue. In conclusion, "causal models", though they were developed partly independently, are based on equivalent logical foundations. A crucial step in the application of these models is the

Repeated Causal Decision Making

Science.gov (United States)

Hagmayer, York; Meder, Bjorn

2013-01-01

Many of our decisions refer to actions that have a causal impact on the external environment. Such actions may not only allow for the mere learning of expected values or utilities but also for acquiring knowledge about the causal structure of our world. We used a repeated decision-making paradigm to examine what kind of knowledge people acquire in…

Causality in Classical Electrodynamics

Science.gov (United States)

Savage, Craig

2012-01-01

Causality in electrodynamics is a subject of some confusion, especially regarding the application of Faraday's law and the Ampere-Maxwell law. This has led to the suggestion that we should not teach students that electric and magnetic fields can cause each other, but rather focus on charges and currents as the causal agents. In this paper I argue…

Investigating the possible causal association of smoking with depression and anxiety using Mendelian randomisation meta-analysis: The CARTA consortium

NARCIS (Netherlands)

A.E. Taylor (Amy E.); M.E. Fluharty (Meg E.); J.H. Bjørngaard (Johan H.); M.E. Gabrielsen (Maiken Elvestad); F. Skorpen (Frank); R.E. Marioni (Riccardo); A. Campbell (Archie); J. Engmann (Jorgen); S.S. Mirza (Saira); A. Loukola (Anu); T. Laatikainen (Tiina); T. Partonen (Timo); M. Kaakinen (Marika); F. Ducci (Francesca); A. Cavadino (Alana); L.L.N. Husemoen (Lise Lotte); T.S. Ahluwalia (Tarunveer Singh); R.K. Jacobsen (Rikke Kart); T. Skaaby (Tea); J.F. Ebstrup (Jeanette Frost); E.L. Mortensen (Erik); C.C. Minica (Camelia C.); J.M. Vink (Jacqueline); G.A.H.M. Willemsen (Gonneke); P. Marques-Vidal (Pedro); C.E. Dale (Caroline E.); A. Amuzu (Antoinette); L.T. Lennon (Lucy T.); J. Lahti (Jari); A. Palotie (Aarno); K. Räikkönen (Katri); A. Wong (Andrew); L. Paternoster (Lavinia); A.P.-Y. Wong (Angelita Pui-Yee); L.J. Horwood (L. John); M. Murphy (Michael); E.C. Johnstone (Elaine C.); M.A. Kennedy (Martin A.); Z. Pausova (Zdenka); T. Paus (Tomáš); Y. Ben-Shlomo; C. Nohr (Christian); D. Kuh (Diana); M. Kivimaki (Mika); J.G. Eriksson (Johan G.); R. Morris (Richard); J.P. Casas (Juan); M. Preisig (Martin); D.I. Boomsma (Dorret); A. Linneberg (Allan); C. Power (Christopher); E. Hypponen (Elina); J. Veijola (Juha); M.-R. Jarvelin (Marjo-Riitta); T. Korhonen (Tellervo); H.W. Tiemeier (Henning); M. Kumari (Meena); D.J. Porteous (David J.); C. Hayward (Caroline); P.R. Romundstad (Pa˚l R.); G.D. Smith; M.R. Munafò (Marcus)

2014-01-01

textabstractObjectives: To investigate whether associations of smoking with depression and anxiety are likely to be causal, using a Mendelian randomisation approach. Design: Mendelian randomisation meta-analyses using a genetic variant (rs16969968/rs1051730) as a proxy for smoking heaviness, and

Treating the Cause of Illness Rather than the Symptoms: Parental Causal Beliefs and Treatment Choices in Autism Spectrum Disorder

Science.gov (United States)

Dardennes, Roland M.; Al Anbar, Nebal N.; Prado-Netto, Arthur; Kaye, Kelley; Contejean, Yves; Al Anbar, Nesreen N.

2011-01-01

Objectives: To explore the relationship between causal beliefs on autism (CBA) and treatment choices. Design and methods: A cross-sectional design was employed. Parents of a child with autism spectrum disorder (ASD) were asked to complete the Lay-Beliefs about Autism Questionnaire (LBA-Q) and answer questions about treatments used. Only items…

Kant on causal laws and powers.

Science.gov (United States)

Henschen, Tobias

2014-12-01

The aim of the paper is threefold. Its first aim is to defend Eric Watkins's claim that for Kant, a cause is not an event but a causal power: a power that is borne by a substance, and that, when active, brings about its effect, i.e. a change of the states of another substance, by generating a continuous flow of intermediate states of that substance. The second aim of the paper is to argue against Watkins that the Kantian concept of causal power is not the pre-critical concept of real ground but the category of causality, and that Kant holds with Hume that causal laws cannot be inferred non-inductively (that he accordingly has no intention to show in the Second analogy or elsewhere that events fall under causal laws). The third aim of the paper is to compare the Kantian position on causality with central tenets of contemporary powers ontology: it argues that unlike the variants endorsed by contemporary powers theorists, the Kantian variants of these tenets are resistant to objections that neo-Humeans raise to these tenets.

An Evaluation of Active Learning Causal Discovery Methods for Reverse-Engineering Local Causal Pathways of Gene Regulation

Science.gov (United States)

Ma, Sisi; Kemmeren, Patrick; Aliferis, Constantin F.; Statnikov, Alexander

2016-01-01

Reverse-engineering of causal pathways that implicate diseases and vital cellular functions is a fundamental problem in biomedicine. Discovery of the local causal pathway of a target variable (that consists of its direct causes and direct effects) is essential for effective intervention and can facilitate accurate diagnosis and prognosis. Recent research has provided several active learning methods that can leverage passively observed high-throughput data to draft causal pathways and then refine the inferred relations with a limited number of experiments. The current study provides a comprehensive evaluation of the performance of active learning methods for local causal pathway discovery in real biological data. Specifically, 54 active learning methods/variants from 3 families of algorithms were applied for local causal pathways reconstruction of gene regulation for 5 transcription factors in S. cerevisiae. Four aspects of the methods’ performance were assessed, including adjacency discovery quality, edge orientation accuracy, complete pathway discovery quality, and experimental cost. The results of this study show that some methods provide significant performance benefits over others and therefore should be routinely used for local causal pathway discovery tasks. This study also demonstrates the feasibility of local causal pathway reconstruction in real biological systems with significant quality and low experimental cost. PMID:26939894

Using genetic loci to understand the relationship between adiposity and psychological distress: a Mendelian Randomization study in the Copenhagen General Population Study of 53,221 adults

DEFF Research Database (Denmark)

Lawlor, Debbie A; Harbord, Roger M; Tybjærg-Hansen, Anne

2011-01-01

We used genetic variants that are robustly associated with adiposity to examine the causal association of adiposity with psychological distress.......We used genetic variants that are robustly associated with adiposity to examine the causal association of adiposity with psychological distress....

Effects of Omalizumab on Rhinovirus Infections, Illnesses, and Exacerbations of Asthma.

Science.gov (United States)

Esquivel, Ann; Busse, William W; Calatroni, Agustin; Togias, Alkis G; Grindle, Kristine G; Bochkov, Yury A; Gruchalla, Rebecca S; Kattan, Meyer; Kercsmar, Carolyn M; Khurana Hershey, G; Kim, Haejin; Lebeau, Petra; Liu, Andrew H; Szefler, Stanley J; Teach, Stephen J; West, Joseph B; Wildfire, Jeremy; Pongracic, Jaqueline A; Gern, James E

2017-10-15

Allergic inflammation has been linked to increased susceptibility to viral illnesses, but it is unclear whether this association is causal. To test whether omalizumab treatment to reduce IgE would shorten the frequency and duration of rhinovirus (RV) illnesses in children with allergic asthma. In the PROSE (Preventative Omalizumab or Step-up Therapy for Severe Fall Exacerbations) study, we examined children with allergic asthma (aged 6-17 yr; n = 478) from low-income census tracts in eight U.S. cities, and we analyzed virology for the groups randomized to treatment with guidelines-based asthma care (n = 89) or add-on omalizumab (n = 259). Weekly nasal mucus samples were analyzed for RVs, and respiratory symptoms and asthma exacerbations were recorded over a 90-day period during the fall seasons of 2012 or 2013. Adjusted illness rates (illnesses per sample) by treatment arm were calculated using Poisson regression. RVs were detected in 97 (57%) of 171 exacerbation samples and 2,150 (36%) of 5,959 nonexacerbation samples (OR, 2.32; P Omalizumab decreased the duration of RV infection (11.2 d vs. 12.4 d; P = 0.03) and reduced peak RV shedding by 0.4 log units (95% confidence interval, -0.77 to -0.02; P = 0.04). Finally, omalizumab decreased the frequency of RV illnesses (risk ratio, 0.64; 95% confidence interval, 0.49-0.84). In children with allergic asthma, treatment with omalizumab decreased the duration of RV infections, viral shedding, and the risk of RV illnesses. These findings provide direct evidence that blocking IgE decreases susceptibility to RV infections and illness. Clinical trial registered with www.clinicaltrials.gov (NCT01430403).

Is thermogenesis a significant causal factor in preventing the "globesity" epidemic?

Science.gov (United States)

Hansen, Jens Carl; Gilman, Andrew P; Odland, Jon Øyvind

2010-08-01

During the last four decades the world has experienced an epidemic of overweight individuals in affluent as well as developing countries. The WHO has predicted a "globesity epidemic" with more than 1 billion adults being overweight and at least 300 million of these being clinically obese. Obesity among children and adolescents is of great significance. From a global population perspective, this epidemic in weight gain and its sequelae are the largest public health problems identified to date and have very significant adverse implications for population health, and have by now almost reached the proportion of a pandemic. While genetic changes have been discussed as a cause of the epidemic, there has been too little time since its start to enable enough genetic adaptation to take place for this to provide a valid explanation. Traditionally positive energy balance and sedentary life style have been regarded as the primary causal factors; however, these factors have so far failed to provide explanations for the entire problem. For these reasons it seems warranted to investigate other possible co-factors contributing to the "globesity epidemic" and to find efficient strategies to counteract further increases in the size and nature of the epidemic. The purpose of this paper is to discuss a potential preventive co-factor, thermogenesis. Special attention has been paid to the influence of ambient temperature as a grossly neglected factor in the debate. As most people today live and work at ambient temperatures close to their body temperature (the thermal neutral point), we hypothesise that this is an important causal co-factor in the "globesity" epidemic. The hypothesis: The null hypothesis that adaptive thermogenesis in brown adipose tissue in adult humans is not significant for weight loss is rejected. We propose the hypothesis that homoeothermic living conditions close to the thermogenic neutral level is an important causal co-factor in the "Globesity" Epidemic

Repair of Partly Misspecified Causal Diagrams.

Science.gov (United States)

Oates, Chris J; Kasza, Jessica; Simpson, Julie A; Forbes, Andrew B

2017-07-01

Errors in causal diagrams elicited from experts can lead to the omission of important confounding variables from adjustment sets and render causal inferences invalid. In this report, a novel method is presented that repairs a misspecified causal diagram through the addition of edges. These edges are determined using a data-driven approach designed to provide improved statistical efficiency relative to de novo structure learning methods. Our main assumption is that the expert is "directionally informed," meaning that "false" edges provided by the expert would not create cycles if added to the "true" causal diagram. The overall procedure is cast as a preprocessing technique that is agnostic to subsequent causal inferences. Results based on simulated data and data derived from an observational cohort illustrate the potential for data-assisted elicitation in epidemiologic applications. See video abstract at, http://links.lww.com/EDE/B208.

Functional equations with causal operators

CERN Document Server

Corduneanu, C

2003-01-01

Functional equations encompass most of the equations used in applied science and engineering: ordinary differential equations, integral equations of the Volterra type, equations with delayed argument, and integro-differential equations of the Volterra type. The basic theory of functional equations includes functional differential equations with causal operators. Functional Equations with Causal Operators explains the connection between equations with causal operators and the classical types of functional equations encountered by mathematicians and engineers. It details the fundamentals of linear equations and stability theory and provides several applications and examples.

Classical planning and causal implicatures

DEFF Research Database (Denmark)

Blackburn, Patrick Rowan; Benotti, Luciana

In this paper we motivate and describe a dialogue manager (called Frolog) which uses classical planning to infer causal implicatures. A causal implicature is a type of Gricean relation implicature, a highly context dependent form of inference. As we shall see, causal implicatures are important...... to generate clarification requests"; as a result we can model task-oriented dialogue as an interactive process locally structured by negotiation of the underlying task. We give several examples of Frolog-human dialog, discuss the limitations imposed by the classical planning paradigm, and indicate...

Causal inference in economics and marketing.

Science.gov (United States)

Varian, Hal R

2016-07-05

This is an elementary introduction to causal inference in economics written for readers familiar with machine learning methods. The critical step in any causal analysis is estimating the counterfactual-a prediction of what would have happened in the absence of the treatment. The powerful techniques used in machine learning may be useful for developing better estimates of the counterfactual, potentially improving causal inference.

Genetics of immune-mediated disorders : from genome-wide association to molecular mechanism

NARCIS (Netherlands)

Kumar, Vinod; Wijmenga, Cisca; Xavier, Ramnik J.

2014-01-01

Genetic association studies have identified not only hundreds of susceptibility loci to immune-mediated diseases but also pinpointed causal amino-acid variants of HLA genes that contribute to many autoimmune reactions. Majority of non-HLA genetic variants are located within non-coding regulatory

Interactions of information transfer along separable causal paths

Science.gov (United States)

Jiang, Peishi; Kumar, Praveen

2018-04-01

Complex systems arise as a result of interdependences between multiple variables, whose causal interactions can be visualized in a time-series graph. Transfer entropy and information partitioning approaches have been used to characterize such dependences. However, these approaches capture net information transfer occurring through a multitude of pathways involved in the interaction and as a result mask our ability to discern the causal interaction within a subgraph of interest through specific pathways. We build on recent developments of momentary information transfer along causal paths proposed by Runge [Phys. Rev. E 92, 062829 (2015), 10.1103/PhysRevE.92.062829] to develop a framework for quantifying information partitioning along separable causal paths. Momentary information transfer along causal paths captures the amount of information transfer between any two variables lagged at two specific points in time. Our approach expands this concept to characterize the causal interaction in terms of synergistic, unique, and redundant information transfer through separable causal paths. Through a graphical model, we analyze the impact of the separable and nonseparable causal paths and the causality structure embedded in the graph as well as the noise effect on information partitioning by using synthetic data generated from two coupled logistic equation models. Our approach can provide a valuable reference for an autonomous information partitioning along separable causal paths which form a causal subgraph influencing a target.

Does Causality Matter More Now? Increase in the Proportion of Causal Language in English Texts.

Science.gov (United States)

Iliev, Rumen; Axelrod, Robert

2016-05-01

The vast majority of the work on culture and cognition has focused on cross-cultural comparisons, largely ignoring the dynamic aspects of culture. In this article, we provide a diachronic analysis of causal cognition over time. We hypothesized that the increased role of education, science, and technology in Western societies should be accompanied by greater attention to causal connections. To test this hypothesis, we compared word frequencies in English texts from different time periods and found an increase in the use of causal language of about 40% over the past two centuries. The observed increase was not attributable to general language effects or to changing semantics of causal words. We also found that there was a consistent difference between the 19th and the 20th centuries, and that the increase happened mainly in the 20th century. © The Author(s) 2016.

Causality, spin, and equal-time commutators

International Nuclear Information System (INIS)

Abdel-Rahman, A.M.

1975-01-01

We study the causality constraints on the structure of the Lorentz-antisymmetric component of the commutator of two conserved isovector currents between fermion states of equal momenta. We discuss the sum rules that follow from causality and scaling, using the recently introduced refined infinite-momentum technique. The complete set of sum rules is found to include the spin-dependent fixed-mass sum rules obtained from light-cone commutators. The causality and scaling restrictions on the structure of the electromagnetic equal-time commutators are discussed, and it is found, in particular, that causality requires the spin-dependent part of the matrix element for the time-space electromagnetic equal-time commutator to vanish identically. It is also shown, in comparison with the electromagnetic case, that the corresponding matrix element for the time-space isovector current equal-time commutator is required, by causality, to have isospin-antisymmetric tensor and scalar operator Schwinger terms

Causal inference, probability theory, and graphical insights.

Science.gov (United States)

Baker, Stuart G

2013-11-10

Causal inference from observational studies is a fundamental topic in biostatistics. The causal graph literature typically views probability theory as insufficient to express causal concepts in observational studies. In contrast, the view here is that probability theory is a desirable and sufficient basis for many topics in causal inference for the following two reasons. First, probability theory is generally more flexible than causal graphs: Besides explaining such causal graph topics as M-bias (adjusting for a collider) and bias amplification and attenuation (when adjusting for instrumental variable), probability theory is also the foundation of the paired availability design for historical controls, which does not fit into a causal graph framework. Second, probability theory is the basis for insightful graphical displays including the BK-Plot for understanding Simpson's paradox with a binary confounder, the BK2-Plot for understanding bias amplification and attenuation in the presence of an unobserved binary confounder, and the PAD-Plot for understanding the principal stratification component of the paired availability design. Published 2013. This article is a US Government work and is in the public domain in the USA.

Causality as a Rigorous Notion and Quantitative Causality Analysis with Time Series

Science.gov (United States)

Liang, X. S.

2017-12-01

Given two time series, can one faithfully tell, in a rigorous and quantitative way, the cause and effect between them? Here we show that this important and challenging question (one of the major challenges in the science of big data), which is of interest in a wide variety of disciplines, has a positive answer. Particularly, for linear systems, the maximal likelihood estimator of the causality from a series X2 to another series X1, written T2→1, turns out to be concise in form: T2→1 = [C11 C12 C2,d1 — C112 C1,d1] / [C112 C22 — C11C122] where Cij (i,j=1,2) is the sample covariance between Xi and Xj, and Ci,dj the covariance between Xi and ΔXj/Δt, the difference approximation of dXj/dt using the Euler forward scheme. An immediate corollary is that causation implies correlation, but not vice versa, resolving the long-standing debate over causation versus correlation. The above formula has been validated with touchstone series purportedly generated with one-way causality that evades the classical approaches such as Granger causality test and transfer entropy analysis. It has also been applied successfully to the investigation of many real problems. Through a simple analysis with the stock series of IBM and GE, an unusually strong one-way causality is identified from the former to the latter in their early era, revealing to us an old story, which has almost faded into oblivion, about "Seven Dwarfs" competing with a "Giant" for the computer market. Another example presented here regards the cause-effect relation between the two climate modes, El Niño and Indian Ocean Dipole (IOD). In general, these modes are mutually causal, but the causality is asymmetric. To El Niño, the information flowing from IOD manifests itself as a propagation of uncertainty from the Indian Ocean. In the third example, an unambiguous one-way causality is found between CO2 and the global mean temperature anomaly. While it is confirmed that CO2 indeed drives the recent global warming

K-causality and degenerate spacetimes

Science.gov (United States)

Dowker, H. F.; Garcia, R. S.; Surya, S.

2000-11-01

The causal relation K+ was introduced by Sorkin and Woolgar to extend the standard causal analysis of C2 spacetimes to those that are only C0. Most of their results also hold true in the case of metrics with degeneracies which are C0 but vanish at isolated points. In this paper we seek to examine K+ explicitly in the case of topology-changing `Morse histories' which contain degeneracies. We first demonstrate some interesting features of this relation in globally Lorentzian spacetimes. In particular, we show that K+ is robust and the Hawking and Sachs characterization of causal continuity translates into a natural condition in terms of K+. We then examine K+ in topology-changing Morse spacetimes with the degenerate points excised and then for the Morse histories in which the degenerate points are reinstated. We find further characterizations of causal continuity in these cases.

Causal inference in econometrics

CERN Document Server

Kreinovich, Vladik; Sriboonchitta, Songsak

2016-01-01

This book is devoted to the analysis of causal inference which is one of the most difficult tasks in data analysis: when two phenomena are observed to be related, it is often difficult to decide whether one of them causally influences the other one, or whether these two phenomena have a common cause. This analysis is the main focus of this volume. To get a good understanding of the causal inference, it is important to have models of economic phenomena which are as accurate as possible. Because of this need, this volume also contains papers that use non-traditional economic models, such as fuzzy models and models obtained by using neural networks and data mining techniques. It also contains papers that apply different econometric models to analyze real-life economic dependencies.

Causal localizations in relativistic quantum mechanics

Science.gov (United States)

Castrigiano, Domenico P. L.; Leiseifer, Andreas D.

2015-07-01

Causal localizations describe the position of quantum systems moving not faster than light. They are constructed for the systems with finite spinor dimension. At the center of interest are the massive relativistic systems. For every positive mass, there is the sequence of Dirac tensor-localizations, which provides a complete set of inequivalent irreducible causal localizations. They obey the principle of special relativity and are fully Poincaré covariant. The boosters are determined by the causal position operator and the other Poincaré generators. The localization with minimal spinor dimension is the Dirac localization. Thus, the Dirac equation is derived here as a mere consequence of the principle of causality. Moreover, the higher tensor-localizations, not known so far, follow from Dirac's localization by a simple construction. The probability of localization for positive energy states results to be described by causal positive operator valued (PO-) localizations, which are the traces of the causal localizations on the subspaces of positive energy. These causal Poincaré covariant PO-localizations for every irreducible massive relativistic system were, all the more, not known before. They are shown to be separated. Hence, the positive energy systems can be localized within every open region by a suitable preparation as accurately as desired. Finally, the attempt is made to provide an interpretation of the PO-localization operators within the frame of conventional quantum mechanics attributing an important role to the negative energy states.

Bayesian networks improve causal environmental ...

Science.gov (United States)

Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the problem, using this knowledge with probabilistic calculus to combine multiple lines of evidence, and minimizing biases in predicting or diagnosing causal relationships. Too often, sources of uncertainty in conventional weight of evidence approaches are ignored that can be accounted for with Bayesian networks. Specifying and propagating uncertainties improve the ability of models to incorporate strength of the evidence in the risk management phase of an assessment. Probabilistic inference from a Bayesian network allows evaluation of changes in uncertainty for variables from the evidence. The network structure and probabilistic framework of a Bayesian approach provide advantages over qualitative approaches in weight of evidence for capturing the impacts of multiple sources of quantifiable uncertainty on predictions of ecological risk. Bayesian networks can facilitate the development of evidence-based policy under conditions of uncertainty by incorporating analytical inaccuracies or the implications of imperfect information, structuring and communicating causal issues through qualitative directed graph formulations, and quantitatively comparing the causal power of multiple stressors on value

Hierarchical organisation of causal graphs

International Nuclear Information System (INIS)

Dziopa, P.

1993-01-01

This paper deals with the design of a supervision system using a hierarchy of models formed by graphs, in which the variables are the nodes and the causal relations between the variables of the arcs. To obtain a representation of the variables evolutions which contains only the relevant features of their real evolutions, the causal relations are completed with qualitative transfer functions (QTFs) which produce roughly the behaviour of the classical transfer functions. Major improvements have been made in the building of the hierarchical organization. First, the basic variables of the uppermost level and the causal relations between them are chosen. The next graph is built by adding intermediary variables to the upper graph. When the undermost graph has been built, the transfer functions parameters corresponding to its causal relations are identified. The second task consists in the upwelling of the information from the undermost graph to the uppermost one. A fusion procedure of the causal relations has been designed to compute the QFTs relevant for each level. This procedure aims to reduce the number of parameters needed to represent an evolution at a high level of abstraction. These techniques have been applied to the hierarchical modelling of nuclear process. (authors). 8 refs., 12 figs

The New Genetics and Natural versus Artificial Genetic Modification

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Mae-Wan Ho

2013-11-01

Full Text Available The original rationale and impetus for artificial genetic modification was the “central dogma” of molecular biology that assumed DNA carries all the instructions for making an organism, which are transmitted via RNA to protein to biological function in linear causal chains. This is contrary to the reality of the “fluid genome” that has emerged since the mid-1970s. In order to survive, the organism needs to engage in natural genetic modification in real time, an exquisitely precise molecular dance of life with RNA and DNA responding to and participating in “downstream” biological functions. Artificial genetic modification, in contrast, is crude, imprecise, and interferes with the natural process. It drives natural systems towards maximum biosemiotic entropy as the perturbations are propagated and amplified through the complex cascades of interactions between subsystems that are essential for health and longevity.

Dynamics and causality constraints

International Nuclear Information System (INIS)

Sousa, Manoelito M. de

2001-04-01

The physical meaning and the geometrical interpretation of causality implementation in classical field theories are discussed. Causality in field theory are kinematical constraints dynamically implemented via solutions of the field equation, but in a limit of zero-distance from the field sources part of these constraints carries a dynamical content that explains old problems of classical electrodynamics away with deep implications to the nature of physicals interactions. (author)

Causal uncertainty, claimed and behavioural self-handicapping.

Science.gov (United States)

Thompson, Ted; Hepburn, Jonathan

2003-06-01

Causal uncertainty beliefs involve doubts about the causes of events, and arise as a consequence of non-contingent evaluative feedback: feedback that leaves the individual uncertain about the causes of his or her achievement outcomes. Individuals high in causal uncertainty are frequently unable to confidently attribute their achievement outcomes, experience anxiety in achievement situations and as a consequence are likely to engage in self-handicapping behaviour. Accordingly, we sought to establish links between trait causal uncertainty, claimed and behavioural self-handicapping. Participants were N=72 undergraduate students divided equally between high and low causally uncertain groups. We used a 2 (causal uncertainty status: high, low) x 3 (performance feedback condition: success, non-contingent success, non-contingent failure) between-subjects factorial design to examine the effects of causal uncertainty on achievement behaviour. Following performance feedback, participants completed 20 single-solution anagrams and 12 remote associate tasks serving as performance measures, and 16 unicursal tasks to assess practice effort. Participants also completed measures of claimed handicaps, state anxiety and attributions. Relative to low causally uncertain participants, high causally uncertain participants claimed more handicaps prior to performance on the anagrams and remote associates, reported higher anxiety, attributed their failure to internal, stable factors, and reduced practice effort on the unicursal tasks, evident in fewer unicursal tasks solved. These findings confirm links between trait causal uncertainty and claimed and behavioural self-handicapping, highlighting the need for educators to facilitate means by which students can achieve surety in the manner in which they attribute the causes of their achievement outcomes.

Causal knowledge and reasoning in decision making

NARCIS (Netherlands)

Hagmayer, Y.; Witteman, C.L.M.

2017-01-01

Normative causal decision theories argue that people should use their causal knowledge in decision making. Based on these ideas, we argue that causal knowledge and reasoning may support and thereby potentially improve decision making based on expected outcomes, narratives, and even cues. We will

Expert Causal Reasoning and Explanation.

Science.gov (United States)

Kuipers, Benjamin

The relationship between cognitive psychologists and researchers in artificial intelligence carries substantial benefits for both. An ongoing investigation in causal reasoning in medical problem solving systems illustrates this interaction. This paper traces a dialectic of sorts in which three different types of causal resaoning for medical…

Vitamin D deficiency is independently associated with mortality among critically ill patients

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Rafael Barberena Moraes

2015-05-01

Full Text Available OBJECTIVE: Studies suggest an association between vitamin D deficiency and morbidity/mortality in critically ill patients. Several issues remain unexplained, including which vitamin D levels are related to morbidity and mortality and the relevance of vitamin D kinetics to clinical outcomes. We conducted this study to address the association of baseline vitamin D levels and vitamin D kinetics with morbidity and mortality in critically ill patients. METHOD: In 135 intensive care unit (ICU patients, vitamin D was prospectively measured on admission and weekly until discharge from the ICU. The following outcomes of interest were analyzed: 28-day mortality, mechanical ventilation, length of stay, infection rate, and culture positivity. RESULTS: Mortality rates were higher among patients with vitamin D levels 12 ng/mL (32.2% vs. 13.2%, with an adjusted relative risk of 2.2 (95% CI 1.07-4.54; p< 0.05. There were no differences in the length of stay, ventilation requirements, infection rate, or culture positivity. CONCLUSIONS: This study suggests that low vitamin D levels on ICU admission are an independent risk factor for mortality in critically ill patients. Low vitamin D levels at ICU admission may have a causal relationship with mortality and may serve as an indicator for vitamin D replacement among critically ill patients.

Links between causal effects and causal association for surrogacy evaluation in a gaussian setting.

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Conlon, Anna; Taylor, Jeremy; Li, Yun; Diaz-Ordaz, Karla; Elliott, Michael

2017-11-30

Two paradigms for the evaluation of surrogate markers in randomized clinical trials have been proposed: the causal effects paradigm and the causal association paradigm. Each of these paradigms rely on assumptions that must be made to proceed with estimation and to validate a candidate surrogate marker (S) for the true outcome of interest (T). We consider the setting in which S and T are Gaussian and are generated from structural models that include an unobserved confounder. Under the assumed structural models, we relate the quantities used to evaluate surrogacy within both the causal effects and causal association frameworks. We review some of the common assumptions made to aid in estimating these quantities and show that assumptions made within one framework can imply strong assumptions within the alternative framework. We demonstrate that there is a similarity, but not exact correspondence between the quantities used to evaluate surrogacy within each framework, and show that the conditions for identifiability of the surrogacy parameters are different from the conditions, which lead to a correspondence of these quantities. Copyright © 2017 John Wiley & Sons, Ltd.

Inter-embodiment and the experience of genetic testing for familial hypercholesterolaemia.

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Jenkins, Nicholas; Lawton, Julia; Douglas, Margaret; Hallowell, Nina

2013-05-01

In this article we explore the concept of inter-embodiment and its potential for advancing sociological research into illness biography and genetic identity. Inter-embodiment theory views embodied knowledge as produced through relations between bodies, as opposed to originating from within the body or as the product of relations between disembodied selves. Drawing on a qualitative study in which we interviewed 38 individuals about their experiences of discovering they had high cholesterol and undergoing genetic testing for familial hypercholesterolaemia (FH), we discuss how their narratives may be understood from an inter-embodiment perspective. The participants frequently talked at length about their family histories of high cholesterol and cardiovascular disease. Through these accounts, we develop the concept of the family corpus in order to highlight the role body networks play in shaping lay constructions of genetic identity and a familial disease biography. The notion of a family corpus, we argue, is useful in understanding why genetic testing for FH was experienced as either biographical re-enforcement or as biographical disruption. We conclude by discussing the implications of our findings for future sociological research into illness biography and genetic identity. © 2012 The Authors. Sociology of Health & Illness © 2012 Foundation for the Sociology of Health & Illness/Blackwell Publishing Ltd.

Non-Gaussian Methods for Causal Structure Learning.

Science.gov (United States)

Shimizu, Shohei

2018-05-22

Causal structure learning is one of the most exciting new topics in the fields of machine learning and statistics. In many empirical sciences including prevention science, the causal mechanisms underlying various phenomena need to be studied. Nevertheless, in many cases, classical methods for causal structure learning are not capable of estimating the causal structure of variables. This is because it explicitly or implicitly assumes Gaussianity of data and typically utilizes only the covariance structure. In many applications, however, non-Gaussian data are often obtained, which means that more information may be contained in the data distribution than the covariance matrix is capable of containing. Thus, many new methods have recently been proposed for using the non-Gaussian structure of data and inferring the causal structure of variables. This paper introduces prevention scientists to such causal structure learning methods, particularly those based on the linear, non-Gaussian, acyclic model known as LiNGAM. These non-Gaussian data analysis tools can fully estimate the underlying causal structures of variables under assumptions even in the presence of unobserved common causes. This feature is in contrast to other approaches. A simulated example is also provided.

Causal beliefs about depression in different cultural groups—what do cognitive psychological theories of causal learning and reasoning predict?

OpenAIRE

Hagmayer, York; Engelmann, Neele

2014-01-01

Cognitive psychological research focuses on causal learning and reasoning while cognitive anthropological and social science research tend to focus on systems of beliefs. Our aim was to explore how these two types of research can inform each other. Cognitive psychological theories (causal model theory and causal Bayes nets) were used to derive predictions for systems of causal beliefs. These predictions were then applied to lay theories of depression as a specific test case. A systematic lite...

Genetics of early growth vigour in lentil (Lens culinaris Medik.)

Indian Academy of Sciences (India)

Rapid early growth vigour, 70–75 days to flowering. Figure 1. Frequency distributions of early growth vigour based on seedling length in parents (DPL15, ILL7663 and ILL6002) and F2 populations derived from two crosses (DPL15 × ILL7663; DPL15 × ILL6002) in lentil. 324. Journal of Genetics, Vol. 92, No. 2, August 2013 ...

Covariation in Natural Causal Induction.

Science.gov (United States)

Cheng, Patricia W.; Novick, Laura R.

1991-01-01

Biases and models usually offered by cognitive and social psychology and by philosophy to explain causal induction are evaluated with respect to focal sets (contextually determined sets of events over which covariation is computed). A probabilistic contrast model is proposed as underlying covariation computation in natural causal induction. (SLD)

A survey of genomic studies supports association of circadian clock genes with bipolar disorder spectrum illnesses and lithium response.

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Michael J McCarthy

Full Text Available Circadian rhythm abnormalities in bipolar disorder (BD have led to a search for genetic abnormalities in circadian "clock genes" associated with BD. However, no significant clock gene findings have emerged from genome-wide association studies (GWAS. At least three factors could account for this discrepancy: complex traits are polygenic, the organization of the clock is more complex than previously recognized, and/or genetic risk for BD may be shared across multiple illnesses. To investigate these issues, we considered the clock gene network at three levels: essential "core" clock genes, upstream circadian clock modulators, and downstream clock controlled genes. Using relaxed thresholds for GWAS statistical significance, we determined the rates of clock vs. control genetic associations with BD, and four additional illnesses that share clinical features and/or genetic risk with BD (major depression, schizophrenia, attention deficit/hyperactivity. Then we compared the results to a set of lithium-responsive genes. Associations with BD-spectrum illnesses and lithium-responsiveness were both enriched among core clock genes but not among upstream clock modulators. Associations with BD-spectrum illnesses and lithium-responsiveness were also enriched among pervasively rhythmic clock-controlled genes but not among genes that were less pervasively rhythmic or non-rhythmic. Our analysis reveals previously unrecognized associations between clock genes and BD-spectrum illnesses, partly reconciling previously discordant results from past GWAS and candidate gene studies.

Exploring Individual Differences in Preschoolers' Causal Stance

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Alvarez, Aubry; Booth, Amy E.

2016-01-01

Preschoolers, as a group, are highly attuned to causality, and this attunement is known to facilitate memory, learning, and problem solving. However, recent work reveals substantial individual variability in the strength of children's "causal stance," as demonstrated by their curiosity about and preference for new causal information. In…

How neuroscience and behavioral genetics improve psychiatric assessment: Report on a violent murder case

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Davide Rigoni

2010-10-01

Full Text Available Despite the advances in the understanding of neural and genetic foundations of violence, the investigation of the biological bases of a mental disorder is rarely included in psychiatric evaluation of mental insanity. Here we report on a case in which cognitive neuroscience and behavioral genetics methods were applied to a psychiatric forensic evaluation conducted on a young woman, J.F., tried for a violent and impulsive murder. The defendant had a history of multidrug and alcohol abuse and non-forensic clinical evaluation concluded for a diagnosis of borderline personality disorder. We analyzed the defendant’s brain structure in order to underlie possible brain structural abnormalities associated with pathological impulsivity. Voxel-Based Morphometry indexed a reduced gray matter volume in the left prefrontal cortex, in a region specifically associated with response inhibition. Furthermore, J.F.’s DNA was genotyped in order to identify genetic polymorphisms associated with various forms of violence and impulsive behaviour. Five polymorphisms that are known to be associated with impulsivity, violence, and other severe psychiatric illnesses were identified in J.F.’s DNA. Taken together, these data provided evidence for the biological correlates of a mental disorder characterized by high impulsivity and aggressive tendencies. Our claim is that the use of neuroscience and behavioral genetics do not change the rationale underlying the determination of criminal liability, which must be based on a causal link between the mental disorder and the crime. Rather, their use is crucial in providing objective data on the biological bases of a defendant’s mental disorder.

Cardiovascular disease among severe mental illness and psychiatric medication

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Sileshi Demelash

2017-01-01

Full Text Available People with mental illness are more likely to have serious coexisting physical health problems than the general population. Although lifestyle and genetics may contribute independent risks of cardiovascular dysfunction in schizophrenia and other serious mental illness, antipsychotic treatment also represents an important contributor to risk of cardiovascular disorder, particularly for certain drugs and for vulnerable patients. Mental health professionals and other health care provider must give emphasis to recognize the clinical signposts indicating mental health related cardiovascular problems to forestall progression to type II diabetes, cardiovascular events and premature death.

Genetics of Triglycerides and the Risk of Atherosclerosis.

Science.gov (United States)

Dron, Jacqueline S; Hegele, Robert A

2017-07-01

Plasma triglycerides are routinely measured with a lipid profile, and elevated plasma triglycerides are commonly encountered in the clinic. The confounded nature of this trait, which is correlated with numerous other metabolic perturbations, including depressed high-density lipoprotein cholesterol (HDL-C), has thwarted efforts to directly implicate triglycerides as causal in atherogenesis. Human genetic approaches involving large-scale populations and high-throughput genomic assessment under a Mendelian randomization framework have undertaken to sort out questions of causality. We review recent large-scale meta-analyses of cohorts and population-based sequencing studies designed to address whether common and rare variants in genes whose products are determinants of plasma triglycerides are also associated with clinical cardiovascular endpoints. The studied loci include genes encoding lipoprotein lipase and proteins that interact with it, such as apolipoprotein (apo) A-V, apo C-III and angiopoietin-like proteins 3 and 4, and common polymorphisms identified in genome-wide association studies. Triglyceride-raising variant alleles of these genes showed generally strong associations with clinical cardiovascular endpoints. However, in most cases, a second lipid disturbance-usually depressed HDL-C-was concurrently associated. While the findings collectively shift our understanding towards a potential causal role for triglycerides, we still cannot rule out the possibilities that triglycerides are a component of a joint phenotype with low HDL-C or that they are but markers of deeper causal metabolic disturbances that are not routinely measured in epidemiological-scale genetic studies.

Assessing the Causal Relationship of Maternal Height on Birth Size and Gestational Age at Birth: A Mendelian Randomization Analysis

Science.gov (United States)

Zhang, Ge; Bacelis, Jonas; Lengyel, Candice; Teramo, Kari; Hallman, Mikko; Helgeland, Øyvind; Johansson, Stefan; Myhre, Ronny; Sengpiel, Verena; Njølstad, Pål Rasmus; Jacobsson, Bo; Muglia, Louis

2015-01-01

Background Observational epidemiological studies indicate that maternal height is associated with gestational age at birth and fetal growth measures (i.e., shorter mothers deliver infants at earlier gestational ages with lower birth weight and birth length). Different mechanisms have been postulated to explain these associations. This study aimed to investigate the casual relationships behind the strong association of maternal height with fetal growth measures (i.e., birth length and birth weight) and gestational age by a Mendelian randomization approach. Methods and Findings We conducted a Mendelian randomization analysis using phenotype and genome-wide single nucleotide polymorphism (SNP) data of 3,485 mother/infant pairs from birth cohorts collected from three Nordic countries (Finland, Denmark, and Norway). We constructed a genetic score based on 697 SNPs known to be associated with adult height to index maternal height. To avoid confounding due to genetic sharing between mother and infant, we inferred parental transmission of the height-associated SNPs and utilized the haplotype genetic score derived from nontransmitted alleles as a valid genetic instrument for maternal height. In observational analysis, maternal height was significantly associated with birth length (p = 6.31 × 10−9), birth weight (p = 2.19 × 10−15), and gestational age (p = 1.51 × 10−7). Our parental-specific haplotype score association analysis revealed that birth length and birth weight were significantly associated with the maternal transmitted haplotype score as well as the paternal transmitted haplotype score. Their association with the maternal nontransmitted haplotype score was far less significant, indicating a major fetal genetic influence on these fetal growth measures. In contrast, gestational age was significantly associated with the nontransmitted haplotype score (p = 0.0424) and demonstrated a significant (p = 0.0234) causal effect of every 1 cm increase in maternal

Behavioural Pattern of Causality Parameter of Autoregressive ...

African Journals Online (AJOL)

In this paper, a causal form of Autoregressive Moving Average process, ARMA (p, q) of various orders and behaviour of the causality parameter of ARMA model is investigated. It is deduced that the behaviour of causality parameter ψi depends on positive and negative values of autoregressive parameter φ and moving ...

Tachyons and causal paradoxes

International Nuclear Information System (INIS)

Maund, J.B.

1979-01-01

Although the existence of tachyons is not ruled out by special relativity, it appears that causal paradoxes will arise if there are tachyons. The usual solutions to these paradoxes employ some form of the reinterpretation principle. In this paper it is argued first that, the principle is incoherent, second, that even if it is not, some causal paradoxes remain, and third, the most plausible ''solution,'' which appeals to boundary conditions of the universe, will conflict with special relativity

Causal beliefs about depression in different cultural groups – What do cognitive psychological theories of causal learning and reasoning predict?

Directory of Open Access Journals (Sweden)

York eHagmayer

2014-11-01

Full Text Available Cognitive psychological research focusses on causal learning and reasoning while cognitive anthropological and social science research tend to focus on systems of beliefs. Our aim was to explore how these two types of research can inform each other. Cognitive psychological theories (causal model theory and causal Bayes nets were used to derive predictions for systems of causal beliefs. These predictions were then applied to lay theories of depression as a specific test case. A systematic literature review on causal beliefs about depression was conducted, including original, quantitative research. Thirty-six studies investigating 13 non-Western and 32 Western cultural groups were analysed by classifying assumed causes and preferred forms of treatment into common categories. Relations between beliefs and treatment preferences were assessed. Substantial agreement between cultural groups was found with respect to the impact of observable causes. Stress was generally rated as most important. Less agreement resulted for hidden, especially supernatural causes. Causal beliefs were clearly related to treatment preferences in Western groups, while evidence was mostly lacking for non-Western groups. Overall predictions were supported, but there were considerable methodological limitations. Pointers to future research, which may combine studies on causal beliefs with experimental paradigms on causal reasoning, are given.

Linear causal modeling with structural equations

CERN Document Server

Mulaik, Stanley A

2009-01-01

Emphasizing causation as a functional relationship between variables that describe objects, Linear Causal Modeling with Structural Equations integrates a general philosophical theory of causation with structural equation modeling (SEM) that concerns the special case of linear causal relations. In addition to describing how the functional relation concept may be generalized to treat probabilistic causation, the book reviews historical treatments of causation and explores recent developments in experimental psychology on studies of the perception of causation. It looks at how to perceive causal

Identity, causality, and pronoun ambiguity.

Science.gov (United States)

Sagi, Eyal; Rips, Lance J

2014-10-01

This article looks at the way people determine the antecedent of a pronoun in sentence pairs, such as: Albert invited Ron to dinner. He spent hours cleaning the house. The experiment reported here is motivated by the idea that such judgments depend on reasoning about identity (e.g., the identity of the he who cleaned the house). Because the identity of an individual over time depends on the causal-historical path connecting the stages of the individual, the correct antecedent will also depend on causal connections. The experiment varied how likely it is that the event of the first sentence (e.g., the invitation) would cause the event of the second (the house cleaning) for each of the two individuals (the likelihood that if Albert invited Ron to dinner, this would cause Albert to clean the house, versus cause Ron to clean the house). Decisions about the antecedent followed causal likelihood. A mathematical model of causal identity accounted for most of the key aspects of the data from the individual sentence pairs. Copyright © 2014 Cognitive Science Society, Inc.

A genetically informative developmental study of the relationship between conduct disorder and peer deviance in males

Science.gov (United States)

Kendler, K. S.; Jacobson, K.; Myers, J. M.; Eaves, L. J.

2014-01-01

Background Conduct disorder (CD) and peer deviance (PD) both powerfully predict future externalizing behaviors. Although levels of CD and PD are strongly correlated, the causal relationship between them has remained controversial and has not been examined by a genetically informative study. Method Levels of CD and PD were assessed in 746 adult male–male twin pairs at personal interview for ages 8–11, 12–14 and 15–17 years using a life history calendar. Model fitting was performed using the Mx program. Results The best-fit model indicated an active developmental relationship between CD and PD including forward transmission of both traits over time and strong causal relationships between CD and PD within time periods. The best-fit model indicated that the causal relationship for genetic risk factors was from CD to PD and was constant over time. For common environmental factors, the causal pathways ran from PD to CD and were stronger in earlier than later age periods. Conclusions A genetically informative model revealed causal pathways difficult to elucidate by other methods. Genes influence risk for CD, which, through social selection, impacts on the deviance of peers. Shared environment, through family and community processes, encourages or discourages adolescent deviant behavior, which, via social influence, alters risk for CD. Social influence is more important than social selection in childhood, but by late adolescence social selection becomes predominant. These findings have implications for prevention efforts for CD and associated externalizing disorders. PMID:17935643

A Causal Theory of Modality

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José Tomás Alvarado

2009-08-01

Full Text Available This work presents a causal conception of metaphysical modality in which a state of affairs is metaphysically possible if and only if it can be caused (in the past, the present or the future by current entities. The conception is contrasted with what is called the “combinatorial” conception of modality, in which everything can co-exist with anything else. This work explains how the notion of ‘causality’ should be construed in the causal theory, what difference exists between modalities thus defined from nomological modality, how accessibility relations between possible worlds should be interpreted, and what is the relation between the causal conception and the necessity of origin.

Causal reasoning with mental models

Science.gov (United States)

Khemlani, Sangeet S.; Barbey, Aron K.; Johnson-Laird, Philip N.

2014-01-01

This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A enables B to occur means that given A, it is possible for B to occur. The paper shows how mental models represent such assertions, and how these models underlie deductive, inductive, and abductive reasoning yielding explanations. It reviews evidence both to corroborate the theory and to account for phenomena sometimes taken to be incompatible with it. Finally, it reviews neuroscience evidence indicating that mental models for causal inference are implemented within lateral prefrontal cortex. PMID:25389398

Causal reasoning with mental models.

Science.gov (United States)

Khemlani, Sangeet S; Barbey, Aron K; Johnson-Laird, Philip N

2014-01-01

This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A enables B to occur means that given A, it is possible for B to occur. The paper shows how mental models represent such assertions, and how these models underlie deductive, inductive, and abductive reasoning yielding explanations. It reviews evidence both to corroborate the theory and to account for phenomena sometimes taken to be incompatible with it. Finally, it reviews neuroscience evidence indicating that mental models for causal inference are implemented within lateral prefrontal cortex.

Causal reasoning with mental models

Directory of Open Access Journals (Sweden)

Sangeet eKhemlani

2014-10-01

Full Text Available This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A enables B to occur means that given A, it is possible for B to occur. The paper shows how mental models represent such assertions, and how these models underlie deductive, inductive, and abductive reasoning yielding explanations. It reviews evidence both to corroborate the theory and to account for phenomena sometimes taken to be incompatible with it. Finally, it reviews neuroscience evidence indicating that mental models for causal inference are implemented within lateral prefrontal cortex.

Foundational perspectives on causality in large-scale brain networks

Science.gov (United States)

Mannino, Michael; Bressler, Steven L.

2015-12-01

A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical

How medical technologies shape the experience of illness.

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Hofmann, Bjørn; Svenaeus, Fredrik

2018-02-03

In this article we explore how diagnostic and therapeutic technologies shape the lived experiences of illness for patients. By analysing a wide range of examples, we identify six ways that technology can (trans)form the experience of illness (and health). First, technology may create awareness of disease by revealing asymptomatic signs or markers (imaging techniques, blood tests). Second, the technology can reveal risk factors for developing diseases (e.g., high blood pressure or genetic tests that reveal risks of falling ill in the future). Third, the technology can affect and change an already present illness experience (e.g., the way blood sugar measurement affects the perceived symptoms of diabetes). Fourth, therapeutic technologies may redefine our experiences of a certain condition as diseased rather than unfortunate (e.g. assisted reproductive technologies or symptom based diagnoses in psychiatry). Fifth, technology influences illness experiences through altering social-cultural norms and values regarding various diagnoses. Sixth, technology influences and changes our experiences of being healthy in contrast and relation to being diseased and ill. This typology of how technology forms illness and related conditions calls for reflection regarding the phenomenology of technology and health. How are medical technologies and their outcomes perceived and understood by patients? The phenomenological way of approaching illness as a lived, bodily being-in-the-world is an important approach for better understanding and evaluating the effects that medical technologies may have on our health, not only in defining, diagnosing, or treating diseases, but also in making us feel more vulnerable and less healthy in different regards.

Risk factors for unplanned pregnancy in women with mental illness living in a developing country.

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du Toit, Elsa; Jordaan, Esme; Niehaus, Dana; Koen, Liezl; Leppanen, Jukka

2018-06-01

Pregnant women in general are at an increased risk of experiencing symptoms of mental illness, and those living in a developing country are even more vulnerable. Research points towards a causal relationship between unplanned pregnancy and perinatal mental illness and suggests that pregnancy planning can aid in reducing the negative impact of mental illness on a woman, her unborn baby, and the rest of the family. In this quantitative, descriptive study, we investigated both socio-demographic factors and variables relating to mental illness itself that may place women at an increased risk of experiencing unplanned pregnancy. Data was gathered at two maternal mental health clinics in Cape Town by means of semi-structured interviews. Univariate analyses of the data revealed five independent key risk factors for unplanned pregnancy: lower levels of education, unmarried status, belonging to the Colored ethnic population, substance use, and having a history of two or more suicide attempts. Some of these factors overlap with findings of similar studies, but others are unique to the specific population (women with mental illness within a developing country). Screening of women based on these risk predictors may pave the way for early interventions and reduce the incidence of unplanned pregnancy and the negative consequences thereof in the South African population.

Using genetic markers to orient the edges in quantitative trait networks: the NEO software.

Science.gov (United States)

Aten, Jason E; Fuller, Tova F; Lusis, Aldons J; Horvath, Steve

2008-04-15

Systems genetic studies have been used to identify genetic loci that affect transcript abundances and clinical traits such as body weight. The pairwise correlations between gene expression traits and/or clinical traits can be used to define undirected trait networks. Several authors have argued that genetic markers (e.g expression quantitative trait loci, eQTLs) can serve as causal anchors for orienting the edges of a trait network. The availability of hundreds of thousands of genetic markers poses new challenges: how to relate (anchor) traits to multiple genetic markers, how to score the genetic evidence in favor of an edge orientation, and how to weigh the information from multiple markers. We develop and implement Network Edge Orienting (NEO) methods and software that address the challenges of inferring unconfounded and directed gene networks from microarray-derived gene expression data by integrating mRNA levels with genetic marker data and Structural Equation Model (SEM) comparisons. The NEO software implements several manual and automatic methods for incorporating genetic information to anchor traits. The networks are oriented by considering each edge separately, thus reducing error propagation. To summarize the genetic evidence in favor of a given edge orientation, we propose Local SEM-based Edge Orienting (LEO) scores that compare the fit of several competing causal graphs. SEM fitting indices allow the user to assess local and overall model fit. The NEO software allows the user to carry out a robustness analysis with regard to genetic marker selection. We demonstrate the utility of NEO by recovering known causal relationships in the sterol homeostasis pathway using liver gene expression data from an F2 mouse cross. Further, we use NEO to study the relationship between a disease gene and a biologically important gene co-expression module in liver tissue. The NEO software can be used to orient the edges of gene co-expression networks or quantitative trait

Medicalizing versus psychologizing mental illness: what are the implications for help seeking and stigma? A general population study.

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Pattyn, E; Verhaeghe, M; Sercu, C; Bracke, P

2013-10-01

This study contrasts the medicalized conceptualization of mental illness with psychologizing mental illness and examines what the consequences are of adhering to one model versus the other for help seeking and stigma. The survey "Stigma in a Global Context-Belgian Mental Health Study" (2009) conducted face-to-face interviews among a representative sample of the general Belgian population using the vignette technique to depict schizophrenia (N = 381). Causal attributions, labeling processes, and the disease view are addressed. Help seeking refers to open-ended help-seeking suggestions (general practitioner, psychiatrist, psychologist, family, friends, and self-care options). Stigma refers to social exclusion after treatment. The data are analyzed by means of logistic and linear regression models in SPSS Statistics 19. People who adhere to the biopsychosocial (versus psychosocial) model are more likely to recommend general medical care and people who apply the disease view are more likely to recommend specialized medical care. Regarding informal help, those who prefer the biopsychosocial model are less likely to recommend consulting friends than those who adhere to the psychosocial model. Respondents who apply a medical compared to a non-medical label are less inclined to recommend self-care. As concerns treatment stigma, respondents who apply a medical instead of a non-medical label are more likely to socially exclude someone who has been in psychiatric treatment. Medicalizing mental illness involves a package deal: biopsychosocial causal attributions and applying the disease view facilitate medical treatment recommendations, while labeling seems to trigger stigmatizing attitudes.

Heterogeneous Causal Effects and Sample Selection Bias

DEFF Research Database (Denmark)

Breen, Richard; Choi, Seongsoo; Holm, Anders

2015-01-01

The role of education in the process of socioeconomic attainment is a topic of long standing interest to sociologists and economists. Recently there has been growing interest not only in estimating the average causal effect of education on outcomes such as earnings, but also in estimating how...... causal effects might vary over individuals or groups. In this paper we point out one of the under-appreciated hazards of seeking to estimate heterogeneous causal effects: conventional selection bias (that is, selection on baseline differences) can easily be mistaken for heterogeneity of causal effects....... This might lead us to find heterogeneous effects when the true effect is homogenous, or to wrongly estimate not only the magnitude but also the sign of heterogeneous effects. We apply a test for the robustness of heterogeneous causal effects in the face of varying degrees and patterns of selection bias...

Behavioral genetics and criminal responsibility at the courtroom.

Science.gov (United States)

Tatarelli, Roberto; Del Casale, Antonio; Tatarelli, Caterina; Serata, Daniele; Rapinesi, Chiara; Sani, Gabriele; Kotzalidis, Georgios D; Girardi, Paolo

2014-04-01

Several questions arise from the recent use of behavioral genetic research data in the courtroom. Ethical issues concerning the influence of biological factors on human free will, must be considered when specific gene patterns are advocated to constrain court's judgment, especially regarding violent crimes. Aggression genetics studies are both difficult to interpret and inconsistent, hence, in the absence of a psychiatric diagnosis, genetic data are currently difficult to prioritize in the courtroom. The judge's probabilistic considerations in formulating a sentence must take into account causality, and the latter cannot be currently ensured by genetic data. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Entanglement entropy in causal set theory

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Sorkin, Rafael D.; Yazdi, Yasaman K.

2018-04-01

Entanglement entropy is now widely accepted as having deep connections with quantum gravity. It is therefore desirable to understand it in the context of causal sets, especially since they provide in a natural manner the UV cutoff needed to render entanglement entropy finite. Formulating a notion of entanglement entropy in a causal set is not straightforward because the type of canonical hypersurface-data on which its definition typically relies is not available. Instead, we appeal to the more global expression given in Sorkin (2012 (arXiv:1205.2953)) which, for a Gaussian scalar field, expresses the entropy of a spacetime region in terms of the field’s correlation function within that region (its ‘Wightman function’ W(x, x') ). Carrying this formula over to the causal set, one obtains an entropy which is both finite and of a Lorentz invariant nature. We evaluate this global entropy-expression numerically for certain regions (primarily order-intervals or ‘causal diamonds’) within causal sets of 1  +  1 dimensions. For the causal-set counterpart of the entanglement entropy, we obtain, in the first instance, a result that follows a (spacetime) volume law instead of the expected (spatial) area law. We find, however, that one obtains an area law if one truncates the commutator function (‘Pauli–Jordan operator’) and the Wightman function by projecting out the eigenmodes of the Pauli–Jordan operator whose eigenvalues are too close to zero according to a geometrical criterion which we describe more fully below. In connection with these results and the questions they raise, we also study the ‘entropy of coarse-graining’ generated by thinning out the causal set, and we compare it with what one obtains by similarly thinning out a chain of harmonic oscillators, finding the same, ‘universal’ behaviour in both cases.

Preschoolers prefer to learn causal information

Directory of Open Access Journals (Sweden)

Aubry eAlvarez

2015-02-01

Full Text Available Young children, in general, appear to have a strong drive to explore the environment in ways that reveal its underlying causal structure. But are they really attuned specifically to casual information in this quest for understanding, or do they show equal interest in other types of non-obvious information about the world? To answer this question, we introduced 20 three-year-old children to two puppets who were anxious to tell the child about a set of novel artifacts and animals. One puppet consistently described causal properties of the items while the other puppet consistently described carefully matched non-causal properties of the same items. After a familiarization period in which children learned which type of information to expect from each informant, children were given the opportunity to choose which they wanted to hear describe each of eight pictured test items. On average, children chose to hear from the informant that provided causal descriptions on 72% of the trials. This preference for causal information has important implications for explaining the role of conceptual information in supporting early learning and may suggest means for maximizing interest and motivation in young children.

Motivation for Psychotherapy and Illness Beliefs in Turkish Immigrant Inpatients in Germany: Results of a Cultural Comparison Study.

Science.gov (United States)

Reich, Hanna; Bockel, Luisa; Mewes, Ricarda

2015-03-01

Some immigrant populations, for instance, Turkish immigrants, suffer from worse mental health than the general population. Moreover, psychotherapeutic treatment does not work well in this group. This might be explained by lower motivation for psychotherapy and particular illness beliefs as important early predictors of treatment outcome. We investigate differences in these predictors between Turkish immigrant inpatients and inpatients without a migration background and evaluate whether particular illness beliefs have a negative impact on motivation for psychotherapy. Turkish immigrant inpatients and inpatients without a migration background (N = 100), suffering from depressive disorder, somatoform disorder, and/or adjustment disorder, completed questionnaires assessing motivation for psychotherapy, depressive and somatic symptoms, illness perception, illness-related locus of control, and causal illness attributions. Despite a higher symptom burden, motivation for psychotherapy was lower in Turkish immigrant inpatients than in inpatients without a migration background (d = 0.54). This was fully explained by stronger beliefs in supernatural causes of illness and higher fatalistic-external illness-related locus of control in the Turkish immigrant sample (mediation analysis; R (2) = 0.27). Turkish immigrants believe in supernatural or fatalistic causes of illness and fatalistic-external locus of control to a greater extent than German inpatients without a migration background. These beliefs reduce motivation for psychotherapy and need to be addressed in psychotherapeutic treatment in order to secure positive treatment outcomes.

Mathematical implications of Einstein-Weyl causality

International Nuclear Information System (INIS)

Borchers, H.J.; Sen, R.N.

2006-01-01

The present work is the first systematic attempt at answering the following fundamental question: what mathematical structures does Einstein-Weyl causality impose on a point-set that has no other previous structure defined on it? The authors propose an axiomatization of Einstein-Weyl causality (inspired by physics), and investigate the topological and uniform structures that it implies. Their final result is that a causal space is densely embedded in one that is locally a differentiable manifold. The mathematical level required of the reader is that of the graduate student in mathematical physics. (orig.)

Culture, threat, and mental illness stigma: identifying culture-specific threat among Chinese-American groups.

Science.gov (United States)

Yang, Lawrence H; Purdie-Vaughns, Valerie; Kotabe, Hiroki; Link, Bruce G; Saw, Anne; Wong, Gloria; Phelan, Jo C

2013-07-01

We incorporate anthropological insights into a stigma framework to elucidate the role of culture in threat perception and stigma among Chinese groups. Prior work suggests that genetic contamination that jeopardizes the extension of one's family lineage may comprise a culture-specific threat among Chinese groups. In Study 1, a national survey conducted from 2002 to 2003 assessed cultural differences in mental illness stigma and perceptions of threat in 56 Chinese-Americans and 589 European-Americans. Study 2 sought to empirically test this culture-specific threat of genetic contamination to lineage via a memory paradigm. Conducted from June to August 2010, 48 Chinese-American and 37 European-American university students in New York City read vignettes containing content referring to lineage or non-lineage concerns. Half the participants in each ethnic group were assigned to a condition in which the illness was likely to be inherited (genetic condition) and the rest read that the illness was unlikely to be inherited (non-genetic condition). Findings from Study 1 and 2 were convergent. In Study 1, culture-specific threat to lineage predicted cultural variation in stigma independently and after accounting for other forms of threat. In Study 2, Chinese-Americans in the genetic condition were more likely to accurately recall and recognize lineage content than the Chinese-Americans in the non-genetic condition, but that memorial pattern was not found for non-lineage content. The identification of this culture-specific threat among Chinese groups has direct implications for culturally-tailored anti-stigma interventions. Further, this framework might be implemented across other conditions and cultural groups to reduce stigma across cultures. Copyright © 2013 Elsevier Ltd. All rights reserved.

Causality violation, gravitational shockwaves and UV completion

Energy Technology Data Exchange (ETDEWEB)

Hollowood, Timothy J.; Shore, Graham M. [Department of Physics, Swansea University,Swansea, SA2 8PP (United Kingdom)

2016-03-18

The effective actions describing the low-energy dynamics of QFTs involving gravity generically exhibit causality violations. These may take the form of superluminal propagation or Shapiro time advances and allow the construction of “time machines”, i.e. spacetimes admitting closed non-spacelike curves. Here, we discuss critically whether such causality violations may be used as a criterion to identify unphysical effective actions or whether, and how, causality problems may be resolved by embedding the action in a fundamental, UV complete QFT. We study in detail the case of photon scattering in an Aichelburg-Sexl gravitational shockwave background and calculate the phase shifts in QED for all energies, demonstrating their smooth interpolation from the causality-violating effective action values at low-energy to their manifestly causal high-energy limits. At low energies, these phase shifts may be interpreted as backwards-in-time coordinate jumps as the photon encounters the shock wavefront, and we illustrate how the resulting causality problems emerge and are resolved in a two-shockwave time machine scenario. The implications of our results for ultra-high (Planck) energy scattering, in which graviton exchange is modelled by the shockwave background, are highlighted.

Introductive remarks on causal inference

Directory of Open Access Journals (Sweden)

Silvana A. Romio

2013-05-01

Full Text Available One of the more challenging issues in epidemiological research is being able to provide an unbiased estimate of the causal exposure-disease effect, to assess the possible etiological mechanisms and the implication for public health. A major source of bias is confounding, which can spuriously create or mask the causal relationship. In the last ten years, methodological research has been developed to better de_ne the concept of causation in epidemiology and some important achievements have resulted in new statistical models. In this review, we aim to show how a technique the well known by statisticians, i.e. standardization, can be seen as a method to estimate causal e_ects, equivalent under certain conditions to the inverse probability treatment weight procedure.

Quasi-Experimental Designs for Causal Inference

Science.gov (United States)

Kim, Yongnam; Steiner, Peter

2016-01-01

When randomized experiments are infeasible, quasi-experimental designs can be exploited to evaluate causal treatment effects. The strongest quasi-experimental designs for causal inference are regression discontinuity designs, instrumental variable designs, matching and propensity score designs, and comparative interrupted time series designs. This…

Foodborne Illness Outbreak Investigation in a High-Profile Sports Club.

Science.gov (United States)

Cavanagh, Kwendy; Johnstone, Travers; Huhtinen, Essi; Najjar, Zeina; Lorentzos, Peter; Shadbolt, Craig; Shields, John; Gupta, Leena

2017-12-01

A foodborne illness outbreak involving an elite sports team was investigated by a public health unit in Sydney, Australia. An epidemiological association was established between gastrointestinal illness and the consumption of food supplied by an external caterer, with a lamb meal most strongly associated with illness. Genetically identical Salmonella isolates were identified from clinical specimens, residual food items, and an environmental swab taken from the catering premises. The training schedule and other club operations were significantly affected by this outbreak. Increased susceptibility due to regular shared activities and the potential for significant impact upon performance indicates that sports clubs must ensure that food suppliers comply with the highest standards of hygiene. Collaboration with public health authorities assists in source identification and prevention of further transmission.

Developing a multi-component immune model for evaluating the risk of respiratory illness in athletes.

Science.gov (United States)

Gleeson, Maree; Pyne, David B; Elkington, Lisa J; Hall, Sharron T; Attia, John R; Oldmeadow, Christopher; Wood, Lisa G; Callister, Robin

2017-01-01

Clinical and laboratory identification of the underlying risk of respiratory illness in athletes has proved problematic. The aim of this study was to determine whether clinical data, combined with immune responses to standardised exercise protocols and genetic cytokine polymorphism status, could identify the risk of respiratory illness (symptoms) in a cohort of highly-trained athletes. Male endurance athletes (n=16; VO2max 66.5 ± 5.1 mL.kg-1.min-1) underwent a clinical evaluation of known risk factors by a physician and comprehensive laboratory analysis of immune responses both at rest and after two cycling ergometer tests: 60 min at 65% VO2max (LONG); and 6 x 3 min intervals at 90% VO2max (INTENSE). Blood tests were performed to determine Epstein Barr virus (EBV) status and DNA was genotyped for a panel of cytokine gene polymorphisms. Saliva was collected for measurement of IgA and detection of EBV DNA. Athletes were then followed for 9 months for self-reported episodes of respiratory illness, with confirmation of the underlying cause by a sports physician. There were no associations with risk of respiratory illness identified for any parameter assessed in the clinical evaluations. The laboratory parameters associated with an increased risk of respiratory illnesses in highly-trained athletes were cytokine gene polymorphisms for the high expression of IL-6 and IFN-ɣ; expression of EBV-DNA in saliva; and low levels of salivary IgA concentration. A genetic risk score was developed for the cumulative number of minor alleles for the cytokines evaluated. Athletes prone to recurrent respiratory illness were more likely to have immune disturbances that allow viral reactivation, and a genetic predisposition to pro-inflammatory cytokine responses to intense exercise. Copyright © 2016 International Society of Exercise and Immunology. All rights reserved.

Gravity and matter in causal set theory

International Nuclear Information System (INIS)

Sverdlov, Roman; Bombelli, Luca

2009-01-01

The goal of this paper is to propose an approach to the formulation of dynamics for causal sets and coupled matter fields. We start from the continuum version of the action for a Klein-Gordon field coupled to gravity, and rewrite it first using quantities that have a direct correspondent in the case of a causal set, namely volumes, causal relations and timelike lengths, as variables to describe the geometry. In this step, the local Lagrangian density L(f;x) for a set of fields f is recast into a quasilocal expression L 0 (f;p,q) that depends on pairs of causally related points pprq and is a function of the values of f in the Alexandrov set defined by those points, and whose limit as p and q approach a common point x is L(f;x). We then describe how to discretize L 0 (f;p,q) and use it to define a causal-set-based action.

Causal theory in (2+1)-dimensional Qed

International Nuclear Information System (INIS)

Scharf, G.; Wreszinski, W.F.

1994-01-01

The program of constructing the S-matrix by means of causality in quantum field theory goes back to Stueckelberg and Bogoliubov. Epstein and Glaser proposed an axiomatic construct where ultraviolet divergences do not appear, leading directly to the renormalized perturbation series. They have shown that in the causal theory the UV problem is a consequence of incorrect distribution splitting. This paper studies the causal theory in (2+1)D Qed

How multiple causes combine: independence constraints on causal inference.

Science.gov (United States)

Liljeholm, Mimi

2015-01-01

According to the causal power view, two core constraints-that causes occur independently (i.e., no confounding) and influence their effects independently-serve as boundary conditions for causal induction. This study investigated how violations of these constraints modulate uncertainty about the existence and strength of a causal relationship. Participants were presented with pairs of candidate causes that were either confounded or not, and that either interacted or exerted their influences independently. Consistent with the causal power view, uncertainty about the existence and strength of causal relationships was greater when causes were confounded or interacted than when unconfounded and acting independently. An elemental Bayesian causal model captured differences in uncertainty due to confounding but not those due to an interaction. Implications of distinct sources of uncertainty for the selection of contingency information and causal generalization are discussed.

The relationship of family characteristics and bipolar disorder using causal-pie models.

Science.gov (United States)

Chen, Y-C; Kao, C-F; Lu, M-K; Yang, Y-K; Liao, S-C; Jang, F-L; Chen, W J; Lu, R-B; Kuo, P-H

2014-01-01

Many family characteristics were reported to increase the risk of bipolar disorder (BPD). The development of BPD may be mediated through different pathways, involving diverse risk factor profiles. We evaluated the associations of family characteristics to build influential causal-pie models to estimate their contributions on the risk of developing BPD at the population level. We recruited 329 clinically diagnosed BPD patients and 202 healthy controls to collect information in parental psychopathology, parent-child relationship, and conflict within family. Other than logistic regression models, we applied causal-pie models to identify pathways involved with different family factors for BPD. The risk of BPD was significantly increased with parental depression, neurosis, anxiety, paternal substance use problems, and poor relationship with parents. Having a depressed mother further predicted early onset of BPD. Additionally, a greater risk for BPD was observed with higher numbers of paternal/maternal psychopathologies. Three significant risk profiles were identified for BPD, including paternal substance use problems (73.0%), maternal depression (17.6%), and through poor relationship with parents and conflict within the family (6.3%). Our findings demonstrate that different aspects of family characteristics elicit negative impacts on bipolar illness, which can be utilized to target specific factors to design and employ efficient intervention programs. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

The mistake of the causal relationship

Directory of Open Access Journals (Sweden)

О. Д. Комаров

2015-03-01

Full Text Available The article deals with issues of the mistake of the causal relationship. The modern criminal law science approaches to the content of the mistake of the causal relationship and its significance to the qualification of the crime are described. It is proved that in cases of dolus generalis different mental attitude of the guilty person to two separate acts of his conduct exist. Consequently, in mentioned above cases mistake of the causal relationship does not have place. The rules of qualification of the crimes commited with the mistake of causation and in cases of dolus generalis are proposed .

'It was all intertwined': Illness representations and self-management in patients with cancer and anxiety/depression.

Science.gov (United States)

Richardson, Emma M; Scott, Jennifer L; Schüz, Natalie; Sanderson, Kristy; Schüz, Benjamin

2017-09-01

Cancer and anxiety/depression frequently co-occur, leading to poorer outcomes for these illnesses. However, the majority of existing research investigates how participants view single illnesses alone. This study aimed to explore the content of individuals' multimorbid representations and how these relate to their coping behaviours and self-management strategies for cancer and anxiety/depression. A semi-structured qualitative research design with theoretical thematic analysis. Multimorbid illness representations, coping behaviours, and self-management strategies. In interviews with 21 participants multimorbid representations varied, three participants viewed cancer and anxiety/depression as unrelated, five participants were uncertain about the relationship between cancer and anxiety/depression, and the majority of participants perceived cancer and anxiety/depression as related. This third group of participants often described relationships as causal, with representations having both positive and negative influences on coping behaviours and self-management strategies. Representations were shown to change over the course of the cancer experience, with fear of cancer recurrence and the influence of participants' most challenging illness also discussed. People hold multimorbid illness representations that can influence self-management. An awareness of these representations by researchers, health professionals, and patients is important for the creation of future interventions that aim to improve and maintain patient wellbeing.

Causal independence between energy consumption and economic growth in Liberia: Evidence from a non-parametric bootstrapped causality test

International Nuclear Information System (INIS)

Wesseh, Presley K.; Zoumara, Babette

2012-01-01

This contribution investigates causal interdependence between energy consumption and economic growth in Liberia and proposes application of a bootstrap methodology. To better reflect causality, employment is incorporated as additional variable. The study demonstrates evidence of distinct bidirectional Granger causality between energy consumption and economic growth. Additionally, the results show that employment in Liberia Granger causes economic growth and apply irrespective of the short-run or long-run. Evidence from a Monte Carlo experiment reveals that the asymptotic Granger causality test suffers size distortion problem for Liberian data, suggesting that the bootstrap technique employed in this study is more appropriate. Given the empirical results, implications are that energy expansion policies like energy subsidy or low energy tariff for instance, would be necessary to cope with demand exerted as a result of economic growth in Liberia. Furthermore, Liberia might have the performance of its employment generation on the economy partly determined by adequate energy. Therefore, it seems fully justified that a quick shift towards energy production based on clean energy sources may significantly slow down economic growth in Liberia. Hence, the government’s target to implement a long-term strategy to make Liberia a carbon neutral country, and eventually less carbon dependent by 2050 is understandable. - Highlights: ► Causality between energy consumption and economic growth in Liberia investigated. ► There is bidirectional causality between energy consumption and economic growth. ► Energy expansion policies are necessary to cope with demand from economic growth. ► Asymptotic Granger causality test suffers size distortion problem for Liberian data. ► The bootstrap methodology employed in our study is more appropriate.

The genetic correlation between procrastination and impulsivity.

Science.gov (United States)

Loehlin, John C; Martin, Nicholas G

2014-12-01

The reported genetic correlation of 1.0 between the traits of procrastination and impulsivity (Gustavson, D. E., Miyake, A., Hewitt, J. K., & Friedman, N. P. (2014). Psychological Science), which was held to support an evolutionary origin of the relationship between the two traits, was tested in data from two large samples of twins from Australia. A genetic correlation of 0.299 was obtained. It was concluded that, although the presence of a genetic correlation between the two traits was supported, the modest magnitude of the correlation was such as to be consistent with many possible hypotheses, evolutionary and otherwise, about causal relationships between the traits in question.

A Bayesian Theory of Sequential Causal Learning and Abstract Transfer.

Science.gov (United States)

Lu, Hongjing; Rojas, Randall R; Beckers, Tom; Yuille, Alan L

2016-03-01

Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about abstract causal constraints? Recent empirical studies have revealed that experience with one set of causal cues can dramatically alter subsequent learning and performance with entirely different cues, suggesting that learning involves abstract transfer, and such transfer effects involve sequential presentation of distinct sets of causal cues. It has been demonstrated that pre-training (or even post-training) can modulate classic causal learning phenomena such as forward and backward blocking. To account for these effects, we propose a Bayesian theory of sequential causal learning. The theory assumes that humans are able to consider and use several alternative causal generative models, each instantiating a different causal integration rule. Model selection is used to decide which integration rule to use in a given learning environment in order to infer causal knowledge from sequential data. Detailed computer simulations demonstrate that humans rely on the abstract characteristics of outcome variables (e.g., binary vs. continuous) to select a causal integration rule, which in turn alters causal learning in a variety of blocking and overshadowing paradigms. When the nature of the outcome variable is ambiguous, humans select the model that yields the best fit with the recent environment, and then apply it to subsequent learning tasks. Based on sequential patterns of cue-outcome co-occurrence, the theory can account for a range of phenomena in sequential causal learning, including various blocking effects, primacy effects in some experimental conditions, and apparently abstract transfer of causal knowledge. Copyright © 2015

On minimizers of causal variational principles

International Nuclear Information System (INIS)

Schiefeneder, Daniela

2011-01-01

Causal variational principles are a class of nonlinear minimization problems which arise in a formulation of relativistic quantum theory referred to as the fermionic projector approach. This thesis is devoted to a numerical and analytic study of the minimizers of a general class of causal variational principles. We begin with a numerical investigation of variational principles for the fermionic projector in discrete space-time. It is shown that for sufficiently many space-time points, the minimizing fermionic projector induces non-trivial causal relations on the space-time points. We then generalize the setting by introducing a class of causal variational principles for measures on a compact manifold. In our main result we prove under general assumptions that the support of a minimizing measure is either completely timelike, or it is singular in the sense that its interior is empty. In the examples of the circle, the sphere and certain flag manifolds, the general results are supplemented by a more detailed analysis of the minimizers. (orig.)

Consciousness and the "Causal Paradox"

OpenAIRE

Velmans, Max

1996-01-01

Viewed from a first-person perspective consciousness appears to be necessary for complex, novel human activity - but viewed from a third-person perspective consciousness appears to play no role in the activity of brains, producing a "causal paradox". To resolve this paradox one needs to distinguish consciousness of processing from consciousness accompanying processing or causing processing. Accounts of consciousness/brain causal interactions switch between first- and third-person perspectives...

Biological indicators of illness risk in offspring of bipolar parents: targeting the hypothalamic-pituitary-adrenal axis and immune system.

Science.gov (United States)

Duffy, Anne; Lewitzka, Ute; Doucette, Sarah; Andreazza, Ana; Grof, Paul

2012-05-01

The study aims to provide a selective review of the literature pertaining to the hypothalamic-pituitary-adrenal (HPA) axis and immune abnormalities as informative biological indicators of vulnerability in bipolar disorder (BD). We summarize key findings relating to HPA axis and immunological abnormalities in bipolar patients and their high-risk offspring. Findings derive from a review of selected original papers published in the literature, and supplemented by papers identified through bibliography review. Neurobiological findings are discussed in the context of emergent BD in those at genetic risk and synthesized into a neurodevelopmental model of illness onset and progression. BD is associated with a number of genetic and possibly epigenetic abnormalities associated with neurotransmitter, hormonal and immunologically mediated neurobiological pathways. Data from clinical and high-risk studies implicate HPA axis and immune system abnormalities, which may represent inherited vulnerabilities important for the transition to illness onset. Post-mortem and clinical studies implicate intracellular signal transduction processes and disturbance in energy metabolism associated with established BD. Specifically, long-standing maladaptive alterations such as changes in neuronal systems may be mediated through changes in intracellular signalling pathways, oxidative stress, cellular energy metabolism and apoptosis associated with substantial burden of illness. Prospective longitudinal studies of endophenotypes and biomarkers such as HPA axis and immune abnormalities in high-risk offspring will be helpful to understand genetically mediated biological pathways associated with illness onset and progression. A clinical staging model describing emergent illness in those at genetic risk should facilitate this line of investigation. © 2011 Blackwell Publishing Asia Pty Ltd.

Towards Improving Point-of-Care Diagnosis of Non-malaria Febrile Illness: A Metabolomics Approach.

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Saskia Decuypere

2016-03-01

Full Text Available Non-malaria febrile illnesses such as bacterial bloodstream infections (BSI are a leading cause of disease and mortality in the tropics. However, there are no reliable, simple diagnostic tests for identifying BSI or other severe non-malaria febrile illnesses. We hypothesized that different infectious agents responsible for severe febrile illness would impact on the host metabolome in different ways, and investigated the potential of plasma metabolites for diagnosis of non-malaria febrile illness.We conducted a comprehensive mass-spectrometry based metabolomics analysis of the plasma of 61 children with severe febrile illness from a malaria-endemic rural African setting. Metabolite features characteristic for non-malaria febrile illness, BSI, severe anemia and poor clinical outcome were identified by receiver operating curve analysis.The plasma metabolome profile of malaria and non-malaria patients revealed fundamental differences in host response, including a differential activation of the hypothalamic-pituitary-adrenal axis. A simple corticosteroid signature was a good classifier of severe malaria and non-malaria febrile patients (AUC 0.82, 95% CI: 0.70-0.93. Patients with BSI were characterized by upregulated plasma bile metabolites; a signature of two bile metabolites was estimated to have a sensitivity of 98.1% (95% CI: 80.2-100 and a specificity of 82.9% (95% CI: 54.7-99.9 to detect BSI in children younger than 5 years. This BSI signature demonstrates that host metabolites can have a superior diagnostic sensitivity compared to pathogen-detecting tests to identify infections characterized by low pathogen load such as BSI.This study demonstrates the potential use of plasma metabolites to identify causality in children with severe febrile illness in malaria-endemic settings.

Genetic associations with viral respiratory illnesses and asthma control in children

DEFF Research Database (Denmark)

Loisel, D A; Du, G; Ahluwalia, T S

2016-01-01

of asthma control phenotypes was performed in 2128 children in the Copenhagen Prospective Study on Asthma in Childhood (COPSAC). Significant associations in RhinoGen were further validated using virus-induced wheezing illness and asthma phenotypes in an independent sample of 122 children enrolled...... in the Childhood Origins of Asthma (COAST) birth cohort study. RESULTS: A significant excess of P values smaller than 0.05 was observed in the analysis of the 10 RhinoGen phenotypes. Polymorphisms in 12 genes were significantly associated with variation in the four phenotypes showing a significant enrichment...... differences in childhood viral respiratory illnesses and virus-induced exacerbations of asthma. Defining mechanisms of these associations may provide insight into the pathogenesis of viral respiratory infections and virus-induced exacerbations of asthma....

Causal inference in biology networks with integrated belief propagation.

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Chang, Rui; Karr, Jonathan R; Schadt, Eric E

2015-01-01

Inferring causal relationships among molecular and higher order phenotypes is a critical step in elucidating the complexity of living systems. Here we propose a novel method for inferring causality that is no longer constrained by the conditional dependency arguments that limit the ability of statistical causal inference methods to resolve causal relationships within sets of graphical models that are Markov equivalent. Our method utilizes Bayesian belief propagation to infer the responses of perturbation events on molecular traits given a hypothesized graph structure. A distance measure between the inferred response distribution and the observed data is defined to assess the 'fitness' of the hypothesized causal relationships. To test our algorithm, we infer causal relationships within equivalence classes of gene networks in which the form of the functional interactions that are possible are assumed to be nonlinear, given synthetic microarray and RNA sequencing data. We also apply our method to infer causality in real metabolic network with v-structure and feedback loop. We show that our method can recapitulate the causal structure and recover the feedback loop only from steady-state data which conventional method cannot.

A general, multivariate definition of causal effects in epidemiology.

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Flanders, W Dana; Klein, Mitchel

2015-07-01

Population causal effects are often defined as contrasts of average individual-level counterfactual outcomes, comparing different exposure levels. Common examples include causal risk difference and risk ratios. These and most other examples emphasize effects on disease onset, a reflection of the usual epidemiological interest in disease occurrence. Exposure effects on other health characteristics, such as prevalence or conditional risk of a particular disability, can be important as well, but contrasts involving these other measures may often be dismissed as non-causal. For example, an observed prevalence ratio might often viewed as an estimator of a causal incidence ratio and hence subject to bias. In this manuscript, we provide and evaluate a definition of causal effects that generalizes those previously available. A key part of the generalization is that contrasts used in the definition can involve multivariate, counterfactual outcomes, rather than only univariate outcomes. An important consequence of our generalization is that, using it, one can properly define causal effects based on a wide variety of additional measures. Examples include causal prevalence ratios and differences and causal conditional risk ratios and differences. We illustrate how these additional measures can be useful, natural, easily estimated, and of public health importance. Furthermore, we discuss conditions for valid estimation of each type of causal effect, and how improper interpretation or inferences for the wrong target population can be sources of bias.

[Mental health beliefs between culture and subjective illness experience].

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Ritter, Kristina; Chaudhry, Haroon R; Aigner, Martin; Zitterl, Werner; Stompe, Thomas

2010-01-01

Subjective health beliefs are representations about pathogenesis, course and treatment options of psychic as well as somatic illnesses. They are important for a psychotherapeutic interaction as well as for a stable drug adherence. However, it remains unclear whether these representations are primarily affected by the cultural background or by an individual's specific illness experiences, a question of increasing importance in our era of globalized migration. The study sample consisted of 203 Austrians (125 with schizophrenia, 78 with obsessivecompulsive disorder) and 190 Pakistanis (120 with schizophrenia, 70 with obsessive-compulsive disorder). All patients completed the "Causal Explanations of Mental Disorders" (CEMD), a 41-item self-rating questionnaire. Pakistani patients reported magic-religious oriented mental health beliefs more frequently. In contrast, Austrians' beliefs are more often in line with the bio-psychosocial explanations of Western medicine. Concerning mental health beliefs the cultural background seems to be more important than the subjective experience with a distinctive mental disorder. Although the subjective experience is of importance for the shape of illnessspecific cognitions, mental health beliefs are primarily caused by the patients' socio-cultural origin. It is a challenge for psychiatry to improve the co-operation with culture-anthropology and other social sciences.

Information causality from an entropic and a probabilistic perspective

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Al-Safi, Sabri W.; Short, Anthony J.

2011-01-01

The information causality principle is a generalization of the no-signaling principle which implies some of the known restrictions on quantum correlations. But despite its clear physical motivation, information causality is formulated in terms of a rather specialized game and figure of merit. We explore different perspectives on information causality, discussing the probability of success as the figure of merit, a relation between information causality and the nonlocal ''inner-product game,'' and the derivation of a quadratic bound for these games. We then examine an entropic formulation of information causality with which one can obtain the same results, arguably in a simpler fashion.

Smoking and caffeine consumption: a genetic analysis of their association

NARCIS (Netherlands)

Treur, J.L.; Taylor, A.E.; Ware, J.J.; Nivard, M.G.; Neale, M.C.; McMahon, G.; Hottenga, J.J.; Baselmans, B.M.L.; Boomsma, D.I.; Munafò, M.; Vink, J.M.

2017-01-01

Smoking and caffeine consumption show a strong positive correlation, but the mechanism underlying this association is unclear. Explanations include shared genetic/environmental factors or causal effects. This study employed three methods to investigate the association between smoking and caffeine.

Causal Mediation Analysis: Warning! Assumptions Ahead

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Keele, Luke

2015-01-01

In policy evaluations, interest may focus on why a particular treatment works. One tool for understanding why treatments work is causal mediation analysis. In this essay, I focus on the assumptions needed to estimate mediation effects. I show that there is no "gold standard" method for the identification of causal mediation effects. In…

An Exploration of Attitudes Among Black Americans Towards Psychiatric Genetic Research

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Murphy, Eleanor; Thompson, Azure

2011-01-01

With increasing emphasis on understanding genetic contribution to disease, inclusion of all racial and ethnic groups in molecular genetic research is necessary to ensure parity in distribution of research benefits. Blacks are underrepresented in large-scale genetic studies of psychiatric disorders. In an effort to understand the reasons for the underrepresentation, this study explored black participants’ attitudes towards genetic research of psychiatric disorders. Twenty-six adults, the majority of whom were black (n = 18) were recruited from a New York City community to participate in six 90-minute focus groups. This paper reports findings about respondents’ understanding of genetics and genetic research, and opinions about psychiatric genetic research. Primary themes revealed participants’ perceived lack of knowledge about genetics, concerns about potentially harmful study procedures, and confidentiality surrounding mental illness in families. Participation incentives included provision of treatment or related service, monetary compensation, and reporting of results to participants. These findings suggest that recruitment of subjects into genetic studies should directly address procedures, privacy, benefits and follow-up with results. Further, there is critical need to engage communities with education about genetics and mental illness, and provide opportunities for continued discussion about concerns related to genetic research. PMID:19614555

Immunology and Genetic of Preeclampsia

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Norma C. Serrano

2006-01-01

Full Text Available Preeclampsia is a disease characterized by hypertension and proteinuria in the third trimester of pregnancy. Preeclampsia is a major cause of maternal mortality, and fetal death, especially in developing countries, but its aetiology remains unclear. Key findings support a causal role of superficial placentation driven by immune mal maladaptation, which then lead to reduced concentrations of angiogenic growth factors and to an increase in placental debris in the maternal circulation resulting in a maternal inflammatory response. Epidemiological research has consistently demonstrated a substantial familial predisposition to preeclampsia. Unfortunately, the conquest of the genes explaining such a individual susceptibility has been proved to be a hard task. However, genetics will also inform us about causality of environmental factors, and then serve as a tool to prioritize therapeutic targets for preventive strategies.

How to Be Causal: Time, Spacetime and Spectra

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Kinsler, Paul

2011-01-01

I explain a simple definition of causality in widespread use, and indicate how it links to the Kramers-Kronig relations. The specification of causality in terms of temporal differential equations then shows us the way to write down dynamical models so that their causal nature "in the sense used here" should be obvious to all. To extend existing…

On the road toward formal reasoning: reasoning with factual causal and contrary-to-fact causal premises during early adolescence.

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Markovits, Henry

2014-12-01

Understanding the development of conditional (if-then) reasoning is critical for theoretical and educational reasons. Here we examined the hypothesis that there is a developmental transition between reasoning with true and contrary-to-fact (CF) causal conditionals. A total of 535 students between 11 and 14 years of age received priming conditions designed to encourage use of either a true or CF alternatives generation strategy and reasoning problems with true causal and CF causal premises (with counterbalanced order). Results show that priming had no effect on reasoning with true causal premises. By contrast, priming with CF alternatives significantly improved logical reasoning with CF premises. Analysis of the effect of order showed that reasoning with CF premises reduced logical responding among younger students but had no effect among older students. Results support the idea that there is a transition in the reasoning processes in this age range associated with the nature of the alternatives generation process required for logical reasoning with true and CF causal conditionals. Copyright © 2014 Elsevier Inc. All rights reserved.

College students' stigmatization of people with mental illness: familiarity, implicit person theory, and attribution.

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Lyndon, Amy E; Crowe, Allison; Wuensch, Karl L; McCammon, Susan L; Davis, Karen B

2016-11-25

Stigma associated with mental illness (MI) results in underutilization of mental health care. We must understand factors contributing to stigma to shape anti-stigma campaigns. To investigate the factors influencing stigma in university students. Undergraduate psychology students completed measures on causal attribution, stigma, social distance, implicit person theory (IPT), and familiarity. The hypothesis was partially supported; people who felt personality traits were unchangeable (i.e. entity IPT) were more likely to stigmatize individuals with mental disorders and desired more social distance from them. Familiarity with people with a MI individually predicted less desire for social distance, yet the redundancy of the predictors made the effect of familiarity on stigma fall just short of statistical significance. Judgments of biogenetic causal attribution were related to higher stigma levels, but not so when familiarity and IPT were taken into account. Educational campaigns may be effective by focusing on aspects of MI highlighting similarity with non-diagnosed people, and that people with MI can recover.

Cystatin C Is Not Causally Related to Coronary Artery Disease.

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Patrik Svensson-Färbom

Full Text Available Strong and independent associations between plasma concentration of cystatin C and risk of cardiovascular disease (CVD suggests causal involvement of cystatin C.The aim of our study was to assess whether there is a causal relationship between plasma concentration of cystatin C and risk of coronary artery disease (CAD using a Mendelian Randomization approach.We estimated the strength of association of plasma cystatin C on CAD risk and the strength of association of the strongest GWAS derived cystatin C SNP (rs13038305 on plasma cystatin C in the population-based Malmö Diet and Cancer Study (MDC and thereafter the association between rs13038305 and CAD in the MDC (3200 cases of CAD and 24418 controls and CARDIOGRAM (22233 cases of CAD and 64762 controls.Each standard deviation (SD increment of plasma cystatin C was associated with increased risk of CAD (OR = 1.20, 95% CI 1.07-1.34 after full adjustment. Each copy of the major allele of rs13038305 was associated with 0.34 SD higher plasma concentration of cystatin C (P98% to detect a significant relationship between rs13038305 and CAD in MDC and CARDIOGRAM pooled. The odds ratio for CAD (per copy of the major rs13038305 allele was 1.00 (0.94-1.07; P = 0.92 in MDC, 0.99 (0.96-1.03; P = 0.84 in CARDIOGRAM and 1.00 (0.97-1.03; P = 0.83 in MDC and CARDIOGRAM pooled.Genetic elevation of plasma cystatin C is not related to altered risk of CAD, suggesting that there is no causal relationship between plasma cystatin C and CAD. Rather, the association between cystatin C and CAD appears to be due to the association of eGFR and CAD.

BOLD Granger causality reflects vascular anatomy.

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J Taylor Webb

Full Text Available A number of studies have tried to exploit subtle phase differences in BOLD time series to resolve the order of sequential activation of brain regions, or more generally the ability of signal in one region to predict subsequent signal in another region. More recently, such lag-based measures have been applied to investigate directed functional connectivity, although this application has been controversial. We attempted to use large publicly available datasets (FCON 1000, ADHD 200, Human Connectome Project to determine whether consistent spatial patterns of Granger Causality are observed in typical fMRI data. For BOLD datasets from 1,240 typically developing subjects ages 7-40, we measured Granger causality between time series for every pair of 7,266 spherical ROIs covering the gray matter and 264 seed ROIs at hubs of the brain's functional network architecture. Granger causality estimates were strongly reproducible for connections in a test and replication sample (n=620 subjects for each group, as well as in data from a single subject scanned repeatedly, both during resting and passive video viewing. The same effect was even stronger in high temporal resolution fMRI data from the Human Connectome Project, and was observed independently in data collected during performance of 7 task paradigms. The spatial distribution of Granger causality reflected vascular anatomy with a progression from Granger causality sources, in Circle of Willis arterial inflow distributions, to sinks, near large venous vascular structures such as dural venous sinuses and at the periphery of the brain. Attempts to resolve BOLD phase differences with Granger causality should consider the possibility of reproducible vascular confounds, a problem that is independent of the known regional variability of the hemodynamic response.

The causal structure of utility conditionals.

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Bonnefon, Jean-François; Sloman, Steven A

2013-01-01

The psychology of reasoning is increasingly considering agents' values and preferences, achieving greater integration with judgment and decision making, social cognition, and moral reasoning. Some of this research investigates utility conditionals, ''if p then q'' statements where the realization of p or q or both is valued by some agents. Various approaches to utility conditionals share the assumption that reasoners make inferences from utility conditionals based on the comparison between the utility of p and the expected utility of q. This article introduces a new parameter in this analysis, the underlying causal structure of the conditional. Four experiments showed that causal structure moderated utility-informed conditional reasoning. These inferences were strongly invited when the underlying structure of the conditional was causal, and significantly less so when the underlying structure of the conditional was diagnostic. This asymmetry was only observed for conditionals in which the utility of q was clear, and disappeared when the utility of q was unclear. Thus, an adequate account of utility-informed inferences conditional reasoning requires three components: utility, probability, and causal structure. Copyright © 2012 Cognitive Science Society, Inc.

Discrimination attributed to mental illness or race-ethnicity by users of community psychiatric services.

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Gabbidon, Jheanell; Farrelly, Simone; Hatch, Stephani L; Henderson, Claire; Williams, Paul; Bhugra, Dinesh; Dockery, Lisa; Lassman, Francesca; Thornicroft, Graham; Clement, Sarah

2014-11-01

This study assessed participants' experienced discrimination and their causal attributions, particularly to mental illness or race-ethnicity. In a cross-sectional study, 202 service users with severe mental illnesses were interviewed to assess their reported experiences of discrimination. The Major Experiences of Discrimination Scale assessed major experiences of discrimination and their recency and frequency across 12 life domains and perceived reasons (attributions). The Everyday Experiences of Discrimination Scale assessed ten types of everyday discrimination and attributions for these experiences. Most participants (88%) reported discrimination in at least one life domain, and 94% reported ever experiencing everyday discrimination. The most common areas of major discrimination were mental health care (44%), neighbors (42%), police (33%), employment (31%), and general medical care (31%). The most common attributions for major discrimination were mental illness (57%), race-ethnicity (24%), education or income (20%), or appearance (19%). Almost half (47%) attributed experiences of major discrimination to two or more causes. No differences were found between racial-ethnic groups in overall experienced discrimination or in main attributions to mental illness. However, compared with the mixed and white groups, participants in the black group were most likely to endorse race-ethnicity as a main attribution (pethnic groups, and discrimination based on race-ethnicity was prevalent for the mixed and black groups. There is a need for antidiscrimination strategies that combine efforts to reduce the experience of discrimination attributed to mental illness and to race-ethnicity for racial-ethnic minority groups.

Entanglement, holography and causal diamonds

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de Boer, Jan; Haehl, Felix M.; Heller, Michal P.; Myers, Robert C.

2016-08-01

We argue that the degrees of freedom in a d-dimensional CFT can be reorganized in an insightful way by studying observables on the moduli space of causal diamonds (or equivalently, the space of pairs of timelike separated points). This 2 d-dimensional space naturally captures some of the fundamental nonlocality and causal structure inherent in the entanglement of CFT states. For any primary CFT operator, we construct an observable on this space, which is defined by smearing the associated one-point function over causal diamonds. Known examples of such quantities are the entanglement entropy of vacuum excitations and its higher spin generalizations. We show that in holographic CFTs, these observables are given by suitably defined integrals of dual bulk fields over the corresponding Ryu-Takayanagi minimal surfaces. Furthermore, we explain connections to the operator product expansion and the first law of entanglemententropy from this unifying point of view. We demonstrate that for small perturbations of the vacuum, our observables obey linear two-derivative equations of motion on the space of causal diamonds. In two dimensions, the latter is given by a product of two copies of a two-dimensional de Sitter space. For a class of universal states, we show that the entanglement entropy and its spin-three generalization obey nonlinear equations of motion with local interactions on this moduli space, which can be identified with Liouville and Toda equations, respectively. This suggests the possibility of extending the definition of our new observables beyond the linear level more generally and in such a way that they give rise to new dynamically interacting theories on the moduli space of causal diamonds. Various challenges one has to face in order to implement this idea are discussed.

Entanglement, holography and causal diamonds

Energy Technology Data Exchange (ETDEWEB)

Boer, Jan de [Institute of Physics, Universiteit van Amsterdam,Science Park 904, 1090 GL Amsterdam (Netherlands); Haehl, Felix M. [Centre for Particle Theory & Department of Mathematical Sciences, Durham University,South Road, Durham DH1 3LE (United Kingdom); Heller, Michal P.; Myers, Robert C. [Perimeter Institute for Theoretical Physics,31 Caroline Street North, Waterloo, Ontario N2L 2Y5 (Canada)

2016-08-29

We argue that the degrees of freedom in a d-dimensional CFT can be re-organized in an insightful way by studying observables on the moduli space of causal diamonds (or equivalently, the space of pairs of timelike separated points). This 2d-dimensional space naturally captures some of the fundamental nonlocality and causal structure inherent in the entanglement of CFT states. For any primary CFT operator, we construct an observable on this space, which is defined by smearing the associated one-point function over causal diamonds. Known examples of such quantities are the entanglement entropy of vacuum excitations and its higher spin generalizations. We show that in holographic CFTs, these observables are given by suitably defined integrals of dual bulk fields over the corresponding Ryu-Takayanagi minimal surfaces. Furthermore, we explain connections to the operator product expansion and the first law of entanglement entropy from this unifying point of view. We demonstrate that for small perturbations of the vacuum, our observables obey linear two-derivative equations of motion on the space of causal diamonds. In two dimensions, the latter is given by a product of two copies of a two-dimensional de Sitter space. For a class of universal states, we show that the entanglement entropy and its spin-three generalization obey nonlinear equations of motion with local interactions on this moduli space, which can be identified with Liouville and Toda equations, respectively. This suggests the possibility of extending the definition of our new observables beyond the linear level more generally and in such a way that they give rise to new dynamically interacting theories on the moduli space of causal diamonds. Various challenges one has to face in order to implement this idea are discussed.

Detectability of Granger causality for subsampled continuous-time neurophysiological processes.

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Barnett, Lionel; Seth, Anil K

2017-01-01

Granger causality is well established within the neurosciences for inference of directed functional connectivity from neurophysiological data. These data usually consist of time series which subsample a continuous-time biophysiological process. While it is well known that subsampling can lead to imputation of spurious causal connections where none exist, less is known about the effects of subsampling on the ability to reliably detect causal connections which do exist. We present a theoretical analysis of the effects of subsampling on Granger-causal inference. Neurophysiological processes typically feature signal propagation delays on multiple time scales; accordingly, we base our analysis on a distributed-lag, continuous-time stochastic model, and consider Granger causality in continuous time at finite prediction horizons. Via exact analytical solutions, we identify relationships among sampling frequency, underlying causal time scales and detectability of causalities. We reveal complex interactions between the time scale(s) of neural signal propagation and sampling frequency. We demonstrate that detectability decays exponentially as the sample time interval increases beyond causal delay times, identify detectability "black spots" and "sweet spots", and show that downsampling may potentially improve detectability. We also demonstrate that the invariance of Granger causality under causal, invertible filtering fails at finite prediction horizons, with particular implications for inference of Granger causality from fMRI data. Our analysis emphasises that sampling rates for causal analysis of neurophysiological time series should be informed by domain-specific time scales, and that state-space modelling should be preferred to purely autoregressive modelling. On the basis of a very general model that captures the structure of neurophysiological processes, we are able to help identify confounds, and offer practical insights, for successful detection of causal connectivity

Dual Causality and the Autonomy of Biology.

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Bock, Walter J

2017-03-01

Ernst Mayr's concept of dual causality in biology with the two forms of causes (proximate and ultimate) continues to provide an essential foundation for the philosophy of biology. They are equivalent to functional (=proximate) and evolutionary (=ultimate) causes with both required for full biological explanations. The natural sciences can be classified into nomological, historical nomological and historical dual causality, the last including only biology. Because evolutionary causality is unique to biology and must be included for all complete biological explanations, biology is autonomous from the physical sciences.

Determining Directional Dependency in Causal Associations

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Pornprasertmanit, Sunthud; Little, Todd D.

2012-01-01

Directional dependency is a method to determine the likely causal direction of effect between two variables. This article aims to critique and improve upon the use of directional dependency as a technique to infer causal associations. We comment on several issues raised by von Eye and DeShon (2012), including: encouraging the use of the signs of…

Assessing causality in the association between child adiposity and physical activity levels: a Mendelian randomization analysis.

Directory of Open Access Journals (Sweden)

Rebecca C Richmond

2014-03-01

Full Text Available Cross-sectional studies have shown that objectively measured physical activity is associated with childhood adiposity, and a strong inverse dose-response association with body mass index (BMI has been found. However, few studies have explored the extent to which this association reflects reverse causation. We aimed to determine whether childhood adiposity causally influences levels of physical activity using genetic variants reliably associated with adiposity to estimate causal effects.The Avon Longitudinal Study of Parents and Children collected data on objectively assessed activity levels of 4,296 children at age 11 y with recorded BMI and genotypic data. We used 32 established genetic correlates of BMI combined in a weighted allelic score as an instrumental variable for adiposity to estimate the causal effect of adiposity on activity. In observational analysis, a 3.3 kg/m² (one standard deviation higher BMI was associated with 22.3 (95% CI, 17.0, 27.6 movement counts/min less total physical activity (p = 1.6×10⁻¹⁶, 2.6 (2.1, 3.1 min/d less moderate-to-vigorous-intensity activity (p = 3.7×10⁻²⁹, and 3.5 (1.5, 5.5 min/d more sedentary time (p = 5.0×10⁻⁴. In Mendelian randomization analyses, the same difference in BMI was associated with 32.4 (0.9, 63.9 movement counts/min less total physical activity (p = 0.04 (∼5.3% of the mean counts/minute, 2.8 (0.1, 5.5 min/d less moderate-to-vigorous-intensity activity (p = 0.04, and 13.2 (1.3, 25.2 min/d more sedentary time (p = 0.03. There was no strong evidence for a difference between variable estimates from observational estimates. Similar results were obtained using fat mass index. Low power and poor instrumentation of activity limited causal analysis of the influence of physical activity on BMI.Our results suggest that increased adiposity causes a reduction in physical activity in children and support research into the targeting of BMI in efforts to

Causal strength induction from time series data.

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Soo, Kevin W; Rottman, Benjamin M

2018-04-01

One challenge when inferring the strength of cause-effect relations from time series data is that the cause and/or effect can exhibit temporal trends. If temporal trends are not accounted for, a learner could infer that a causal relation exists when it does not, or even infer that there is a positive causal relation when the relation is negative, or vice versa. We propose that learners use a simple heuristic to control for temporal trends-that they focus not on the states of the cause and effect at a given instant, but on how the cause and effect change from one observation to the next, which we call transitions. Six experiments were conducted to understand how people infer causal strength from time series data. We found that participants indeed use transitions in addition to states, which helps them to reach more accurate causal judgments (Experiments 1A and 1B). Participants use transitions more when the stimuli are presented in a naturalistic visual format than a numerical format (Experiment 2), and the effect of transitions is not driven by primacy or recency effects (Experiment 3). Finally, we found that participants primarily use the direction in which variables change rather than the magnitude of the change for estimating causal strength (Experiments 4 and 5). Collectively, these studies provide evidence that people often use a simple yet effective heuristic for inferring causal strength from time series data. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The Relevance of Causal Social Construction

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Marques Teresa

2017-02-01

Full Text Available Social constructionist claims are surprising and interesting when they entail that presumably natural kinds are in fact socially constructed. The claims are interesting because of their theoretical and political importance. Authors like Díaz-León argue that constitutive social construction is more relevant for achieving social justice than causal social construction. This paper challenges this claim. Assuming there are socially salient groups that are discriminated against, the paper presents a dilemma: if there were no constitutively constructed social kinds, the causes of the discrimination of existing social groups would have to be addressed, and understanding causal social construction would be relevant to achieve social justice. On the other hand, not all possible constitutively socially constructed kinds are actual social kinds. If an existing social group is constitutively constructed as a social kind K, the fact that it actually exists as a K has social causes. Again, causal social construction is relevant. The paper argues that (i for any actual social kind X, if X is constitutively socially constructed as K, then it is also causally socially constructed; and (ii causal social construction is at least as relevant as constitutive social construction for concerns of social justice. For illustration, I draw upon two phenomena that are presumed to contribute towards the discrimination of women: (i the poor performance effects of stereotype threat, and (ii the silencing effects of gendered language use.

Selecting appropriate cases when tracing causal mechanisms

DEFF Research Database (Denmark)

Beach, Derek; Pedersen, Rasmus Brun

2016-01-01

The last decade has witnessed resurgence in the interest in studying the causal mechanisms linking causes and outcomes in the social sciences. This article explores the overlooked implications for case selection when tracing mechanisms using in-depth case studies. Our argument is that existing case...... selection guidelines are appropriate for research aimed at making cross-case claims about causal relationships, where case selection is primarily used to control for other causes. However, existing guidelines are not in alignment with case-based research that aims to trace mechanisms, where the goal...... is to unpack the causal mechanism between X and Y, enabling causal inferences to be made because empirical evidence is provided for how the mechanism actually operated in a particular case. The in-depth, within-case tracing of how mechanisms operate in particular cases produces what can be termed mechanistic...

Tachyon kinematics and causality: a systematic thorough analysis of the tachyon causal paradoxes

International Nuclear Information System (INIS)

Recami, E.

1987-01-01

The chronological order of the events along a spacelike path is not invariant under Lorentz transformations, as is well known. This led to an early conviction that tachyons would give rise to causal anomalies. A relativistic version of the Stueckelberg-Feynman switching procedure (SWP) has been invoked as the suitable tool to eliminate those anomalies. The application of the SWP does eliminate the motions backwards in time, but interchanges the roles of source and detector. This fact triggered the proposal of a host of causal paradoxes. Till now, however, it has not been recognized that such paradoxes can be sensibly discussed (and completely solved, at least in microphysics) only after the tachyon relativistic mechanics has been properly developed. They start by showing how to apply the SWP, both in the case of ordinary special relativity and in the case with tachyons. Then they carefully exploit the kinetics of the tachyon exchange between two (ordinary) bodies. Being finally able to tackle the tachyon causality problem, they successively solve the paradoxes of: (i) Tolman-Regge, (ii) Pirani, (iii) Edmonds, and (iv) Bell. Finally, they discuss a further, new paradox associated with the transmission of signals by modulated tachyon beams

Illness perception, help-seeking attitudes, and knowledge related to obsessive-compulsive disorder across different ethnic groups: a community survey.

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Fernández de la Cruz, Lorena; Kolvenbach, Sarah; Vidal-Ribas, Pablo; Jassi, Amita; Llorens, Marta; Patel, Natasha; Weinman, John; Hatch, Stephani L; Bhugra, Dinesh; Mataix-Cols, David

2016-03-01

Despite similar prevalence rates across ethnicities, ethnic minorities with obsessive-compulsive disorder (OCD) are under-represented in research and clinical settings. The reasons for this disproportion have been sparsely studied. We explored potential differences in illness perception, help-seeking attitudes, illness knowledge, and causal attributions that could help explain the lower uptake of treatment for OCD amongst ethnic minorities. Two-hundred and ninety-three parents (139 White British, 61 Black African, 46 Black Caribbean, and 47 Indian) were recruited from the general population in South-East London, UK. Using a text vignette methodology, participants completed a survey including questions on illness perception, help-seeking attitudes, OCD knowledge, and causal attributions. The groups did not differ in socio-demographic characteristics and family history of OCD. White British parents perceived that the OCD difficulties would have more negative impact on their children and that treatment would be more helpful, compared to the ethnic minorities; the largest differences were observed between White British and Indian parents. Ethnic minorities were more prone to say that would seek help from their religious communities. Black African parents were more in favor of not seeking help for the described difficulties and, in general, perceived more treatment barriers. White British parents seemed to be better informed about OCD than ethnic minority parents. The results offer some plausible explanations for the large inequalities in access to services amongst ethnic minorities with OCD. Clinicians and policy-makers need to be aware of these socio-cultural factors when designing strategies to encourage help-seeking behaviors in these populations.

The Causality of Evolution on Different Fitness Landscapes

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Vyawahare, Saurabh; Austin, Robert; Zhang, Qiucen; Kim, Hyunsung; Bestoso, John

2013-03-01

Evolution of antibiotic resistance is a growing problem. One major reason why most antibiotics fail is because of mutations on drug targets (e.g. essential enzymes). Sequencing of clinically resistant isolates have shown that multiple mutational-hotspots exist in coding regions, which could potentially prohibit the binding of drugs. However, it is not clear whether the appearance of each mutation is random or influenced by other factors. In this paper, we compare evolution of resistance to ciprofloxacin from two distinct but well characterized genetic backgrounds. By combining our recently developed evolution reactor and deep whole-genome sequencing, we show different alleles of σs factor lead to fixation of different mutations in gyrA gene that confer ciprofloxacin resistance to bacteria Escherichia coli. Such causality of evolution in different genes provides an opportunity to control the evolution of antibiotic resistance. Sponsored by the NCI/NIH Physical Sciences Oncology Centers

Trends in rates of mental illness in homicide perpetrators.

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Swinson, Nicola; Flynn, Sandra M; While, David; Roscoe, Alison; Kapur, Navneet; Appleby, Louis; Shaw, Jenny

2011-06-01

The rise in homicides by those with serious mental illness is of concern, although this increase may not be continuing. To examine rates of mental illness among homicide perpetrators. A national consecutive case series of homicide perpetrators in England and Wales from 1997 to 2006. Rates of mental disorder were based on data from psychiatric reports, contact with psychiatric services, diminished responsibility verdict and hospital disposal. Of the 5884 homicides notified to the National Confidential Inquiry into Suicide and Homicide by People with Mental Illness between 1997 and 2006, the number of homicide perpetrators with schizophrenia increased at a rate of 4% per year, those with psychotic symptoms at the time of the offence increased by 6% per year. The number of verdicts of diminished responsibility decreased but no change was found in the number of perpetrators receiving a hospital order disposal. The likeliest explanation for the rise in homicide by people with psychosis is the misuse of drugs and/or alcohol, which our data show increased at a similar magnitude to homicides by those with psychotic symptoms. However, we are unable to demonstrate a causal association. Although the Poisson regression provides evidence of an upward trend in homicide by people with serious mental illness between 1997 and 2006, the number of homicides fell in the final 2 years of data collection, so these findings should be treated with caution. There appears to be a concomitant increase in drug misuse over the period, which may account for this rise in homicide. However, an increase in the number of people in contact with mental health services may suggest that access to mental health services is improving. Previous studies have used court verdicts such as diminished responsibility as a proxy measure of mental disorder. Our data indicate that this does not reflect accurately the prevalence of mental disorder in this population.

Illness Identity in Adults with a Chronic Illness.

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Oris, Leen; Luyckx, Koen; Rassart, Jessica; Goubert, Liesbet; Goossens, Eva; Apers, Silke; Arat, Seher; Vandenberghe, Joris; Westhovens, René; Moons, Philip

2018-02-21

The present study examines the concept of illness identity, the degree to which a chronic illness is integrated into one's identity, in adults with a chronic illness by validating a new self-report questionnaire, the Illness Identity Questionnaire (IIQ). Self-report questionnaires on illness identity, psychological, and physical functioning were assessed in two samples: adults with congenital heart disease (22-78 year old; n = 276) and with multisystem connective tissue disorders (systemic lupus erythematosus or systemic sclerosis; 17-81 year old; n = 241). The IIQ could differentiate four illness identity states (i.e., engulfment, rejection, acceptance, and enrichment) in both samples, based on exploratory and confirmatory factor analysis. All four subscales proved to be reliable. Rejection and engulfment were related to maladaptive psychological and physical functioning, whereas acceptance and enrichment were related to adaptive psychological and physical functioning. The present findings underscore the importance of the concept of illness identity. The IIQ, a self-report questionnaire, is introduced to measure four different illness identity states in adults with a chronic illness.

Variable number of tandem repeat markers in the genome sequence of Mycosphaerella fijiensis, the causal agent of black leaf streak disease of banana (Musa spp)

NARCIS (Netherlands)

Garcia, S.A.L.; Lee, van der T.A.J.; Ferreira, C.F.; Lintel Hekkert, te B.; Zapater, M.F.; Goodwin, S.B.; Guzmán, M.; Kema, G.H.J.; Souza, M.T.

2010-01-01

ABSTRACT. We searched the genome of Mycosphaerella fijiensis for molecular markers that would allow population genetics analysis of this plant pathogen. M. fijiensis, the causal agent of banana leaf streak disease, also known as black Sigatoka, is the most devastating pathogen attacking bananas

Spirituality, Illness Unpredictability, and Math Anxiety Effects on Negative Affect and Affect-Management Coping for Individuals Diagnosed with Alpha-1 Antitrypsin Deficiency.

Science.gov (United States)

Worthington, Amber K; Parrott, Roxanne L; Smith, Rachel A

2018-04-01

A growing number of genetic tests are included in diagnostic protocols associated with many common conditions. A positive diagnosis associated with the presence of some gene versions in many instances predicts a range of possible outcomes, and the uncertainty linked to such results contributes to the need to understand varied responses and plan strategic communication. Uncertainty in illness theory (UIT; Mishel, 1988, 1990) guided the investigation of efforts to feel in control and hopeful regarding genetic testing and diagnosis for alpha-1 antitrypsin deficiency (AATD). Participants included 137 individuals with AATD recruited from the Alpha-1 Research Registry who were surveyed about their subjective numeracy, anxiety about math, spirituality, perceptions of illness unpredictability, negative affect regarding genetic testing, and coping strategies about a diagnosis. Results revealed that experiencing more fear and worry contributed both directly and indirectly to affect-management coping strategies, operating through individual perceptions of illness unpredictability. The inability to predict the symptoms and course of events related to a genetic illness and anxiety regarding math heightened fear and worry. Spirituality lessened both illness unpredictability and negative affective responses to a diagnosis. Results affirm the importance of clinician and counselor efforts to incorporate attention to patient spirituality. They also illustrate the complexity associated with strategic efforts to plan communication about the different versions of a gene's effects on well-being, when some versions align with mild health effects and others with severe effects.

Causal learning and inference as a rational process: the new synthesis.

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Holyoak, Keith J; Cheng, Patricia W

2011-01-01

Over the past decade, an active line of research within the field of human causal learning and inference has converged on a general representational framework: causal models integrated with bayesian probabilistic inference. We describe this new synthesis, which views causal learning and inference as a fundamentally rational process, and review a sample of the empirical findings that support the causal framework over associative alternatives. Causal events, like all events in the distal world as opposed to our proximal perceptual input, are inherently unobservable. A central assumption of the causal approach is that humans (and potentially nonhuman animals) have been designed in such a way as to infer the most invariant causal relations for achieving their goals based on observed events. In contrast, the associative approach assumes that learners only acquire associations among important observed events, omitting the representation of the distal relations. By incorporating bayesian inference over distributions of causal strength and causal structures, along with noisy-logical (i.e., causal) functions for integrating the influences of multiple causes on a single effect, human judgments about causal strength and structure can be predicted accurately for relatively simple causal structures. Dynamic models of learning based on the causal framework can explain patterns of acquisition observed with serial presentation of contingency data and are consistent with available neuroimaging data. The approach has been extended to a diverse range of inductive tasks, including category-based and analogical inferences.

New Insights into Signed Path Coefficient Granger Causality Analysis.

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Zhang, Jian; Li, Chong; Jiang, Tianzi

2016-01-01

Granger causality analysis, as a time series analysis technique derived from econometrics, has been applied in an ever-increasing number of publications in the field of neuroscience, including fMRI, EEG/MEG, and fNIRS. The present study mainly focuses on the validity of "signed path coefficient Granger causality," a Granger-causality-derived analysis method that has been adopted by many fMRI researches in the last few years. This method generally estimates the causality effect among the time series by an order-1 autoregression, and defines a positive or negative coefficient as an "excitatory" or "inhibitory" influence. In the current work we conducted a series of computations from resting-state fMRI data and simulation experiments to illustrate the signed path coefficient method was flawed and untenable, due to the fact that the autoregressive coefficients were not always consistent with the real causal relationships and this would inevitablely lead to erroneous conclusions. Overall our findings suggested that the applicability of this kind of causality analysis was rather limited, hence researchers should be more cautious in applying the signed path coefficient Granger causality to fMRI data to avoid misinterpretation.

Illness beliefs of Chinese American immigrants with major depressive disorder in a primary care setting.

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Chen, Justin A; Hung, Galen Chin-Lun; Parkin, Susannah; Fava, Maurizio; Yeung, Albert S

2015-02-01

Underutilization of mental health services in the U.S. is compounded among racial/ethnic minorities, especially Chinese Americans. Culturally based illness beliefs influence help-seeking behavior and may provide insights into strategies for increasing utilization rates among vulnerable populations. This is the first large descriptive study of depressed Chinese American immigrant patients' illness beliefs using a standardized instrument. 190 depressed Chinese immigrants seeking primary care at South Cove Community Health Center completed the Explanatory Model Interview Catalogue, which probes different dimensions of illness beliefs: chief complaint, labeling of illness, stigma perception, causal attributions, and help-seeking patterns. Responses were sorted into categories by independent raters and results compared to an earlier study at the same site and using the same instrument. Contrary to prior findings that depressed Chinese individuals tend to present with primarily somatic symptoms, subjects were more likely to report chief complaints and illness labels related to depressed mood than physical symptoms. Nearly half reported they would conceal the name of their problem from others. Mean stigma levels were significantly higher than in the previous study. Most subjects identified psychological stress as the most likely cause of their problem. Chinese immigrants' illness beliefs were notable for psychological explanations regarding their symptoms, possibly reflecting increased acceptance of Western biomedical frameworks, in accordance with recent research. However, reported stigma regarding these symptoms also increased. As Asian American immigrant populations increasingly accept psychological models of depression, stigma may become an increasingly important target for addressing disparities in mental health service utilization. Copyright © 2014 Elsevier B.V. All rights reserved.

Granger Causality Testing with Intensive Longitudinal Data.

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Molenaar, Peter C M

2018-06-01

The availability of intensive longitudinal data obtained by means of ambulatory assessment opens up new prospects for prevention research in that it allows the derivation of subject-specific dynamic networks of interacting variables by means of vector autoregressive (VAR) modeling. The dynamic networks thus obtained can be subjected to Granger causality testing in order to identify causal relations among the observed time-dependent variables. VARs have two equivalent representations: standard and structural. Results obtained with Granger causality testing depend upon which representation is chosen, yet no criteria exist on which this important choice can be based. A new equivalent representation is introduced called hybrid VARs with which the best representation can be chosen in a data-driven way. Partial directed coherence, a frequency-domain statistic for Granger causality testing, is shown to perform optimally when based on hybrid VARs. An application to real data is provided.

Causality Between Urban Concentration and Environmental Quality

Directory of Open Access Journals (Sweden)

Amin Pujiati

2015-08-01

Full Text Available Population is concentrated in urban areas can cause the external diseconomies on environment if it exceeds the carrying capacity of the space and the urban economy. Otherwise the quality of the environment is getting better, led to the concentration of population in urban areas are increasingly high. This study aims to analyze the relationship of causality between the urban concentration and environmental quality in urban agglomeration areas. The data used in the study of secondary data obtained from the Central Bureau of statistics and the City Government from 2000 to 2013. The analytical method used is the Granger causality and descriptive. Granger causality study results showed no pattern of reciprocal causality, between urban concentration and the quality of the environment, but there unidirectional relationship between the urban concentration and environmental quality. This means that increasing urban concentration led to decreased environmental quality.

Partial Granger causality--eliminating exogenous inputs and latent variables.

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Guo, Shuixia; Seth, Anil K; Kendrick, Keith M; Zhou, Cong; Feng, Jianfeng

2008-07-15

Attempts to identify causal interactions in multivariable biological time series (e.g., gene data, protein data, physiological data) can be undermined by the confounding influence of environmental (exogenous) inputs. Compounding this problem, we are commonly only able to record a subset of all related variables in a system. These recorded variables are likely to be influenced by unrecorded (latent) variables. To address this problem, we introduce a novel variant of a widely used statistical measure of causality--Granger causality--that is inspired by the definition of partial correlation. Our 'partial Granger causality' measure is extensively tested with toy models, both linear and nonlinear, and is applied to experimental data: in vivo multielectrode array (MEA) local field potentials (LFPs) recorded from the inferotemporal cortex of sheep. Our results demonstrate that partial Granger causality can reveal the underlying interactions among elements in a network in the presence of exogenous inputs and latent variables in many cases where the existing conditional Granger causality fails.

Inductive reasoning about causally transmitted properties.

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Shafto, Patrick; Kemp, Charles; Bonawitz, Elizabeth Baraff; Coley, John D; Tenenbaum, Joshua B

2008-11-01

Different intuitive theories constrain and guide inferences in different contexts. Formalizing simple intuitive theories as probabilistic processes operating over structured representations, we present a new computational model of category-based induction about causally transmitted properties. A first experiment demonstrates undergraduates' context-sensitive use of taxonomic and food web knowledge to guide reasoning about causal transmission and shows good qualitative agreement between model predictions and human inferences. A second experiment demonstrates strong quantitative and qualitative fits to inferences about a more complex artificial food web. A third experiment investigates human reasoning about complex novel food webs where species have known taxonomic relations. Results demonstrate a double-dissociation between the predictions of our causal model and a related taxonomic model [Kemp, C., & Tenenbaum, J. B. (2003). Learning domain structures. In Proceedings of the 25th annual conference of the cognitive science society]: the causal model predicts human inferences about diseases but not genes, while the taxonomic model predicts human inferences about genes but not diseases. We contrast our framework with previous models of category-based induction and previous formal instantiations of intuitive theories, and outline challenges in developing a complete model of context-sensitive reasoning.

Neural correlates of continuous causal word generation.

Science.gov (United States)

Wende, Kim C; Straube, Benjamin; Stratmann, Mirjam; Sommer, Jens; Kircher, Tilo; Nagels, Arne

2012-09-01

Causality provides a natural structure for organizing our experience and language. Causal reasoning during speech production is a distinct aspect of verbal communication, whose related brain processes are yet unknown. The aim of the current study was to investigate the neural mechanisms underlying the continuous generation of cause-and-effect coherences during overt word production. During fMRI data acquisition participants performed three verbal fluency tasks on identical cue words: A novel causal verbal fluency task (CVF), requiring the production of multiple reasons to a given cue word (e.g. reasons for heat are fire, sun etc.), a semantic (free association, FA, e.g. associations with heat are sweat, shower etc.) and a phonological control task (phonological verbal fluency, PVF, e.g. rhymes with heat are meat, wheat etc.). We found that, in contrast to PVF, both CVF and FA activated a left lateralized network encompassing inferior frontal, inferior parietal and angular regions, with further bilateral activation in middle and inferior as well as superior temporal gyri and the cerebellum. For CVF contrasted against FA, we found greater bold responses only in the left middle frontal cortex. Large overlaps in the neural activations during free association and causal verbal fluency indicate that the access to causal relationships between verbal concepts is at least partly based on the semantic neural network. The selective activation in the left middle frontal cortex for causal verbal fluency suggests that distinct neural processes related to cause-and-effect-relations are associated with the recruitment of middle frontal brain areas. Copyright © 2012 Elsevier Inc. All rights reserved.

Testing causal relationships between wholesale electricity prices and primary energy prices

International Nuclear Information System (INIS)

Nakajima, Tadahiro; Hamori, Shigeyuki

2013-01-01

We apply the lag-augmented vector autoregression technique to test the Granger-causal relationships among wholesale electricity prices, natural gas prices, and crude oil prices. In addition, by adopting a cross-correlation function approach, we test not only the causality in mean but also the causality in variance between the variables. The results of tests using both techniques show that gas prices Granger-cause electricity prices in mean. We find no Granger-causality in variance among these variables. -- Highlights: •We test the Granger-causality among wholesale electricity and primary energy prices. •We test not only the causality in mean but also the causality in variance. •The results show that gas prices Granger-cause electricity prices in mean. •We find no Granger-causality in variance among these variables

World oil and agricultural commodity prices: Evidence from nonlinear causality

International Nuclear Information System (INIS)

Nazlioglu, Saban

2011-01-01

The increasing co-movements between the world oil and agricultural commodity prices have renewed interest in determining price transmission from oil prices to those of agricultural commodities. This study extends the literature on the oil-agricultural commodity prices nexus, which particularly concentrates on nonlinear causal relationships between the world oil and three key agricultural commodity prices (corn, soybeans, and wheat). To this end, the linear causality approach of Toda-Yamamoto and the nonparametric causality method of Diks-Panchenko are applied to the weekly data spanning from 1994 to 2010. The linear causality analysis indicates that the oil prices and the agricultural commodity prices do not influence each other, which supports evidence on the neutrality hypothesis. In contrast, the nonlinear causality analysis shows that: (i) there are nonlinear feedbacks between the oil and the agricultural prices, and (ii) there is a persistent unidirectional nonlinear causality running from the oil prices to the corn and to the soybeans prices. The findings from the nonlinear causality analysis therefore provide clues for better understanding the recent dynamics of the agricultural commodity prices and some policy implications for policy makers, farmers, and global investors. This study also suggests the directions for future studies. - Research highlights: → This study determines the price transmission mechanisms between the world oil and three key agricultural commodity prices (corn, soybeans, and wheat). → The linear and nonlinear cointegration and causality methods are carried out. → The linear causality analysis supports evidence on the neutrality hypothesis. → The nonlinear causality analysis shows that there is a persistent unidirectional causality from the oil prices to the corn and to the soybeans prices.

Genetic stability in potato germplasm for resistance to root galling caused by the powdery scab pathogen spongospora subterranea

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Spongospora subteranea, the causal agent of potato powdery scab is becoming increasingly important worldwide. Little is known about the genetic basis of resistance to this disease. The present study tested the hypothesis that potato genotypes with stable genetic resistance to "Spongospora root galli...

Making Sense of Your Genes: A Guide to Genetic Counseling

Science.gov (United States)

... become ill. • The genetic counselor may also discuss environmental risk factors in and outside of the home, what ... make decisions about cancer screening and cancer prevention methods. It could also ... about their cancer risks. A genetic counselor can also refer you to ...

Scientific evidence of dockworker illness to nursing clinical reasoning.

Science.gov (United States)

Almeida, Marlise Capa Verde de; Cezar-Vaz, Marta Regina

2016-04-01

To identify scientific evidence of occupational illness of dockworkers published in the literature. systematic review of the literature, developed according to the Cochrane method. The databases searched were: Cochrane, LILACS, MEDLINE/PubMed, CINAHL and SciELO. Studies from 1988 to 2014 were selected. The data were analyzed according to the level of evidence and Strengthening the Reporting of Observational Studies in Epidemiology. We included 14 studies, in which 11 (78.6%) were from international journals. The year of 2012 showed greater number of studies. All studies were classified as: Level of Evidence 4, highlighting lung cancer, musculoskeletal and ischemic diseases, causal link in chemical risks. The development of preventive measures should especially include chemical exposure of workers applying the clinical reasoning of nurses' environmental knowledge to care for illnesses. Identificar evidências científicas de adoecimento ocupacional do trabalhador portuário publicadas na literatura. Revisão sistemática da literatura, construída conforme o método Cochrane. As bases de dados pesquisadas foram Cochrane, LILACS, MEDLINE/PubMed, CINAHL e SciELO. Foram selecionados artigos publicados de 1988 a 2014. Os dados foram analisados conforme o Nível de Evidência e Strengthening the Reporting of Observational Studies in Epidemiology. Foram selecionadas 14 publicações, das quais 11 (78,6%) de revistas internacionais. O ano de 2012 reuniu maior número de publicações no período de estudo. Todas as publicações pertenciam ao Nível de Evidência 4, destacando o câncer pulmonar, doenças osteomusculares e isquêmicas, com nexo causal nos riscos químicos. A elaboração de medidas preventivas deve prever especialmente a exposição química do trabalhador, aplicando ao raciocínio clínico do enfermeiro um conhecimento ambiental para a assistência aos adoecimentos.

UMA TEORÍA CAUSAL PARA LOS CASOS FREGE

Directory of Open Access Journals (Sweden)

ABEL WAJNERMAN PAZ

2015-06-01

Full Text Available Fodor ha argumentado a favor de un par de tesis que pueden caracterizarse como constituyendo un dilema: Por un lado, si adoptamos una teoría funcional para los conceptos explicamos semánticamente los casos Frege pero caemos en el holismo semántico. Por otro lado, si adoptamos una teoría causal/informacional evitamos el holismo pero no explicamos los casos Frege semánticamente. Fodor (por ej, 1994, 1998 y 2008 intenta evitar la segunda parte del dilema argumentando que los casos de Frege pueden tener una explicación sintáctica y no semántica. En este trabajo intentaré ofrecer una salida alternativa al dilema fodoriano. Propondré una explicación semántica de los casos Frege que incorpora tanto elementos de una teoría causal como de una de rol funcional. Afirmaré que el contenido cognitivo o estrecho de un concepto (el tipo de contenido aparentemente exigido por los casos Frege es el conjunto de contenidos causales/informacionales de las representaciones que figuran en su rol funcional. Considero que individuar a las representaciones en los roles por medio de sus contenidos causales permite evitar el holismo (evitando el proceso de ramsificación típicamente empleado para individuar a los roles y que identificar el contenido cognitivo con contenidos causales/informacionales de las representaciones en los roles permite evitar el referencialismo de las propuestas causales (podemos distinguir sentido de referencia en términos causales.

Granger Causality and Unit Roots

DEFF Research Database (Denmark)

Rodríguez-Caballero, Carlos Vladimir; Ventosa-Santaulària, Daniel

2014-01-01

The asymptotic behavior of the Granger-causality test under stochastic nonstationarity is studied. Our results confirm that the inference drawn from the test is not reliable when the series are integrated to the first order. In the presence of deterministic components, the test statistic diverges......, eventually rejecting the null hypothesis, even when the series are independent of each other. Moreover, controlling for these deterministic elements (in the auxiliary regressions of the test) does not preclude the possibility of drawing erroneous inferences. Granger-causality tests should not be used under...

Quantum theory and local causality

CERN Document Server

Hofer-Szabó, Gábor

2018-01-01

This book summarizes the results of research the authors have pursued in the past years on the problem of implementing Bell's notion of local causality in local physical theories and relating it to other important concepts and principles in the foundations of physics such as the Common Cause Principle, Bell's inequalities, the EPR (Einstein-Podolsky-Rosen) scenario, and various other locality and causality concepts. The book is intended for philosophers of science with an interest in the formal background of sciences, philosophers of physics and physicists working in foundation of physics.

Quantum causality conceptual issues in the causal theory of quantum mechanics

CERN Document Server

Riggs, Peter J; French, Steven RD

2009-01-01

This is a treatise devoted to the foundations of quantum physics and the role that causality plays in the microscopic world governed by the laws of quantum mechanics. The book is controversial and will engender some lively debate on the various issues raised.

Genetic Alterations in Glioma

International Nuclear Information System (INIS)

Bralten, Linda B. C.; French, Pim J.

2011-01-01

Gliomas are the most common type of primary brain tumor and have a dismal prognosis. Understanding the genetic alterations that drive glioma formation and progression may help improve patient prognosis by identification of novel treatment targets. Recently, two major studies have performed in-depth mutation analysis of glioblastomas (the most common and aggressive subtype of glioma). This systematic approach revealed three major pathways that are affected in glioblastomas: The receptor tyrosine kinase signaling pathway, the TP53 pathway and the pRB pathway. Apart from frequent mutations in the IDH1/2 gene, much less is known about the causal genetic changes of grade II and III (anaplastic) gliomas. Exceptions include TP53 mutations and fusion genes involving the BRAF gene in astrocytic and pilocytic glioma subtypes, respectively. In this review, we provide an update on all common events involved in the initiation and/or progression across the different subtypes of glioma and provide future directions for research into the genetic changes

A Causal Model of Faculty Research Productivity.

Science.gov (United States)

Bean, John P.

A causal model of faculty research productivity was developed through a survey of the literature. Models of organizational behavior, organizational effectiveness, and motivation were synthesized into a causal model of productivity. Two general types of variables were assumed to affect individual research productivity: institutional variables and…

Causal inheritance in plane wave quotients

International Nuclear Information System (INIS)

Hubeny, Veronika E.; Rangamani, Mukund; Ross, Simon F.

2003-01-01

We investigate the appearance of closed timelike curves in quotients of plane waves along spacelike isometries. First we formulate a necessary and sufficient condition for a quotient of a general spacetime to preserve stable causality. We explicitly show that the plane waves are stably causal; in passing, we observe that some pp-waves are not even distinguishing. We then consider the classification of all quotients of the maximally supersymmetric ten-dimensional plane wave under a spacelike isometry, and show that the quotient will lead to closed timelike curves iff the isometry involves a translation along the u direction. The appearance of these closed timelike curves is thus connected to the special properties of the light cones in plane wave spacetimes. We show that all other quotients preserve stable causality

Testing the causal theory of reference.

Science.gov (United States)

Domaneschi, Filippo; Vignolo, Massimiliano; Di Paola, Simona

2017-04-01

Theories of reference are a crucial research topic in analytic philosophy. Since the publication of Kripke's Naming and Necessity, most philosophers have endorsed the causal/historical theory of reference. The goal of this paper is twofold: (i) to discuss a method for testing experimentally the causal theory of reference for proper names by investigating linguistic usage and (ii) to present the results from two experiments conducted with that method. Data collected in our experiments confirm the causal theory of reference for people proper names and for geographical proper names. A secondary but interesting result is that the semantic domain affects reference assignment: while with people proper names speakers tend to assign the semantic reference, with geographical proper names they are prompted to assign the speaker's reference. Copyright © 2016 Elsevier B.V. All rights reserved.

Causal inheritance in plane wave quotients

Science.gov (United States)

Hubeny, Veronika E.; Rangamani, Mukund; Ross, Simon F.

2004-01-01

We investigate the appearance of closed timelike curves in quotients of plane waves along spacelike isometries. First we formulate a necessary and sufficient condition for a quotient of a general space-time to preserve stable causality. We explicitly show that the plane waves are stably causal; in passing, we observe that some pp waves are not even distinguishing. We then consider the classification of all quotients of the maximally supersymmetric ten-dimensional plane wave under a spacelike isometry, and show that the quotient will lead to closed timelike curves iff the isometry involves a translation along the u direction. The appearance of these closed timelike curves is thus connected to the special properties of the light cones in plane wave space-times. We show that all other quotients preserve stable causality.

Associations between childhood ADHD, gender, and adolescent alcohol and marijuana involvement: A causally informative design.

Science.gov (United States)

Elkins, Irene J; Saunders, Gretchen R B; Malone, Stephen M; Keyes, Margaret A; McGue, Matt; Iacono, William G

2018-03-01

We report whether the etiology underlying associations of childhood ADHD with adolescent alcohol and marijuana involvement is consistent with causal relationships or shared predispositions, and whether it differs by gender. In three population-based twin samples (N = 3762; 64% monozygotic), including one oversampling females with ADHD, regressions were conducted with childhood inattentive or hyperactive-impulsive symptoms predicting alcohol and marijuana outcomes by age 17. To determine whether ADHD effects were consistent with causality, twin difference analyses divided effects into those shared between twins in the pair and those differing within pairs. Adolescents with more severe childhood ADHD were more likely to initiate alcohol and marijuana use earlier, escalate to frequent or heavy use, and develop symptoms. While risks were similar across genders, females with more hyperactivity-impulsivity had higher alcohol consumption and progressed further toward daily marijuana use than did males. Monozygotic twins with more severe ADHD than their co-twins did not differ significantly on alcohol or marijuana outcomes, however, suggesting a non-causal relationship. When co-occurring use of other substances and conduct/oppositional defiant disorders were considered, hyperactivity-impulsivity remained significantly associated with both substances, as did inattention with marijuana, but not alcohol. Childhood ADHD predicts when alcohol and marijuana use are initiated and how quickly use escalates. Shared familial environment and genetics, rather than causal influences, primarily account for these associations. Stronger relationships between hyperactivity-impulsivity and heavy drinking/frequent marijuana use among adolescent females than males, as well as the greater salience of inattention for marijuana, merit further investigation. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimating the causal influence of body mass index on risk of Parkinson disease: A Mendelian randomisation study.

Directory of Open Access Journals (Sweden)

Alastair J Noyce

2017-06-01

Full Text Available Both positive and negative associations between higher body mass index (BMI and Parkinson disease (PD have been reported in observational studies, but it has been difficult to establish causality because of the possibility of residual confounding or reverse causation. To our knowledge, Mendelian randomisation (MR-the use of genetic instrumental variables (IVs to explore causal effects-has not previously been used to test the effect of BMI on PD.Two-sample MR was undertaken using genome-wide association (GWA study data. The associations between the genetic instruments and BMI were obtained from the GIANT consortium and consisted of the per-allele difference in mean BMI for 77 independent variants that reached genome-wide significance. The per-allele difference in log-odds of PD for each of these variants was estimated from a recent meta-analysis, which included 13,708 cases of PD and 95,282 controls. The inverse-variance weighted method was used to estimate a pooled odds ratio (OR for the effect of a 5-kg/m2 higher BMI on PD. Evidence of directional pleiotropy averaged across all variants was sought using MR-Egger regression. Frailty simulations were used to assess whether causal associations were affected by mortality selection. A combined genetic IV expected to confer a lifetime exposure of 5-kg/m2 higher BMI was associated with a lower risk of PD (OR 0.82, 95% CI 0.69-0.98. MR-Egger regression gave similar results, suggesting that directional pleiotropy was unlikely to be biasing the result (intercept 0.002; p = 0.654. However, the apparent protective influence of higher BMI could be at least partially induced by survival bias in the PD GWA study, as demonstrated by frailty simulations. Other important limitations of this application of MR include the inability to analyse non-linear associations, to undertake subgroup analyses, and to gain mechanistic insights.In this large study using two-sample MR, we found that variants known to influence

Causal mediation analysis with multiple causally non-ordered mediators.

Science.gov (United States)

Taguri, Masataka; Featherstone, John; Cheng, Jing

2018-01-01

In many health studies, researchers are interested in estimating the treatment effects on the outcome around and through an intermediate variable. Such causal mediation analyses aim to understand the mechanisms that explain the treatment effect. Although multiple mediators are often involved in real studies, most of the literature considered mediation analyses with one mediator at a time. In this article, we consider mediation analyses when there are causally non-ordered multiple mediators. Even if the mediators do not affect each other, the sum of two indirect effects through the two mediators considered separately may diverge from the joint natural indirect effect when there are additive interactions between the effects of the two mediators on the outcome. Therefore, we derive an equation for the joint natural indirect effect based on the individual mediation effects and their interactive effect, which helps us understand how the mediation effect works through the two mediators and relative contributions of the mediators and their interaction. We also discuss an extension for three mediators. The proposed method is illustrated using data from a randomized trial on the prevention of dental caries.

Beyond Markov: Accounting for independence violations in causal reasoning.

Science.gov (United States)

Rehder, Bob

2018-06-01

Although many theories of causal cognition are based on causal graphical models, a key property of such models-the independence relations stipulated by the Markov condition-is routinely violated by human reasoners. This article presents three new accounts of those independence violations, accounts that share the assumption that people's understanding of the correlational structure of data generated from a causal graph differs from that stipulated by causal graphical model framework. To distinguish these models, experiments assessed how people reason with causal graphs that are larger than those tested in previous studies. A traditional common cause network (Y 1 ←X→Y 2 ) was extended so that the effects themselves had effects (Z 1 ←Y 1 ←X→Y 2 →Z 2 ). A traditional common effect network (Y 1 →X←Y 2 ) was extended so that the causes themselves had causes (Z 1 →Y 1 →X←Y 2 ←Z 2 ). Subjects' inferences were most consistent with the beta-Q model in which consistent states of the world-those in which variables are either mostly all present or mostly all absent-are viewed as more probable than stipulated by the causal graphical model framework. Substantial variability in subjects' inferences was also observed, with the result that substantial minorities of subjects were best fit by one of the other models (the dual prototype or a leaky gate models). The discrepancy between normative and human causal cognition stipulated by these models is foundational in the sense that they locate the error not in people's causal reasoning but rather in their causal representations. As a result, they are applicable to any cognitive theory grounded in causal graphical models, including theories of analogy, learning, explanation, categorization, decision-making, and counterfactual reasoning. Preliminary evidence that independence violations indeed generalize to other judgment types is presented. Copyright © 2018 Elsevier Inc. All rights reserved.

Trivariate causality between economic growth, urbanisation and electricity consumption in Angola: Cointegration and causality analysis

International Nuclear Information System (INIS)

Solarin, Sakiru Adebola; Shahbaz, Muhammad

2013-01-01

This paper investigates the causal relationship between economic growth, urbanisation and electricity consumption in the case of Angola, while utilizing the data over the period of 1971–2009. We have applied Lee and Strazicich (2003. The Review of Economics and Statistics 63, 1082–1089; 2004. Working Paper. Department of Economics, Appalachian State University) unit root tests to examine the stationarity properties of the series. Using the Gregory–Hansen structural break cointegration procedure as a complement, we employ the ARDL bounds test to investigate long run relationships. The VECM Granger causality test is subsequently used to examine the direction of causality between economic growth, urbanisation, and electricity consumption. Our results indicate the existence of long run relationships. We further observe evidence in favour of bidirectional causality between electricity consumption and economic growth. The feedback hypothesis is also found between urbanisation and economic growth. Urbanisation and electricity consumption Granger cause each other. We conclude that Angola is energy-dependent country. Consequently, the relevant authorities should boost electricity production as one of the means of achieving sustainable economic development in the long run. - Highlights: • We consider the link between electricity consumption and economic growth in Angola. • Urbanisation is added to turn the research into a trivariate investigation. • Various time series procedures are used. • Results show that increasing electricity will improve economic growth in Angola. • Results show urbanisations reduced economic growth during civil war

Triglyceride-rich lipoproteins as a causal factor for cardiovascular disease

Science.gov (United States)

Toth, Peter P

2016-01-01

Approximately 25% of US adults are estimated to have hypertriglyceridemia (triglyceride [TG] level ≥150 mg/dL [≥1.7 mmol/L]). Elevated TG levels are associated with increased cardiovascular disease (CVD) risk, and severe hypertriglyceridemia (TG levels ≥500 mg/dL [≥5.6 mmol/L]) is a well-established risk factor for acute pancreatitis. Plasma TG levels correspond to the sum of the TG content in TG-rich lipoproteins (TRLs; ie, very low-density lipoproteins plus chylomicrons) and their remnants. There remains some uncertainty regarding the direct causal role of TRLs in the progression of atherosclerosis and CVD, with cardiovascular outcome studies of TG-lowering agents, to date, having produced inconsistent results. Although low-density lipoprotein cholesterol (LDL-C) remains the primary treatment target to reduce CVD risk, a number of large-scale epidemiological studies have shown that elevated TG levels are independently associated with increased incidence of cardiovascular events, even in patients treated effectively with statins. Genetic studies have further clarified the causal association between TRLs and CVD. Variants in several key genes involved in TRL metabolism are strongly associated with CVD risk, with the strength of a variant’s effect on TG levels correlating with the magnitude of the variant’s effect on CVD. TRLs are thought to contribute to the progression of atherosclerosis and CVD via a number of direct and indirect mechanisms. They directly contribute to intimal cholesterol deposition and are also involved in the activation and enhancement of several proinflammatory, proapoptotic, and procoagulant pathways. Evidence suggests that non-high-density lipoprotein cholesterol, the sum of the total cholesterol carried by atherogenic lipoproteins (including LDL, TRL, and TRL remnants), provides a better indication of CVD risk than LDL-C, particularly in patients with hypertriglyceridemia. This article aims to provide an overview of the

Triglyceride-rich lipoproteins as a causal factor for cardiovascular disease.

Science.gov (United States)

Toth, Peter P

2016-01-01

Approximately 25% of US adults are estimated to have hypertriglyceridemia (triglyceride [TG] level ≥150 mg/dL [≥1.7 mmol/L]). Elevated TG levels are associated with increased cardiovascular disease (CVD) risk, and severe hypertriglyceridemia (TG levels ≥500 mg/dL [≥5.6 mmol/L]) is a well-established risk factor for acute pancreatitis. Plasma TG levels correspond to the sum of the TG content in TG-rich lipoproteins (TRLs; ie, very low-density lipoproteins plus chylomicrons) and their remnants. There remains some uncertainty regarding the direct causal role of TRLs in the progression of atherosclerosis and CVD, with cardiovascular outcome studies of TG-lowering agents, to date, having produced inconsistent results. Although low-density lipoprotein cholesterol (LDL-C) remains the primary treatment target to reduce CVD risk, a number of large-scale epidemiological studies have shown that elevated TG levels are independently associated with increased incidence of cardiovascular events, even in patients treated effectively with statins. Genetic studies have further clarified the causal association between TRLs and CVD. Variants in several key genes involved in TRL metabolism are strongly associated with CVD risk, with the strength of a variant's effect on TG levels correlating with the magnitude of the variant's effect on CVD. TRLs are thought to contribute to the progression of atherosclerosis and CVD via a number of direct and indirect mechanisms. They directly contribute to intimal cholesterol deposition and are also involved in the activation and enhancement of several proinflammatory, proapoptotic, and procoagulant pathways. Evidence suggests that non-high-density lipoprotein cholesterol, the sum of the total cholesterol carried by atherogenic lipoproteins (including LDL, TRL, and TRL remnants), provides a better indication of CVD risk than LDL-C, particularly in patients with hypertriglyceridemia. This article aims to provide an overview of the available

Simplifying Causal Complexity: How Interactions between Modes of Causal Induction and Information Availability Lead to Heuristic-Driven Reasoning

Science.gov (United States)

Grotzer, Tina A.; Tutwiler, M. Shane

2014-01-01

This article considers a set of well-researched default assumptions that people make in reasoning about complex causality and argues that, in part, they result from the forms of causal induction that we engage in and the type of information available in complex environments. It considers how information often falls outside our attentional frame…

Causal Relationship between Construction Production and GDP in Turkey

Directory of Open Access Journals (Sweden)

Hakkı Kutay Bolkol

2015-12-01

Full Text Available This study empirically investigates the causal relationship between construction production and GDP for Turkey during 2005Q1-2013Q4 period. Because it is found that, there is no cointegration which means there is no long run relationship between variables, VAR Granger Causality Method is used to test the causality in short run. The findings reveal that, the causality runs from GDP to Building Production and Building Production to Non-Building Production (i.e. bidirectional relationship. Findings of this paper suggest that, because there is no long run relationship between Construction Production (Building and Non-Building and GDP and also in short run the causality runs from GDP to Construction Production, the growth strategy based on mainly Construction Sector growth is not a good idea for Turkey.

Causal Relationship between Construction Production and GDP in Turkey

Directory of Open Access Journals (Sweden)

Hakkı Kutay Bolkol

2015-09-01

Full Text Available This study empirically investigates the causal relationship between construction production and GDP for Turkey during 2005Q1-2013Q4 period. Because it is found that, there is no cointegration which means there is no long run relationship between variables, VAR Granger Causality Method is used to test the causality in short run. The findings reveal that, the causality runs from GDP to Building Production and Building Production to Non-Building Production (i.e. bidirectional relationship. Findings of this paper suggest that, because there is no long run relationship between Construction Production (Building and Non-Building and GDP and also in short run the causality runs from GDP to Construction Production, the growth strategy based on mainly Construction Sector growth is not a good idea for Turkey.

Causality in demand

DEFF Research Database (Denmark)

Nielsen, Max; Jensen, Frank; Setälä, Jari

2011-01-01

to fish demand. On the German market for farmed trout and substitutes, it is found that supply sources, i.e. aquaculture and fishery, are not the only determinant of causality. Storing, tightness of management and aggregation level of integrated markets might also be important. The methodological...

Autobiologies on YouTube: Narratives of Direct-to-Consumer Genetic Testing

Science.gov (United States)

Harris, Anna; Kelly, Susan E.; Wyatt, Sally

2014-01-01

Despite a growing personal genomics market, little is known about how people engage with the possibilities offered by direct-to-consumer (DTC) genetic testing. In order to help address this gap, this study deploys narrative analysis of YouTube videos posted by individuals who have purchased DTC genetic testing for disease. Genetic testing is said to be contributing to new states of illness, where individuals may become “patients-in-waiting.” In the videos analyzed, we found a new form of storytelling about this ambiguous state of illness, which we refer to as autobiology. Autobiology – the study of, and story about, one's own biology – concerns narratives of sense-making through forms of biological practice, as well as wayfaring narratives which interweave genetic markers and family histories of disease. These autobiologies – part of a broader shift toward public stories about genetics and other healthcare technologies – exhibit playfulness, as well as being bound with consumerist practices. PMID:24772003

The causal relationship between Foreign Direct Investment (FDI ...

African Journals Online (AJOL)

The causal relationship between Foreign Direct Investment (FDI) and the ... of selected west African countries: Panel ARDL/Granger Causality Analysis. ... among this developing countries and an important revelation for policy implication.

The genetic difference principle.

Science.gov (United States)

Farrelly, Colin

2004-01-01

In the newly emerging debates about genetics and justice three distinct principles have begun to emerge concerning what the distributive aim of genetic interventions should be. These principles are: genetic equality, a genetic decent minimum, and the genetic difference principle. In this paper, I examine the rationale of each of these principles and argue that genetic equality and a genetic decent minimum are ill-equipped to tackle what I call the currency problem and the problem of weight. The genetic difference principle is the most promising of the three principles and I develop this principle so that it takes seriously the concerns of just health care and distributive justice in general. Given the strains on public funds for other important social programmes, the costs of pursuing genetic interventions and the nature of genetic interventions, I conclude that a more lax interpretation of the genetic difference principle is appropriate. This interpretation stipulates that genetic inequalities should be arranged so that they are to the greatest reasonable benefit of the least advantaged. Such a proposal is consistent with prioritarianism and provides some practical guidance for non-ideal societies--that is, societies that do not have the endless amount of resources needed to satisfy every requirement of justice.

Study about Illness: Through the Narrative of "Illness Image"

OpenAIRE

岩城, 晶子

2013-01-01

In this research, the meaning of the illness was studied from the perpective of Image. From listening to the narrative about two types of Illness Image, i.e., "my illness" and "A's illness, " we found that there was a characteristic that the Illness Image was similar to the real image. In addition, there were several differences between 2 images, which indicated that distance between the narrator and these images had an influence. From the syudy of two cases, it was indicated that Illness Ima...

Sensitivity Analysis and Bounding of Causal Effects with Alternative Identifying Assumptions

Science.gov (United States)

Jo, Booil; Vinokur, Amiram D.

2011-01-01

When identification of causal effects relies on untestable assumptions regarding nonidentified parameters, sensitivity of causal effect estimates is often questioned. For proper interpretation of causal effect estimates in this situation, deriving bounds on causal parameters or exploring the sensitivity of estimates to scientifically plausible…

Causal quantum theory and the collapse locality loophole

International Nuclear Information System (INIS)

Kent, Adrian

2005-01-01

Causal quantum theory is an umbrella term for ordinary quantum theory modified by two hypotheses: state vector reduction is a well-defined process, and strict local causality applies. The first of these holds in some versions of Copenhagen quantum theory and need not necessarily imply practically testable deviations from ordinary quantum theory. The second implies that measurement events which are spacelike separated have no nonlocal correlations. To test this prediction, which sharply differs from standard quantum theory, requires a precise definition of state vector reduction. Formally speaking, any precise version of causal quantum theory defines a local hidden variable theory. However, causal quantum theory is most naturally seen as a variant of standard quantum theory. For that reason it seems a more serious rival to standard quantum theory than local hidden variable models relying on the locality or detector efficiency loopholes. Some plausible versions of causal quantum theory are not refuted by any Bell experiments to date, nor is it evident that they are inconsistent with other experiments. They evade refutation via a neglected loophole in Bell experiments--the collapse locality loophole--which exists because of the possible time lag between a particle entering a measurement device and a collapse taking place. Fairly definitive tests of causal versus standard quantum theory could be made by observing entangled particles separated by ≅0.1 light seconds

Causal inference in survival analysis using pseudo-observations.

Science.gov (United States)

Andersen, Per K; Syriopoulou, Elisavet; Parner, Erik T

2017-07-30

Causal inference for non-censored response variables, such as binary or quantitative outcomes, is often based on either (1) direct standardization ('G-formula') or (2) inverse probability of treatment assignment weights ('propensity score'). To do causal inference in survival analysis, one needs to address right-censoring, and often, special techniques are required for that purpose. We will show how censoring can be dealt with 'once and for all' by means of so-called pseudo-observations when doing causal inference in survival analysis. The pseudo-observations can be used as a replacement of the outcomes without censoring when applying 'standard' causal inference methods, such as (1) or (2) earlier. We study this idea for estimating the average causal effect of a binary treatment on the survival probability, the restricted mean lifetime, and the cumulative incidence in a competing risks situation. The methods will be illustrated in a small simulation study and via a study of patients with acute myeloid leukemia who received either myeloablative or non-myeloablative conditioning before allogeneic hematopoetic cell transplantation. We will estimate the average causal effect of the conditioning regime on outcomes such as the 3-year overall survival probability and the 3-year risk of chronic graft-versus-host disease. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Causal Bayes Model of Mathematical Competence in Kindergarten

Directory of Open Access Journals (Sweden)

Božidar Tepeš

2016-06-01

Full Text Available In this paper authors define mathematical competences in the kindergarten. The basic objective was to measure the mathematical competences or mathematical knowledge, skills and abilities in mathematical education. Mathematical competences were grouped in the following areas: Arithmetic and Geometry. Statistical set consisted of 59 children, 65 to 85 months of age, from the Kindergarten Milan Sachs from Zagreb. The authors describe 13 variables for measuring mathematical competences. Five measuring variables were described for the geometry, and eight measuring variables for the arithmetic. Measuring variables are tasks which children solved with the evaluated results. By measuring mathematical competences the authors make causal Bayes model using free software Tetrad 5.2.1-3. Software makes many causal Bayes models and authors as experts chose the model of the mathematical competences in the kindergarten. Causal Bayes model describes five levels for mathematical competences. At the end of the modeling authors use Bayes estimator. In the results, authors describe by causal Bayes model of mathematical competences, causal effect mathematical competences or how intervention on some competences cause other competences. Authors measure mathematical competences with their expectation as random variables. When expectation of competences was greater, competences improved. Mathematical competences can be improved with intervention on causal competences. Levels of mathematical competences and the result of intervention on mathematical competences can help mathematical teachers.

A General Approach to Causal Mediation Analysis

Science.gov (United States)

Imai, Kosuke; Keele, Luke; Tingley, Dustin

2010-01-01

Traditionally in the social sciences, causal mediation analysis has been formulated, understood, and implemented within the framework of linear structural equation models. We argue and demonstrate that this is problematic for 3 reasons: the lack of a general definition of causal mediation effects independent of a particular statistical model, the…

Causal knowledge and the development of inductive reasoning

OpenAIRE

Bright, Aimée K.; Feeney, Aidan

2014-01-01

We explored the development of sensitivity to causal relations in children’s inductive reasoning. Children (5-, 8-, and 12-year-olds) and adults were given trials in which they decided whether a property known to be possessed by members of one category was also possessed by members of (a) a taxonomically related category or (b) a causally related category. The direction of the causal link was either predictive (prey → predator) or diagnostic (predator → prey), and the property that participan...

Normalizing the causality between time series

Science.gov (United States)

Liang, X. San

2015-08-01

Recently, a rigorous yet concise formula was derived to evaluate information flow, and hence the causality in a quantitative sense, between time series. To assess the importance of a resulting causality, it needs to be normalized. The normalization is achieved through distinguishing a Lyapunov exponent-like, one-dimensional phase-space stretching rate and a noise-to-signal ratio from the rate of information flow in the balance of the marginal entropy evolution of the flow recipient. It is verified with autoregressive models and applied to a real financial analysis problem. An unusually strong one-way causality is identified from IBM (International Business Machines Corporation) to GE (General Electric Company) in their early era, revealing to us an old story, which has almost faded into oblivion, about "Seven Dwarfs" competing with a giant for the mainframe computer market.

Inference of boundaries in causal sets

Science.gov (United States)

Cunningham, William J.

2018-05-01

We investigate the extrinsic geometry of causal sets in (1+1) -dimensional Minkowski spacetime. The properties of boundaries in an embedding space can be used not only to measure observables, but also to supplement the discrete action in the partition function via discretized Gibbons–Hawking–York boundary terms. We define several ways to represent a causal set using overlapping subsets, which then allows us to distinguish between null and non-null bounding hypersurfaces in an embedding space. We discuss algorithms to differentiate between different types of regions, consider when these distinctions are possible, and then apply the algorithms to several spacetime regions. Numerical results indicate the volumes of timelike boundaries can be measured to within 0.5% accuracy for flat boundaries and within 10% accuracy for highly curved boundaries for medium-sized causal sets with N  =  214 spacetime elements.

Spatial hypersurfaces in causal set cosmology

International Nuclear Information System (INIS)

Major, Seth A; Rideout, David; Surya, Sumati

2006-01-01

Within the causal set approach to quantum gravity, a discrete analogue of a spacelike region is a set of unrelated elements, or an antichain. In the continuum approximation of the theory, a moment-of-time hypersurface is well represented by an inextendible antichain. We construct a richer structure corresponding to a thickening of this antichain containing non-trivial geometric and topological information. We find that covariant observables can be associated with such thickened antichains and transitions between them, in classical sequential growth models of causal sets. This construction highlights the difference between the covariant measure on causal set cosmology and the standard sum-over-histories approach: the measure is assigned to completed histories rather than to histories on a restricted spacetime region. The resulting re-phrasing of the sum-over-histories may be fruitful in other approaches to quantum gravity

Analogy in causal inference: rethinking Austin Bradford Hill's neglected consideration.

Science.gov (United States)

Weed, Douglas L

2018-05-01

The purpose of this article was to rethink and resurrect Austin Bradford Hill's "criterion" of analogy as an important consideration in causal inference. In epidemiology today, analogy is either completely ignored (e.g., in many textbooks), or equated with biologic plausibility or coherence, or aligned with the scientist's imagination. None of these examples, however, captures Hill's description of analogy. His words suggest that there may be something gained by contrasting two bodies of evidence, one from an established causal relationship, the other not. Coupled with developments in the methods of systematic assessments of evidence-including but not limited to meta-analysis-analogy can be restructured as a key component in causal inference. This new approach will require that a collection-a library-of known cases of causal inference (i.e., bodies of evidence involving established causal relationships) be developed. This library would likely include causal assessments by organizations such as the International Agency for Research on Cancer, the National Toxicology Program, and the United States Environmental Protection Agency. In addition, a process for describing key features of a causal relationship would need to be developed along with what will be considered paradigm cases of causation. Finally, it will be important to develop ways to objectively compare a "new" body of evidence with the relevant paradigm case of causation. Analogy, along with all other existing methods and causal considerations, may improve our ability to identify causal relationships. Copyright © 2018 Elsevier Inc. All rights reserved.

Multichannel Signal Enhancement using Non-Causal, Time-Domain Filters

DEFF Research Database (Denmark)

Jensen, Jesper Rindom; Christensen, Mads Græsbøll; Benesty, Jacob

2013-01-01

In the vast amount of time-domain filtering methods for speech enhancement, the filters are designed to be causal. Recently, however, it was shown that the noise reduction and signal distortion capabilities of such single-channel filters can be improved by allowing the filters to be non-causal. W......In the vast amount of time-domain filtering methods for speech enhancement, the filters are designed to be causal. Recently, however, it was shown that the noise reduction and signal distortion capabilities of such single-channel filters can be improved by allowing the filters to be non......-causal, multichannel filters for enhancement based on an orthogonal decomposition is proposed. The evaluation shows that there is a potential gain in noise reduction and signal distortion by introducing non-causality. Moreover, experiments on real-life speech show that we can improve the perceptual quality....

Elements of Causal Inference: Foundations and Learning Algorithms

DEFF Research Database (Denmark)

Peters, Jonas Martin; Janzing, Dominik; Schölkopf, Bernhard

A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning......A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning...

Counterfactual overdetermination vs. the causal exclusion problem.

Science.gov (United States)

Sparber, Georg

2005-01-01

This paper aims to show that a counterfactual approach to causation is not sufficient to provide a solution to the causal exclusion problem in the form of systematic overdetermination. Taking into account the truthmakers of causal counterfactuals provides a strong argument in favour of the identity of causes in situations of translevel, causation.

Non-Bayesian Inference: Causal Structure Trumps Correlation

Science.gov (United States)

Bes, Benedicte; Sloman, Steven; Lucas, Christopher G.; Raufaste, Eric

2012-01-01

The study tests the hypothesis that conditional probability judgments can be influenced by causal links between the target event and the evidence even when the statistical relations among variables are held constant. Three experiments varied the causal structure relating three variables and found that (a) the target event was perceived as more…

Causality and complexity: the myth of objectivity in science.

Science.gov (United States)

Mikulecky, Donald C

2007-10-01

Two distinctly different worldviews dominate today's thinking in science and in the world of ideas outside of science. Using the approach advocated by Robert M. Hutchins, it is possible to see a pattern of interaction between ideas in science and in other spheres such as philosophy, religion, and politics. Instead of compartmentalizing these intellectual activities, it is worthwhile to look for common threads of mutual influence. Robert Rosen has created an approach to scientific epistemology that might seem radical to some. However, it has characteristics that resemble ideas in other fields, in particular in the writings of George Lakoff, Leo Strauss, and George Soros. Historically, the atmosphere at the University of Chicago during Hutchins' presidency gave rise to Rashevsky's relational biology, which Rosen carried forward. Strauss was writing his political philosophy there at the same time. One idea is paramount in all this, and it is Lakoff who gives us the most insight into how the worldviews differ using this idea. The central difference has to do with causality, the fundamental concept that we use to build a worldview. Causal entailment has two distinct forms in Lakoff 's analysis: direct causality and complex causality. Rosen's writings on complexity create a picture of complex causality that is extremely useful in its detail, grounding in the ideas of Aristotle. Strauss asks for a return to the ancients to put philosophy back on track. Lakoff sees the weaknesses in Western philosophy in a similar way, and Rosen provides tools for dealing with the problem. This introduction to the relationships between the thinking of these authors is meant to stimulate further discourse on the role of complex causal entailment in all areas of thought, and how it brings them together in a holistic worldview. The worldview built on complex causality is clearly distinct from that built around simple, direct causality. One important difference is that the impoverished causal

Causal Relations and Feature Similarity in Children's Inductive Reasoning

Science.gov (United States)

Hayes, Brett K.; Thompson, Susan P.

2007-01-01

Four experiments examined the development of property induction on the basis of causal relations. In the first 2 studies, 5-year-olds, 8-year-olds, and adults were presented with triads in which a target instance was equally similar to 2 inductive bases but shared a causal antecedent feature with 1 of them. All 3 age groups used causal relations…

Enhanced genetic characterization of influenza A(H3N2) viruses and vaccine effectiveness by genetic group, 2014–2015

Science.gov (United States)

Flannery, Brendan; Zimmerman, Richard K.; Gubareva, Larisa V.; Garten, Rebecca J.; Chung, Jessie R.; Nowalk, Mary Patricia; Jackson, Michael L.; Jackson, Lisa A.; Monto, Arnold S.; Ohmit, Suzanne E.; Belongia, Edward A.; McLean, Huong Q.; Gaglani, Manjusha; Piedra, Pedro A.; Mishin, Vasiliy P.; Chesnokov, Anton P.; Spencer, Sarah; Thaker, Swathi N.; Barnes, John R.; Foust, Angie; Sessions, Wendy; Xu, Xiyan; Katz, Jacqueline; Fry, Alicia M.

2018-01-01

Background During the 2014–15 US influenza season, expanded genetic characterization of circulating influenza A(H3N2) viruses was used to assess the impact of genetic variability of influenza A(H3N2) viruses on influenza vaccine effectiveness (VE). Methods A novel pyrosequencing assay was used to determine genetic group based on hemagglutinin (HA) gene sequences of influenza A(H3N2) viruses from patients enrolled US Flu Vaccine Effectiveness network sites. Vaccine effectiveness was estimated using a test-negative design comparing vaccination among patients infected with influenza A(H3N2) viruses and uninfected patients. Results Among 9710 enrollees, 1868 (19%) tested positive for influenza A(H3N2); genetic characterization of 1397 viruses showed 1134 (81%) belonged to one HA genetic group (3C.2a) of antigenically drifted H3N2 viruses. Effectiveness of 2014–15 influenza vaccination varied by A(H3N2) genetic group from 1% (95% confidence interval [CI], −14% to 14%) against illness caused by antigenically drifted A(H3N2) group 3C.2a viruses versus 44% (95% CI, 16% to 63%) against illness caused by vaccine-like A(H3N2) group 3C.3b viruses. Conclusion Effectiveness of 2014–15 influenza vaccination varied by genetic group of influenza A(H3N2) virus. Changes in hemagglutinin genes related to antigenic drift were associated with reduced vaccine effectiveness. PMID:27190176

Causality and subjectivity in discourse : The meaning and use of causal connectives in spontaneous conversation, chat interactions and written text

NARCIS (Netherlands)

Sanders, T.J.M.|info:eu-repo/dai/nl/075243911; Spooren, W.P.M.S.

Many languages of the world have connectives to express causal relations at the discourse level. Often, language users systematically prefer one lexical item (because) over another (even highly similar) one (since) to express a causal relationship. Such choices provide a window on speakers'

Psychiatric genetic research at the National Institute of Mental Health

Energy Technology Data Exchange (ETDEWEB)

Berg, K.; Mullican, C.; Maestri, N. [NIMH/NIH, Rockville, MD (United States)] [and others

1994-12-15

For some time it has been known through the results of family, twin, and adoption studies that hereditary appears to play a significant casual role in many mental disorders, including schizophrenia, bipolar disorder, and other mood disorders, Alzheimer`s Disease, panic disorder, obsessive compulsive disorder, autism, dyslexia, and Tourette`s syndrome. The precise patterns of inheritance of these complex disorders have not been determined, nor have the relevant genes been localized or cloned. Because the genetics are complex and because there is also clearly an environmental contribution to behavior, we expect the analysis of the genetics of mental illness to be arduous and not quickly resolved. There are several compelling reasons to continue to focus our attention on uncovering the genetic factors for severe mental illness. Prominent among these are the implications for better treatment of mental disorders. The National Institute of Mental Health supports a wide range of studies on psychiatric genetic research. 16 refs.

Campbell's and Rubin's Perspectives on Causal Inference

Science.gov (United States)

West, Stephen G.; Thoemmes, Felix

2010-01-01

Donald Campbell's approach to causal inference (D. T. Campbell, 1957; W. R. Shadish, T. D. Cook, & D. T. Campbell, 2002) is widely used in psychology and education, whereas Donald Rubin's causal model (P. W. Holland, 1986; D. B. Rubin, 1974, 2005) is widely used in economics, statistics, medicine, and public health. Campbell's approach focuses on…

Epidemiology and Heritability of Major Depressive Disorder, Stratified by Age of Onset, Sex, and Illness Course in Generation Scotland: Scottish Family Health Study (GS:SFHS.

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Ana Maria Fernandez-Pujals

Full Text Available The heritability of Major Depressive Disorder (MDD has been estimated at 37% based largely on twin studies that rely on contested assumptions. More recently, the heritability of MDD has been estimated on large populations from registries such as the Swedish, Finnish, and Chinese cohorts. Family-based designs utilise a number of different relationships and provide an alternative means of estimating heritability. Generation Scotland: Scottish Family Health Study (GS:SFHS is a large (n = 20,198, family-based population study designed to identify the genetic determinants of common diseases, including Major Depressive Disorder. Two thousand seven hundred and six individuals were SCID diagnosed with MDD, 13.5% of the cohort, from which we inferred a population prevalence of 12.2% (95% credible interval: 11.4% to 13.1%. Increased risk of MDD was associated with being female, unemployed due to a disability, current smokers, former drinkers, and living in areas of greater social deprivation. The heritability of MDD in GS:SFHS was between 28% and 44%, estimated from a pedigree model. The genetic correlation of MDD between sexes, age of onset, and illness course were examined and showed strong genetic correlations. The genetic correlation between males and females with MDD was 0.75 (0.43 to 0.99; between earlier (≤ age 40 and later (> age 40 onset was 0.85 (0.66 to 0.98; and between single and recurrent episodic illness course was 0.87 (0.72 to 0.98. We found that the heritability of recurrent MDD illness course was significantly greater than the heritability of single MDD illness course. The study confirms a moderate genetic contribution to depression, with a small contribution of the common family environment (variance proportion = 0.07, CI: 0.01 to 0.15, and supports the relationship of MDD with previously identified risk factors. This study did not find robust support for genetic differences in MDD due to sex, age of onset, or illness course. However

Epidemiology and Heritability of Major Depressive Disorder, Stratified by Age of Onset, Sex, and Illness Course in Generation Scotland: Scottish Family Health Study (GS:SFHS).

Science.gov (United States)

Fernandez-Pujals, Ana Maria; Adams, Mark James; Thomson, Pippa; McKechanie, Andrew G; Blackwood, Douglas H R; Smith, Blair H; Dominiczak, Anna F; Morris, Andrew D; Matthews, Keith; Campbell, Archie; Linksted, Pamela; Haley, Chris S; Deary, Ian J; Porteous, David J; MacIntyre, Donald J; McIntosh, Andrew M

2015-01-01

The heritability of Major Depressive Disorder (MDD) has been estimated at 37% based largely on twin studies that rely on contested assumptions. More recently, the heritability of MDD has been estimated on large populations from registries such as the Swedish, Finnish, and Chinese cohorts. Family-based designs utilise a number of different relationships and provide an alternative means of estimating heritability. Generation Scotland: Scottish Family Health Study (GS:SFHS) is a large (n = 20,198), family-based population study designed to identify the genetic determinants of common diseases, including Major Depressive Disorder. Two thousand seven hundred and six individuals were SCID diagnosed with MDD, 13.5% of the cohort, from which we inferred a population prevalence of 12.2% (95% credible interval: 11.4% to 13.1%). Increased risk of MDD was associated with being female, unemployed due to a disability, current smokers, former drinkers, and living in areas of greater social deprivation. The heritability of MDD in GS:SFHS was between 28% and 44%, estimated from a pedigree model. The genetic correlation of MDD between sexes, age of onset, and illness course were examined and showed strong genetic correlations. The genetic correlation between males and females with MDD was 0.75 (0.43 to 0.99); between earlier (≤ age 40) and later (> age 40) onset was 0.85 (0.66 to 0.98); and between single and recurrent episodic illness course was 0.87 (0.72 to 0.98). We found that the heritability of recurrent MDD illness course was significantly greater than the heritability of single MDD illness course. The study confirms a moderate genetic contribution to depression, with a small contribution of the common family environment (variance proportion = 0.07, CI: 0.01 to 0.15), and supports the relationship of MDD with previously identified risk factors. This study did not find robust support for genetic differences in MDD due to sex, age of onset, or illness course. However, we found

A genetic perspective on the association between exercise and mental health.

NARCIS (Netherlands)

de Geus, E.J.C.; de Moor, M.H.M.

2008-01-01

Regular exercise is associated with better mental health. This association is widely assumed to reflect causal effects of exercise. In this paper we propose that two additional mechanisms contribute to the association between exercise and mental health in the population-at-large: genetic pleiotropy

Increasing fMRI sampling rate improves Granger causality estimates.

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Fa-Hsuan Lin

Full Text Available Estimation of causal interactions between brain areas is necessary for elucidating large-scale functional brain networks underlying behavior and cognition. Granger causality analysis of time series data can quantitatively estimate directional information flow between brain regions. Here, we show that such estimates are significantly improved when the temporal sampling rate of functional magnetic resonance imaging (fMRI is increased 20-fold. Specifically, healthy volunteers performed a simple visuomotor task during blood oxygenation level dependent (BOLD contrast based whole-head inverse imaging (InI. Granger causality analysis based on raw InI BOLD data sampled at 100-ms resolution detected the expected causal relations, whereas when the data were downsampled to the temporal resolution of 2 s typically used in echo-planar fMRI, the causality could not be detected. An additional control analysis, in which we SINC interpolated additional data points to the downsampled time series at 0.1-s intervals, confirmed that the improvements achieved with the real InI data were not explainable by the increased time-series length alone. We therefore conclude that the high-temporal resolution of InI improves the Granger causality connectivity analysis of the human brain.

Vector Autoregressive Models and Granger Causality in Time Series Analysis in Nursing Research: Dynamic Changes Among Vital Signs Prior to Cardiorespiratory Instability Events as an Example.

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Bose, Eliezer; Hravnak, Marilyn; Sereika, Susan M

Patients undergoing continuous vital sign monitoring (heart rate [HR], respiratory rate [RR], pulse oximetry [SpO2]) in real time display interrelated vital sign changes during situations of physiological stress. Patterns in this physiological cross-talk could portend impending cardiorespiratory instability (CRI). Vector autoregressive (VAR) modeling with Granger causality tests is one of the most flexible ways to elucidate underlying causal mechanisms in time series data. The purpose of this article is to illustrate the development of patient-specific VAR models using vital sign time series data in a sample of acutely ill, monitored, step-down unit patients and determine their Granger causal dynamics prior to onset of an incident CRI. CRI was defined as vital signs beyond stipulated normality thresholds (HR = 40-140/minute, RR = 8-36/minute, SpO2 time segment prior to onset of first CRI was chosen for time series modeling in 20 patients using a six-step procedure: (a) the uniform time series for each vital sign was assessed for stationarity, (b) appropriate lag was determined using a lag-length selection criteria, (c) the VAR model was constructed, (d) residual autocorrelation was assessed with the Lagrange Multiplier test, (e) stability of the VAR system was checked, and (f) Granger causality was evaluated in the final stable model. The primary cause of incident CRI was low SpO2 (60% of cases), followed by out-of-range RR (30%) and HR (10%). Granger causality testing revealed that change in RR caused change in HR (21%; i.e., RR changed before HR changed) more often than change in HR causing change in RR (15%). Similarly, changes in RR caused changes in SpO2 (15%) more often than changes in SpO2 caused changes in RR (9%). For HR and SpO2, changes in HR causing changes in SpO2 and changes in SpO2 causing changes in HR occurred with equal frequency (18%). Within this sample of acutely ill patients who experienced a CRI event, VAR modeling indicated that RR changes

Inference of Boundaries in Causal Sets

OpenAIRE

Cunningham, William

2017-01-01

We investigate the extrinsic geometry of causal sets in $(1+1)$-dimensional Minkowski spacetime. The properties of boundaries in an embedding space can be used not only to measure observables, but also to supplement the discrete action in the partition function via discretized Gibbons-Hawking-York boundary terms. We define several ways to represent a causal set using overlapping subsets, which then allows us to distinguish between null and non-null bounding hypersurfaces in an embedding space...

Causal Relationship Between Relative Price Variability and Inflation in Turkey:

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Nebiye Yamak

2016-09-01

Full Text Available This study investigates the causal relationship between inflation and relative price variability in Turkey for the period of January 2003-January 2014, by using panel data. In the study, a Granger (1969 non-causality test in heterogeneous panel data models developed by Dumitrescu and Hurlin (2012 is utilized to determine the causal relations between inflation rate relative price variability. The panel data consists of 4123 observations: 133 time observations and 31 cross-section observations. The results of panel causality test indicate that there is a bidirectional causality between inflation rate and relative price variability by not supporting the imperfection information model of Lucas and the menu cost model of Ball and Mankiw.

Causality and prediction: differences and points of contact

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Luis Carlos Silva Ayçaguer, PhD

2014-09-01

Full Text Available This contribution presents the differences between those variables that might play a causal role in a certain process and those only valuable for predicting the outcome. Some considerations are made about the core intervention of the association and the temporal precedence and biases in both cases, the study of causality and predictive modeling. In that context, several relevant aspects related to the design of the corresponding studies are briefly reviewed and some of the mistakes that are often committed in handling both, causality and prediction, are illustrated.

Incorporating Functional Genomic Information in Genetic Association Studies Using an Empirical Bayes Approach.

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Spencer, Amy V; Cox, Angela; Lin, Wei-Yu; Easton, Douglas F; Michailidou, Kyriaki; Walters, Kevin

2016-04-01

There is a large amount of functional genetic data available, which can be used to inform fine-mapping association studies (in diseases with well-characterised disease pathways). Single nucleotide polymorphism (SNP) prioritization via Bayes factors is attractive because prior information can inform the effect size or the prior probability of causal association. This approach requires the specification of the effect size. If the information needed to estimate a priori the probability density for the effect sizes for causal SNPs in a genomic region isn't consistent or isn't available, then specifying a prior variance for the effect sizes is challenging. We propose both an empirical method to estimate this prior variance, and a coherent approach to using SNP-level functional data, to inform the prior probability of causal association. Through simulation we show that when ranking SNPs by our empirical Bayes factor in a fine-mapping study, the causal SNP rank is generally as high or higher than the rank using Bayes factors with other plausible values of the prior variance. Importantly, we also show that assigning SNP-specific prior probabilities of association based on expert prior functional knowledge of the disease mechanism can lead to improved causal SNPs ranks compared to ranking with identical prior probabilities of association. We demonstrate the use of our methods by applying the methods to the fine mapping of the CASP8 region of chromosome 2 using genotype data from the Collaborative Oncological Gene-Environment Study (COGS) Consortium. The data we analysed included approximately 46,000 breast cancer case and 43,000 healthy control samples. © 2016 The Authors. *Genetic Epidemiology published by Wiley Periodicals, Inc.

Cortical hierarchies perform Bayesian causal inference in multisensory perception.

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Tim Rohe

2015-02-01

Full Text Available To form a veridical percept of the environment, the brain needs to integrate sensory signals from a common source but segregate those from independent sources. Thus, perception inherently relies on solving the "causal inference problem." Behaviorally, humans solve this problem optimally as predicted by Bayesian Causal Inference; yet, the underlying neural mechanisms are unexplored. Combining psychophysics, Bayesian modeling, functional magnetic resonance imaging (fMRI, and multivariate decoding in an audiovisual spatial localization task, we demonstrate that Bayesian Causal Inference is performed by a hierarchy of multisensory processes in the human brain. At the bottom of the hierarchy, in auditory and visual areas, location is represented on the basis that the two signals are generated by independent sources (= segregation. At the next stage, in posterior intraparietal sulcus, location is estimated under the assumption that the two signals are from a common source (= forced fusion. Only at the top of the hierarchy, in anterior intraparietal sulcus, the uncertainty about the causal structure of the world is taken into account and sensory signals are combined as predicted by Bayesian Causal Inference. Characterizing the computational operations of signal interactions reveals the hierarchical nature of multisensory perception in human neocortex. It unravels how the brain accomplishes Bayesian Causal Inference, a statistical computation fundamental for perception and cognition. Our results demonstrate how the brain combines information in the face of uncertainty about the underlying causal structure of the world.

An update on the genetic architecture of hyperuricemia and gout.

Science.gov (United States)

Merriman, Tony R

2015-04-10

Genome-wide association studies that scan the genome for common genetic variants associated with phenotype have greatly advanced medical knowledge. Hyperuricemia is no exception, with 28 loci identified. However, genetic control of pathways determining gout in the presence of hyperuricemia is still poorly understood. Two important pathways determining hyperuricemia have been confirmed (renal and gut excretion of uric acid with glycolysis now firmly implicated). Major urate loci are SLC2A9 and ABCG2. Recent studies show that SLC2A9 is involved in renal and gut excretion of uric acid and is implicated in antioxidant defense. Although etiological variants at SLC2A9 are yet to be identified, it is clear that considerable genetic complexity exists at the SLC2A9 locus, with multiple statistically independent genetic variants and local epistatic interactions. The positions of implicated genetic variants within or near chromatin regions involved in transcriptional control suggest that this mechanism (rather than structural changes in SLC2A9) is important in regulating the activity of SLC2A9. ABCG2 is involved primarily in extra-renal uric acid under-excretion with the etiological variant influencing expression. At the other 26 loci, probable causal genes can be identified at three (PDZK1, SLC22A11, and INHBB) with strong candidates at a further 10 loci. Confirmation of the causal gene will require a combination of re-sequencing, trans-ancestral mapping, and correlation of genetic association data with expression data. As expected, the urate loci associate with gout, although inconsistent effect sizes for gout require investigation. Finally, there has been no genome-wide association study using clinically ascertained cases to investigate the causes of gout in the presence of hyperuricemia. In such a study, use of asymptomatic hyperurcemic controls would be expected to increase the ability to detect genetic associations with gout.

Genetic Diversity and Population Differentiation of the Causal Agent of Citrus Black Spot in Brazil

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Ester Wickert

2012-01-01

Full Text Available One of the most important diseases that affect sweet orange orchards in Brazil is the Citrus Black Spot that is caused by the fungus Guignardia citricarpa. This disease causes irreparable losses due to the premature falling of fruit, as well as its severe effects on the epidermis of ripe fruit that renders them unacceptable at the fresh fruit markets. Despite the fact that the fungus and the disease are well studied, little is known about the genetic diversity and the structure of the fungi populations in Brazilian orchards. The objective of this work was study the genetic diversity and population differentiation of G. citricarpa associated with four sweet orange varieties in two geographic locations using DNA sequence of ITS1-5.8S-ITS2 region from fungi isolates. We observed that different populations are closely related and present little genetic structure according to varieties and geographic places with the highest genetic diversity distributed among isolates of the same populations. The same haplotypes were sampled in different populations from the same and different orange varieties and from similar and different origins. If new and pathogenic fungi would become resistant to fungicides, the observed genetic structure could rapidly spread this new form from one population to others.

Whose statistical reasoning is facilitated by a causal structure intervention?

Science.gov (United States)

McNair, Simon; Feeney, Aidan

2015-02-01

People often struggle when making Bayesian probabilistic estimates on the basis of competing sources of statistical evidence. Recently, Krynski and Tenenbaum (Journal of Experimental Psychology: General, 136, 430-450, 2007) proposed that a causal Bayesian framework accounts for peoples' errors in Bayesian reasoning and showed that, by clarifying the causal relations among the pieces of evidence, judgments on a classic statistical reasoning problem could be significantly improved. We aimed to understand whose statistical reasoning is facilitated by the causal structure intervention. In Experiment 1, although we observed causal facilitation effects overall, the effect was confined to participants high in numeracy. We did not find an overall facilitation effect in Experiment 2 but did replicate the earlier interaction between numerical ability and the presence or absence of causal content. This effect held when we controlled for general cognitive ability and thinking disposition. Our results suggest that clarifying causal structure facilitates Bayesian judgments, but only for participants with sufficient understanding of basic concepts in probability and statistics.

Modeling of causality with metamaterials

International Nuclear Information System (INIS)

Smolyaninov, Igor I

2013-01-01

Hyperbolic metamaterials may be used to model a 2 + 1-dimensional Minkowski space–time in which the role of time is played by one of the spatial coordinates. When a metamaterial is built and illuminated with a coherent extraordinary laser beam, the stationary pattern of light propagation inside the metamaterial may be treated as a collection of particle world lines, which represents a complete ‘history’ of this 2 + 1-dimensional space–time. While this model may be used to build interesting space–time analogs, such as metamaterial ‘black holes’ and a metamaterial ‘big bang’, it lacks causality: since light inside the metamaterial may propagate back and forth along the ‘timelike’ spatial coordinate, events in the ‘future’ may affect events in the ‘past’. Here we demonstrate that a more sophisticated metamaterial model may fix this deficiency via breaking the mirror and temporal (PT) symmetries of the original model and producing one-way propagation along the ‘timelike’ spatial coordinate. The resulting 2 + 1-dimensional Minkowski space–time appears to be causal. This scenario may be considered as a metamaterial model of the Wheeler–Feynman absorber theory of causality. (paper)

Human Genetic Variation and Parkinson’s Disease

Directory of Open Access Journals (Sweden)

Sun Ju Chung

2010-05-01

Full Text Available Parkinson’s disease (PD is a chronic neurodegenerative disorder with multifactorial etiology. In the past decade, the genetic causes of monogenic forms of familial PD have been defined. However, the etiology and pathogenesis of the majority of sporadic PD cases that occur in outbred populations have yet to be clarified. The recent development of resources such as the International HapMap Project and technological advances in high-throughput genotyping have provided new basis for genetic association studies of common complex diseases, including PD. A new generation of genome-wide association studies will soon offer a potentially powerful approach for mapping causal genes and will likely change treatment and alter our perception of the genetic determinants of PD. However, the execution and analysis of such studies will require great care.

Different conceptions of mental illness: consequences for the association with patients.

Science.gov (United States)

Helmchen, Hanfried

2013-01-01

Whenever partial knowledge is considered absolute and turned into ideological and dogmatic conceptions, the risk increases that the conditions for the people involved might become dangerous. This will be illustrated by casuistic examples of consequences of one-sided psychiatric conceptions such as social, biological, and psychological ideas about the treatment and care of the mentally ill. Present perspectives of an integrative model, i.e., an advanced bio-psycho-social conception about evidence-based characteristics on the social, psychological, and molecular-genetic level, require that all of these dimensions should be considered in order to personalize and thereby improve the care and treatment of the mentally ill.

Human genetics of infectious diseases: a unified theory

Science.gov (United States)

Casanova, Jean-Laurent; Abel, Laurent

2007-01-01

Since the early 1950s, the dominant paradigm in the human genetics of infectious diseases postulates that rare monogenic immunodeficiencies confer vulnerability to multiple infectious diseases (one gene, multiple infections), whereas common infections are associated with the polygenic inheritance of multiple susceptibility genes (one infection, multiple genes). Recent studies, since 1996 in particular, have challenged this view. A newly recognised group of primary immunodeficiencies predisposing the individual to a principal or single type of infection is emerging. In parallel, several common infections have been shown to reflect the inheritance of one major susceptibility gene, at least in some populations. This novel causal relationship (one gene, one infection) blurs the distinction between patient-based Mendelian genetics and population-based complex genetics, and provides a unified conceptual frame for exploring the molecular genetic basis of infectious diseases in humans. PMID:17255931

Electricity consumption-real GDP causality nexus: Evidence from a bootstrapped causality test for 30 OECD countries

International Nuclear Information System (INIS)

Narayan, Paresh Kumar; Prasad, Arti

2008-01-01

The goal of this paper is to examine any causal effects between electricity consumption and real GDP for 30 OECD countries. We use a bootstrapped causality testing approach and unravel evidence in favour of electricity consumption causing real GDP in Australia, Iceland, Italy, the Slovak Republic, the Czech Republic, Korea, Portugal, and the UK. The implication is that electricity conservation policies will negatively impact real GDP in these countries. However, for the rest of the 22 countries our findings suggest that electricity conversation policies will not affect real GDP

Non-Causal Time-Domain Filters for Single-Channel Noise Reduction

DEFF Research Database (Denmark)

Jensen, Jesper Rindom; Benesty, Jacob; Christensen, Mads Græsbøll

2012-01-01

suppression and signal distortion by allowing the filters to be non-causal. Non-causal time-domain filters require knowledge of the future, and are therefore not directly implementable. If the observed signal is processed in blocks, however, the non-causal filters are implementable. In this paper, we propose...

Basic approaches for the handling of illnesses of the cultivation of the rice

International Nuclear Information System (INIS)

Tapiero Ortiz, A.L.

2001-01-01

Some basic concepts are exposed for the handling of illnesses in the cultivation of the rice, beginning with the illness definition in the plants, integrating the concept in a system plant-pathogen-environment that in turn would have the subsystem it plants, subsystem pathogen and subsystem environmental conditions. It discusses each one of these subsystems and their influence in the development of the infection. The illnesses of the rice are described taken place by the mushrooms Pyricularia oryzae and Rizoctonia solani and the resistance and receptivity to the pathogens on the part of genetic materials, as well as it influences of the environment and indications are given for their handling. The spotted of the grain of the rice like an illness is described caused by a complex of mushrooms, bacteria and nutritional and climatic factors that cause decrease in the yield and they reduce the quality of the grain and the seed. They are related the pathogens organisms causing the illness, the influence of the environment in their development and instructions are given for their handling

Causal Effect Inference with Deep Latent-Variable Models

NARCIS (Netherlands)

Louizos, C; Shalit, U.; Mooij, J.; Sontag, D.; Zemel, R.; Welling, M.

2017-01-01

Learning individual-level causal effects from observational data, such as inferring the most effective medication for a specific patient, is a problem of growing importance for policy makers. The most important aspect of inferring causal effects from observational data is the handling of

Causal inference in survival analysis using pseudo-observations

DEFF Research Database (Denmark)

Andersen, Per K; Syriopoulou, Elisavet; Parner, Erik T

2017-01-01

Causal inference for non-censored response variables, such as binary or quantitative outcomes, is often based on either (1) direct standardization ('G-formula') or (2) inverse probability of treatment assignment weights ('propensity score'). To do causal inference in survival analysis, one needs ...

Causal Indicators Can Help to Interpret Factors

Science.gov (United States)

Bentler, Peter M.

2016-01-01

The latent factor in a causal indicator model is no more than the latent factor of the factor part of the model. However, if the causal indicator variables are well-understood and help to improve the prediction of individuals' factor scores, they can help to interpret the meaning of the latent factor. Aguirre-Urreta, Rönkkö, and Marakas (2016)…

QED representation for the net of causal loops

Science.gov (United States)

Ciolli, Fabio; Ruzzi, Giuseppe; Vasselli, Ezio

2015-06-01

The present work tackles the existence of local gauge symmetries in the setting of Algebraic Quantum Field Theory (AQFT). The net of causal loops, previously introduced by the authors, is a model independent construction of a covariant net of local C*-algebras on any 4-dimensional globally hyperbolic space-time, aimed to capture structural properties of any reasonable quantum gauge theory. Representations of this net can be described by causal and covariant connection systems, and local gauge transformations arise as maps between equivalent connection systems. The present paper completes these abstract results, realizing QED as a representation of the net of causal loops in Minkowski space-time. More precisely, we map the quantum electromagnetic field Fμν, not free in general, into a representation of the net of causal loops and show that the corresponding connection system and the local gauge transformations find a counterpart in terms of Fμν.

Causal learning is collaborative: Examining explanation and exploration in social contexts.

Science.gov (United States)

Legare, Cristine H; Sobel, David M; Callanan, Maureen

2017-10-01

Causal learning in childhood is a dynamic and collaborative process of explanation and exploration within complex physical and social environments. Understanding how children learn causal knowledge requires examining how they update beliefs about the world given novel information and studying the processes by which children learn in collaboration with caregivers, educators, and peers. The objective of this article is to review evidence for how children learn causal knowledge by explaining and exploring in collaboration with others. We review three examples of causal learning in social contexts, which elucidate how interaction with others influences causal learning. First, we consider children's explanation-seeking behaviors in the form of "why" questions. Second, we examine parents' elaboration of meaning about causal relations. Finally, we consider parents' interactive styles with children during free play, which constrains how children explore. We propose that the best way to understand children's causal learning in social context is to combine results from laboratory and natural interactive informal learning environments.

Human Papilloma Viruses and Breast Cancer - Assessment of Causality.

Science.gov (United States)

Lawson, James Sutherland; Glenn, Wendy K; Whitaker, Noel James

2016-01-01

High risk human papilloma viruses (HPVs) may have a causal role in some breast cancers. Case-control studies, conducted in many different countries, consistently indicate that HPVs are more frequently present in breast cancers as compared to benign breast and normal breast controls (odds ratio 4.02). The assessment of causality of HPVs in breast cancer is difficult because (i) the HPV viral load is extremely low, (ii) HPV infections are common but HPV associated breast cancers are uncommon, and (iii) HPV infections may precede the development of breast and other cancers by years or even decades. Further, HPV oncogenesis can be indirect. Despite these difficulties, the emergence of new evidence has made the assessment of HPV causality, in breast cancer, a practical proposition. With one exception, the evidence meets all the conventional criteria for a causal role of HPVs in breast cancer. The exception is "specificity." HPVs are ubiquitous, which is the exact opposite of specificity. An additional reservation is that the prevalence of breast cancer is not increased in immunocompromised patients as is the case with respect to HPV-associated cervical cancer. This indicates that HPVs may have an indirect causal influence in breast cancer. Based on the overall evidence, high-risk HPVs may have a causal role in some breast cancers.

Causality and Free Will

Czech Academy of Sciences Publication Activity Database

Hvorecký, Juraj

2012-01-01

Roč. 19, Supp.2 (2012), s. 64-69 ISSN 1335-0668 R&D Projects: GA ČR(CZ) GAP401/12/0833 Institutional support: RVO:67985955 Keywords : conciousness * free will * determinism * causality Subject RIV: AA - Philosophy ; Religion

Genetic Predisposition to Dyslipidemia and Risk of Preeclampsia.

Science.gov (United States)

Spracklen, Cassandra N; Saftlas, Audrey F; Triche, Elizabeth W; Bjonnes, Andrew; Keating, Brendan; Saxena, Richa; Breheny, Patrick J; Dewan, Andrew T; Robinson, Jennifer G; Hoh, Josephine; Ryckman, Kelli K

2015-07-01

Large epidemiologic studies support the role of dyslipidemia in preeclampsia; however, the etiology of preeclampsia or whether dyslipidemia plays a causal role remains unclear. We examined the association between the genetic predisposition to dyslipidemia and risk of preeclampsia using validated genetic markers of dyslipidemia. Preeclampsia cases (n = 164) and normotensive controls (n = 110) were selected from live birth certificates to nulliparous Iowa women during the period August 2002 to May 2005. Disease status was verified by medical chart review. Genetic predisposition to dyslipidemia was estimated by 4 genetic risk scores (GRS) (total cholesterol (TC), LDL cholesterol (LDL-C), HDL cholesterol (HDL-C), and triglycerides) on the basis of established loci for blood lipids. Logistic regression analyses were used to evaluate the relationships between each of the 4 genotype scores and preeclampsia. Replication analyses were performed in an independent, US population of preeclampsia cases (n = 516) and controls (n = 1,097) of European ancestry. The GRS related to higher levels of TC, LDL-C, and triglycerides demonstrated no association with the risk of preeclampsia in either the Iowa or replication population. The GRS related to lower HDL-C was marginally associated with an increased risk for preeclampsia (odds ratio (OR) = 1.03, 95% confidence interval (CI) = 0.99-1.07; P = 0.10). In the independent replication population, the association with the HDL-C GRS was also marginally significant (OR = 1.03, 95% CI: 1.00-1.06; P = 0.04). Our data suggest a potential effect between the genetic predisposition to dyslipidemic levels of HDL-C and an increased risk of preeclampsia, and, as such, suggest that dyslipidemia may be a component along the causal pathway to preeclampsia. © American Journal of Hypertension, Ltd 2014. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Genetically elevated non-fasting triglycerides and calculated remnant cholesterol as causal risk factors for myocardial infarction

DEFF Research Database (Denmark)

Jørgensen, Anders Berg; Frikke-Schmidt, Ruth; West, Anders Sode

2012-01-01

AimsElevated non-fasting triglycerides mark elevated levels of remnant cholesterol. Using a Mendelian randomization approach, we tested whether genetically increased remnant cholesterol in hypertriglyceridaemia due to genetic variation in the apolipoprotein A5 gene (APOA5) associates with an incr......AimsElevated non-fasting triglycerides mark elevated levels of remnant cholesterol. Using a Mendelian randomization approach, we tested whether genetically increased remnant cholesterol in hypertriglyceridaemia due to genetic variation in the apolipoprotein A5 gene (APOA5) associates...... with an increased risk of myocardial infarction (MI).Methods and resultsWe resequenced the core promoter and coding regions of APOA5 in individuals with the lowest 1% (n = 95) and highest 2% (n = 190) triglyceride levels in the Copenhagen City Heart Study (CCHS, n = 10 391). Genetic variants which differed...... in frequency between the two extreme triglyceride groups (c.-1131T > C, S19W, and c.*31C > T; P-value: 0.06 to...

Causality and skies: is non-refocussing necessary?

International Nuclear Information System (INIS)

Bautista, A; Ibort, A; Lafuente, J

2015-01-01

The causal structure of a strongly causal, null pseudo-convex, space-time M is completely characterized in terms of a partial order on its space of skies defined by means of a class of non-negative Legendrian isotopies called sky isotopies. It is also shown that such partial order is determined by the class of future causal celestial curves, that is, curves in the space of light rays which are tangent to skies and such that they determine non-negative sky isotopies. It will also be proved that the space of skies Σ equipped with Low’s (or reconstructive) topology is homeomorphic and diffeomorphic to M under the only additional assumption that M separates skies, that is, that different events determine different skies. The sky-separating property of M is sharp and the previous result provides an answer to the question about the class of space-times whose causal structure, topological and differentiable structure can be reconstructed from their spaces of light rays and skies. These results can be understood as a Malament–Hawking-like theorem stated in terms of the partial order defined on the space of skies. (paper)

A quantum probability model of causal reasoning

Directory of Open Access Journals (Sweden)

Jennifer S Trueblood

2012-05-01

Full Text Available People can often outperform statistical methods and machine learning algorithms in situations that involve making inferences about the relationship between causes and effects. While people are remarkably good at causal reasoning in many situations, there are several instances where they deviate from expected responses. This paper examines three situations where judgments related to causal inference problems produce unexpected results and describes a quantum inference model based on the axiomatic principles of quantum probability theory that can explain these effects. Two of the three phenomena arise from the comparison of predictive judgments (i.e., the conditional probability of an effect given a cause with diagnostic judgments (i.e., the conditional probability of a cause given an effect. The third phenomenon is a new finding examining order effects in predictive causal judgments. The quantum inference model uses the notion of incompatibility among different causes to account for all three phenomena. Psychologically, the model assumes that individuals adopt different points of view when thinking about different causes. The model provides good fits to the data and offers a coherent account for all three causal reasoning effects thus proving to be a viable new candidate for modeling human judgment.

Scalar field Green functions on causal sets

International Nuclear Information System (INIS)

Nomaan Ahmed, S; Surya, Sumati; Dowker, Fay

2017-01-01

We examine the validity and scope of Johnston’s models for scalar field retarded Green functions on causal sets in 2 and 4 dimensions. As in the continuum, the massive Green function can be obtained from the massless one, and hence the key task in causal set theory is to first identify the massless Green function. We propose that the 2d model provides a Green function for the massive scalar field on causal sets approximated by any topologically trivial 2-dimensional spacetime. We explicitly demonstrate that this is indeed the case in a Riemann normal neighbourhood. In 4d the model can again be used to provide a Green function for the massive scalar field in a Riemann normal neighbourhood which we compare to Bunch and Parker’s continuum Green function. We find that the same prescription can also be used for de Sitter spacetime and the conformally flat patch of anti-de Sitter spacetime. Our analysis then allows us to suggest a generalisation of Johnston’s model for the Green function for a causal set approximated by 3-dimensional flat spacetime. (paper)

Causal Scale of Rotors in a Cardiac System

Science.gov (United States)

Ashikaga, Hiroshi; Prieto-Castrillo, Francisco; Kawakatsu, Mari; Dehghani, Nima

2018-04-01

Rotors of spiral waves are thought to be one of the potential mechanisms that maintain atrial fibrillation (AF). However, disappointing clinical outcomes of rotor mapping and ablation to eliminate AF raise a serious doubt on rotors as a macro-scale mechanism that causes the micro-scale behavior of individual cardiomyocytes to maintain spiral waves. In this study, we aimed to elucidate the causal relationship between rotors and spiral waves in a numerical model of cardiac excitation. To accomplish the aim, we described the system in a series of spatiotemporal scales by generating a renormalization group, and evaluated the causal architecture of the system by quantifying causal emergence. Causal emergence is an information-theoretic metric that quantifies emergence or reduction between micro- and macro-scale behaviors of a system by evaluating effective information at each scale. We found that the cardiac system with rotors has a spatiotemporal scale at which effective information peaks. A positive correlation between the number of rotors and causal emergence was observed only up to the scale of peak causation. We conclude that rotors are not the universal mechanism to maintain spiral waves at all spatiotemporal scales. This finding may account for the conflicting benefit of rotor ablation in clinical studies.

Norms and customs: causally important or causally impotent?

Science.gov (United States)

Jones, Todd

2010-01-01

In this article, I argue that norms and customs, despite frequently being described as being causes of behavior in the social sciences and ordinary conversation, cannot really cause behavior. Terms like "norms" and the like seem to refer to philosophically disreputable disjunctive properties. More problematically, even if they do not, or even if there can be disjunctive properties after all, I argue that norms and customs still cannot cause behavior. The social sciences would be better off without referring to properties like norms and customs as if they could be causal.

Optimization of a dynamic uncertain causality graph for fault diagnosis in nuclear power plant

Institute of Scientific and Technical Information of China (English)

Yue Zhao; Francesco Di Maio; Enrico Zio; Qin Zhang; Chun-Ling Dong; Jin-Ying Zhang

2017-01-01

Fault diagnostics is important for safe operation of nuclear power plants (NPPs).In recent years,data-driven approaches have been proposed and implemented to tackle the problem,e.g.,neural networks,fuzzy and neurofuzzy approaches,support vector machine,K-nearest neighbor classifiers and inference methodologies.Among these methods,dynamic uncertain causality graph (DUCG)has been proved effective in many practical cases.However,the causal graph construction behind the DUCG is complicate and,in many cases,results redundant on the symptoms needed to correctly classify the fault.In this paper,we propose a method to simplify causal graph construction in an automatic way.The method consists in transforming the expert knowledge-based DCUG into a fuzzy decision tree (FDT) by extracting from the DUCG a fuzzy rule base that resumes the used symptoms at the basis of the FDT.Genetic algorithm (GA) is,then,used for the optimization of the FDT,by performing a wrapper search around the FDT:the set of symptoms selected during the iterative search are taken as the best set of symptoms for the diagnosis of the faults that can occur in the system.The effectiveness of the approach is shown with respect to a DUCG model initially built to diagnose 23 faults originally using 262 symptoms of Unit-1 in the Ningde NPP of the China Guangdong Nuclear Power Corporation.The results show that the FDT,with GA-optimized symptoms and diagnosis strategy,can drive the construction of DUCG and lower the computational burden without loss of accuracy in diagnosis.

Optimization of a dynamic uncertain causality graph for fault diagnosis in nuclear power plant

Institute of Scientific and Technical Information of China (English)

Yue Zhao; Francesco Di Maio; Enrico Zio; Qin Zhang; Chun-Ling Dong; Jin-Ying Zhang

2017-01-01

Fault diagnostics is important for safe operation of nuclear power plants (NPPs).In recent years,data-driven approaches have been proposed and implemented to tackle the problem,e.g.,neural networks,fuzzy and neurofuzzy approaches,support vector machine,K-nearest neighbor classifiers and inference methodologies.Among these methods,dynamic uncertain causality graph (DUCG) has been proved effective in many practical cases.However,the causal graph construction behind the DUCG is complicate and,in many cases,results redundant on the symptoms needed to correctly classify the fault.In this paper,we propose a method to simplify causal graph construction in an automatic way.The method consists in transforming the expert knowledge-based DCUG into a fuzzy decision tree (FDT) by extracting from the DUCG a fuzzy rule base that resumes the used symptoms at the basis of the FDT.Genetic algorithm (GA) is,then,used for the optimization of the FDT,by performing a wrapper search around the FDT:the set of symptoms selected during the iterative search are taken as the best set of symptoms for the diagnosis of the faults that can occur in the system.The effectiveness of the approach is shown with respect to a DUCG model initially built to diagnose 23 faults originally using 262 symptoms of Unit-1 in the Ningde NPP of the China Guangdong Nuclear Power Corporation.The results show that the FDT,with GA-optimized symptoms and diagnosis strategy,can drive the construction of DUCG and lower the computational burden without loss of accuracy in diagnosis.

Causal reasoning and models of cognitive tasks for naval nuclear power plant operators; Raisonnement causal et modelisation de l`activite cognitive d`operateurs de chaufferie nucleaire navale

Energy Technology Data Exchange (ETDEWEB)

Salazar-Ferrer, P

1995-06-01

In complex industrial process control, causal reasoning appears as a major component in operators` cognitive tasks. It is tightly linked to diagnosis, prediction of normal and failure states, and explanation. This work provides a detailed review of literature in causal reasoning. A synthesis is proposed as a model of causal reasoning in process control. This model integrates distinct approaches in Cognitive Science: especially qualitative physics, Bayesian networks, knowledge-based systems, and cognitive psychology. Our model defines a framework for the analysis of causal human errors in simulated naval nuclear power plant fault management. Through the methodological framework of critical incident analysis we define a classification of errors and difficulties linked to causal reasoning. This classification is based on shallow characteristics of causal reasoning. As an origin of these errors, more elementary component activities in causal reasoning are identified. The applications cover the field of functional specification for man-machine interfaces, operators support systems design as well as nuclear safety. In addition of this study, we integrate the model of causal reasoning in a model of cognitive task in process control. (authors). 106 refs., 49 figs., 8 tabs.

Genetically determined angiotensin converting enzyme level and myocardial tolerance to ischemia

OpenAIRE

Messadi, Erij; Vincent, Marie-Pascale; Griol-Charhbili, Violaine; Mandet, Chantal; Colucci, Juliana; Krege, John H.; Bruneval, Patrick; Bouby, Nadine; Smithies, Oliver; Alhenc-Gelas, François; Richer, Christine

2010-01-01

Angiotensin I-converting enzyme (ACE; kininase II) levels in humans are genetically determined. ACE levels have been linked to risk of myocardial infarction, but the association has been inconsistent, and the causality underlying it remains undocumented. We tested the hypothesis that genetic variation in ACE levels influences myocardial tolerance to ischemia. We studied ischemia-reperfusion injury in mice bearing 1 (ACE1c), 2 (ACE2c, wild type), or 3 (ACE3c) functional copies of the ACE gene ...

BioCause: Annotating and analysing causality in the biomedical domain.

Science.gov (United States)

Mihăilă, Claudiu; Ohta, Tomoko; Pyysalo, Sampo; Ananiadou, Sophia

2013-01-16

Biomedical corpora annotated with event-level information represent an important resource for domain-specific information extraction (IE) systems. However, bio-event annotation alone cannot cater for all the needs of biologists. Unlike work on relation and event extraction, most of which focusses on specific events and named entities, we aim to build a comprehensive resource, covering all statements of causal association present in discourse. Causality lies at the heart of biomedical knowledge, such as diagnosis, pathology or systems biology, and, thus, automatic causality recognition can greatly reduce the human workload by suggesting possible causal connections and aiding in the curation of pathway models. A biomedical text corpus annotated with such relations is, hence, crucial for developing and evaluating biomedical text mining. We have defined an annotation scheme for enriching biomedical domain corpora with causality relations. This schema has subsequently been used to annotate 851 causal relations to form BioCause, a collection of 19 open-access full-text biomedical journal articles belonging to the subdomain of infectious diseases. These documents have been pre-annotated with named entity and event information in the context of previous shared tasks. We report an inter-annotator agreement rate of over 60% for triggers and of over 80% for arguments using an exact match constraint. These increase significantly using a relaxed match setting. Moreover, we analyse and describe the causality relations in BioCause from various points of view. This information can then be leveraged for the training of automatic causality detection systems. Augmenting named entity and event annotations with information about causal discourse relations could benefit the development of more sophisticated IE systems. These will further influence the development of multiple tasks, such as enabling textual inference to detect entailments, discovering new facts and providing new

Theories of conduct disorder: a causal modelling analysis

NARCIS (Netherlands)

Krol, N.P.C.M.; Morton, J.; Bruyn, E.E.J. De

2004-01-01

Background: If a clinician has to make decisions on diagnosis and treatment, he or she is confronted with a variety of causal theories. In order to compare these theories a neutral terminology and notational system is needed. The Causal Modelling framework involving three levels of description –

Quasi-causal associations of physical activity and neighborhood walkability with body mass index: a twin study.

Science.gov (United States)

Duncan, Glen E; Cash, Stephanie Whisnant; Horn, Erin E; Turkheimer, Eric

2015-01-01

Physical activity, neighborhood walkability, and body mass index (BMI, kg/m(2)) associations were tested using quasi-experimental twin methods. We hypothesized that physical activity and walkability were independently associated with BMI within twin pairs, controlling for genetic and environmental background shared between them. Data were from 6376 (64% female; 58% identical) same-sex pairs, University of Washington Twin Registry, 2008-2013. Neighborhood walking, moderate-to-vigorous physical activity (MVPA), and BMI were self-reported. Residential address was used to calculate walkability. Phenotypic (non-genetically informed) and biometric (genetically informed) regression was employed, controlling for age, sex, and race. Walking and MVPA were associated with BMI in phenotypic analyses; associations were attenuated but significant in biometric analyses (PsWalkability was not associated with BMI, however, was associated with walking (but not MVPA) in both phenotypic and biometric analyses (Pswalkability is not associated with BMI, it is associated with neighborhood walking (but not MVPA) accounting for shared background, suggesting a causal relationship between them. Copyright © 2014 Elsevier Inc. All rights reserved.

Violation of causality in f(T) gravity

Energy Technology Data Exchange (ETDEWEB)

Otalora, G. [Pontificia Universidad Catolica de Valparaiso, Instituto de Fisica, Valparaiso (Chile); Reboucas, M.J. [Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, RJ (Brazil)

2017-11-15

In the standard formulation, the f(T) field equations are not invariant under local Lorentz transformations, and thus the theory does not inherit the causal structure of special relativity. Actually, even locally violation of causality can occur in this formulation of f(T) gravity. A locally Lorentz covariant f(T) gravity theory has been devised recently, and this local causality problem seems to have been overcome. The non-locality question, however, is left open. If gravitation is to be described by this covariant f(T) gravity theory there are a number of issues that ought to be examined in its context, including the question as to whether its field equations allow homogeneous Goedel-type solutions, which necessarily leads to violation of causality on non-local scale. Here, to look into the potentialities and difficulties of the covariant f(T) theories, we examine whether they admit Goedel-type solutions. We take a combination of a perfect fluid with electromagnetic plus a scalar field as source, and determine a general Goedel-type solution, which contains special solutions in which the essential parameter of Goedel-type geometries, m{sup 2}, defines any class of homogeneous Goedel-type geometries. We show that solutions of the trigonometric and linear classes (m{sup 2} < 0 and m = 0) are permitted only for the combined matter sources with an electromagnetic field matter component. We extended to the context of covariant f(T) gravity a theorem which ensures that any perfect-fluid homogeneous Goedel-type solution defines the same set of Goedel tetrads h{sub A}{sup μ} up to a Lorentz transformation. We also showed that the single massless scalar field generates Goedel-type solution with no closed time-like curves. Even though the covariant f(T) gravity restores Lorentz covariance of the field equations and the local validity of the causality principle, the bare existence of the Goedel-type solutions makes apparent that the covariant formulation of f(T) gravity