Causal Indicators Can Help to Interpret Factors

ERIC Educational Resources Information Center

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)…

Are Hill's criteria for causality satisfied for vitamin D and periodontal disease?

PubMed

Grant, William B; Boucher, Barbara J

2010-01-01

There is mounting evidence that periodontal disease (PD) is linked to low serum 25-hydroxyvitamin D [25(OH)D] concentrations in addition to recognized risk factors like diet and smoking. This paper reviews this evidence using Hill's criteria for causality in a biological system. Evidence for strength of association, consistency, cohesion and 'dose-effects' [biological 'gradients'] include strong inverse correlations between serum 25(OH) and PD cross-sectionally and that PD is consistently more prevalent in darker vs. lighter skinned people and increases at higher latitudes with analogy for gingivitis and for disorders associated with PD whose risks also increase with hypovitaminosis D. Evidence for plausibility includes that vitamin D increases calcium absorption and protects bone strength; induces formation of cathelicidin and other defensins that combat bacterial infection; reduces tissue production of destructive matrix metalloproteinases actively associated with PD and that prevalence of PD varies with common vitamin D receptor polymorphisms. Experimental evidence from limited supplementation studies [using calcium and vitamin D] shows that supplementation reduces tooth loss. Thus, existing evidence for hypovitaminosis D as a risk factor for PD to date meets Hill's criteria for causality in a biological system. Further experimental evidence for effectiveness and temporality, preferably from randomized controlled trials of vitamin D supplementation [adjusting for other PD risk factors including diet and smoking to reduce confounding] are necessary to confirm causality. If confirmed, dentists and periodontists could perform a valuable service to their patients by discussing the importance of adequate vitamin D status and how to avoid deficiency.

Are Hill's criteria for causality satisfied for vitamin D and periodontal disease?

PubMed Central

Boucher, Barbara J

2010-01-01

There is mounting evidence that periodontal disease (PD) is linked to low serum 25-hydroxyvitamin D [25(OH)D] concentrations in addition to recognized risk factors like diet and smoking. This paper reviews this evidence using Hill's criteria for causality in a biological system. Evidence for strength of association, consistency, cohesion and ‘dose-effects’ [biological ‘gradients’] include strong inverse correlations between serum 25(OH) and PD cross-sectionally and that PD is consistently more prevalent in darker vs. lighter skinned people and increases at higher latitudes with analogy for gingivitis and for disorders associated with PD whose risks also increase with hypovitaminosis D. Evidence for plausibility includes that vitamin D increases calcium absorption and protects bone strength; induces formation of cathelicidin and other defensins that combat bacterial infection; reduces tissue production of destructive matrix metalloproteinases actively associated with PD and that prevalence of PD varies with common vitamin D receptor polymorphisms. Experimental evidence from limited supplementation studies [using calcium and vitamin D] shows that supplementation reduces tooth loss. Thus, existing evidence for hypovitaminosis D as a risk factor for PD to date meets Hill's criteria for causality in a biological system. Further experimental evidence for effectiveness and temporality, preferably from randomized controlled trials of vitamin D supplementation [adjusting for other PD risk factors including diet and smoking to reduce confounding] are necessary to confirm causality. If confirmed, dentists and periodontists could perform a valuable service to their patients by discussing the importance of adequate vitamin D status and how to avoid deficiency. PMID:21547146

Human error and commercial aviation accidents: an analysis using the human factors analysis and classification system.

PubMed

Shappell, Scott; Detwiler, Cristy; Holcomb, Kali; Hackworth, Carla; Boquet, Albert; Wiegmann, Douglas A

2007-04-01

The aim of this study was to extend previous examinations of aviation accidents to include specific aircrew, environmental, supervisory, and organizational factors associated with two types of commercial aviation (air carrier and commuter/ on-demand) accidents using the Human Factors Analysis and Classification System (HFACS). HFACS is a theoretically based tool for investigating and analyzing human error associated with accidents and incidents. Previous research has shown that HFACS can be reliably used to identify human factors trends associated with military and general aviation accidents. Using data obtained from both the National Transportation Safety Board and the Federal Aviation Administration, 6 pilot-raters classified aircrew, supervisory, organizational, and environmental causal factors associated with 1020 commercial aviation accidents that occurred over a 13-year period. The majority of accident causal factors were attributed to aircrew and the environment, with decidedly fewer associated with supervisory and organizational causes. Comparisons were made between HFACS causal categories and traditional situational variables such as visual conditions, injury severity, and regional differences. These data will provide support for the continuation, modification, and/or development of interventions aimed at commercial aviation safety. HFACS provides a tool for assessing human factors associated with accidents and incidents.

Aircraft Loss-of-Control Accident Analysis

NASA Technical Reports Server (NTRS)

Belcastro, Christine M.; Foster, John V.

2010-01-01

Loss of control remains one of the largest contributors to fatal aircraft accidents worldwide. Aircraft loss-of-control accidents are complex in that they can result from numerous causal and contributing factors acting alone or (more often) in combination. Hence, there is no single intervention strategy to prevent these accidents. To gain a better understanding into aircraft loss-of-control events and possible intervention strategies, this paper presents a detailed analysis of loss-of-control accident data (predominantly from Part 121), including worst case combinations of causal and contributing factors and their sequencing. Future potential risks are also considered.

[Exploration of influencing factors of price of herbal based on VAR model].

PubMed

Wang, Nuo; Liu, Shu-Zhen; Yang, Guang

2014-10-01

Based on vector auto-regression (VAR) model, this paper takes advantage of Granger causality test, variance decomposition and impulse response analysis techniques to carry out a comprehensive study of the factors influencing the price of Chinese herbal, including herbal cultivation costs, acreage, natural disasters, the residents' needs and inflation. The study found that there is Granger causality relationship between inflation and herbal prices, cultivation costs and herbal prices. And in the total variance analysis of Chinese herbal and medicine price index, the largest contribution to it is from its own fluctuations, followed by the cultivation costs and inflation.

A review of covariate selection for non-experimental comparative effectiveness research.

PubMed

Sauer, Brian C; Brookhart, M Alan; Roy, Jason; VanderWeele, Tyler

2013-11-01

This paper addresses strategies for selecting variables for adjustment in non-experimental comparative effectiveness research and uses causal graphs to illustrate the causal network that relates treatment to outcome. Variables in the causal network take on multiple structural forms. Adjustment for a common cause pathway between treatment and outcome can remove confounding, whereas adjustment for other structural types may increase bias. For this reason, variable selection would ideally be based on an understanding of the causal network; however, the true causal network is rarely known. Therefore, we describe more practical variable selection approaches based on background knowledge when the causal structure is only partially known. These approaches include adjustment for all observed pretreatment variables thought to have some connection to the outcome, all known risk factors for the outcome, and all direct causes of the treatment or the outcome. Empirical approaches, such as forward and backward selection and automatic high-dimensional proxy adjustment, are also discussed. As there is a continuum between knowing and not knowing the causal, structural relations of variables, we recommend addressing variable selection in a practical way that involves a combination of background knowledge and empirical selection and that uses high-dimensional approaches. This empirical approach can be used to select from a set of a priori variables based on the researcher's knowledge to be included in the final analysis or to identify additional variables for consideration. This more limited use of empirically derived variables may reduce confounding while simultaneously reducing the risk of including variables that may increase bias. Copyright © 2013 John Wiley & Sons, Ltd.

A Review of Covariate Selection for Nonexperimental Comparative Effectiveness Research

PubMed Central

Sauer, Brian C.; Brookhart, Alan; Roy, Jason; Vanderweele, Tyler

2014-01-01

This paper addresses strategies for selecting variables for adjustment in non-experimental comparative effectiveness research (CER), and uses causal graphs to illustrate the causal network that relates treatment to outcome. Variables in the causal network take on multiple structural forms. Adjustment for on a common cause pathway between treatment and outcome can remove confounding, while adjustment for other structural types may increase bias. For this reason variable selection would ideally be based on an understanding of the causal network; however, the true causal network is rarely know. Therefore, we describe more practical variable selection approaches based on background knowledge when the causal structure is only partially known. These approaches include adjustment for all observed pretreatment variables thought to have some connection to the outcome, all known risk factors for the outcome, and all direct causes of the treatment or the outcome. Empirical approaches, such as forward and backward selection and automatic high-dimensional proxy adjustment, are also discussed. As there is a continuum between knowing and not knowing the causal, structural relations of variables, we recommend addressing variable selection in a practical way that involves a combination of background knowledge and empirical selection and that uses the high-dimensional approaches. This empirical approach can be used to select from a set of a priori variables based on the researcher’s knowledge to be included in the final analysis or to identify additional variables for consideration. This more limited use of empirically-derived variables may reduce confounding while simultaneously reducing the risk of including variables that may increase bias. PMID:24006330

Mendelian randomisation in type 2 diabetes and coronary artery disease.

PubMed

Frayling, Timothy M; Stoneman, Charli E

2018-06-20

Type 2 diabetes, coronary artery disease and hypertension are associated with anthropometric and biomarker traits, including waist-to-hip-ratio, body mass index and altered glucose and insulin levels. Clinical trials, for example of weight-loss interventions, show these factors are causal, but lifelong impact of subtle changes in body mass index and body fat distribution are less clear. The use of human genetics can quantify the causal effects of long-term exposure to subtle changes of modifiable risk factors. Mendelian randomisation (MR) uses human genetic variants associated with the risk factor to quantify the relationship between risk factor and disease outcome. The last two years have seen an increase in the number of MR studies investigating the relationship between anthropometric traits and metabolic diseases. This review provides an overview of these recent MR studies in relation to type 2 diabetes, coronary artery disease and hypertension. MR provides evidence for causal associations of waist-to-hip-ratio, body mass index and altered glucose levels with type 2 diabetes, coronary artery disease and hypertension. Crown Copyright © 2018. Published by Elsevier Ltd. All rights reserved.

What causes breast cancer? A systematic review of causal attributions among breast cancer survivors and how these compare to expert-endorsed risk factors.

PubMed

Dumalaon-Canaria, Jo Anne; Hutchinson, Amanda D; Prichard, Ivanka; Wilson, Carlene

2014-07-01

The aim of this paper was to review published research that analyzed causal attributions for breast cancer among women previously diagnosed with breast cancer. These attributions were compared with risk factors identified by published scientific evidence in order to determine the level of agreement between cancer survivors' attributions and expert opinion. A comprehensive search for articles, published between 1982 and 2012, reporting studies on causal attributions for breast cancer among patients and survivors was undertaken. Of 5,135 potentially relevant articles, 22 studies met the inclusion criteria. Two additional articles were sourced from reference lists of included studies. Results indicated a consistent belief among survivors that their own breast cancer could be attributed to family history, environmental factors, stress, fate, or chance. Lifestyle factors were less frequently identified, despite expert health information highlighting the importance of these factors in controlling and modifying cancer risk. This review demonstrated that misperceptions about the contribution of modifiable lifestyle factors to the risk of breast cancer have remained largely unchanged over the past 30 years. The findings of this review indicate that beliefs about the causes of breast cancer among affected women are not always consistent with the judgement of experts. Breast cancer survivors did not regularly identify causal factors supported by expert consensus such as age, physical inactivity, breast density, alcohol consumption, and reproductive history. Further research examining psychological predictors of attributions and the impact of cancer prevention messages on adjustment and well-being of cancer survivors is warranted.

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

PubMed Central

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

Modelling runway incursion severity.

PubMed

Wilke, Sabine; Majumdar, Arnab; Ochieng, Washington Y

2015-06-01

Analysis of the causes underlying runway incursions is fundamental for the development of effective mitigation measures. However, there are significant weaknesses in the current methods to model these factors. This paper proposes a structured framework for modelling causal factors and their relationship to severity, which includes a description of the airport surface system architecture, establishment of terminological definitions, the determination and collection of appropriate data, the analysis of occurrences for severity and causes, and the execution of a statistical analysis framework. It is implemented in the context of U.S. airports, enabling the identification of a number of priority interventions, including the need for better investigation and causal factor capture, recommendations for airfield design, operating scenarios and technologies, and better training for human operators in the system. The framework is recommended for the analysis of runway incursions to support safety improvements and the methodology is transferable to other areas of aviation safety risk analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Interactions among poverty, gender, and health systems affect women's participation in services to prevent HIV transmission from mother to child: A causal loop analysis.

PubMed

Yourkavitch, Jennifer; Hassmiller Lich, Kristen; Flax, Valerie L; Okello, Elialilia S; Kadzandira, John; Katahoire, Anne Ruhweza; Munthali, Alister C; Thomas, James C

2018-01-01

Retention in care remains an important issue for prevention of mother-to-child transmission (PMTCT) programs according to WHO guidelines, formerly called the "Option B+" approach. The objective of this study was to examine how poverty, gender, and health system factors interact to influence women's participation in PMTCT services. We used qualitative research, literature, and hypothesized variable connections to diagram causes and effects in causal loop models. We found that many factors, including antiretroviral therapy (ART) use, service design and quality, stigma, disclosure, spouse/partner influence, decision-making autonomy, and knowledge about PMTCT, influence psychosocial health, which in turn affects women's participation in PMTCT services. Thus, interventions to improve psychosocial health need to address many factors to be successful. We also found that the design of PMTCT services, a modifiable factor, is important because it affects several other factors. We identified 66 feedback loops that may contribute to policy resistance-that is, a policy's failure to have its intended effect. Our findings point to the need for a multipronged intervention to encourage women's continued participation in PMTCT services and for longitudinal research to quantify and test our causal loop model.

Evaluation of near-miss and adverse events in radiation oncology using a comprehensive causal factor taxonomy.

PubMed

Spraker, Matthew B; Fain, Robert; Gopan, Olga; Zeng, Jing; Nyflot, Matthew; Jordan, Loucille; Kane, Gabrielle; Ford, Eric

Incident learning systems (ILSs) are a popular strategy for improving safety in radiation oncology (RO) clinics, but few reports focus on the causes of errors in RO. The goal of this study was to test a causal factor taxonomy developed in 2012 by the American Association of Physicists in Medicine and adopted for use in the RO: Incident Learning System (RO-ILS). Three hundred event reports were randomly selected from an institutional ILS database and Safety in Radiation Oncology (SAFRON), an international ILS. The reports were split into 3 groups of 100 events each: low-risk institutional, high-risk institutional, and SAFRON. Three raters retrospectively analyzed each event for contributing factors using the American Association of Physicists in Medicine taxonomy. No events were described by a single causal factor (median, 7). The causal factor taxonomy was found to be applicable for all events, but 4 causal factors were not described in the taxonomy: linear accelerator failure (n = 3), hardware/equipment failure (n = 2), failure to follow through with a quality improvement intervention (n = 1), and workflow documentation was misleading (n = 1). The most common causal factor categories contributing to events were similar in all event types. The most common specific causal factor to contribute to events was a "slip causing physical error." Poor human factors engineering was the only causal factor found to contribute more frequently to high-risk institutional versus low-risk institutional events. The taxonomy in the study was found to be applicable for all events and may be useful in root cause analyses and future studies. Communication and human behaviors were the most common errors affecting all types of events. Poor human factors engineering was found to specifically contribute to high-risk more than low-risk institutional events, and may represent a strategy for reducing errors in all types of events. Copyright © 2017 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

SU-E-P-07: Retrospective Analysis of Incident Reports at a Radiology Department: Feedback From Incident Reporting System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kakinohana, Y; Toita, T; Heianna, J

Purpose: To provide an overview of reported incidents that occurred in a radiology department and to describe the most common causal source of incidents. Methods: Incident reports from the radiology department at the University of the Ryukyus Hospital between 2008 and 2013 were collected and analyzed retrospectively. The incident report form contains the following items, causal factors of the incident and desirable corrective actions to prevent recurrence of similar incidents. These items allow the institution to investigate/analyze root causes of the incidents and suggest measures to be taken to prevent further, similar incidents. The ‘causal factors of the incident’ itemmore » comprises multiple selections from among 24 selections and includes some synonymous selections. In this study, this item was re-categorized into four causal source types: (i) carelessness, (ii) lack of skill or knowledge, (iii) deficiencies in communication, and (iv) external factors. Results: There were a total of 7490 incident reports over the study period and 276 (3.7%) were identified as originating from the radiology department. The most frequent causal source type was carelessness (62%). The other three types showed similar frequencies (10–14%). The staff members involved in incidents indicate three predominant desirable corrective actions to prevent or decrease the recurrence of similar incidents. These are ‘improvement in communication’ (24%), ‘staff training/education’ (19%), and ‘daily medical procedures’ (22%), and the most frequent was ‘improvement in communication’. Even though the most frequent causal factor was related to carelessness, the most desirable corrective action indicated by the staff members was related to communication. Conclusion: Our finding suggests that the most immediate causes are strongly related to carelessness. However, the most likely underlying causes of incidents would be related to deficiencies in effective communication. At our department, therefore, the primary action to prevent/reduce similar incidents should be ‘communication improvement’.« less

[A study of relation between hopelessness and causal attribution in school-aged children].

PubMed

Sakurai, S

1989-12-01

This study was conducted to investigate the relation between hopelessness and causal attribution in Japanese school-aged children. In Study 1, the Japanese edition of hopelessness scale for children developed by Kazdin, French, Unis, Esveldt-Dawsan, and Sherick (1983) was constructed. Seventeen original items were translated into Japanese and they were administrated to 405 fifth- and sixth-graders. All of the items could be included to the Japanese edition of hopelessness scale. The reliability and validity was examined. In Study 2, the relation between hopelessness and causal attribution in children were investigated. The causal attribution questionnaire developed by Higuchi, Kambare, and Otsuka (1983) and the hopelessness scale developed by Study 1 were administered to 188 sixth-graders. Children with high scores in hopelessness scale significantly attributed negative events to much more effort factor than children with low scores. It supports neither the reformulated learned helplessness model nor the causal attribution theory of achievement motivation. It was explained mainly from points of self-serving attribution, cultural difference, and social desirability. Some questions were discussed for developing studies on depression and causal attribution in Japan.

Therapists' causal attributions of clients' problems and selection of intervention strategies.

PubMed

Royce, W S; Muehlke, C V

1991-04-01

Therapists' choices of intervention strategies are influenced by many factors, including judgments about the bases of clients' problems. To assess the relationships between such causal attributions and the selection of intervention strategies, 196 counselors, psychologists, and social workers responded to the written transcript of a client's interview by answering two questionnaires, a 1982 scale (Causal Dimension Scale by Russell) which measured causal attribution of the client's problem, and another which measured preference for emotional, rational, and active intervention strategies in dealing with the client, based on the 1979 E-R-A taxonomy of Frey and Raming. A significant relationship was found between the two sets of variables, with internal attributions linked to rational intervention strategies and stable attributions linked to active strategies. The results support Halleck's 1978 hypothesis that theories of psychotherapy tie interventions to etiological considerations.

Causality in cancer research: a journey through models in molecular epidemiology and their philosophical interpretation.

PubMed

Vineis, Paolo; Illari, Phyllis; Russo, Federica

2017-01-01

In the last decades, Systems Biology (including cancer research) has been driven by technology, statistical modelling and bioinformatics. In this paper we try to bring biological and philosophical thinking back. We thus aim at making different traditions of thought compatible: (a) causality in epidemiology and in philosophical theorizing-notably, the "sufficient-component-cause framework" and the "mark transmission" approach; (b) new acquisitions about disease pathogenesis, e.g. the "branched model" in cancer, and the role of biomarkers in this process; (c) the burgeoning of omics research, with a large number of "signals" and of associations that need to be interpreted. In the paper we summarize first the current views on carcinogenesis, and then explore the relevance of current philosophical interpretations of "cancer causes". We try to offer a unifying framework to incorporate biomarkers and omic data into causal models, referring to a position called "evidential pluralism". According to this view, causal reasoning is based on both "evidence of difference-making" (e.g. associations) and on "evidence of underlying biological mechanisms". We conceptualize the way scientists detect and trace signals in terms of information transmission , which is a generalization of the mark transmission theory developed by philosopher Wesley Salmon. Our approach is capable of helping us conceptualize how heterogeneous factors such as micro and macro-biological and psycho-social-are causally linked. This is important not only to understand cancer etiology, but also to design public health policies that target the right causal factors at the macro-level.

Tumor Secreted Autocrine Motility Factor (AMF): Causal Role in an Animal Model of Cachexia

DTIC Science & Technology

2005-08-01

AD Award Number: DAMD17-02-1-0586 TITLE: Tumor Secreted Autocrine Motility Factor ( AMF ): Causal Role in an Animal Model of Cachexia PRINCIPAL...5a. CONTRACT NUMBER Tumor Secreted Autocrine Motility Factor ( AMF ): Causal Role in an Animal Model of Cachexia 5b. GRANT NUMBER DAM D1 7-02-1-0586 5c...quality of life and postpone mortality. We proposed that autocrine motility factor ( AMF ) is released into the bloodstream from cancer sites and

Examination of Icing Induced Loss of Control and Its Mitigations

NASA Technical Reports Server (NTRS)

Reehorst, Andrew L.; Addy, Harold E., Jr.; Colantonio, Renato O.

2010-01-01

Factors external to the aircraft are often a significant causal factor in loss of control (LOC) accidents. In today s aviation world, very few accidents stem from a single cause and typically have a number of causal factors that culminate in a LOC accident. Very often the "trigger" that initiates an accident sequence is an external environment factor. In a recent NASA statistical analysis of LOC accidents, aircraft icing was shown to be the most common external environmental LOC causal factor for scheduled operations. When investigating LOC accident or incidents aircraft icing causal factors can be categorized into groups of 1) in-flight encounter with super-cooled liquid water clouds, 2) take-off with ice contamination, or 3) in-flight encounter with high concentrations of ice crystals. As with other flight hazards, icing induced LOC accidents can be prevented through avoidance, detection, and recovery mitigations. For icing hazards, avoidance can take the form of avoiding flight into icing conditions or avoiding the hazard of icing by making the aircraft tolerant to icing conditions. Icing detection mitigations can take the form of detecting icing conditions or detecting early performance degradation caused by icing. Recovery from icing induced LOC requires flight crew or automated systems capable of accounting for reduced aircraft performance and degraded control authority during the recovery maneuvers. In this report we review the icing induced LOC accident mitigations defined in a recent LOC study and for each mitigation describe a research topic required to enable or strengthen the mitigation. Many of these research topics are already included in ongoing or planned NASA icing research activities or are being addressed by members of the icing research community. These research activities are described and the status of the ongoing or planned research to address the technology needs is discussed

Applying causal mediation analysis to personality disorder research.

PubMed

Walters, Glenn D

2018-01-01

This article is designed to address fundamental issues in the application of causal mediation analysis to research on personality disorders. Causal mediation analysis is used to identify mechanisms of effect by testing variables as putative links between the independent and dependent variables. As such, it would appear to have relevance to personality disorder research. It is argued that proper implementation of causal mediation analysis requires that investigators take several factors into account. These factors are discussed under 5 headings: variable selection, model specification, significance evaluation, effect size estimation, and sensitivity testing. First, care must be taken when selecting the independent, dependent, mediator, and control variables for a mediation analysis. Some variables make better mediators than others and all variables should be based on reasonably reliable indicators. Second, the mediation model needs to be properly specified. This requires that the data for the analysis be prospectively or historically ordered and possess proper causal direction. Third, it is imperative that the significance of the identified pathways be established, preferably with a nonparametric bootstrap resampling approach. Fourth, effect size estimates should be computed or competing pathways compared. Finally, investigators employing the mediation method are advised to perform a sensitivity analysis. Additional topics covered in this article include parallel and serial multiple mediation designs, moderation, and the relationship between mediation and moderation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Academic Success Factors: An IT Student Perspective

ERIC Educational Resources Information Center

Zhang, Aimao; Aasheim, Cheryl L.

2011-01-01

Numerous studies have identified causal factors for academic success. Factors vary from personal factors, such as cognitive style (McKenzie & Schweitzer, 2001), to social factors, such as culture differences (Aysan, Tanriogen, & Tanriogen, 1996). However, in these studies it is re-searchers who theorized the causal dimensions and…

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

PubMed

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.

Identification of risk factors associated with onset and progression of amyotrophic lateral sclerosis using systematic review and meta-analysis.

PubMed

Wang, Ming-Dong; Little, Julian; Gomes, James; Cashman, Neil R; Krewski, Daniel

2017-07-01

Although amyotrophic lateral sclerosis (ALS) was identified as a neurological condition 150 years ago, risk factors related to the onset and progression of ALS remain largely unknown. Monogenic mutations in over 30 genes are associated with about 10% of ALS cases. The age at onset of ALS and disease types has been found to influence ALS progression. The present study was designed to identify additional putative risk factors associated with the onset and progression of ALS using systematic review and meta-analysis of observational studies. Risk factors that may be associated with ALS include: 1) genetic mutations, including the intermediate CAG repeat expansion in ATXN2; 2) previous exposure to heavy metals such as lead and mercury; 3) previous exposure to organic chemicals, such as pesticides and solvents; 4) history of electric shock; 5) history of physical trauma/injury (including head trauma/injury); 6) smoking (a weak risk factor for ALS in women); and 6) other risk factors, such as participating in professional sports, lower body mass index, lower educational attainment, or occupations requiring repetitive/strenuous work, military service, exposure to Beta-N-methylamino-l-alanin and viral infections. Risk factors that may be associated with ALS progression rate include: 1) nutritional status, including vitamin D deficiency; 2) comorbidities; 3) ethnicity and genetic factors; 4) lack of supportive care; and 4) smoking. The extent to which these associations may be causal is discussed, with further research recommended to strengthen the evidence on which determinations of causality may be based. Copyright © 2016. Published by Elsevier B.V.

A new approach to hierarchical data analysis: Targeted maximum likelihood estimation for the causal effect of a cluster-level exposure.

PubMed

Balzer, Laura B; Zheng, Wenjing; van der Laan, Mark J; Petersen, Maya L

2018-01-01

We often seek to estimate the impact of an exposure naturally occurring or randomly assigned at the cluster-level. For example, the literature on neighborhood determinants of health continues to grow. Likewise, community randomized trials are applied to learn about real-world implementation, sustainability, and population effects of interventions with proven individual-level efficacy. In these settings, individual-level outcomes are correlated due to shared cluster-level factors, including the exposure, as well as social or biological interactions between individuals. To flexibly and efficiently estimate the effect of a cluster-level exposure, we present two targeted maximum likelihood estimators (TMLEs). The first TMLE is developed under a non-parametric causal model, which allows for arbitrary interactions between individuals within a cluster. These interactions include direct transmission of the outcome (i.e. contagion) and influence of one individual's covariates on another's outcome (i.e. covariate interference). The second TMLE is developed under a causal sub-model assuming the cluster-level and individual-specific covariates are sufficient to control for confounding. Simulations compare the alternative estimators and illustrate the potential gains from pairing individual-level risk factors and outcomes during estimation, while avoiding unwarranted assumptions. Our results suggest that estimation under the sub-model can result in bias and misleading inference in an observational setting. Incorporating working assumptions during estimation is more robust than assuming they hold in the underlying causal model. We illustrate our approach with an application to HIV prevention and treatment.

Risk and protective factors for the development of childhood asthma.

PubMed

Ding, Guodong; Ji, Ruoxu; Bao, Yixiao

2015-03-01

Childhood asthma prevalence worldwide has been increasing markedly over several decades. Various theories have been proposed to account for this alarming trend. The disease has a broad spectrum of potential determinants ranging from genetics to lifestyle and environmental factors. Epidemiological observations have demonstrated that several important lifestyle and environmental factors including obesity, urban living, dietary patterns such as food low in antioxidants and fast food, non-breastfeeding, gut flora imbalance, cigarette smoking, air pollution, and viral infection are associated with asthma exacerbations in children. However, only environmental tobacco smoke has been associated with the development of asthma. Despite epidemiological studies indicating that many other factors are probably associated with the development of asthma, the relationships are not considered causal due to the inadequate evidence and inconsistent results from recent studies. This may highlight that sufficient data and exact mechanisms of causality are still in need of further study. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

PubMed

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 that shapes child development. Copyright © 2015 Elsevier Inc. All rights reserved.

Etiologic effects and optimal intakes of foods and nutrients for risk of cardiovascular diseases and diabetes: Systematic reviews and meta-analyses from the Nutrition and Chronic Diseases Expert Group (NutriCoDE)

PubMed Central

Peñalvo, Jose L.; Khatibzadeh, Shahab; Singh, Gitanjali M.; Rao, Mayuree; Fahimi, Saman; Powles, John; Mozaffarian, Dariush

2017-01-01

Background Dietary habits are major contributors to coronary heart disease, stroke, and diabetes. However, comprehensive evaluation of etiologic effects of dietary factors on cardiometabolic outcomes, their quantitative effects, and corresponding optimal intakes are not well-established. Objective To systematically review the evidence for effects of dietary factors on cardiometabolic diseases, including comprehensively assess evidence for causality; estimate magnitudes of etiologic effects; evaluate heterogeneity and potential for bias in these etiologic effects; and determine optimal population intake levels. Methods We utilized Bradford-Hill criteria to assess probable or convincing evidence for causal effects of multiple diet-cardiometabolic disease relationships. Etiologic effects were quantified from published or de novo meta-analyses of prospective studies or randomized clinical trials, incorporating standardized units, dose-response estimates, and heterogeneity by age and other characteristics. Potential for bias was assessed in validity analyses. Optimal intakes were determined by levels associated with lowest disease risk. Results We identified 10 foods and 7 nutrients with evidence for causal cardiometabolic effects, including protective effects of fruits, vegetables, beans/legumes, nuts/seeds, whole grains, fish, yogurt, fiber, seafood omega-3s, polyunsaturated fats, and potassium; and harms of unprocessed red meats, processed meats, sugar-sweetened beverages, glycemic load, trans-fats, and sodium. Proportional etiologic effects declined with age, but did not generally vary by sex. Established optimal population intakes were generally consistent with observed national intakes and major dietary guidelines. In validity analyses, the identified effects of individual dietary components were similar to quantified effects of dietary patterns on cardiovascular risk factors and hard endpoints. Conclusions These novel findings provide a comprehensive summary of causal evidence, quantitative etiologic effects, heterogeneity, and optimal intakes of major dietary factors for cardiometabolic diseases, informing disease impact estimation and policy planning and priorities. PMID:28448503

Why cachexia kills: examining the causality of poor outcomes in wasting conditions.

PubMed

Kalantar-Zadeh, Kamyar; Rhee, Connie; Sim, John J; Stenvinkel, Peter; Anker, Stefan D; Kovesdy, Csaba P

2013-06-01

Weight loss is the hallmark of any progressive acute or chronic disease state. In its extreme form of significant lean body mass (including skeletal muscle) and fat loss, it is referred to as cachexia. It has been known for millennia that muscle and fat wasting leads to poor outcomes including death. On one hand, conditions and risk factors that lead to cachexia and inadequate nutrition may independently lead to increased mortality. Additionaly, cachexia per se, withdrawal of nutritional support in progressive cachexia, and advanced age may lead to death via cachexia-specific pathways. Despite the strong and consistent association of cachexia with mortality, no unifying mechanism has yet been suggested as to why wasting conditions are associated with an exceptionally high mortality risk. Hence, the causality of the cachexia-death association, even though it is biologically plausible, is widely unknown. This century-long uncertainty may have played a role as to why the field of cachexia treatment development has not shown major advances over the past decades. We suggest that cachexia-associated relative thrombocytosis and platelet activation may play a causal role in cachexia-related death, while other mechanisms may also contribute including arrhythmia-associated sudden deaths, endocrine disorders such as hypothyroidism, and immune system compromise leading to infectious events and deaths. Multidimensional research including examining biologically plausible models is urgently needed to investigate the causality of the cachexia-death association.

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

PubMed

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.

The causality between smoking and lung cancer among groups and individuals: addressing issues in tobacco litigation in South Korea

PubMed Central

Khang, Young-Ho

2015-01-01

This article discusses issues on the causality between smoking and lung cancer, which have been raised during the tobacco litigation in South Korea. It should be recognized that the explanatory ability of risk factor(s) for inter-individual variations in disease occurrence is different from the causal contribution of the risk factor(s) to disease occurrence. The affected subjects of the tobacco litigation in South Korea are lung cancer patients with a history of cigarette smoking. Thus, the attributable fraction of the exposed rather than the population attributable fraction should be used in the tobacco litigation regarding the causal contribution of smoking to lung cancer. Scientific evidence for the causal relationship between smoking and lung cancer is based on studies of individuals and groups, studies in animals and humans, studies that are observational or experimental, studies in laboratories and communities, and studies in both underdeveloped and developed countries. The scientific evidence collected is applicable to both groups and individuals. The probability of causation, which is calculated based on the attributable fraction for the association between smoking and lung cancer, could be utilized as evidence to prove causality in individuals. PMID:26137845

The causality between smoking and lung cancer among groups and individuals: addressing issues in tobacco litigation in South Korea.

PubMed

Khang, Young-Ho

2015-01-01

This article discusses issues on the causality between smoking and lung cancer, which have been raised during the tobacco litigation in South Korea. It should be recognized that the explanatory ability of risk factor(s) for inter-individual variations in disease occurrence is different from the causal contribution of the risk factor(s) to disease occurrence. The affected subjects of the tobacco litigation in South Korea are lung cancer patients with a history of cigarette smoking. Thus, the attributable fraction of the exposed rather than the population attributable fraction should be used in the tobacco litigation regarding the causal contribution of smoking to lung cancer. Scientific evidence for the causal relationship between smoking and lung cancer is based on studies of individuals and groups, studies in animals and humans, studies that are observational or experimental, studies in laboratories and communities, and studies in both underdeveloped and developed countries. The scientific evidence collected is applicable to both groups and individuals. The probability of causation, which is calculated based on the attributable fraction for the association between smoking and lung cancer, could be utilized as evidence to prove causality in individuals.

Causal Attribution and Coping Maxims Differences between Immigrants and Non-Immigrants Suffering from Back Pain in Switzerland.

PubMed

Mantwill, Sarah; Schulz, Peter J

2016-01-01

This study aimed at investigating the relationship between causal attributions and coping maxims in people suffering from back pain. Further, it aimed at identifying in how far causal attributions and related coping maxims would defer between immigrants and non-immigrants in Switzerland. Data for this study came from a larger survey study that was conducted among immigrant populations in the German- and Italian-speaking part of Switzerland. Included in the analyses were native Swiss participants, as well as Albanian- and Serbian-speaking immigrants, who had indicated to have suffered from back pain within the last 12 months prior to the study. Data was analyzed for overall 495 participants. Items for causal attributions and coping maxims were subject to factor analyses. Cultural differences were assessed with ANOVA and regression analyses. Interaction terms were included to investigate whether the relationship between causal attributions and coping maxims would differ with cultural affiliation. For both immigrant groups the physician's influence on the course of their back pain was more important than for Swiss participants (p <.05). With regard to coping, both immigrant groups were more likely to agree with maxims that were related to the improvement of the back pain, as well as the acceptance of the current situation (p <.05). The only consistent interaction effect that was found indicated that being Albanian-speaking negatively moderated the relationship between physical activity as an attributed cause of back pain and all three identified coping maxims. The study shows that differences in causal attribution and coping maxims between immigrants and non-immigrants exist. Further, the results support the assumption of an association between causal attribution and coping maxims. However cultural affiliation did not considerably moderate this relationship.

Causal Attribution and Coping Maxims Differences between Immigrants and Non-Immigrants Suffering from Back Pain in Switzerland

PubMed Central

2016-01-01

Objectives This study aimed at investigating the relationship between causal attributions and coping maxims in people suffering from back pain. Further, it aimed at identifying in how far causal attributions and related coping maxims would defer between immigrants and non-immigrants in Switzerland. Methods Data for this study came from a larger survey study that was conducted among immigrant populations in the German- and Italian-speaking part of Switzerland. Included in the analyses were native Swiss participants, as well as Albanian- and Serbian-speaking immigrants, who had indicated to have suffered from back pain within the last 12 months prior to the study. Data was analyzed for overall 495 participants. Items for causal attributions and coping maxims were subject to factor analyses. Cultural differences were assessed with ANOVA and regression analyses. Interaction terms were included to investigate whether the relationship between causal attributions and coping maxims would differ with cultural affiliation. Results For both immigrant groups the physician’s influence on the course of their back pain was more important than for Swiss participants (p <.05). With regard to coping, both immigrant groups were more likely to agree with maxims that were related to the improvement of the back pain, as well as the acceptance of the current situation (p <.05). The only consistent interaction effect that was found indicated that being Albanian-speaking negatively moderated the relationship between physical activity as an attributed cause of back pain and all three identified coping maxims. Conclusion The study shows that differences in causal attribution and coping maxims between immigrants and non-immigrants exist. Further, the results support the assumption of an association between causal attribution and coping maxims. However cultural affiliation did not considerably moderate this relationship. PMID:27583445

The influence of linguistic and cognitive factors on the time course of verb-based implicit causality.

PubMed

Koornneef, Arnout; Dotlačil, Jakub; van den Broek, Paul; Sanders, Ted

2016-01-01

In three eye-tracking experiments the influence of the Dutch causal connective "want" (because) and the working memory capacity of readers on the usage of verb-based implicit causality was examined. Experiments 1 and 2 showed that although a causal connective is not required to activate implicit causality information during reading, effects of implicit causality surfaced more rapidly and were more pronounced when a connective was present in the discourse than when it was absent. In addition, Experiment 3 revealed that-in contrast to previous claims-the activation of implicit causality is not a resource-consuming mental operation. Moreover, readers with higher and lower working memory capacities behaved differently in a dual-task situation. Higher span readers were more likely to use implicit causality when they had all their working memory resources at their disposal. Lower span readers showed the opposite pattern as they were more likely to use the implicit causality cue in the case of an additional working memory load. The results emphasize that both linguistic and cognitive factors mediate the impact of implicit causality on text comprehension. The implications of these results are discussed in terms of the ongoing controversies in the literature-that is, the focusing-integration debate and the debates on the source of implicit causality.

Your visual system provides all the information you need to make moral judgments about generic visual events.

PubMed

De Freitas, Julian; Alvarez, George A

2018-05-28

To what extent are people's moral judgments susceptible to subtle factors of which they are unaware? Here we show that we can change people's moral judgments outside of their awareness by subtly biasing perceived causality. Specifically, we used subtle visual manipulations to create visual illusions of causality in morally relevant scenarios, and this systematically changed people's moral judgments. After demonstrating the basic effect using simple displays involving an ambiguous car collision that ends up injuring a person (E1), we show that the effect is sensitive on the millisecond timescale to manipulations of task-irrelevant factors that are known to affect perceived causality, including the duration (E2a) and asynchrony (E2b) of specific task-irrelevant contextual factors in the display. We then conceptually replicate the effect using a different paradigm (E3a), and also show that we can eliminate the effect by interfering with motion processing (E3b). Finally, we show that the effect generalizes across different kinds of moral judgments (E3c). Combined, these studies show that obligatory, abstract inferences made by the visual system influence moral judgments. Copyright © 2018 Elsevier B.V. All rights reserved.

The Mental Health Outcomes of Drought: A Systematic Review and Causal Process Diagram

PubMed Central

Vins, Holly; Bell, Jesse; Saha, Shubhayu; Hess, Jeremy J.

2015-01-01

Little is understood about the long term, indirect health consequences of drought (a period of abnormally dry weather). In particular, the implications of drought for mental health via pathways such as loss of livelihood, diminished social support, and rupture of place bonds have not been extensively studied, leaving a knowledge gap for practitioners and researchers alike. A systematic review of literature was performed to examine the mental health effects of drought. The systematic review results were synthesized to create a causal process diagram that illustrates the pathways linking drought effects to mental health outcomes. Eighty-two articles using a variety of methods in different contexts were gathered from the systematic review. The pathways in the causal process diagram with greatest support in the literature are those focusing on the economic and migratory effects of drought. The diagram highlights the complexity of the relationships between drought and mental health, including the multiple ways that factors can interact and lead to various outcomes. The systematic review and resulting causal process diagram can be used in both practice and theory, including prevention planning, public health programming, vulnerability and risk assessment, and research question guidance. The use of a causal process diagram provides a much needed avenue for integrating the findings of diverse research to further the understanding of the mental health implications of drought. PMID:26506367

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

PubMed Central

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

How Can Historical Understanding Best be Assessed? Use of Prediction Tasks To Assess How Students Understand the Role of Causal Factors that Produce Historical Events.

ERIC Educational Resources Information Center

Alonso-Tapia, Jesus; Villa, Jose Luis

1999-01-01

Examines the viability of using hypothetical problems that need the application of causal models for their solution as a method to assessing understanding in the social sciences. Explains that this method was used to describe how seventh-grade students understand causal factors affecting the "discovery and colonization of America." (CMK)

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

PubMed Central

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

2015-01-01

Objective 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. Design 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. Main Outcome Measures Self-reported daily fruit and vegetable intake and weekly leisure-time physical activity. Results 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. Conclusion 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. PMID:26542069

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

PubMed

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.

Beyond Scientism and Skepticism: An Integrative Approach to Global Mental Health

PubMed Central

Stein, Dan J.; Illes, Judy

2015-01-01

The global burden of disorders has shifted from infectious disease to non-communicable diseases, including neuropsychiatric disorders. Whereas infectious disease can sometimes be combated by targeting single causal mechanisms, such as prevention of contact-spread illness by handwashing, in the case of mental disorders multiple causal mechanisms are typically relevant. The emergent field of global mental health has emphasized the magnitude of the treatment gap, particularly in the low- and middle-income world and has paid particular attention to upstream causal factors, for example, poverty, inequality, and gender discrimination in the pathogenesis of mental disorders. However, this field has also been criticized for relying erroneously on Western paradigms of mental illness, which may not be relevant or appropriate to the low- and middle-income context. Here, it is important to steer a path between scientism and skepticism. Scientism regards mental disorders as essential categories, and takes a covering law approach to causality; skepticism regards mental disorders as merely social constructions and emphasizes the role of political power in causal relations. We propose an integrative model that emphasizes the contribution of a broad range of causal mechanisms operating at biological and societal levels to mental disorders and the consequent importance of broad spectrum and multipronged approaches to intervention. PMID:26635641

Causal illusions in children when the outcome is frequent

PubMed Central

2017-01-01

Causal illusions occur when people perceive a causal relation between two events that are actually unrelated. One factor that has been shown to promote these mistaken beliefs is the outcome probability. Thus, people tend to overestimate the strength of a causal relation when the potential consequence (i.e. the outcome) occurs with a high probability (outcome-density bias). Given that children and adults differ in several important features involved in causal judgment, including prior knowledge and basic cognitive skills, developmental studies can be considered an outstanding approach to detect and further explore the psychological processes and mechanisms underlying this bias. However, the outcome density bias has been mainly explored in adulthood, and no previous evidence for this bias has been reported in children. Thus, the purpose of this study was to extend outcome-density bias research to childhood. In two experiments, children between 6 and 8 years old were exposed to two similar setups, both showing a non-contingent relation between the potential cause and the outcome. These two scenarios differed only in the probability of the outcome, which could either be high or low. Children judged the relation between the two events to be stronger in the high probability of the outcome setting, revealing that, like adults, they develop causal illusions when the outcome is frequent. PMID:28898294

Causal attribution for success and failure in mathematics among MDAB pre-diploma students

NASA Astrophysics Data System (ADS)

Maidinsah, Hamidah; Embong, Rokiah; Wahab, Zubaidah Abd

2014-07-01

The Program Mengubah Destini Anak Bangsa (MDAB) is a pre-diploma programme catering to SPM school leavers who do not meet the minimum requirement to enter any of UiTM diploma programmes. The study aims to evaluate the perceptions of MDAB students toward the main causal attribution factors underlying students' success and failure in mathematics. Research sample comprised of 482 students from five UiTM branch campuses. Research instrument used was a set of GALUS questionnaire consisting of 36 items based on the Weiner Attribution Theory. Four causal attributions factors for success and failures evaluated are ability, effort, question difficulty and environment. GALUS reliability index was 0.93. The research found that effort appears to be the main causal attribution factor in students' success and failure in mathematics, followed by environment, question difficulty and ability. High achiever students strongly agree that the ability factor influenced their success while low achiever students strongly agree that all attributing factors influenced their failures in mathematics.

ECOREGION: ECOREGIONS OF CONTERMINOUS UNITED STATES

EPA Science Inventory

The Ecoregion data set covers aquatic ecoregions of the conterminous U.S. It is provided by the USGS and is intended for national-level studies of water resources. Aquatic ecoregions are based on perceived patterns of a combination of causal and integrative factors including lan...

A Critique of the Diagnostic Construct Schizophrenia

ERIC Educational Resources Information Center

Wong, Stephen E.

2014-01-01

This article examines problems in the clinical utility of the diagnosis of schizophrenia including reliance on questionable data, arbitrary criteria and categorization, inadequate precision for assessment and treatment evaluation, and omission of information on causal current and historical environmental factors. Some alternatives to the…

Stable Causal Relationships Are Better Causal Relationships.

PubMed

Vasilyeva, Nadya; Blanchard, Thomas; Lombrozo, Tania

2018-05-01

We report three experiments investigating whether people's judgments about causal relationships are sensitive to the robustness or stability of such relationships across a range of background circumstances. In Experiment 1, we demonstrate that people are more willing to endorse causal and explanatory claims based on stable (as opposed to unstable) relationships, even when the overall causal strength of the relationship is held constant. In Experiment 2, we show that this effect is not driven by a causal generalization's actual scope of application. In Experiment 3, we offer evidence that stable causal relationships may be seen as better guides to action. Collectively, these experiments document a previously underappreciated factor that shapes people's causal reasoning: the stability of the causal relationship. Copyright © 2018 Cognitive Science Society, Inc.

Drug-disease association and drug-repositioning predictions in complex diseases using causal inference-probabilistic matrix factorization.

PubMed

Yang, Jihong; Li, Zheng; Fan, Xiaohui; Cheng, Yiyu

2014-09-22

The high incidence of complex diseases has become a worldwide threat to human health. Multiple targets and pathways are perturbed during the pathological process of complex diseases. Systematic investigation of complex relationship between drugs and diseases is necessary for new association discovery and drug repurposing. For this purpose, three causal networks were constructed herein for cardiovascular diseases, diabetes mellitus, and neoplasms, respectively. A causal inference-probabilistic matrix factorization (CI-PMF) approach was proposed to predict and classify drug-disease associations, and further used for drug-repositioning predictions. First, multilevel systematic relations between drugs and diseases were integrated from heterogeneous databases to construct causal networks connecting drug-target-pathway-gene-disease. Then, the association scores between drugs and diseases were assessed by evaluating a drug's effects on multiple targets and pathways. Furthermore, PMF models were learned based on known interactions, and associations were then classified into three types by trained models. Finally, therapeutic associations were predicted based upon the ranking of association scores and predicted association types. In terms of drug-disease association prediction, modified causal inference included in CI-PMF outperformed existing causal inference with a higher AUC (area under receiver operating characteristic curve) score and greater precision. Moreover, CI-PMF performed better than single modified causal inference in predicting therapeutic drug-disease associations. In the top 30% of predicted associations, 58.6% (136/232), 50.8% (31/61), and 39.8% (140/352) hit known therapeutic associations, while precisions obtained by the latter were only 10.2% (231/2264), 8.8% (36/411), and 9.7% (189/1948). Clinical verifications were further conducted for the top 100 newly predicted therapeutic associations. As a result, 21, 12, and 32 associations have been studied and many treatment effects of drugs on diseases were investigated for cardiovascular diseases, diabetes mellitus, and neoplasms, respectively. Related chains in causal networks were extracted for these 65 clinical-verified associations, and we further illustrated the therapeutic role of etodolac in breast cancer by inferred chains. Overall, CI-PMF is a useful approach for associating drugs with complex diseases and provides potential values for drug repositioning.

[FROM STATISTICAL ASSOCIATIONS TO SCIENTIFIC CAUSALITY].

PubMed

Golan, Daniel; Linn, Shay

2015-06-01

The pathogenesis of most chronic diseases is complex and probably involves the interaction of multiple genetic and environmental risk factors. One way to learn about disease triggers is from statistically significant associations in epidemiological studies. However, associations do not necessarily prove causation. Associations can commonly result from bias, confounding and reverse causation. Several paradigms for causality inference have been developed. Henle-Koch postulates are mainly applied for infectious diseases. Austin Bradford Hill's criteria may serve as a practical tool to weigh the evidence regarding the probability that a single new risk factor for a given disease is indeed causal. These criteria are irrelevant for estimating the causal relationship between exposure to a risk factor and disease whenever biological causality has been previously established. Thus, it is highly probable that past exposure of an individual to definite carcinogens is related to his cancer, even without proving an association between this exposure and cancer in his group. For multifactorial diseases, Rothman's model of interacting sets of component causes can be applied.

Drug- and Herb-Induced Liver Injury in Clinical and Translational Hepatology: Causality Assessment Methods, Quo Vadis?

PubMed Central

Eickhoff, Axel; Schulze, Johannes

2013-01-01

Drug-induced liver injury (DILI) and herb-induced liver injury (HILI) are typical diseases of clinical and translational hepatology. Their diagnosis is complex and requires an experienced clinician to translate basic science into clinical judgment and identify a valid causality algorithm. To prospectively assess causality starting on the day DILI or HILI is suspected, the best approach for physicians is to use the Council for International Organizations of Medical Sciences (CIOMS) scale in its original or preferably its updated version. The CIOMS scale is validated, liver-specific, structured, and quantitative, providing final causality grades based on scores of specific items for individual patients. These items include latency period, decline in liver values after treatment cessation, risk factors, co-medication, alternative diagnoses, hepatotoxicity track record of the suspected product, and unintentional re-exposure. Provided causality is established as probable or highly probable, data of the CIOMS scale with all individual items, a short clinical report, and complete raw data should be transmitted to the regulatory agencies, manufacturers, expert panels, and possibly to the scientific community for further refinement of the causality evaluation in a setting of retrospective expert opinion. Good-quality case data combined with thorough CIOMS-based assessment as a standardized approach should avert subsequent necessity for other complex causality assessment methods that may have inter-rater problems because of poor-quality data. In the future, the CIOMS scale will continue to be the preferred tool to assess causality of DILI and HILI cases and should be used consistently, both prospectively by physicians, and retrospectively for subsequent expert opinion if needed. For comparability and international harmonization, all parties assessing causality in DILI and HILI cases should attempt this standardized approach using the updated CIOMS scale. PMID:26357608

Air Force Research Laboratory Warfighter Readiness Research Division Participation in the 2008 IITSEC

DTIC Science & Technology

2008-12-15

of the underlying behaviors that led to each element being cited. The AFSC Human Factors Database listed all human factors cited in the Life...situations of increased pressure. Through an understanding of the causal factors of human behavior , and by analysis of one’s own behavioral patterns...JTAC training and overall lessons learned from modeling and simulation of the JTAC environment to include behavior scripting, artillery models

Are bruxism and the bite causally related?

PubMed

Lobbezoo, F; Ahlberg, J; Manfredini, D; Winocur, E

2012-07-01

In the dental profession, the belief that bruxism and dental (mal-)occlusion ('the bite') are causally related is widespread. The aim of this review was to critically assess the available literature on this topic. A PubMed search of the English-language literature, using the query 'Bruxism [Majr] AND (Dental Occlusion [Majr] OR Malocclusion [Majr])', yielded 93 articles, of which 46 papers were finally included in the present review*. Part of the included publications dealt with the possible associations between bruxism and aspects of occlusion, from which it was concluded that neither for occlusal interferences nor for factors related to the anatomy of the oro-facial skeleton, there is any evidence available that they are involved in the aetiology of bruxism. Instead, there is a growing awareness of other factors (viz. psychosocial and behavioural ones) being important in the aetiology of bruxism. Another part of the included papers assessed the possible mediating role of occlusion between bruxism and its purported consequences (e.g. tooth wear, loss of periodontal tissues, and temporomandibular pain and dysfunction). Even though most dentists agree that bruxism may have several adverse effects on the masticatory system, for none of these purported adverse effects, evidence for a mediating role of occlusion and articulation has been found to date. Hence, based on this review, it should be concluded that to date, there is no evidence whatsoever for a causal relationship between bruxism and the bite. © 2012 Blackwell Publishing Ltd.

When Work is Related to Disease, What Establishes Evidence for a Causal Relation?

PubMed

Verbeek, Jos

2012-06-01

Establishing a causal relationship between factors at work and disease is difficult for occupational physicians and researchers. This paper seeks to provide arguments for the judgement of evidence of causality in observational studies that relate work factors to disease. I derived criteria for the judgement of evidence of causality from the following sources: the criteria list of Hill, the approach by Rothman, the methods used by International Agency for Research on Cancer (IARC), and methods used by epidemiologists. The criteria are applied to two cases of putative occupational diseases; breast cancer caused by shift work and aerotoxic syndrome. Only three of the Hill criteria can be applied to an actual study. Rothman stresses the importance of confounding and alternative explanations than the putative cause. IARC closely follows Hill, but they also incorporate other than epidemiological evidence. Applied to shift work and breast cancer, these results have found moderate evidence for a causal relationship, but applied to the aerotoxic syndrome, there is an absence of evidence of causality. There are no ready to use algorithms for judgement of evidence of causality. Criteria from different sources lead to similar results and can make a conclusion of causality more or less likely.

When Work is Related to Disease, What Establishes Evidence for a Causal Relation?

PubMed Central

2012-01-01

Establishing a causal relationship between factors at work and disease is difficult for occupational physicians and researchers. This paper seeks to provide arguments for the judgement of evidence of causality in observational studies that relate work factors to disease. I derived criteria for the judgement of evidence of causality from the following sources: the criteria list of Hill, the approach by Rothman, the methods used by International Agency for Research on Cancer (IARC), and methods used by epidemiologists. The criteria are applied to two cases of putative occupational diseases; breast cancer caused by shift work and aerotoxic syndrome. Only three of the Hill criteria can be applied to an actual study. Rothman stresses the importance of confounding and alternative explanations than the putative cause. IARC closely follows Hill, but they also incorporate other than epidemiological evidence. Applied to shift work and breast cancer, these results have found moderate evidence for a causal relationship, but applied to the aerotoxic syndrome, there is an absence of evidence of causality. There are no ready to use algorithms for judgement of evidence of causality. Criteria from different sources lead to similar results and can make a conclusion of causality more or less likely. PMID:22993715

Dynamics of safety performance and culture: a group model building approach.

PubMed

Goh, Yang Miang; Love, Peter E D; Stagbouer, Greg; Annesley, Chris

2012-09-01

The management of occupational health and safety (OHS) including safety culture interventions is comprised of complex problems that are often hard to scope and define. Due to the dynamic nature and complexity of OHS management, the concept of system dynamics (SD) is used to analyze accident prevention. In this paper, a system dynamics group model building (GMB) approach is used to create a causal loop diagram of the underlying factors influencing the OHS performance of a major drilling and mining contractor in Australia. While the organization has invested considerable resources into OHS their disabling injury frequency rate (DIFR) has not been decreasing. With this in mind, rich individualistic knowledge about the dynamics influencing the DIFR was acquired from experienced employees with operations, health and safety and training background using a GMB workshop. Findings derived from the workshop were used to develop a series of causal loop diagrams that includes a wide range of dynamics that can assist in better understanding the causal influences OHS performance. The causal loop diagram provides a tool for organizations to hypothesize the dynamics influencing effectiveness of OHS management, particularly the impact on DIFR. In addition the paper demonstrates that the SD GMB approach has significant potential in understanding and improving OHS management. Copyright © 2011 Elsevier Ltd. All rights reserved.

Risk-Based Causal Modeling of Airborne Loss of Separation

NASA Technical Reports Server (NTRS)

Geuther, Steven C.; Shih, Ann T.

2015-01-01

Maintaining safe separation between aircraft remains one of the key aviation challenges as the Next Generation Air Transportation System (NextGen) emerges. The goals of the NextGen are to increase capacity and reduce flight delays to meet the aviation demand growth through the 2025 time frame while maintaining safety and efficiency. The envisioned NextGen is expected to enable high air traffic density, diverse fleet operations in the airspace, and a decrease in separation distance. All of these factors contribute to the potential for Loss of Separation (LOS) between aircraft. LOS is a precursor to a potential mid-air collision (MAC). The NASA Airspace Operations and Safety Program (AOSP) is committed to developing aircraft separation assurance concepts and technologies to mitigate LOS instances, therefore, preventing MAC. This paper focuses on the analysis of causal and contributing factors of LOS accidents and incidents leading to MAC occurrences. Mid-air collisions among large commercial aircraft are rare in the past decade, therefore, the LOS instances in this study are for general aviation using visual flight rules in the years 2000-2010. The study includes the investigation of causal paths leading to LOS, and the development of the Airborne Loss of Separation Analysis Model (ALOSAM) using Bayesian Belief Networks (BBN) to capture the multi-dependent relations of causal factors. The ALOSAM is currently a qualitative model, although further development could lead to a quantitative model. ALOSAM could then be used to perform impact analysis of concepts and technologies in the AOSP portfolio on the reduction of LOS risk.

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

PubMed

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.

Causal chain mapping: a novel method to analyse treatment compliance decisions relating to lymphatic filariasis elimination in Alor, Indonesia.

PubMed

Krentel, Alison; Aunger, Robert

2012-08-01

Many public health programmes require individuals to comply with particular behaviours that are novel to them, for example, acquiring new eating habits, accepting immunizations or taking a new medication. In particular, mass drug administration programmes only work to reduce the prevalence of a disease if significant proportions of the target population take the drug in question. In such cases, knowledge of the factors most likely to lead to high levels of compliance is crucial to the programme's success. Existing models of compliance tend to either address interpersonal, organizational or psychological causes independently. Here, the authors present a formal method for analysing relevant factors in the situational context of the compliant behaviour, identifying how these factors may interact within the individual. This method was developed from semantic network analysis, augmented to include environmental and demographic variables to show causal linkages-hence the name 'causal chain mapping'. The ability of this method to provide significant insight into the actual behaviour of individuals is demonstrated with examples from a mass drug administration for lymphatic filariasis in Alor District, Indonesia. The use of this method is likely to help identify key components influencing compliance, and thus make any public health programme reliant on the adoption of novel behaviours more effective.

What Women Think: Cancer Causal Attributions in a Diverse Sample of Women

PubMed Central

Rodríguez, Vivian M.; Gyure, Maria E.; Corona, Rosalie; Bodurtha, Joann N.; Bowen, Deborah J.; Quillin, John M.

2014-01-01

Women hold diverse beliefs about cancer etiology, potentially affecting their use of cancer preventive behaviors. To date, research has greatly focused on the causal attributions cancer patients and survivors hold about cancer, and studies have been conducted primarily with White participants. Less is known about causal attributions held by women with and without a family history of cancer from a diverse community sample. This study sought to identify cancer causal attributions of women with and without a family history of cancer, and explore its relation to socio-cultural factors. Diverse women (60% African-American) recruited at an urban, safety-net women's health clinic (N=471) reported factors they believed cause cancer. Responses were coded into nine attributions and analyzed using chi-squares and logistic regressions. Lifestyle-choices (63%), genetics/heredity (34%), and environmental-exposures (19%) were the top causal attributions identified. Women without a family history of cancer were more likely to identify genetics/heredity as an attribution for cancer than women with a history of cancer in their families. Women who identified as White, who had a higher educational attainment, and had commercial insurance were more likely to report genetics/heredity as a causal attribution for cancer. These findings suggest that socio-cultural factors may play a role in the causal attributions individuals make about cancer, which can, in turn, inform cancer awareness and prevention messages. PMID:25398057

Multivariate Granger causality: an estimation framework based on factorization of the spectral density matrix

PubMed Central

Wen, Xiaotong; Rangarajan, Govindan; Ding, Mingzhou

2013-01-01

Granger causality is increasingly being applied to multi-electrode neurophysiological and functional imaging data to characterize directional interactions between neurons and brain regions. For a multivariate dataset, one might be interested in different subsets of the recorded neurons or brain regions. According to the current estimation framework, for each subset, one conducts a separate autoregressive model fitting process, introducing the potential for unwanted variability and uncertainty. In this paper, we propose a multivariate framework for estimating Granger causality. It is based on spectral density matrix factorization and offers the advantage that the estimation of such a matrix needs to be done only once for the entire multivariate dataset. For any subset of recorded data, Granger causality can be calculated through factorizing the appropriate submatrix of the overall spectral density matrix. PMID:23858479

Breast-feeding and cardiovascular risk factors and outcomes in later life: evidence from epidemiological studies.

PubMed

Owen, Christopher G; Whincup, Peter H; Cook, Derek G

2011-11-01

This paper considers the body of observational evidence examining the association of being breast-fed to cardiovascular risk factors and outcomes in later life, and whether any potentially advantageous findings are causal. Early cardiovascular consequences/correlates of breast-feeding, compared to being formula fed, include markedly higher levels of total blood cholesterol, lower levels of pre-prandial blood glucose and insulin and lower levels of adiposity. However, a key issue is whether these early differences at a period of rapid development programme/influence cardiovascular risk factors and outcomes in later life. Evidence of long-term effects of early feeding, largely from observational studies, has shown that those breast-fed have lower levels of blood total cholesterol, lower risk of type-2 diabetes and marginally lower levels of adiposity and blood pressure in adult life. There is no strong evidence to suggest effects of early feeding on adult levels of blood glucose, blood insulin and CHD outcomes, although further data are needed. However, the influence of confounding factors, such as maternal body size, maternal smoking and socio-demographic factors, and exclusivity of early feeding on these potentially beneficial associations needs to be considered before inferring any causal effects. Moreover, fewer studies have examined whether duration of exclusive breast-feeding has a graded influence on these risk factors and outcomes; such data would help further in deciding upon causal associations. While strong observational evidence suggests nutritional programming of adult cholesterol levels, associations with other markers of cardiometabolic risk and their consequences in later life need to be confirmed in well-conducted observational and experimental studies.

The causal role of fatigue in the stress-perceived health relationship: a MetroNet study.

PubMed

Maghout-Juratli, Sham; Janisse, James; Schwartz, Kendra; Arnetz, Bengt B

2010-01-01

We conducted a cross-sectional survey of 4 primary care MetroNet centers in metropolitan Detroit. Our objective was to describe the causal role of fatigue in the relationship among stress, stress resiliency, and perceived health in primary care. Fatigue is a public health problem that has been linked to stress and poor health. The causal role of fatigue between stress and perceived health is unknown. Four hundred surveys were distributed to adult patients in 4 primary care centers in metropolitan Detroit between 2006 and 2007. Internal consistency reliabilities and principal factor analyses were calculated for the key psychological scales. Perceived health is the primary outcome. Path models were used to study the relationship among stress, fatigue, and perceived health. We also modeled the impact of select stress resiliency factors including sleep, recovery, and social support. Of the 400 distributed surveys, 315 (78.7%) had a response rate of 70% or more and were included in the analysis. Respondents were predominantly middle aged (median age, 43 years); female (58.7%); and African American (52.0%). The majority worked full time (56.5%); did not have a college degree (77.7%); and were not married (55.2%). Fatigue was reported by 59% of respondents, 42.7% of which was unexplained. The path model supported the causal role of fatigue between stress and perceived health. The positive effects of sleep, recovery, and social support on fatigue, stress, and perceived health were validated. Fatigue was common in this metropolitan primary care environment and completely mediated the relationship between stress and poor perceived health. Therefore, stress, when significant enough to cause fatigue, may lead to poor health.

Property transmission: an explanatory account of the role of similarity information in causal inference.

PubMed

White, Peter A

2009-09-01

Many kinds of common and easily observed causal relations exhibit property transmission, which is a tendency for the causal object to impose its own properties on the effect object. It is proposed that property transmission becomes a general and readily available hypothesis used to make interpretations and judgments about causal questions under conditions of uncertainty, in which property transmission functions as a heuristic. The property transmission hypothesis explains why and when similarity information is used in causal inference. It can account for magical contagion beliefs, some cases of illusory correlation, the correspondence bias, overestimation of cross-situational consistency in behavior, nonregressive tendencies in prediction, the belief that acts of will are causes of behavior, and a range of other phenomena. People learn that property transmission is often moderated by other factors, but under conditions of uncertainty in which the operation of relevant other factors is unknown, it tends to exhibit a pervasive influence on thinking about causality. (c) 2009 APA, all rights reserved.

Health locus of control as manifested in individuals attending a state-run medical dispensary in northern India.

PubMed

Berg, Michael B; Anshika, Avi

2017-04-01

To investigate the health locus of control (HLOC) beliefs of patients and visitors at a free, state-run medical clinic in Faridabad, India, in order to establish a norm for this population and to explore potential associations between the different categories of causal health beliefs. Participants (110 men, 96 women) were interviewed in Hindi and asked a shortened version of the Multidimensional Health Locus of Control Scale assessing both internal HLOC and three aspects of external HLOC (chance, powerful others, and God). Additional variables of interest included a Traditional Values Scale, a measure of spirituality, an assessment of health status, and demographic information including gender, age, employment status, and religion. Participants rated the external-God factor as a stronger determinant of their health than the internal or other external HLOC factors. Internal HLOC was positively correlated with external HLOC in terms of chance and the role of powerful others and these associations were strongest for the most interdependent participants (i.e. women and the unemployed). For patients and visitors at the Faridabad clinic, religion played a significant role in their causal health beliefs. In addition, internal HLOC was positively associated with aspects of external locus of control, suggesting that causal health beliefs were viewed in a holistic, integrated fashion. Interventions based on these findings are suggested.

Supporting shared hypothesis testing in the biomedical domain.

PubMed

Agibetov, Asan; Jiménez-Ruiz, Ernesto; Ondrésik, Marta; Solimando, Alessandro; Banerjee, Imon; Guerrini, Giovanna; Catalano, Chiara E; Oliveira, Joaquim M; Patanè, Giuseppe; Reis, Rui L; Spagnuolo, Michela

2018-02-08

Pathogenesis of inflammatory diseases can be tracked by studying the causality relationships among the factors contributing to its development. We could, for instance, hypothesize on the connections of the pathogenesis outcomes to the observed conditions. And to prove such causal hypotheses we would need to have the full understanding of the causal relationships, and we would have to provide all the necessary evidences to support our claims. In practice, however, we might not possess all the background knowledge on the causality relationships, and we might be unable to collect all the evidence to prove our hypotheses. In this work we propose a methodology for the translation of biological knowledge on causality relationships of biological processes and their effects on conditions to a computational framework for hypothesis testing. The methodology consists of two main points: hypothesis graph construction from the formalization of the background knowledge on causality relationships, and confidence measurement in a causality hypothesis as a normalized weighted path computation in the hypothesis graph. In this framework, we can simulate collection of evidences and assess confidence in a causality hypothesis by measuring it proportionally to the amount of available knowledge and collected evidences. We evaluate our methodology on a hypothesis graph that represents both contributing factors which may cause cartilage degradation and the factors which might be caused by the cartilage degradation during osteoarthritis. Hypothesis graph construction has proven to be robust to the addition of potentially contradictory information on the simultaneously positive and negative effects. The obtained confidence measures for the specific causality hypotheses have been validated by our domain experts, and, correspond closely to their subjective assessments of confidences in investigated hypotheses. Overall, our methodology for a shared hypothesis testing framework exhibits important properties that researchers will find useful in literature review for their experimental studies, planning and prioritizing evidence collection acquisition procedures, and testing their hypotheses with different depths of knowledge on causal dependencies of biological processes and their effects on the observed conditions.

Confounding factors in determining causal soil moisture-precipitation feedback

NASA Astrophysics Data System (ADS)

Tuttle, Samuel E.; Salvucci, Guido D.

2017-07-01

Identification of causal links in the land-atmosphere system is important for construction and testing of land surface and general circulation models. However, the land and atmosphere are highly coupled and linked by a vast number of complex, interdependent processes. Statistical methods, such as Granger causality, can help to identify feedbacks from observational data, independent of the different parameterizations of physical processes and spatiotemporal resolution effects that influence feedbacks in models. However, statistical causal identification methods can easily be misapplied, leading to erroneous conclusions about feedback strength and sign. Here, we discuss three factors that must be accounted for in determination of causal soil moisture-precipitation feedback in observations and model output: seasonal and interannual variability, precipitation persistence, and endogeneity. The effect of neglecting these factors is demonstrated in simulated and observational data. The results show that long-timescale variability and precipitation persistence can have a substantial effect on detected soil moisture-precipitation feedback strength, while endogeneity has a smaller effect that is often masked by measurement error and thus is more likely to be an issue when analyzing model data or highly accurate observational data.

A Unifying Theory of Biological Function.

PubMed

van Hateren, J H

2017-01-01

A new theory that naturalizes biological function is explained and compared with earlier etiological and causal role theories. Etiological (or selected effects) theories explain functions from how they are caused over their evolutionary history. Causal role theories analyze how functional mechanisms serve the current capacities of their containing system. The new proposal unifies the key notions of both kinds of theories, but goes beyond them by explaining how functions in an organism can exist as factors with autonomous causal efficacy. The goal-directedness and normativity of functions exist in this strict sense as well. The theory depends on an internal physiological or neural process that mimics an organism's fitness, and modulates the organism's variability accordingly. The structure of the internal process can be subdivided into subprocesses that monitor specific functions in an organism. The theory matches well with each intuition on a previously published list of intuited ideas about biological functions, including intuitions that have posed difficulties for other theories.

The Global Drivers of Photosynthesis and Light Use Efficiency Seasonality: A Granger Frequency Causality Analysis

NASA Technical Reports Server (NTRS)

Nemani, Ramakrishna R.

2016-01-01

Photosynthesis and light use efficiency (LUE) are major factors in the evolution of the continental carbon cycle due to their contribution to gross primary production (GPP). However, while the drivers of photosynthesis and LUE on a plant or canopy scale can often be identified, significant uncertainties exist when modeling these on a global scale. This is due to sparse observations in regions such as the tropics and the lack of a direct global observation dataset. Although others have attempted to address this issue using correlations (Beer, 2010) or calculating GPP from vegetation indices (Running, 2004), in this study we take a new approach. We combine the statistical method of Granger frequency causality and partial Granger frequency causality with remote sensing data products (including sun-induced fluorescence used as a proxy for GPP) to determine the main environmental drivers of GPP across the globe.

The Model Analyst’s Toolkit: Scientific Model Development, Analysis, and Validation

DTIC Science & Technology

2013-11-20

Granger causality F-test validation 3.1.2. Dynamic time warping for uneven temporal relationships Many causal relationships are imperfectly...mapping for dynamic feedback models Granger causality and DTW can identify causal relationships and consider complex temporal factors. However, many ...variant of the tf-idf algorithm (Manning, Raghavan, Schutze et al., 2008), typically used in search engines, to “score” features. The (-log tf) in

Age- and Sex-Specific Causal Effects of Adiposity on Cardiovascular Risk Factors

PubMed Central

Fall, Tove; Hägg, Sara; Ploner, Alexander; Mägi, Reedik; Fischer, Krista; Draisma, Harmen H.M.; Sarin, Antti-Pekka; Benyamin, Beben; Ladenvall, Claes; Åkerlund, Mikael; Kals, Mart; Esko, Tõnu; Nelson, Christopher P.; Kaakinen, Marika; Huikari, Ville; Mangino, Massimo; Meirhaeghe, Aline; Kristiansson, Kati; Nuotio, Marja-Liisa; Kobl, Michael; Grallert, Harald; Dehghan, Abbas; Kuningas, Maris; de Vries, Paul S.; de Bruijn, Renée F.A.G.; Willems, Sara M.; Heikkilä, Kauko; Silventoinen, Karri; Pietiläinen, Kirsi H.; Legry, Vanessa; Giedraitis, Vilmantas; Goumidi, Louisa; Syvänen, Ann-Christine; Strauch, Konstantin; Koenig, Wolfgang; Lichtner, Peter; Herder, Christian; Palotie, Aarno; Menni, Cristina; Uitterlinden, André G.; Kuulasmaa, Kari; Havulinna, Aki S.; Moreno, Luis A.; Gonzalez-Gross, Marcela; Evans, Alun; Tregouet, David-Alexandre; Yarnell, John W.G.; Virtamo, Jarmo; Ferrières, Jean; Veronesi, Giovanni; Perola, Markus; Arveiler, Dominique; Brambilla, Paolo; Lind, Lars; Kaprio, Jaakko; Hofman, Albert; Stricker, Bruno H.; van Duijn, Cornelia M.; Ikram, M. Arfan; Franco, Oscar H.; Cottel, Dominique; Dallongeville, Jean; Hall, Alistair S.; Jula, Antti; Tobin, Martin D.; Penninx, Brenda W.; Peters, Annette; Gieger, Christian; Samani, Nilesh J.; Montgomery, Grant W.; Whitfield, John B.; Martin, Nicholas G.; Groop, Leif; Spector, Tim D.; Magnusson, Patrik K.; Amouyel, Philippe; Boomsma, Dorret I.; Nilsson, Peter M.; Järvelin, Marjo-Riitta; Lyssenko, Valeriya; Metspalu, Andres; Strachan, David P.; Salomaa, Veikko; Ripatti, Samuli; Pedersen, Nancy L.; Prokopenko, Inga; McCarthy, Mark I.

2015-01-01

Observational studies have reported different effects of adiposity on cardiovascular risk factors across age and sex. Since cardiovascular risk factors are enriched in obese individuals, it has not been easy to dissect the effects of adiposity from those of other risk factors. We used a Mendelian randomization approach, applying a set of 32 genetic markers to estimate the causal effect of adiposity on blood pressure, glycemic indices, circulating lipid levels, and markers of inflammation and liver disease in up to 67,553 individuals. All analyses were stratified by age (cutoff 55 years of age) and sex. The genetic score was associated with BMI in both nonstratified analysis (P = 2.8 × 10−107) and stratified analyses (all P < 3.3 × 10−30). We found evidence of a causal effect of adiposity on blood pressure, fasting levels of insulin, C-reactive protein, interleukin-6, HDL cholesterol, and triglycerides in a nonstratified analysis and in the <55-year stratum. Further, we found evidence of a smaller causal effect on total cholesterol (P for difference = 0.015) in the ≥55-year stratum than in the <55-year stratum, a finding that could be explained by biology, survival bias, or differential medication. In conclusion, this study extends previous knowledge of the effects of adiposity by providing sex- and age-specific causal estimates on cardiovascular risk factors. PMID:25712996

Timing and Methodology of Application of Azoxystrobin to Control Rhizoctonia Solani in Sugarbeet

USDA-ARS?s Scientific Manuscript database

Rhizoctonia solani AG 2-2 is the causal agent of Rhizoctonia root and crown rot of sugar beet (Beta vulgaris) in North Dakota and Minnesota. This disease is a major limiting factor to sugar beet production. Management strategies currently include using partially resistant cultivars and fungicides. ...

Outbreak of sudden cardiac deaths in a tire manufacturing facility: can it be caused by nanoparticles?

PubMed

Kim, Eun-A; Park, Jungsun; Kim, Kun-Hyung; Lee, Naroo; Kim, Dae-Seong; Kang, Seong-Kyu

2012-03-01

The purpose of this study was to review clinical characteristics and working environments of sudden cardiac death (SCD) cases associated with a tire manufacturer in Korea, and review possible occupational risk factors for cardiovascular disease including nanoparticles (ultrafine particles, UFPs). We reviewed (i) the clinical course of SCD cases and (ii) occupational and non-occupational risk factors including chemicals, the physical work environment, and job characteristics. Possible occupational factors were chemicals, UFPs of rubber fume, a hot environment, shift work, overworking, and noise exposure. The mean diameter of rubber fume (63-73 nm) was (larger than diesel exhaust [12 nm] and outdoor dust [50 nm]). The concentration of carbon disulfide, carbon monoxide and styrene were lower than the limit of detection. Five SCD cases were exposed to shift work and overworking. Most of the cases had several non-occupational factors such as hypertension, overweight and smoking. The diameter of rubber fume was larger than outdoor and the diesel exhaust, the most well known particulate having a causal relationship with cardiovascular disease. The possibility of a causal relation between UFPs of rubber fume and SCD was not supported in this study. However, it is necessary to continue studying the relationship between large sized UFPs and SCD.

Outbreak of Sudden Cardiac Deaths in a Tire Manufacturing Facility: Can It Be Caused by Nanoparticles?

PubMed Central

Kim, Eun-A; Kim, Kun-Hyung; Lee, Naroo; Kim, Dae-Seong; Kang, Seong-Kyu

2012-01-01

Objectives The purpose of this study was to review clinical characteristics and working environments of sudden cardiac death (SCD) cases associated with a tire manufacturer in Korea, and review possible occupational risk factors for cardiovascular disease including nanoparticles (ultrafine particles, UFPs). Methods We reviewed (i) the clinical course of SCD cases and (ii) occupational and non-occupational risk factors including chemicals, the physical work environment, and job characteristics. Results Possible occupational factors were chemicals, UFPs of rubber fume, a hot environment, shift work, overworking, and noise exposure. The mean diameter of rubber fume (63-73 nm) was (larger than diesel exhaust [12 nm] and outdoor dust [50 nm]). The concentration of carbon disulfide, carbon monoxide and styrene were lower than the limit of detection. Five SCD cases were exposed to shift work and overworking. Most of the cases had several non-occupational factors such as hypertension, overweight and smoking. Conclusion The diameter of rubber fume was larger than outdoor and the diesel exhaust, the most well known particulate having a causal relationship with cardiovascular disease. The possibility of a causal relation between UFPs of rubber fume and SCD was not supported in this study. However, it is necessary to continue studying the relationship between large sized UFPs and SCD. PMID:22953232

Monitoring signals for vaccine safety: the assessment of individual adverse event reports by an expert advisory committee. Advisory Committee on Causality Assessment.

PubMed Central

Collet, J. P.; MacDonald, N.; Cashman, N.; Pless, R.

2000-01-01

Monitoring vaccine safety is a complex and shared responsibility. It can be carried out in many ways, one of which is the reporting of individual cases of adverse reactions thought to be due to vaccination. The task is difficult because ascribing causality to an individual case report is fraught with challenges. A standardized evaluation instrument--known as the causality assessment form--was therefore developed for use by an expert advisory committee to facilitate the process. By following the several sections in this form, the members of the committee are taken through a series of points to establish causality. These points include the basic criteria for causation such as biological plausibility, the time elapsed between the vaccine administration and the onset of the adverse event, and whether other factors (drugs, chemicals or underlying disease) could account for the adverse symptoms. The form concludes with a consensus assessment of causality, a commentary about the assessment, and advice for further study or follow-up. This method of assessing the more serious cases of adverse reaction reported to vaccination has proven useful in evaluating ongoing safety of vaccines in Canada. Through analyses such as this, new signals can be identified and investigated further. PMID:10743282

The joint Simon effect depends on perceived agency, but not intentionality, of the alternative action

PubMed Central

Stenzel, Anna; Dolk, Thomas; Colzato, Lorenza S.; Sellaro, Roberta; Hommel, Bernhard; Liepelt, Roman

2014-01-01

A co-actor's intentionality has been suggested to be a key modulating factor for joint action effects like the joint Simon effect (JSE). However, in previous studies intentionality has often been confounded with agency defined as perceiving the initiator of an action as being the causal source of the action. The aim of the present study was to disentangle the role of agency and intentionality as modulating factors of the JSE. In Experiment 1, participants performed a joint go/nogo Simon task next to a co-actor who either intentionally controlled a response button with own finger movements (agency+/intentionality+) or who passively placed the hand on a response button that moved up and down on its own as triggered by computer signals (agency−/intentionality−). In Experiment 2, we included a condition in which participants believed that the co-actor intentionally controlled the response button with a Brain-Computer Interface (BCI) while placing the response finger clearly besides the response button, so that the causal relationship between agent and action effect was perceptually disrupted (agency−/intentionality+). As a control condition, the response button was computer controlled while the co-actor placed the response finger besides the response button (agency−/intentionality−). Experiment 1 showed that the JSE is present with an intentional co-actor and causality between co-actor and action effect, but absent with an unintentional co-actor and a lack of causality between co-actor and action effect. Experiment 2 showed that the JSE is absent with an intentional co-actor, but no causality between co-actor and action effect. Our findings indicate an important role of the co-actor's agency for the JSE. They also suggest that the attribution of agency has a strong perceptual basis. PMID:25140144

The joint Simon effect depends on perceived agency, but not intentionality, of the alternative action.

PubMed

Stenzel, Anna; Dolk, Thomas; Colzato, Lorenza S; Sellaro, Roberta; Hommel, Bernhard; Liepelt, Roman

2014-01-01

A co-actor's intentionality has been suggested to be a key modulating factor for joint action effects like the joint Simon effect (JSE). However, in previous studies intentionality has often been confounded with agency defined as perceiving the initiator of an action as being the causal source of the action. The aim of the present study was to disentangle the role of agency and intentionality as modulating factors of the JSE. In Experiment 1, participants performed a joint go/nogo Simon task next to a co-actor who either intentionally controlled a response button with own finger movements (agency+/intentionality+) or who passively placed the hand on a response button that moved up and down on its own as triggered by computer signals (agency-/intentionality-). In Experiment 2, we included a condition in which participants believed that the co-actor intentionally controlled the response button with a Brain-Computer Interface (BCI) while placing the response finger clearly besides the response button, so that the causal relationship between agent and action effect was perceptually disrupted (agency-/intentionality+). As a control condition, the response button was computer controlled while the co-actor placed the response finger besides the response button (agency-/intentionality-). Experiment 1 showed that the JSE is present with an intentional co-actor and causality between co-actor and action effect, but absent with an unintentional co-actor and a lack of causality between co-actor and action effect. Experiment 2 showed that the JSE is absent with an intentional co-actor, but no causality between co-actor and action effect. Our findings indicate an important role of the co-actor's agency for the JSE. They also suggest that the attribution of agency has a strong perceptual basis.

Establishing causality in the decline and deformity of amphibians: The amphibian research and monitoring initiative model

USGS Publications Warehouse

Little, E.E.; Bridges, C.M.; Linder, G.; Boone, M.; ,

2003-01-01

Research to date has indicated that a range of environmental variables such as disease, parasitism, predation, competition, environmental contamination, solar ultraviolet radiation, climate change, or habitat alteration may be responsible for declining amphibian populations and the appearance of deformed organisms, yet in many cases no definitive environmental variable stands out as a causal factor. Multiple Stressors are often present in the habitat, and interactions among these can magnify injury to biota. This raises the possibility that the additive or synergistic impact of these Stressors may be the underlying cause of amphibian declines. Effective management for the restoration of amphibian populations requires the identification of causal factors contributing to their declines. A systematic approach to determine causality is especially important because initial impressions may be misleading or ambiguous. In addition, the evaluation of amphibian populations requires consideration of a broader spatial scale than commonly used in regulatory monitoring. We describe a systematic three-tiered approach to determine causality in amphibian declines and deformities. Tier 1 includes an evaluation of historic databases and extant data and would involve a desktop synopsis of the status of various stressors as well as site visits. Tier 2 studies are iterative, hypothesis driven studies beginning with general tests and continuing with analyses of increasing complexity as certain stressors are identified for further investigation. Tier 3 applies information developed in Tier 2 as predictive indicators of habitats and species at risk over broad landscape scales and provides decision support for the adaptive management of amphibian recovery. This comprehensive, tiered program could provide a mechanistic approach to identifying and addressing specific stressors responsible for amphibian declines across various landscapes.

Evaluation of crash rates and causal factors for high-risk locations on rural and urban two-lane highways in Virginia.

DOT National Transportation Integrated Search

2008-01-01

Considerable efforts have been made in recent years to make highway travel safer. Traffic engineers continue to emphasize the identification of causal factors for crashes on individual sections and on different functional classes of highways as an ar...

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

PubMed Central

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

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

PubMed

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.

Users' and GPs' causal attributions of illegal substance use: an exploratory interview study.

PubMed

Wynn, Rolf; Karlsen, Kjetil; Lorntzsen, Bianca; Bjerke, Trond Nergaard; Bergvik, Svein

2009-08-01

There is a need to explore the beliefs regarding the causes of illegal substance use of the people who themselves use the substances (SU) and their GPs. Increased knowledge about such beliefs--often referred to as causal attributions--may improve mutual understanding and communication between SU and GPs. Eight SU and five GPs were interviewed about the causes of illegal substance use. They also talked about how substance use was discussed in consultations. Data were analysed qualitatively. Both the SU and the GPs believed that several factors usually were important in each case of illegal substance use. The SU more often than the GPs emphasised the positive aspects of illegal substance use. We discerned five main causes: biological, social, lack of self-control, positive experiences, and chance. Several of the SU and GPs emphasised that it was difficult to communicate about substance use. The GPs and the SU believed illegal substance use is caused by many factors, including biological, social, and lack of self-control. Communicating about illegal substance use is challenging. GPs should be aware of the clinical importance of causal attributions and should explore beliefs held by SU about the causes of their substance use.

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

PubMed

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.

[Causal "cancer personality" attribution--an expression of maladaptive coping with illness?].

PubMed

Faller, H; Lang, H; Schilling, S

1996-01-01

In psycho-oncology, the concept of a "cancer-prone personality" has gained some attention. This notion means that persons who try to stay pseudo-normal in spite of severe life stress, suppress negative emotions, particularly anger, and sacrifice themselves for other people without uttering any personal demands, are at a high risk to develop cancer. However, it has been demonstrated by previous research that features of the cancer-prone personality could only be found if the ill person was convinced to suffer from cancer, irrespective of what the factual diagnosis was. Thus it can be concluded that at least some aspects of the so called cancer personality might be the results of coping with the belief of having cancer. The present study had the objective to describe causal attributions to psychosocial factors in cancer patients, and to find out if these were connected with emotional state and coping. N = 120 newly diagnosed lung cancer patients were included in the study. The instruments consisted of a semi-structured interview, a check-list of subjective causal factors, self-reports and interviewer ratings on emotional state and standardised questionnaires about depression and coping. Patients who made a psychosocial causal attribution proved to suffer from greater emotional distress, to be more depressed and less hopeful than other patients. This difference seemed to be mediated by a depressive way of coping with the illness (brooding, wrangling). Thus, an attribution of the illness to psychological factors seems indicative of a maladaptive way of coping with illness. This result is supported by similar findings of previous research. The question is put up to discussion if the psychosomatic concept of a cancer personality may reflect patients' subjective theories which in turn may be the expression of their depressive coping modes.

Causal Effect of Self-esteem on Cigarette Smoking Stages in Adolescents: Coarsened Exact Matching in a Longitudinal Study.

PubMed

Khosravi, Ahmad; Mohammadpoorasl, Asghar; Holakouie-Naieni, Kourosh; Mahmoodi, Mahmood; Pouyan, Ali Akbar; Mansournia, Mohammad Ali

2016-12-01

Identification of the causal impact of self-esteem on smoking stages faces seemingly insurmountable problems in observational data, where self-esteem is not manipulable by the researcher and cannot be assigned randomly. The aim of this study was to find out if weaker self-esteem in adolescence is a risk factor of cigarette smoking in a longitudinal study in Iran. In this longitudinal study, 4,853 students (14-18 years) completed a self-administered multiple-choice anonym questionnaire. The students were evaluated twice, 12 months apart. Students were matched based on coarsened exact matching on pretreatment variables, including age, gender, smoking stages at the first wave of study, socioeconomic status, general risk-taking behavior, having a smoker in the family, having a smoker friend, attitude toward smoking, and self-injury, to ensure statistically equivalent comparison groups. Self-esteem was measured using the Rosenberg 10-item questionnaire and were classified using a latent class analysis. After matching, the effect of self-esteem was evaluated using a multinomial logistic model. In the causal fitted model, for adolescents with weaker self-esteem relative to those with stronger self-esteem, the relative risk for experimenters and regular smokers relative to nonsmokers would be expected to increase by a factor of 2.2 (1.9-2.6) and 2.0 (1.5-2.6), respectively. Using a causal approach, our study indicates that low self-esteem is consistently associated with progression in cigarette smoking stages.

Causal inference between bioavailability of heavy metals and environmental factors in a large-scale region.

PubMed

Liu, Yuqiong; Du, Qingyun; Wang, Qi; Yu, Huanyun; Liu, Jianfeng; Tian, Yu; Chang, Chunying; Lei, Jing

2017-07-01

The causation between bioavailability of heavy metals and environmental factors are generally obtained from field experiments at local scales at present, and lack sufficient evidence from large scales. However, inferring causation between bioavailability of heavy metals and environmental factors across large-scale regions is challenging. Because the conventional correlation-based approaches used for causation assessments across large-scale regions, at the expense of actual causation, can result in spurious insights. In this study, a general approach framework, Intervention calculus when the directed acyclic graph (DAG) is absent (IDA) combined with the backdoor criterion (BC), was introduced to identify causation between the bioavailability of heavy metals and the potential environmental factors across large-scale regions. We take the Pearl River Delta (PRD) in China as a case study. The causal structures and effects were identified based on the concentrations of heavy metals (Zn, As, Cu, Hg, Pb, Cr, Ni and Cd) in soil (0-20 cm depth) and vegetable (lettuce) and 40 environmental factors (soil properties, extractable heavy metals and weathering indices) in 94 samples across the PRD. Results show that the bioavailability of heavy metals (Cd, Zn, Cr, Ni and As) was causally influenced by soil properties and soil weathering factors, whereas no causal factor impacted the bioavailability of Cu, Hg and Pb. No latent factor was found between the bioavailability of heavy metals and environmental factors. The causation between the bioavailability of heavy metals and environmental factors at field experiments is consistent with that on a large scale. The IDA combined with the BC provides a powerful tool to identify causation between the bioavailability of heavy metals and environmental factors across large-scale regions. Causal inference in a large system with the dynamic changes has great implications for system-based risk management. Copyright © 2017 Elsevier Ltd. All rights reserved.

Beliefs and perceptions about the causes of breast cancer: a case-control study.

PubMed

Thomson, Allyson K; Heyworth, Jane S; Girschik, Jennifer; Slevin, Terry; Saunders, Christobel; Fritschi, Lin

2014-08-21

Attributions of causality are common for many diseases, including breast cancer. The risk of developing breast cancer can be reduced by modifications to lifestyle and behaviours to minimise exposure to specific risk factors, such as obesity. However, these modifications will only occur if women believe that certain behaviours/lifestyle factors have an impact on the development of breast cancer. The Breast Cancer, Environment and Employment Study is a case-control study of breast cancer conducted in Western Australia between 2009 and 2011. As part of the study 1109 women with breast cancer and 1633 women without the disease completed a Risk Perception Questionnaire in which they were asked in an open-ended question for specific cause/s to the development of breast cancer in themselves or in others. The study identified specific causal beliefs, and assessed differences in the beliefs between women with and without breast cancer. The most common attributions in women without breast cancer were to familial or inherited factors (77.6%), followed by lifestyle factors, such as poor diet and smoking (47.1%), and environmental factors, such as food additives (45.4%). The most common attributions in women with breast cancer were to mental or emotional factors (46.3%), especially stress, followed by lifestyle factors (38.6%) and physiological factors (37.5%), particularly relating to hormonal history. While the majority of participants in this study provided one or more causal attributions for breast cancer, many of the reported risk factors do not correspond to those generally accepted by the scientific community. These misperceptions could be having a significant impact on the success of prevention and early detection programs that seek to minimise the pain and suffering caused by this disease. In particular, women who have no family history of the disease may not work to minimise their exposure to the modifiable risk factors.

Causal reports: Context-dependent contributions of intuitive physics and visual impressions of launching.

PubMed

Vicovaro, Michele

2018-05-01

Everyday causal reports appear to be based on a blend of perceptual and cognitive processes. Causality can sometimes be perceived automatically through low-level visual processing of stimuli, but it can also be inferred on the basis of an intuitive understanding of the physical mechanism that underlies an observable event. We investigated how visual impressions of launching and the intuitive physics of collisions contribute to the formation of explicit causal responses. In Experiment 1, participants observed collisions between realistic objects differing in apparent material and hence implied mass, whereas in Experiment 2, participants observed collisions between abstract, non-material objects. The results of Experiment 1 showed that ratings of causality were mainly driven by the intuitive physics of collisions, whereas the results of Experiment 2 provide some support to the hypothesis that ratings of causality were mainly driven by visual impressions of launching. These results suggest that stimulus factors and experimental design factors - such as the realism of the stimuli and the variation in the implied mass of the colliding objects - may determine the relative contributions of perceptual and post-perceptual cognitive processes to explicit causal responses. A revised version of the impetus transmission heuristic provides a satisfactory explanation for these results, whereas the hypothesis that causal responses and intuitive physics are based on the internalization of physical laws does not. Copyright © 2018 Elsevier B.V. All rights reserved.

Evaluating the potential for watershed restoration to reduce nutrient loading to Upper Klamath Lake, Oregon

USGS Publications Warehouse

McCormick, Paul V.; Campbell, Sharon G.

2007-01-01

A literature review of best management practices to reduce nutrient loading was performed to provide information for resource managers in the Klamath Basin, Oregon. Although BMPs have already been implemented in the watershed, some sense of their effectiveness in reducing phosphorus loading and their cost for installation and maintenance is still lacking. This report discusses both causes of nutrient loading and a wide-variety of BMPs used to treat or reduce causal factors. We specifically focused on cattle grazing as the principal land-use and causal factor for nutrient loading in the Klamath Basin above Upper Klamath Lake, Oregon. Several BMP types, including stream corridor fencing, riparian buffer strips and constructed wetlands, seem to have potential for reducing phosphorus loading that may result from cattle grazing. However, no single BMP is likely to be the most effective in all locations or situations.

Climate Change and Collective Violence.

PubMed

Levy, Barry S; Sidel, Victor W; Patz, Jonathan A

2017-03-20

Climate change is causing increases in temperature, changes in precipitation and extreme weather events, sea-level rise, and other environmental impacts. It is also causing or contributing to heat-related disorders, respiratory and allergic disorders, infectious diseases, malnutrition due to food insecurity, and mental health disorders. In addition, increasing evidence indicates that climate change is causally associated with collective violence, generally in combination with other causal factors. Increased temperatures and extremes of precipitation with their associated consequences, including resultant scarcity of cropland and other key environmental resources, are major pathways by which climate change leads to collective violence. Public health professionals can help prevent collective violence due to climate change (a) by supporting mitigation measures to reduce greenhouse gas emissions, (b) by promoting adaptation measures to address the consequences of climate change and to improve community resilience, and (c) by addressing underlying risk factors for collective violence, such as poverty and socioeconomic disparities.

A Hierarchical Causal Taxonomy of Psychopathology across the Life Span

PubMed Central

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

Identifying causal linkages between environmental variables and African conflicts

NASA Astrophysics Data System (ADS)

Nguy-Robertson, A. L.; Dartevelle, S.

2017-12-01

Environmental variables that contribute to droughts, flooding, and other natural hazards are often identified as factors contributing to conflict; however, few studies attempt to quantify these causal linkages. Recent research has demonstrated that the environment operates within a dynamical system framework and the influence of variables can be identified from convergent cross mapping (CCM) between shadow manifolds. We propose to use CCM to identify causal linkages between environmental variables and incidences of conflict. This study utilizes time series data from Climate Forecast System ver. 2 and MODIS satellite sensors processed using Google Earth Engine to aggregate country and regional trends. These variables are then compared to Armed Conflict Location & Event Data Project observations at similar scales. Results provide relative rankings of variables and their linkage to conflict. Being able to identify which factors contributed more strongly to a conflict can allow policy makers to prepare solutions to mitigate future crises. Knowledge of the primary environmental factors can lead to the identification of other variables to examine in the causal network influencing conflict.

Modeling drivers of phosphorus loads in Chesapeake Bay tributaries and inferences about long-term change

USGS Publications Warehouse

Ryberg, Karen R.; Blomquist, Joel; Sprague, Lori A.; Sekellick, Andrew J.; Keisman, Jennifer

2018-01-01

Causal attribution of changes in water quality often consists of correlation, qualitative reasoning, listing references to the work of others, or speculation. To better support statements of attribution for water-quality trends, structural equation modeling was used to model the causal factors of total phosphorus loads in the Chesapeake Bay watershed. By transforming, scaling, and standardizing variables, grouping similar sites, grouping some causal factors into latent variable models, and using methods that correct for assumption violations, we developed a structural equation model to show how causal factors interact to produce total phosphorus loads. Climate (in the form of annual total precipitation and the Palmer Hydrologic Drought Index) and anthropogenic inputs are the major drivers of total phosphorus load in the Chesapeake Bay watershed. Increasing runoff due to natural climate variability is offsetting purposeful management actions that are otherwise decreasing phosphorus loading; consequently, management actions may need to be reexamined to achieve target reductions in the face of climate variability.

Causal Factors Influencing Adversity Quotient of Twelfth Grade and Third-Year Vocational Students

ERIC Educational Resources Information Center

Pangma, Rachapoom; Tayraukham, Sombat; Nuangchalerm, Prasart

2009-01-01

Problem statement: The aim of this research was to study the causal factors influencing students' adversity between twelfth grade and third-year vocational students in Sisaket province, Thailand. Six hundred and seventy two of twelfth grade and 376 third-year vocational students were selected by multi-stage random sampling techniques. Approach:…

Knowing Who Dunnit: Infants Identify the Causal Agent in an Unseen Causal Interaction

ERIC Educational Resources Information Center

Saxe, Rebecca; Tzelnic, Tania; Carey, Susan

2007-01-01

Preverbal infants can represent the causal structure of events, including distinguishing the agentive and receptive roles and categorizing entities according to stable causal dispositions. This study investigated how infants combine these 2 kinds of causal inference. In Experiments 1 and 2, 9.5-month-olds used the position of a human hand or a…

A Descriptive Survey of Inflammatory Bowel Disease within the Active Army Population (1971-1982).

DTIC Science & Technology

1985-06-01

psychological response to stress has an impact on the disease once it is established. This includes the recurrence of the disease as well as its severity. An...underlying question that remains is: Which is the causal agent, the disease or the psychological response to the disease? The inflammatory process of the... psychological factor. Only with increased knowledge of their epidemiologic factors will researchers begin to understand the basis for these devastating

Evaluating a Computational Model of Social Causality and Responsibility

DTIC Science & Technology

2006-01-01

Evaluating a Computational Model of Social Causality and Responsibility Wenji Mao University of Southern California Institute for Creative...empirically evaluate a computa- tional model of social causality and responsibility against human social judgments. Results from our experimental...developed a general computational model of social cau- sality and responsibility [10, 11] that formalizes the factors people use in reasoning about

Myalgic encephalomyelitis, chronic fatigue syndrome: An infectious disease.

PubMed

Underhill, R A

2015-12-01

The etiology of myalgic encephalomyelitis also known as chronic fatigue syndrome or ME/CFS has not been established. Controversies exist over whether it is an organic disease or a psychological disorder and even the existence of ME/CFS as a disease entity is sometimes denied. Suggested causal hypotheses have included psychosomatic disorders, infectious agents, immune dysfunctions, autoimmunity, metabolic disturbances, toxins and inherited genetic factors. Clinical, immunological and epidemiological evidence supports the hypothesis that: ME/CFS is an infectious disease; the causal pathogen persists in patients; the pathogen can be transmitted by casual contact; host factors determine susceptibility to the illness; and there is a population of healthy carriers, who may be able to shed the pathogen. ME/CFS is endemic globally as sporadic cases and occasional cluster outbreaks (epidemics). Cluster outbreaks imply an infectious agent. An abrupt flu-like onset resembling an infectious illness occurs in outbreak patients and many sporadic patients. Immune responses in sporadic patients resemble immune responses in other infectious diseases. Contagion is shown by finding secondary cases in outbreaks, and suggested by a higher prevalence of ME/CFS in sporadic patients' genetically unrelated close contacts (spouses/partners) than the community. Abortive cases, sub-clinical cases, and carrier state individuals were found in outbreaks. The chronic phase of ME/CFS does not appear to be particularly infective. Some healthy patient-contacts show immune responses similar to patients' immune responses, suggesting exposure to the same antigen (a pathogen). The chronicity of symptoms and of immune system changes and the occurrence of secondary cases suggest persistence of a causal pathogen. Risk factors which predispose to developing ME/CFS are: a close family member with ME/CFS; inherited genetic factors; female gender; age; rest/activity; previous exposure to stress or toxins; various infectious diseases preceding the onset of ME/CFS; and occupational exposure of health care professionals. The hypothesis implies that ME/CFS patients should not donate blood or tissue and usual precautions should be taken when handling patients' blood and tissue. No known pathogen has been shown to cause ME/CFS. Confirmation of the hypothesis requires identification of a causal pathogen. Research should focus on a search for unknown and known pathogens. Finding a causal pathogen could assist with diagnosis; help find a biomarker; enable the development of anti-microbial treatments; suggest preventive measures; explain pathophysiological findings; and reassure patients about the validity of their symptoms.

Evaluating the Intervention-Based Evidence Surrounding the Causal Role of Breakfast on Markers of Weight Management, with Specific Focus on Breakfast Composition and Size1234

PubMed Central

Leidy, Heather J; Gwin, Jess A; Roenfeldt, Connor A; Zino, Adam Z; Shafer, Rebecca S

2016-01-01

Nutritional strategies are vitally needed to aid in the management of obesity. Cross-sectional and epidemiologic studies consistently demonstrate that breakfast consumption is strongly associated with a healthy body weight. However, the intervention-based long-term evidence supporting a causal role of breakfast consumption is quite limited and appears to be influenced by several key dietary factors, such as dietary protein, fiber, and energy content. This article provides a comprehensive review of the intervention-based literature that examines the effects of breakfast consumption on markers of weight management and daily food intake. In addition, specific focus on the composition and size (i.e., energy content) of the breakfast meal is included. Overall, there is limited evidence supporting (or refuting) the daily consumption of breakfast for body weight management and daily food intake. In terms of whether the type of breakfast influences these outcomes, there is accumulating evidence supporting the consumption of increased dietary protein and fiber content at breakfast, as well as the consumption of more energy during the morning hours. However, the majority of the studies that manipulated breakfast composition and content did not control for habitual breakfast behaviors, nor did these studies include a breakfast-skipping control arm. Thus, it is unclear whether the addition of these types of breakfast plays a causal role in weight management. Future research, including large randomized controlled trials of longer-term (i.e., ≥6 mo) duration with a focus on key dietary factors, is critical to begin to assess whether breakfast recommendations are appropriate for the prevention and/or treatment of obesity. PMID:27184285

Does sufficient evidence exist to support a causal association between vitamin D status and cardiovascular disease risk? An assessment using Hill's criteria for causality.

PubMed

Weyland, Patricia G; Grant, William B; Howie-Esquivel, Jill

2014-09-02

Serum 25-hydroxyvitamin D (25(OH)D) levels have been found to be inversely associated with both prevalent and incident cardiovascular disease (CVD) risk factors; dyslipidemia, hypertension and diabetes mellitus. This review looks for evidence of a causal association between low 25(OH)D levels and increased CVD risk. We evaluated journal articles in light of Hill's criteria for causality in a biological system. The results of our assessment are as follows. Strength of association: many randomized controlled trials (RCTs), prospective and cross-sectional studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors. Consistency of observed association: most studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors in various populations, locations and circumstances. Temporality of association: many RCTs and prospective studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors. Biological gradient (dose-response curve): most studies assessing 25(OH)D levels and CVD risk found an inverse association exhibiting a linear biological gradient. Plausibility of biology: several plausible cellular-level causative mechanisms and biological pathways may lead from a low 25(OH)D level to increased risk for CVD with mediators, such as dyslipidemia, hypertension and diabetes mellitus. Experimental evidence: some well-designed RCTs found increased CVD risk factors with decreasing 25(OH)D levels. Analogy: the association between serum 25(OH)D levels and CVD risk is analogous to that between 25(OH)D levels and the risk of overall cancer, periodontal disease, multiple sclerosis and breast cancer. all relevant Hill criteria for a causal association in a biological system are satisfied to indicate a low 25(OH)D level as a CVD risk factor.

Expert explanations of honeybee losses in areas of extensive agriculture in France: Gaucho® compared with other supposed causal factors

NASA Astrophysics Data System (ADS)

Maxim, L.; van der Sluijs, J. P.

2010-01-01

Debates on causality are at the core of controversies as regards environmental changes. The present paper presents a new method for analyzing controversies on causality in a context of social debate and the results of its empirical testing. The case study used is the controversy as regards the role played by the insecticide Gaucho®, compared with other supposed causal factors, in the substantial honeybee (Apis mellifera L.) losses reported to have occurred in France between 1994 and 2004. The method makes use of expert elicitation of the perceived strength of evidence regarding each of Bradford Hill's causality criteria, as regards the link between each of eight possible causal factors identified in attempts to explain each of five signs observed in honeybee colonies. These judgments are elicited from stakeholders and experts involved in the debate, i.e., representatives of Bayer Cropscience, of the Ministry of Agriculture, of the French Food Safety Authority, of beekeepers and of public scientists. We show that the intense controversy observed in confused and passionate public discourses is much less salient when the various arguments are structured using causation criteria. The contradictions between the different expert views have a triple origin: (1) the lack of shared definition and quantification of the signs observed in colonies; (2) the lack of specialist knowledge on honeybees; and (3) the strategic discursive practices associated with the lack of trust between experts representing stakeholders having diverging stakes in the case.

Age- and sex-specific causal effects of adiposity on cardiovascular risk factors.

PubMed

Fall, Tove; Hägg, Sara; Ploner, Alexander; Mägi, Reedik; Fischer, Krista; Draisma, Harmen H M; Sarin, Antti-Pekka; Benyamin, Beben; Ladenvall, Claes; Åkerlund, Mikael; Kals, Mart; Esko, Tõnu; Nelson, Christopher P; Kaakinen, Marika; Huikari, Ville; Mangino, Massimo; Meirhaeghe, Aline; Kristiansson, Kati; Nuotio, Marja-Liisa; Kobl, Michael; Grallert, Harald; Dehghan, Abbas; Kuningas, Maris; de Vries, Paul S; de Bruijn, Renée F A G; Willems, Sara M; Heikkilä, Kauko; Silventoinen, Karri; Pietiläinen, Kirsi H; Legry, Vanessa; Giedraitis, Vilmantas; Goumidi, Louisa; Syvänen, Ann-Christine; Strauch, Konstantin; Koenig, Wolfgang; Lichtner, Peter; Herder, Christian; Palotie, Aarno; Menni, Cristina; Uitterlinden, André G; Kuulasmaa, Kari; Havulinna, Aki S; Moreno, Luis A; Gonzalez-Gross, Marcela; Evans, Alun; Tregouet, David-Alexandre; Yarnell, John W G; Virtamo, Jarmo; Ferrières, Jean; Veronesi, Giovanni; Perola, Markus; Arveiler, Dominique; Brambilla, Paolo; Lind, Lars; Kaprio, Jaakko; Hofman, Albert; Stricker, Bruno H; van Duijn, Cornelia M; Ikram, M Arfan; Franco, Oscar H; Cottel, Dominique; Dallongeville, Jean; Hall, Alistair S; Jula, Antti; Tobin, Martin D; Penninx, Brenda W; Peters, Annette; Gieger, Christian; Samani, Nilesh J; Montgomery, Grant W; Whitfield, John B; Martin, Nicholas G; Groop, Leif; Spector, Tim D; Magnusson, Patrik K; Amouyel, Philippe; Boomsma, Dorret I; Nilsson, Peter M; Järvelin, Marjo-Riitta; Lyssenko, Valeriya; Metspalu, Andres; Strachan, David P; Salomaa, Veikko; Ripatti, Samuli; Pedersen, Nancy L; Prokopenko, Inga; McCarthy, Mark I; Ingelsson, Erik

2015-05-01

Observational studies have reported different effects of adiposity on cardiovascular risk factors across age and sex. Since cardiovascular risk factors are enriched in obese individuals, it has not been easy to dissect the effects of adiposity from those of other risk factors. We used a Mendelian randomization approach, applying a set of 32 genetic markers to estimate the causal effect of adiposity on blood pressure, glycemic indices, circulating lipid levels, and markers of inflammation and liver disease in up to 67,553 individuals. All analyses were stratified by age (cutoff 55 years of age) and sex. The genetic score was associated with BMI in both nonstratified analysis (P = 2.8 × 10(-107)) and stratified analyses (all P < 3.3 × 10(-30)). We found evidence of a causal effect of adiposity on blood pressure, fasting levels of insulin, C-reactive protein, interleukin-6, HDL cholesterol, and triglycerides in a nonstratified analysis and in the <55-year stratum. Further, we found evidence of a smaller causal effect on total cholesterol (P for difference = 0.015) in the ≥55-year stratum than in the <55-year stratum, a finding that could be explained by biology, survival bias, or differential medication. In conclusion, this study extends previous knowledge of the effects of adiposity by providing sex- and age-specific causal estimates on cardiovascular risk factors. © 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

A hierarchical causal taxonomy of psychopathology across the life span.

PubMed

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

2017-02-01

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 3 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. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Causal Relationships between the Psychological Acceptance Process of Athletic Injury and Athletic Rehabilitation Behavior

PubMed Central

Tatsumi, Tomonori; Takenouchi, Takashi

2014-01-01

[Purpose] The purpose of this study was to examine the causal relationships between the psychological acceptance process of athletic injury and athletic-rehabilitation behavior. [Subjects] One hundred forty-four athletes who had injury experiences participated in this study, and 133 (mean age = 20.21 years, SD = 1.07; mean weeks without playing sports = 7.97 weeks, SD = 11.26) of them provided valid questionnaire responses which were subjected to analysis. [Methods] The subjects were asked to answer our originally designed questionnaire, the Psychosocial Recovery Factor Scale (PSRF-S), and two other pre-existing scales, the Athletic Injury Psychological Acceptance Scale and the Athletic-Rehabilitation Dedication Scale. [Results] The results of factor analysis indicate “emotional stability”, “social competence in the team”, “temporal perspective”, and “communication with the teammates” are factors of the PSRF-S. Lastly, the causal model in which psychosocial recovery factors are mediated by psychological acceptance of athletic injury, and influence on rehabilitation behaviors, was examined using structural equation modeling (SEM). The results of SEM indicate that the factors of emotional stability and temporal perspective are mediated by the psychological acceptance of the injury, which positively influences athletic-rehabilitation dedication. [Conclusion] The causal model was confirmed to be valid. PMID:25202190

Guidelines for developing and updating Bayesian belief networks applied to ecological modeling and conservation.

Treesearch

B.G. Marcot; J.D. Steventon; G.D. Sutherland; R.K. McCann

2006-01-01

We provide practical guidelines for developing, testing, and revising Bayesian belief networks (BBNs). Primary steps in this process include creating influence diagrams of the hypothesized "causal web" of key factors affecting a species or ecological outcome of interest; developing a first, alpha-level BBN model from the influence diagram; revising the model...

Persistence among Non-Traditional Hispanic College Students: A Causal Model. ASHE Annual Meeting Paper.

ERIC Educational Resources Information Center

Nora, Amaury; Kraemer, Barbara; Itzen, Richard

This study examined environmental and institutional factors affecting persistence of Hispanic college students. The sample of 324 first- and second-year students surveyed in the spring of 1995 included students who were enrolled in programs at a private, Illinois, bilingual junior college which were established to educate students who were older,…

HIV prevention for South African youth: which interventions work? A systematic review of current evidence

PubMed Central

2010-01-01

Background In South Africa, HIV prevalence among youth aged 15-24 is among the world's highest. Given the urgent need to identify effective HIV prevention approaches, this review assesses the evidence base for youth HIV prevention in South Africa. Methods Systematic, analytical review of HIV prevention interventions targeting youth in South Africa since 2000. Critical assessment of interventions in 4 domains: 1) study design and outcomes, 2) intervention design (content, curriculum, theory, adaptation process), 3) thematic focus and HIV causal pathways, 4) intervention delivery (duration, intensity, who, how, where). Results Eight youth HIV prevention interventions were included; all were similar in HIV prevention content and objectives, but varied in thematic focus, hypothesised causal pathways, theoretical basis, delivery method, intensity and duration. Interventions were school- (5) or group-based (3), involving in- and out-of-school youth. Primary outcomes included HIV incidence (2), reported sexual risk behavior alone (4), or with alcohol use (2). Interventions led to reductions in STI incidence (1), and reported sexual or alcohol risk behaviours (5), although effect size varied. All but one targeted at least one structural factor associated with HIV infection: gender and sexual coercion (3), alcohol/substance use (2), or economic factors (2). Delivery methods and formats varied, and included teachers (5), peer educators (5), and older mentors (1). School-based interventions experienced frequent implementation challenges. Conclusions Key recommendations include: address HIV social risk factors, such as gender, poverty and alcohol; target the structural and institutional context; work to change social norms; and engage schools in new ways, including participatory learning. PMID:20187957

Cavernosal Abscess due to Streptococcus Anginosus: A Case Report and Comprehensive Review of the Literature

PubMed Central

Dugdale, Caitlin M.; Tompkins, Andrew J.; Reece, Rebecca M.; Gardner, Adrian F.

2013-01-01

Corpus cavernosum abscesses are uncommon with only 23 prior reports in the literature. Several precipitating factors for cavernosal infections have been described including injection therapy for erectile dysfunction, trauma, and priapism. Common causal organisms include Staphylococcus aureus, Streptococci, and Bacteroides. We report a unique case of a corpus cavernosum abscess due to proctitis with hematological seeding and review the literature on cavernosal abscesses. PMID:24917758

Failure to define low back pain as a disease or an episode renders research on causality unsuitable: results of a systematic review.

PubMed

Ardakani, Emad M; Leboeuf-Yde, Charlotte; Walker, Bruce F

2018-01-01

Causative factors may be different for the very first onset of symptoms of the 'disease' of low back pain (LBP) than for ensuing episodes that occur after a pain-free period. This differentiation hinges on a life-time absence of low back pain at first onset and short-term absence for further episodes. In this systematic review, we explored whether researchers make these distinctions when investigating the causality of LBP. A literature search of PUBMED, CINAHL, and SCOPUS databases was performed from January 2010 until September 2016 using the search terms 'low back pain' or 'back pain' and 'risk factor' or 'caus*' or 'predict*' or 'onset' or 'first-time' or 'inception' or 'incidence'. Two reviewers extracted information on study design, types of episodes of back pain to distinguish the disease of LBP and recurring episodes, and also to determine the definitions of disease- or pain-free periods. Thirty-three articles purporting to study causes of LBP were included. Upon scrutiny, 31 of the 33 articles were unclear as to what type of causality they were studying, that of the 'disease' or the episode, or a mere association with LBP. Only 9 studies used a prospective study design. Five studies appeared to investigate the onset of the disease of LBP, however, only one study truly captured the first incidence of LBP, which was the result of sports injury. Six appeared to study episodes but only one clearly related to the concept of episodes. Therefore, among those 11 studies, nine included both first-time LBP and episodes of LBP. Consequently, 22 studies related to the prevalence of LBP, as they probably included a mixture of first-time, recurring and ongoing episodes without distinction. Recent literature concerning the causality of LBP does not differentiate between the 'disease' of LBP and its recurring episodes mainly due to a lack of a clear definition of absence of LBP at baseline. Therefore, current research is not capable of providing a valid answer on this topic.

Causal inference in public health.

PubMed

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.

The Relative Predictive Contribution and Causal Role of Phoneme Awareness, Rhyme Awareness, and Verbal Short-Term Memory in Reading Skills: A Review

ERIC Educational Resources Information Center

Melby-Lervag, Monica

2012-01-01

The acknowledgement that educational achievement is highly dependent on successful reading development has led to extensive research on its underlying factors. A strong argument has been made for a causal relationship between reading and phoneme awareness; similarly, causal relations have been suggested for reading with short-term memory and rhyme…

The effects of stress-tension on depression and anxiety symptoms: evidence from a novel twin modelling analysis.

PubMed

Davey, C G; López-Solà, C; Bui, M; Hopper, J L; Pantelis, C; Fontenelle, L F; Harrison, B J

2016-11-01

Negative mood states are composed of symptoms of depression and anxiety, and by a third factor related to stress, tension and irritability. We sought to clarify the nature of the relationships between the factors by studying twin pairs. A total of 503 monozygotic twin pairs completed the Depression Anxiety Stress Scales (DASS), an instrument that assesses symptoms of depression, anxiety and stress-tension. We applied a recently developed twin regression methodology - Inference about Causation from Examination of FAmiliaL CONfounding (ICE FALCON) - to test for evidence consistent with the existence of 'causal' influences between the DASS factors. There was evidence consistent with the stress-tension factor having a causal influence on both the depression (p < 0.0001) and anxiety factors (p = 0.001), and for the depression factor having a causal influence on the anxiety factor (p < 0.001). Our findings suggest a critical role for stress-tension in the structure of negative mood states, and that interventions that target it may be particularly effective in reducing depression and anxiety symptoms.

Tools for Detecting Causality in Space Systems

NASA Astrophysics Data System (ADS)

Johnson, J.; Wing, S.

2017-12-01

Complex systems such as the solar and magnetospheric envivonment often exhibit patterns of behavior that suggest underlying organizing principles. Causality is a key organizing principle that is particularly difficult to establish in strongly coupled nonlinear systems, but essential for understanding and modeling the behavior of systems. While traditional methods of time-series analysis can identify linear correlations, they do not adequately quantify the distinction between causal and coincidental dependence. We discuss tools for detecting causality including: granger causality, transfer entropy, conditional redundancy, and convergent cross maps. The tools are illustrated by applications to magnetospheric and solar physics including radiation belt, Dst (a magnetospheric state variable), substorm, and solar cycle dynamics.

Socioeconomic inequality in health in the British household panel: Tests of the social causation, health selection and the indirect selection hypothesis using dynamic fixed effects panel models.

PubMed

Foverskov, Else; Holm, Anders

2016-02-01

Despite social inequality in health being well documented, it is still debated which causal mechanism best explains the negative association between socioeconomic position (SEP) and health. This paper is concerned with testing the explanatory power of three widely proposed causal explanations for social inequality in health in adulthood: the social causation hypothesis (SEP determines health), the health selection hypothesis (health determines SEP) and the indirect selection hypothesis (no causal relationship). We employ dynamic data of respondents aged 30 to 60 from the last nine waves of the British Household Panel Survey. Household income and location on the Cambridge Scale is included as measures of different dimensions of SEP and health is measured as a latent factor score. The causal hypotheses are tested using a time-based Granger approach by estimating dynamic fixed effects panel regression models following the method suggested by Anderson and Hsiao. We propose using this method to estimate the associations over time since it allows one to control for all unobserved time-invariant factors and hence lower the chances of biased estimates due to unobserved heterogeneity. The results showed no proof of the social causation hypothesis over a one to five year period and limited support for the health selection hypothesis was seen only for men in relation to HH income. These findings were robust in multiple sensitivity analysis. We conclude that the indirect selection hypothesis may be the most important in explaining social inequality in health in adulthood, indicating that the well-known cross-sectional correlations between health and SEP in adulthood seem not to be driven by a causal relationship, but instead by dynamics and influences in place before the respondents turn 30 years old that affect both their health and SEP onwards. The conclusion is limited in that we do not consider the effect of specific diseases and causal relationships in adulthood may be present over a longer timespan than 5 years. Copyright © 2015 Elsevier Ltd. All rights reserved.

Dual Causality and the Autonomy of Biology.

PubMed

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.

[Urinary incontinence as a risk factor for pressure sores does not withstand a critical examination].

PubMed

Krause, Tom; Anders, Jennifer; von Renteln-Kruse, Wolfgang

2005-10-01

The association between urinary incontinence and pressure sores is put down to various causes. Most frequently urinary wet and following maceration of the skin are mentioned. However, it is possible that urinary incontinence is only an indicator for other risk factors or a measure of the need for care without any causal relation to pressure sores. There are hardly any controlled or randomised studies; this lack of scientific evidence is problematic. Based on a case-control-study including data of 200 patients as well as on the existing models of explanation, the following study tries to examine critically the connections between pressure sores and urinary incontinence. Out of the patients in our study population 97.5 percent were incontinent. Different categories of the risk factor urinary incontinence and different dichotomisations have led to different statistical results. Statements concerning the connection between urinary incontinence and pressure sores have to be interpreted critically. The dependence of urinary incontinence on other risk factors such as patients' need for care or compliance suggests that the causal connection to pressure sores be not reduced to the influence of wetness. We advise to research connections between urinary incontinence and pressure sores in a methodologically appropriate setting.

Infant acetylcholine, dopamine, and melatonin dysregulation: Neonatal biomarkers and causal factors for ASD and ADHD phenotypes.

PubMed

Hellmer, Kahl; Nyström, Pär

2017-03-01

Autism spectrum disorders (ASD) and ADHD are common neurodevelopmental disorders that benefit from early intervention but currently suffer from late detection and diagnosis: neurochemical dysregulations are extant already at birth but clinical phenotypes are not distinguishable until preschool age or later. The vast heterogeneity between subjects' phenotypes relates to interaction between multiple unknown factors, making research on factor causality insurmountable. To unlock this situation we pose the hypothesis that atypical pupillary light responses from rods, cones, and the recently discovered ipRGC system reflect early acetylcholine, melatonin, and dopamine dysregulation that are sufficient but not necessary factors for developing ASD and/or ADHD disorders. Current technology allows non-invasive cost-efficient assessment already from the first postnatal month. The benefits of the current proposal are: identification of clinical subgroups based on cause rather than phenotypes; facilitation of research on other causal factors; neonatal prediction of later diagnoses; and guidance for targeted therapeutical intervention. Copyright © 2017 Elsevier Ltd. All rights reserved.

Granger causality revisited

PubMed Central

Friston, Karl J.; Bastos, André M.; Oswal, Ashwini; van Wijk, Bernadette; Richter, Craig; Litvak, Vladimir

2014-01-01

This technical paper offers a critical re-evaluation of (spectral) Granger causality measures in the analysis of biological timeseries. Using realistic (neural mass) models of coupled neuronal dynamics, we evaluate the robustness of parametric and nonparametric Granger causality. Starting from a broad class of generative (state-space) models of neuronal dynamics, we show how their Volterra kernels prescribe the second-order statistics of their response to random fluctuations; characterised in terms of cross-spectral density, cross-covariance, autoregressive coefficients and directed transfer functions. These quantities in turn specify Granger causality — providing a direct (analytic) link between the parameters of a generative model and the expected Granger causality. We use this link to show that Granger causality measures based upon autoregressive models can become unreliable when the underlying dynamics is dominated by slow (unstable) modes — as quantified by the principal Lyapunov exponent. However, nonparametric measures based on causal spectral factors are robust to dynamical instability. We then demonstrate how both parametric and nonparametric spectral causality measures can become unreliable in the presence of measurement noise. Finally, we show that this problem can be finessed by deriving spectral causality measures from Volterra kernels, estimated using dynamic causal modelling. PMID:25003817

Quantum Common Causes and Quantum Causal Models

NASA Astrophysics Data System (ADS)

Allen, John-Mark A.; Barrett, Jonathan; Horsman, Dominic C.; Lee, Ciarán M.; Spekkens, Robert W.

2017-07-01

Reichenbach's principle asserts that if two observed variables are found to be correlated, then there should be a causal explanation of these correlations. Furthermore, if the explanation is in terms of a common cause, then the conditional probability distribution over the variables given the complete common cause should factorize. The principle is generalized by the formalism of causal models, in which the causal relationships among variables constrain the form of their joint probability distribution. In the quantum case, however, the observed correlations in Bell experiments cannot be explained in the manner Reichenbach's principle would seem to demand. Motivated by this, we introduce a quantum counterpart to the principle. We demonstrate that under the assumption that quantum dynamics is fundamentally unitary, if a quantum channel with input A and outputs B and C is compatible with A being a complete common cause of B and C , then it must factorize in a particular way. Finally, we show how to generalize our quantum version of Reichenbach's principle to a formalism for quantum causal models and provide examples of how the formalism works.

The fuzzy cube and causal efficacy: representation of concomitant mechanisms in stroke.

PubMed

Jobe, Thomas H.; Helgason, Cathy M.

1998-04-01

Twentieth century medical science has embraced nineteenth century Boolean probability theory based upon two-valued Aristotelian logic. With the later addition of bit-based, von Neumann structured computational architectures, an epistemology based on randomness has led to a bivalent epidemiological methodology that dominates medical decision making. In contrast, fuzzy logic, based on twentieth century multi-valued logic, and computational structures that are content addressed and adaptively modified, has advanced a new scientific paradigm for the twenty-first century. Diseases such as stroke involve multiple concomitant causal factors that are difficult to represent using conventional statistical methods. We tested which paradigm best represented this complex multi-causal clinical phenomenon-stroke. We show that the fuzzy logic paradigm better represented clinical complexity in cerebrovascular disease than current probability theory based methodology. We believe this finding is generalizable to all of clinical science since multiple concomitant causal factors are involved in nearly all known pathological processes.

Non-Western students' causal reasoning about biologically adaptive changes in humans, other animals and plants: instructional and curricular implications

NASA Astrophysics Data System (ADS)

Mbajiorgu, Ngozika; Anidu, Innocent

2017-06-01

Senior secondary school students (N = 360), 14- to 18-year-olds, from the Igbo culture of eastern Nigeria responded to a questionnaire requiring them to give causal explanations of biologically adaptive changes in humans, other animals and plants. A student subsample (n = 36) was, subsequently, selected for in-depth interviews. Significant differences were found between prompts within the prompt categories, suggesting item feature effects. However, the most coherent pattern was found within the plant category as patterns differed for the mechanistic proximate (MP) reasoning category only. Patterns also differed highly significantly between the prompt categories, with patterns for teleology, MP, mechanistic ultimate and don't know categories similar for plants and other animals but different for the human category. Both urban and rural students recognise commonalities in causality between the three prompt categories, in that their preferences for causal explanations were similar across four reasoning categories. The rural students, however, were more likely than their urban counterparts to give multiple causal explanations in the span of a single response and less likely to attribute causal agency to God. Two factors, religious belief and language, for all the students; and one factor, ecological closeness to nature, for rural students were suspected to have produced these patterns.

The influence of farmer demographic characteristics on environmental behaviour: a review.

PubMed

Burton, Rob J F

2014-03-15

Many agricultural studies have observed a relationship between farmer demographic characteristics and environmental behaviours. These relationships are frequently employed in the construction of models, the identification of farmer types, or as part of more descriptive analyses aimed at understanding farmers' environmental behaviour. However, they have also often been found to be inconsistent or contradictory. Although a considerable body of literature has built up around the subject area, research has a tendency to focus on factors such as the direction, strength and consistency of the relationship - leaving the issue of causality largely to speculation. This review addresses this gap by reviewing literature on 4 key demographic variables: age, experience, education, and gender for hypothesised causal links. Overall the review indicates that the issue of causality is a complex one. Inconsistent relationships can be attributed to the presence of multiple causal pathways, the role of scheme factors in determining which pathway is important, inadequately specified measurements of demographic characteristics, and the treatment of non-linear causalities as linear. In addition, all demographic characteristics were perceived to be influenced (to varying extents) by cultural-historical patterns leading to cohort effects or socialised differences in the relationship with environmental behaviour. The paper concludes that more work is required on the issue of causality. Copyright © 2013 Elsevier Ltd. All rights reserved.

Subfertility factors rather than assisted conception factors affect cognitive and behavioural development of 4-year-old singletons.

PubMed

Schendelaar, Pamela; La Bastide-Van Gemert, Sacha; Heineman, Maas Jan; Middelburg, Karin J; Seggers, Jorien; Van den Heuvel, Edwin R; Hadders-Algra, Mijna

2016-12-01

Research on cognitive and behavioural development of children born after assisted conception is inconsistent. This prospective study aimed to explore underlying causal relationships between ovarian stimulation, in-vitro procedures, subfertility components and child cognition and behaviour. Participants were singletons born to subfertile couples after ovarian stimulation IVF (n = 63), modified natural cycle IVF (n = 53), natural conception (n = 79) and singletons born to fertile couples (reference group) (n = 98). At 4 years, cognition (Kaufmann-ABC-II; total IQ) and behaviour (Child Behavior Checklist; total problem T-score) were assessed. Causal inference search algorithms and structural equation modelling was applied to unravel causal mechanisms. Most children had typical cognitive and behavioural scores. No underlying causal effect was found between ovarian stimulation and the in-vitro procedure and outcome. Direct negative causal effects were found between severity of subfertility (time to pregnancy) and cognition and presence of subfertility and behaviour. Maternal age and maternal education acted as confounders. The study concludes that no causal effects were found between ovarian stimulation or in-vitro procedures and cognition and behaviour in childrenaged 4 years born to subfertile couples. Subfertility, especially severe subfertility, however, was associated with worse cognition and behaviour. Copyright © 2016 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

Proceedings of the international conference on cybernetics and societ

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1985-01-01

This book presents the papers given at a conference on artificial intelligence, expert systems and knowledge bases. Topics considered at the conference included automating expert system development, modeling expert systems, causal maps, data covariances, robot vision, image processing, multiprocessors, parallel processing, VLSI structures, man-machine systems, human factors engineering, cognitive decision analysis, natural language, computerized control systems, and cybernetics.

Current Status of Research in Teaching and Learning Evolution: I. Philosophical/Epistemological Issues

NASA Astrophysics Data System (ADS)

Smith, Mike U.

2010-06-01

Scholarship that addresses teaching and learning about evolution has rapidly increased in recent years. This review of that scholarship first addresses the philosophical/epistemological issues that impinge on teaching and learning about evolution, including the proper philosophical goals of evolution instruction; the correlational and possibly causal relationships among knowing, understanding, accepting, and believing; and the factors that affect student understanding, acceptance, and/or belief. Second, I summarize the specific epistemological issues involved, including empiricism, naturalism, philosophical vs methodological materialism, science vs religion as non-overlapping magisteria, and science as a way of knowing. Third, the paper critically reviews the strengths and weaknesses of the research tools available to measure the nature of science, epistemological beliefs, and especially the acceptance of evolution. Based on these findings, further research in these areas, especially study of the factors that cause lack of explanatory coherence as well as replications of studies that promise to explain current confusing findings about the interrelationships among student understanding, acceptance, and belief in evolution, are called for. In addition, this review calls for more longitudinal studies to delineate causal connections as well as improved measurement tools.

Perceived Causal Relations: Novel Methodology for Assessing Client Attributions about Causal Associations between Variables Including Symptoms and Functional Impairment

ERIC Educational Resources Information Center

Frewen, Paul A.; Allen, Samantha L.; Lanius, Ruth A.; Neufeld, Richard W. J.

2012-01-01

Researchers have argued that the investigation of causal interrelationships between symptoms may help explain the high comorbidity rate between certain psychiatric disorders. Clients' own attributions concerning the causal interrelationships linking the co-occurrence of their symptoms represent data that may inform their clinical case…

A quantum causal discovery algorithm

NASA Astrophysics Data System (ADS)

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.

An Examination of Commercial Aviation Accidents and Incidents Related to Integrated Vehicle Health Management

NASA Technical Reports Server (NTRS)

Reveley, Mary S.; Briggs, Jeffrey L.; Thomas, Megan A.; Evans, Joni K.; Jones, Sharon M.

2011-01-01

The Integrated Vehicle Health Management (IVHM) Project is one of the four projects within the National Aeronautics and Space Administration's (NASA) Aviation Safety Program (AvSafe). The IVHM Project conducts research to develop validated tools and technologies for automated detection, diagnosis, and prognosis that enable mitigation of adverse events during flight. Adverse events include those that arise from system, subsystem, or component failure, faults, and malfunctions due to damage, degradation, or environmental hazards that occur during flight. Determining the causal factors and adverse events related to IVHM technologies will help in the formulation of research requirements and establish a list of example adverse conditions against which IVHM technologies can be evaluated. This paper documents the results of an examination of the most recent statistical/prognostic accident and incident data that is available from the Aviation Safety Information Analysis and Sharing (ASIAS) System to determine the causal factors of system/component failures and/or malfunctions in U.S. commercial aviation accidents and incidents.

Noninflammatory Joint Contractures Arising from Immobility: Animal Models to Future Treatments

PubMed Central

Wong, Kayleigh; Trudel, Guy; Laneuville, Odette

2015-01-01

Joint contractures, defined as the limitation in the passive range of motion of a mobile joint, can be classified as noninflammatory diseases of the musculoskeletal system. The pathophysiology is not well understood; limited information is available on causal factors, progression, the pathophysiology involved, and prediction of response to treatment. The clinical heterogeneity of joint contractures combined with the heterogeneous contribution of joint connective tissues to joint mobility presents challenges to the study of joint contractures. Furthermore, contractures are often a symptom of a wide variety of heterogeneous disorders that are in many cases multifactorial. Extended immobility has been identified as a causal factor and evidence is provided from both experimental and epidemiology studies. Of interest is the involvement of the joint capsule in the pathophysiology of joint contractures and lack of response to remobilization. While molecular pathways involved in the development of joint contractures are being investigated, current treatments focus on physiotherapy, which is ineffective on irreversible contractures. Future treatments may include early diagnosis and prevention. PMID:26247029

How medicine has become a science?

PubMed

Zieliński, Andrzej

2014-01-01

The historical review of medical activities draws attention how late in its very long history therapies of proven effectiveness were introduced. Author attributes it to the late development of methods which would be capable to determine the causal relations which would scientifically justified identification the causes and risk factors of diseases as well as checking the effectiveness of preventive and therapeutic procedures. Among the fundamental tools for scientific knowledge of the causes and mechanisms of diseases, the author indicates: achievements of basic science and the development of epidemiological methods used to study causal relationships. In the author's opinion the results of basic research are an essential source of variables among which, with an increased likelihood could be found the causes and risk factors of studied conditions, including diseases. The author also stresses the role of medical technology, which is the primary source of potential medicines, other therapeutic procedures and diagnostic methods whose effectiveness is tested in experimental epidemiological studies. Medical technologies create also tools for the development of basic sciences.

Influence analysis for high-dimensional time series with an application to epileptic seizure onset zone detection

PubMed Central

Flamm, Christoph; Graef, Andreas; Pirker, Susanne; Baumgartner, Christoph; Deistler, Manfred

2013-01-01

Granger causality is a useful concept for studying causal relations in networks. However, numerical problems occur when applying the corresponding methodology to high-dimensional time series showing co-movement, e.g. EEG recordings or economic data. In order to deal with these shortcomings, we propose a novel method for the causal analysis of such multivariate time series based on Granger causality and factor models. We present the theoretical background, successfully assess our methodology with the help of simulated data and show a potential application in EEG analysis of epileptic seizures. PMID:23354014

In Support of Clinical Case Reports: A System of Causality Assessment

PubMed Central

Hamre, Harald J.; Kienle, Gunver S.

2013-01-01

The usefulness of clinical research depends on an assessment of causality. This assessment determines what constitutes clinical evidence. Case reports are an example of evidence that is frequently overlooked because it is believed they cannot address causal links between treatment and outcomes. This may be a mistake. Clarity on the topic of causality and its assessment will be of benefit for researchers and clinicians. This article outlines an overall system of causality and causality assessment. The system proposed involves two dimensions: horizontal and vertical; each of these dimensions consists of three different types of causality and three corresponding types of causality assessment. Included in this system are diverse forms of case causality illustrated with examples from everyday life and clinical medicine. Assessing case causality can complement conventional clinical research in an era of personalized medicine. PMID:24416665

Critical Factors Analysis for Offshore Software Development Success by Structural Equation Modeling

NASA Astrophysics Data System (ADS)

Wada, Yoshihisa; Tsuji, Hiroshi

In order to analyze the success/failure factors in offshore software development service by the structural equation modeling, this paper proposes to follow two approaches together; domain knowledge based heuristic analysis and factor analysis based rational analysis. The former works for generating and verifying of hypothesis to find factors and causalities. The latter works for verifying factors introduced by theory to build the model without heuristics. Following the proposed combined approaches for the responses from skilled project managers of the questionnaire, this paper found that the vendor property has high causality for the success compared to software property and project property.

Bayes and blickets: Effects of knowledge on causal induction in children and adults

PubMed Central

Griffiths, Thomas L.; Sobel, David M.; Tenenbaum, Joshua B.; Gopnik, Alison

2011-01-01

People are adept at inferring novel causal relations, even from only a few observations. Prior knowledge about the probability of encountering causal relations of various types and the nature of the mechanisms relating causes and effects plays a crucial role in these inferences. We test a formal account of how this knowledge can be used and acquired, based on analyzing causal induction as Bayesian inference. Five studies explored the predictions of this account with adults and 4-year-olds, using tasks in which participants learned about the causal properties of a set of objects. The studies varied the two factors that our Bayesian approach predicted should be relevant to causal induction: the prior probability with which causal relations exist, and the assumption of a deterministic or a probabilistic relation between cause and effect. Adults’ judgments (Experiments 1, 2, and 4) were in close correspondence with the quantitative predictions of the model, and children’s judgments (Experiments 3 and 5) agreed qualitatively with this account. PMID:21972897

Omission of Causal Indicators: Consequences and Implications for Measurement

ERIC Educational Resources Information Center

Aguirre-Urreta, Miguel I.; Rönkkö, Mikko; Marakas, George M.

2016-01-01

One of the central assumptions of the causal-indicator literature is that all causal indicators must be included in the research model and that the exclusion of one or more relevant causal indicators would have severe negative consequences by altering the meaning of the latent variable. In this research we show that the omission of a relevant…

Spatiotemporal causal modeling for the management of Dengue Fever

NASA Astrophysics Data System (ADS)

Yu, Hwa-Lung; Huang, Tailin; Lee, Chieh-Han

2015-04-01

Increasing climatic extremes have caused growing concerns about the health effects and disease outbreaks. The association between climate variation and the occurrence of epidemic diseases play an important role on a country's public health systems. Part of the impacts are direct casualties associated with the increasing frequency and intensity of typhoons, the proliferation of disease vectors and the short-term increase of clinic visits on gastro-intestinal discomforts, diarrhea, dermatosis, or psychological trauma. Other impacts come indirectly from the influence of disasters on the ecological and socio-economic systems, including the changes of air/water quality, living environment and employment condition. Previous risk assessment studies on dengue fever focus mostly on climatic and non-climatic factors and their association with vectors' reproducing pattern. The public-health implication may appear simple. Considering the seasonal changes and regional differences, however, the causality of the impacts is full of uncertainties. Without further investigation, the underlying dengue fever risk dynamics may not be assessed accurately. The objective of this study is to develop an epistemic framework for assessing dynamic dengue fever risk across space and time. The proposed framework integrates cross-departmental data, including public-health databases, precipitation data over time and various socio-economic data. We explore public-health issues induced by typhoon through literature review and spatiotemporal analytic techniques on public health databases. From those data, we identify relevant variables and possible causal relationships, and their spatiotemporal patterns derived from our proposed spatiotemporal techniques. Eventually, we create a spatiotemporal causal network and a framework for modeling dynamic dengue fever risk.

Explaining compound generalization in associative and causal learning through rational principles of dimensional generalization.

PubMed

Soto, Fabian A; Gershman, Samuel J; Niv, Yael

2014-07-01

How do we apply learning from one situation to a similar, but not identical, situation? The principles governing the extent to which animals and humans generalize what they have learned about certain stimuli to novel compounds containing those stimuli vary depending on a number of factors. Perhaps the best studied among these factors is the type of stimuli used to generate compounds. One prominent hypothesis is that different generalization principles apply depending on whether the stimuli in a compound are similar or dissimilar to each other. However, the results of many experiments cannot be explained by this hypothesis. Here, we propose a rational Bayesian theory of compound generalization that uses the notion of consequential regions, first developed in the context of rational theories of multidimensional generalization, to explain the effects of stimulus factors on compound generalization. The model explains a large number of results from the compound generalization literature, including the influence of stimulus modality and spatial contiguity on the summation effect, the lack of influence of stimulus factors on summation with a recovered inhibitor, the effect of spatial position of stimuli on the blocking effect, the asymmetrical generalization decrement in overshadowing and external inhibition, and the conditions leading to a reliable external inhibition effect. By integrating rational theories of compound and dimensional generalization, our model provides the first comprehensive computational account of the effects of stimulus factors on compound generalization, including spatial and temporal contiguity between components, which have posed long-standing problems for rational theories of associative and causal learning. (c) 2014 APA, all rights reserved.

Explaining Compound Generalization in Associative and Causal Learning Through Rational Principles of Dimensional Generalization

PubMed Central

Soto, Fabian A.; Gershman, Samuel J.; Niv, Yael

2014-01-01

How do we apply learning from one situation to a similar, but not identical, situation? The principles governing the extent to which animals and humans generalize what they have learned about certain stimuli to novel compounds containing those stimuli vary depending on a number of factors. Perhaps the best studied among these factors is the type of stimuli used to generate compounds. One prominent hypothesis is that different generalization principles apply depending on whether the stimuli in a compound are similar or dissimilar to each other. However, the results of many experiments cannot be explained by this hypothesis. Here we propose a rational Bayesian theory of compound generalization that uses the notion of consequential regions, first developed in the context of rational theories of multidimensional generalization, to explain the effects of stimulus factors on compound generalization. The model explains a large number of results from the compound generalization literature, including the influence of stimulus modality and spatial contiguity on the summation effect, the lack of influence of stimulus factors on summation with a recovered inhibitor, the effect of spatial position of stimuli on the blocking effect, the asymmetrical generalization decrement in overshadowing and external inhibition, and the conditions leading to a reliable external inhibition effect. By integrating rational theories of compound and dimensional generalization, our model provides the first comprehensive computational account of the effects of stimulus factors on compound generalization, including spatial and temporal contiguity between components, which have posed longstanding problems for rational theories of associative and causal learning. PMID:25090430

Associations of Sleep Quality and Awake Physical Activity with Fluctuations in Nocturnal Blood Pressure in Patients with Cardiovascular Risk Factors

PubMed Central

Kadoya, Manabu; Koyama, Hidenori; Kurajoh, Masafumi; Naka, Mariko; Miyoshi, Akio; Kanzaki, Akinori; Kakutani, Miki; Shoji, Takuhito; Moriwaki, Yuji; Yamamoto, Tetsuya; Inaba, Masaaki; Namba, Mitsuyoshi

2016-01-01

Background Sleep quality and awake physical activity are important behavioral factors involved in the occurrence of cardiovascular diseases, potentially through nocturnal blood pressure (BP) changes. However, the impacts of quantitatively measured sleep quality and awake physical activity on BP fluctuation, and their relationships with several candidate causal factors for nocturnal hypertension are not well elucidated. Methods This cross-sectional study included 303 patients registered in the HSCAA study. Measurements included quantitatively determined sleep quality parameters and awake physical activity obtained by actigraph, nocturnal systolic BP (SBP) fall [100 × (1- sleep SBP/awake SBP ratio)], apnea hypopnea index, urinary sodium and cortisol secretion, plasma aldosterone concentration and renin activity, insulin resistance index, parameters of heart rate variability (HRV), and plasma brain-derived neurotrophic factor (BDNF). Results Simple regression analysis showed that time awake after sleep onset (r = -0.150), a parameter of sleep quality, and awake physical activity (r = 0.164) were significantly correlated with nocturnal SBP fall. Among those, time awake after sleep onset (β = -0.179) and awake physical activity (β = 0.190) were significantly and independently associated with nocturnal SBP fall in multiple regression analysis. In a subgroup of patients without taking anti-hypertensive medications, both time awake after sleep onset (β = -0.336) and awake physical activity (β = 0.489) were more strongly and independently associated with nocturnal SBP falls. Conclusion Sleep quality and awake physical activity were found to be significantly associated with nocturnal SBP fall, and that relationship was not necessarily confounded by candidate causal factors for nocturnal hypertension. PMID:27166822

Does Sufficient Evidence Exist to Support a Causal Association between Vitamin D Status and Cardiovascular Disease Risk? An Assessment Using Hill’s Criteria for Causality

PubMed Central

Weyland, Patricia G.; Grant, William B.; Howie-Esquivel, Jill

2014-01-01

Serum 25-hydroxyvitamin D (25(OH)D) levels have been found to be inversely associated with both prevalent and incident cardiovascular disease (CVD) risk factors; dyslipidemia, hypertension and diabetes mellitus. This review looks for evidence of a causal association between low 25(OH)D levels and increased CVD risk. We evaluated journal articles in light of Hill’s criteria for causality in a biological system. The results of our assessment are as follows. Strength of association: many randomized controlled trials (RCTs), prospective and cross-sectional studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors. Consistency of observed association: most studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors in various populations, locations and circumstances. Temporality of association: many RCTs and prospective studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors. Biological gradient (dose-response curve): most studies assessing 25(OH)D levels and CVD risk found an inverse association exhibiting a linear biological gradient. Plausibility of biology: several plausible cellular-level causative mechanisms and biological pathways may lead from a low 25(OH)D level to increased risk for CVD with mediators, such as dyslipidemia, hypertension and diabetes mellitus. Experimental evidence: some well-designed RCTs found increased CVD risk factors with decreasing 25(OH)D levels. Analogy: the association between serum 25(OH)D levels and CVD risk is analogous to that between 25(OH)D levels and the risk of overall cancer, periodontal disease, multiple sclerosis and breast cancer. Conclusion: all relevant Hill criteria for a causal association in a biological system are satisfied to indicate a low 25(OH)D level as a CVD risk factor. PMID:25184368

A general, multivariate definition of causal effects in epidemiology.

PubMed

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.

Use of allele scores as instrumental variables for Mendelian randomization

PubMed Central

Burgess, Stephen; Thompson, Simon G

2013-01-01

Background An allele score is a single variable summarizing multiple genetic variants associated with a risk factor. It is calculated as the total number of risk factor-increasing alleles for an individual (unweighted score), or the sum of weights for each allele corresponding to estimated genetic effect sizes (weighted score). An allele score can be used in a Mendelian randomization analysis to estimate the causal effect of the risk factor on an outcome. Methods Data were simulated to investigate the use of allele scores in Mendelian randomization where conventional instrumental variable techniques using multiple genetic variants demonstrate ‘weak instrument’ bias. The robustness of estimates using the allele score to misspecification (for example non-linearity, effect modification) and to violations of the instrumental variable assumptions was assessed. Results Causal estimates using a correctly specified allele score were unbiased with appropriate coverage levels. The estimates were generally robust to misspecification of the allele score, but not to instrumental variable violations, even if the majority of variants in the allele score were valid instruments. Using a weighted rather than an unweighted allele score increased power, but the increase was small when genetic variants had similar effect sizes. Naive use of the data under analysis to choose which variants to include in an allele score, or for deriving weights, resulted in substantial biases. Conclusions Allele scores enable valid causal estimates with large numbers of genetic variants. The stringency of criteria for genetic variants in Mendelian randomization should be maintained for all variants in an allele score. PMID:24062299

Factors Relating to Staff Attributions of Control over Challenging Behaviour

ERIC Educational Resources Information Center

Dilworth, Jennifer A.; Phillips, Neil; Rose, John

2011-01-01

Background: Previous research has suggested that severity of intellectual disability (ID) and topography of behaviour may influence staff causal attributions regarding challenging behaviour. Subsequently, these causal attributions may influence helping behaviours. This study investigated the relationship between attributions of control over…

A systematic review of the etiopathogenesis of Kienböck's disease and a critical appraisal of its recognition as an occupational disease related to hand-arm vibration.

PubMed

Stahl, Stéphane; Stahl, Adelana Santos; Meisner, Christoph; Rahmanian-Schwarz, Afshin; Schaller, Hans-Eberhard; Lotter, Oliver

2012-11-21

We systematically reviewed etiological factors of Kienböck's disease (osteonecrosis of the lunate) discussed in the literature in order to examine the justification for including Kienböck's disease (KD) in the European Listing of Occupational Diseases. We searched the Ovid/Medline and the Cochrane Library for articles discussing the etiology of osteonecrosis of the lunate published since the first description of KD in 1910 and up until July 2012 in English, French or German. Literature was classified by the level of evidence presented, the etiopathological hypothesis discussed, and the author's conclusion about the role of the etiopathological hypothesis. The causal relationship between KD and hand-arm vibration was elucidated by the Bradford Hill criteria. A total of 220 references was found. Of the included 152 articles, 140 (92%) reached the evidence level IV (case series). The four most frequently discussed factors were negative ulnar variance (n=72; 47%), primary arterial ischemia of the lunate (n=63; 41%), trauma (n=63; 41%) and hand-arm vibration (n=53; 35%). The quality of the cohort studies on hand-arm vibration did not permit a meta-analysis to evaluate the strength of an association to KD. Evidence for the lack of consistency, plausibility and coherence of the 4 most frequently discussed etiopathologies was found. No evidence was found to support any of the nine Bradford Hill criteria for a causal relationship between KD and hand-arm vibration. A systematic review of 220 articles on the etiopathology of KD and the application of the Bradford Hill criteria does not provide sufficient scientific evidence to confirm or refute a causal relationship between KD and hand-arm vibration. This currently suggests that, KD does not comply with the criteria of the International Labour Organization determining occupational diseases. However, research with a higher level of evidence is required to further determine if hand-arm vibration is a risk factor for KD.

Causal factors of corporate crime in Taiwan: qualitative and quantitative findings.

PubMed

Mon, Wei-Teh

2002-04-01

Street crimes are a primary concern of most criminologists in Taiwan. In recent years, however, crimes committed by corporations have increased greatly in this country. Employing the empirical approach to collect data about causal factors of corporate crime, the research presented in this article is the first systematic empirical study concerning corporate crime in Taiwan. The research sample was selected from a corporation with a criminal record of pollution caused by the release of toxic chemicals into the environment and a corporation with no criminal record. Questionnaire survey and interviews of corporate employees and managers were conducted, and secondary data were collected from official agencies. This research indicated the causal factors of corporate crime as follows: the failure of government regulation, lack of corporate self-regulation, lack of public concern about corporate crime, corporate mechanistic structure, and the low self-control tendency of corporate managers.

Life Strain, Social Control, Social Learning, and Delinquency: The Effects of Gender, Age, and Family SES Among Chinese Adolescents.

PubMed

Bao, Wan-Ning; Haas, Ain; Xie, Yunping

2016-09-01

Very few studies have examined the pathways to delinquency and causal factors for demographic subgroups of adolescents in a different culture. This article explores the effects of gender, age, and family socioeconomic status (SES) in an integrated model of strain, social control, social learning, and delinquency among a sample of Chinese adolescents. ANOVA is used to check for significant differences between categories of demographic groups on the variables in the integrated model, and the differential effects of causal factors in the theoretical path models are examined. Further tests of interaction effects are conducted to compare path coefficients between "high-risk" youths (i.e., male, mid-teen, and low family SES adolescents) and other subgroups. The findings identified similar pathways to delinquency across subgroups and clarified the salience of causal factors for male, mid-teen, and low SES adolescents in a different cultural context. © The Author(s) 2015.

Exploratory Causal Analysis in Bivariate Time Series Data

NASA Astrophysics Data System (ADS)

McCracken, James M.

Many scientific disciplines rely on observational data of systems for which it is difficult (or impossible) to implement controlled experiments and data analysis techniques are required for identifying causal information and relationships directly from observational data. This need has lead to the development of many different time series causality approaches and tools including transfer entropy, convergent cross-mapping (CCM), and Granger causality statistics. In this thesis, the existing time series causality method of CCM is extended by introducing a new method called pairwise asymmetric inference (PAI). It is found that CCM may provide counter-intuitive causal inferences for simple dynamics with strong intuitive notions of causality, and the CCM causal inference can be a function of physical parameters that are seemingly unrelated to the existence of a driving relationship in the system. For example, a CCM causal inference might alternate between ''voltage drives current'' and ''current drives voltage'' as the frequency of the voltage signal is changed in a series circuit with a single resistor and inductor. PAI is introduced to address both of these limitations. Many of the current approaches in the times series causality literature are not computationally straightforward to apply, do not follow directly from assumptions of probabilistic causality, depend on assumed models for the time series generating process, or rely on embedding procedures. A new approach, called causal leaning, is introduced in this work to avoid these issues. The leaning is found to provide causal inferences that agree with intuition for both simple systems and more complicated empirical examples, including space weather data sets. The leaning may provide a clearer interpretation of the results than those from existing time series causality tools. A practicing analyst can explore the literature to find many proposals for identifying drivers and causal connections in times series data sets, but little research exists of how these tools compare to each other in practice. This work introduces and defines exploratory causal analysis (ECA) to address this issue along with the concept of data causality in the taxonomy of causal studies introduced in this work. The motivation is to provide a framework for exploring potential causal structures in time series data sets. ECA is used on several synthetic and empirical data sets, and it is found that all of the tested time series causality tools agree with each other (and intuitive notions of causality) for many simple systems but can provide conflicting causal inferences for more complicated systems. It is proposed that such disagreements between different time series causality tools during ECA might provide deeper insight into the data than could be found otherwise.

Systems and methods for modeling and analyzing networks

DOEpatents

Hill, Colin C; Church, Bruce W; McDonagh, Paul D; Khalil, Iya G; Neyarapally, Thomas A; Pitluk, Zachary W

2013-10-29

The systems and methods described herein utilize a probabilistic modeling framework for reverse engineering an ensemble of causal models, from data and then forward simulating the ensemble of models to analyze and predict the behavior of the network. In certain embodiments, the systems and methods described herein include data-driven techniques for developing causal models for biological networks. Causal network models include computational representations of the causal relationships between independent variables such as a compound of interest and dependent variables such as measured DNA alterations, changes in mRNA, protein, and metabolites to phenotypic readouts of efficacy and toxicity.

DNA methylation as a potential mediator of environmental risks in the development of childhood acute lymphoblastic leukemia.

PubMed

Timms, Jessica A; Relton, Caroline L; Rankin, Judith; Strathdee, Gordon; McKay, Jill A

2016-04-01

5-year survival rate for childhood acute lymphoblastic leukemia (ALL) has risen to approximately 90%, yet the causal disease pathway is still poorly understood. Evidence suggests multiple 'hits' are required for disease progression; an initial genetic abnormality followed by additional secondary 'hits'. It is plausible that environmental influences may trigger these secondary hits, and with the peak incidence of diagnosis between 2 and 5 years of age, early life exposures are likely to be key. DNA methylation can be modified by many environmental exposures and is dramatically altered in cancers, including childhood ALL. Here we explore the potential that DNA methylation may be involved in the causal pathway toward disease by acting as a mediator between established environmental factors and childhood ALL development.

Adaptive Non-Interventional Heuristics for Covariation Detection in Causal Induction: Model Comparison and Rational Analysis

ERIC Educational Resources Information Center

Hattori, Masasi; Oaksford, Mike

2007-01-01

In this article, 41 models of covariation detection from 2 x 2 contingency tables were evaluated against past data in the literature and against data from new experiments. A new model was also included based on a limiting case of the normative phi-coefficient under an extreme rarity assumption, which has been shown to be an important factor in…

Practical Management of Pressure Sores

PubMed Central

Jordan, John M.

1992-01-01

Pressure sores are common in the debilitated elderly. Causal factors are unrelieved pressure, shearing forces, friction, and moisture. Preventive measures should be used for all high-risk patients, defined by general condition, mental status, degree of incontinence, amount of activity, and mobility. Principles of treating ulcers include pressure relief, reducing bacterial counts, debriding necrotic tissue, and providing a moist, clean environment. Imagesp2385-ap2389-ap2392-a PMID:21221298

When a checklist is not enough: How to improve them and what else is needed.

PubMed

Raman, Jaishankar; Leveson, Nancy; Samost, Aubrey Lynn; Dobrilovic, Nikola; Oldham, Maggie; Dekker, Sidney; Finkelstein, Stan

2016-08-01

Checklists are being introduced to enhance patient safety, but the results have been mixed. The goal of this research is to understand why time-outs and checklists are sometimes not effective in preventing surgical adverse events and to identify additional measures needed to reduce these events. A total of 380 consecutive patients underwent complex cardiac surgery over a 24-month period between November 2011 and November 2013 at an academic medical center, out of a total of 529 cardiac cases. Elective isolated aortic valve replacements, mitral valve repairs, and coronary artery bypass graft surgical procedures (N = 149) were excluded. A time-out was conducted in a standard fashion in all patients in accordance with the World Health Organization surgical checklist protocol. Adverse events were classified as anything that resulted in an operative delay, nonavailability of equipment, failure of drug administration, or unexpected adverse clinical outcome. These events and their details were collected every week and analyzed using a systemic causal analysis technique using a technique called CAST (causal analysis based on systems theory). This analytic technique evaluated the sociotechnical system to identify the set of causal factors involved in the adverse events and the causal factors explored to identify reasons. Recommendations were made for the improvement of checklists and the use of system design changes that could prevent such events in the future. Thirty events were identified. The causal analysis of these 30 adverse events was carried out and actionable events classified. There were important limitations in the use of standard checklists as a stand-alone patient safety measure in the operating room setting, because of multiple factors. Major categories included miscommunication between staff, medication errors, missing instrumentation, missing implants, and improper handling of equipment or instruments. An average of 3.9 recommendations were generated for each adverse event scenario. Time-outs and checklists can prevent some types of adverse events, but they need to be carefully designed. Additional interventions aimed at improving safety controls in the system design are needed to augment the use of checklists. Customization of checklists for specialized surgical procedures may reduce adverse events. Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Diagram-based Analysis of Causal Systems (DACS): elucidating inter-relationships between determinants of acute lower respiratory infections among children in sub-Saharan Africa.

PubMed

Rehfuess, Eva A; Best, Nicky; Briggs, David J; Joffe, Mike

2013-12-06

Effective interventions require evidence on how individual causal pathways jointly determine disease. Based on the concept of systems epidemiology, this paper develops Diagram-based Analysis of Causal Systems (DACS) as an approach to analyze complex systems, and applies it by examining the contributions of proximal and distal determinants of childhood acute lower respiratory infections (ALRI) in sub-Saharan Africa. Diagram-based Analysis of Causal Systems combines the use of causal diagrams with multiple routinely available data sources, using a variety of statistical techniques. In a step-by-step process, the causal diagram evolves from conceptual based on a priori knowledge and assumptions, through operational informed by data availability which then undergoes empirical testing, to integrated which synthesizes information from multiple datasets. In our application, we apply different regression techniques to Demographic and Health Survey (DHS) datasets for Benin, Ethiopia, Kenya and Namibia and a pooled World Health Survey (WHS) dataset for sixteen African countries. Explicit strategies are employed to make decisions transparent about the inclusion/omission of arrows, the sign and strength of the relationships and homogeneity/heterogeneity across settings.Findings about the current state of evidence on the complex web of socio-economic, environmental, behavioral and healthcare factors influencing childhood ALRI, based on DHS and WHS data, are summarized in an integrated causal diagram. Notably, solid fuel use is structured by socio-economic factors and increases the risk of childhood ALRI mortality. Diagram-based Analysis of Causal Systems is a means of organizing the current state of knowledge about a specific area of research, and a framework for integrating statistical analyses across a whole system. This partly a priori approach is explicit about causal assumptions guiding the analysis and about researcher judgment, and wrong assumptions can be reversed following empirical testing. This approach is well-suited to dealing with complex systems, in particular where data are scarce.

Re-Ranking Sequencing Variants in the Post-GWAS Era for Accurate Causal Variant Identification

PubMed Central

Faye, Laura L.; Machiela, Mitchell J.; Kraft, Peter; Bull, Shelley B.; Sun, Lei

2013-01-01

Next generation sequencing has dramatically increased our ability to localize disease-causing variants by providing base-pair level information at costs increasingly feasible for the large sample sizes required to detect complex-trait associations. Yet, identification of causal variants within an established region of association remains a challenge. Counter-intuitively, certain factors that increase power to detect an associated region can decrease power to localize the causal variant. First, combining GWAS with imputation or low coverage sequencing to achieve the large sample sizes required for high power can have the unintended effect of producing differential genotyping error among SNPs. This tends to bias the relative evidence for association toward better genotyped SNPs. Second, re-use of GWAS data for fine-mapping exploits previous findings to ensure genome-wide significance in GWAS-associated regions. However, using GWAS findings to inform fine-mapping analysis can bias evidence away from the causal SNP toward the tag SNP and SNPs in high LD with the tag. Together these factors can reduce power to localize the causal SNP by more than half. Other strategies commonly employed to increase power to detect association, namely increasing sample size and using higher density genotyping arrays, can, in certain common scenarios, actually exacerbate these effects and further decrease power to localize causal variants. We develop a re-ranking procedure that accounts for these adverse effects and substantially improves the accuracy of causal SNP identification, often doubling the probability that the causal SNP is top-ranked. Application to the NCI BPC3 aggressive prostate cancer GWAS with imputation meta-analysis identified a new top SNP at 2 of 3 associated loci and several additional possible causal SNPs at these loci that may have otherwise been overlooked. This method is simple to implement using R scripts provided on the author's website. PMID:23950724

Diagram-based Analysis of Causal Systems (DACS): elucidating inter-relationships between determinants of acute lower respiratory infections among children in sub-Saharan Africa

PubMed Central

2013-01-01

Background Effective interventions require evidence on how individual causal pathways jointly determine disease. Based on the concept of systems epidemiology, this paper develops Diagram-based Analysis of Causal Systems (DACS) as an approach to analyze complex systems, and applies it by examining the contributions of proximal and distal determinants of childhood acute lower respiratory infections (ALRI) in sub-Saharan Africa. Results Diagram-based Analysis of Causal Systems combines the use of causal diagrams with multiple routinely available data sources, using a variety of statistical techniques. In a step-by-step process, the causal diagram evolves from conceptual based on a priori knowledge and assumptions, through operational informed by data availability which then undergoes empirical testing, to integrated which synthesizes information from multiple datasets. In our application, we apply different regression techniques to Demographic and Health Survey (DHS) datasets for Benin, Ethiopia, Kenya and Namibia and a pooled World Health Survey (WHS) dataset for sixteen African countries. Explicit strategies are employed to make decisions transparent about the inclusion/omission of arrows, the sign and strength of the relationships and homogeneity/heterogeneity across settings. Findings about the current state of evidence on the complex web of socio-economic, environmental, behavioral and healthcare factors influencing childhood ALRI, based on DHS and WHS data, are summarized in an integrated causal diagram. Notably, solid fuel use is structured by socio-economic factors and increases the risk of childhood ALRI mortality. Conclusions Diagram-based Analysis of Causal Systems is a means of organizing the current state of knowledge about a specific area of research, and a framework for integrating statistical analyses across a whole system. This partly a priori approach is explicit about causal assumptions guiding the analysis and about researcher judgment, and wrong assumptions can be reversed following empirical testing. This approach is well-suited to dealing with complex systems, in particular where data are scarce. PMID:24314302

Altitude exposure in sports: the Athlete Biological Passport standpoint.

PubMed

Sanchis-Gomar, Fabian; Pareja-Galeano, Helios; Brioche, Thomas; Martinez-Bello, Vladimir; Lippi, Giuseppe

2014-03-01

The Athlete Biological Passport (ABP) is principally founded on monitoring an athlete's biological variables over time, to identify abnormal biases on a longitudinal basis. Several factors are known to influence the results of these markers. However, the manner in which the altitude factor is taken into account still needs to be standardized. Causal relationships between haematological variables should be correctly integrated into ABP software. In particular, modifications of haematological parameters during and after exposure to different altitudes/hypoxic protocols need to be properly included within detection models. Copyright © 2013 John Wiley & Sons, Ltd.

Evaluating the impact of implementation factors on family-based prevention programming: methods for strengthening causal inference.

PubMed

Crowley, D Max; Coffman, Donna L; Feinberg, Mark E; Greenberg, Mark T; Spoth, Richard L

2014-04-01

Despite growing recognition of the important role implementation plays in successful prevention efforts, relatively little work has sought to demonstrate a causal relationship between implementation factors and participant outcomes. In turn, failure to explore the implementation-to-outcome link limits our understanding of the mechanisms essential to successful programming. This gap is partially due to the inability of current methodological procedures within prevention science to account for the multitude of confounders responsible for variation in implementation factors (i.e., selection bias). The current paper illustrates how propensity and marginal structural models can be used to improve causal inferences involving implementation factors not easily randomized (e.g., participant attendance). We first present analytic steps for simultaneously evaluating the impact of multiple implementation factors on prevention program outcome. Then, we demonstrate this approach for evaluating the impact of enrollment and attendance in a family program, over and above the impact of a school-based program, within PROSPER, a large-scale real-world prevention trial. Findings illustrate the capacity of this approach to successfully account for confounders that influence enrollment and attendance, thereby more accurately representing true causal relations. For instance, after accounting for selection bias, we observed a 5% reduction in the prevalence of 11th grade underage drinking for those who chose to receive a family program and school program compared to those who received only the school program. Further, we detected a 7% reduction in underage drinking for those with high attendance in the family program.

STAMP-Based HRA Considering Causality Within a Sociotechnical System: A Case of Minuteman III Missile Accident.

PubMed

Rong, Hao; Tian, Jin

2015-05-01

The study contributes to human reliability analysis (HRA) by proposing a method that focuses more on human error causality within a sociotechnical system, illustrating its rationality and feasibility by using a case of the Minuteman (MM) III missile accident. Due to the complexity and dynamics within a sociotechnical system, previous analyses of accidents involving human and organizational factors clearly demonstrated that the methods using a sequential accident model are inadequate to analyze human error within a sociotechnical system. System-theoretic accident model and processes (STAMP) was used to develop a universal framework of human error causal analysis. To elaborate the causal relationships and demonstrate the dynamics of human error, system dynamics (SD) modeling was conducted based on the framework. A total of 41 contributing factors, categorized into four types of human error, were identified through the STAMP-based analysis. All factors are related to a broad view of sociotechnical systems, and more comprehensive than the causation presented in the accident investigation report issued officially. Recommendations regarding both technical and managerial improvement for a lower risk of the accident are proposed. The interests of an interdisciplinary approach provide complementary support between system safety and human factors. The integrated method based on STAMP and SD model contributes to HRA effectively. The proposed method will be beneficial to HRA, risk assessment, and control of the MM III operating process, as well as other sociotechnical systems. © 2014, Human Factors and Ergonomics Society.

Breast cancer: critical data analysis concludes that estrogens are not the cause, however lifestyle changes can alter risk rapidly.

PubMed

Wiseman, Richard A

2004-08-01

The theory that estrogens are causally associated with increased risk of breast cancer and the question of whether lifetime cumulative exposure is necessary are critically reviewed. Systematic search was made of published epidemiological and clinical data relating to estrogen concentrations at different times and situations, and of breast cancer incidence with age and after lifestyle changes. Breast cancer incidence increases with age, although the rate of increase slows. Reproductive factors are known to affect risk, but data that do not fit the theory of estrogen causation include low estradiol levels and decline of estrogen excretion postmenopausally, rates in HRT-takers, absence of increased rate during or after pregnancy, and breast cancer in men. Breast cancer risk can be altered by external factors within a few years, as shown by studies in both Norway and England during World War II, by changing rates in migrant populations, and by the effect on rates of recent adiposity. It is probable that estrogens act as promoters rather than being directly causal. Even as promoters, lifetime exposure to estrogens is not necessary. The cause is most probably a lifestyle factor, changes in which can rapidly alter risk. This has important implications in the search for a causative factor.

Optimal quantum networks and one-shot entropies

NASA Astrophysics Data System (ADS)

Chiribella, Giulio; Ebler, Daniel

2016-09-01

We develop a semidefinite programming method for the optimization of quantum networks, including both causal networks and networks with indefinite causal structure. Our method applies to a broad class of performance measures, defined operationally in terms of interative tests set up by a verifier. We show that the optimal performance is equal to a max relative entropy, which quantifies the informativeness of the test. Building on this result, we extend the notion of conditional min-entropy from quantum states to quantum causal networks. The optimization method is illustrated in a number of applications, including the inversion, charge conjugation, and controlization of an unknown unitary dynamics. In the non-causal setting, we show a proof-of-principle application to the maximization of the winning probability in a non-causal quantum game.

Thermal and energy battery management optimization in electric vehicles using Pontryagin's maximum principle

NASA Astrophysics Data System (ADS)

Bauer, Sebastian; Suchaneck, Andre; Puente León, Fernando

2014-01-01

Depending on the actual battery temperature, electrical power demands in general have a varying impact on the life span of a battery. As electrical energy provided by the battery is needed to temper it, the question arises at which temperature which amount of energy optimally should be utilized for tempering. Therefore, the objective function that has to be optimized contains both the goal to maximize life expectancy and to minimize the amount of energy used for obtaining the first goal. In this paper, Pontryagin's maximum principle is used to derive a causal control strategy from such an objective function. The derivation of the causal strategy includes the determination of major factors that rule the optimal solution calculated with the maximum principle. The optimization is calculated offline on a desktop computer for all possible vehicle parameters and major factors. For the practical implementation in the vehicle, it is sufficient to have the values of the major factors determined only roughly in advance and the offline calculation results available. This feature sidesteps the drawback of several optimization strategies that require the exact knowledge of the future power demand. The resulting strategy's application is not limited to batteries in electric vehicles.

Environmental logistics performance indicators affecting per capita income and sectoral growth: evidence from a panel of selected global ranked logistics countries.

PubMed

Khan, Syed Abdul Rehman; Qianli, Dong; SongBo, Wei; Zaman, Khalid; Zhang, Yu

2017-01-01

The objective of the study is to examine the long-run and causal relationship between environmental logistics performance indicators (ELPI) and growth-specific factors in a panel of 15 selected global ranked logistics countries over a period of 2007-2015. This study is exclusive as we utilized a number of LPI factors including logistics performance, logistics competence, and logistics infrastructure with mediation of sustainable factors, i.e., carbon dioxide (CO 2 ), fossil fuel, and greenhouse gas (GHG) emissions in a region. The results show that the per capita income, industry, manufacturing, and service share to GDP is affected by CO 2 emissions and GHG emissions. Logistics competence and infrastructure promote economic growth and sectoral value added, while energy demand and FDI inflows both are prerequisite for sustainable agriculture in a region. The causal relationships confirm that more energy demand results in an increase in economic growth, industry value added, and the service sector (i.e., feedback hypothesis), while the sustainable supply chain system improves energy demand, FDI inflows, economic growth, and sectoral growth (i.e., conservation hypothesis) in a panel of countries.

Statistical Evidence Suggests that Inattention Drives Hyperactivity/Impulsivity in Attention Deficit-Hyperactivity Disorder

PubMed Central

Sokolova, Elena; Groot, Perry; Claassen, Tom; van Hulzen, Kimm J.; Glennon, Jeffrey C.; Franke, Barbara

2016-01-01

Background Numerous factor analytic studies consistently support a distinction between two symptom domains of attention-deficit/hyperactivity disorder (ADHD), inattention and hyperactivity/impulsivity. Both dimensions show high internal consistency and moderate to strong correlations with each other. However, it is not clear what drives this strong correlation. The aim of this paper is to address this issue. Method We applied a sophisticated approach for causal discovery on three independent data sets of scores of the two ADHD dimensions in NeuroIMAGE (total N = 675), ADHD-200 (N = 245), and IMpACT (N = 164), assessed by different raters and instruments, and further used information on gender or a genetic risk haplotype. Results In all data sets we found strong statistical evidence for the same pattern: the clear dependence between hyperactivity/impulsivity symptom level and an established genetic factor (either gender or risk haplotype) vanishes when one conditions upon inattention symptom level. Under reasonable assumptions, e.g., that phenotypes do not cause genotypes, a causal model that is consistent with this pattern contains a causal path from inattention to hyperactivity/impulsivity. Conclusions The robust dependency cancellation observed in three different data sets suggests that inattention is a driving factor for hyperactivity/impulsivity. This causal hypothesis can be further validated in intervention studies. Our model suggests that interventions that affect inattention will also have an effect on the level of hyperactivity/impulsivity. On the other hand, interventions that affect hyperactivity/impulsivity would not change the level of inattention. This causal model may explain earlier findings on heritable factors causing ADHD reported in the study of twins with learning difficulties. PMID:27768717

Burnout in Relation to Specific Contributing Factors and Health Outcomes among Nurses: A Systematic Review

PubMed Central

Khamisa, Natasha; Peltzer, Karl; Oldenburg, Brian

2013-01-01

Nurses have been found to experience higher levels of stress-related burnout compared to other health care professionals. Despite studies showing that both job satisfaction and burnout are effects of exposure to stressful working environments, leading to poor health among nurses, little is known about the causal nature and direction of these relationships. The aim of this systematic review is to identify published research that has formally investigated relationships between these variables. Six databases (including CINAHL, COCHRANE, EMBASE, MEDLINE, PROQUEST and PsyINFO) were searched for combinations of keywords, a manual search was conducted and an independent reviewer was asked to cross validate all the electronically identified articles. Of the eighty five articles that were identified from these databases, twenty one articles were excluded based on exclusion criteria; hence, a total of seventy articles were included in the study sample. The majority of identified studies exploring two and three way relationships (n = 63) were conducted in developed countries. Existing research includes predominantly cross-sectional studies (n = 68) with only a few longitudinal studies (n = 2); hence, the evidence base for causality is still very limited. Despite minimal availability of research concerning the small number of studies to investigate the relationships between work-related stress, burnout, job satisfaction and the general health of nurses, this review has identified some contradictory evidence for the role of job satisfaction. This emphasizes the need for further research towards understanding causality. PMID:23727902

Evaluating WAIS-IV structure through a different psychometric lens: structural causal model discovery as an alternative to confirmatory factor analysis.

PubMed

van Dijk, Marjolein J A M; Claassen, Tom; Suwartono, Christiany; van der Veld, William M; van der Heijden, Paul T; Hendriks, Marc P H

Since the publication of the WAIS-IV in the U.S. in 2008, efforts have been made to explore the structural validity by applying factor analysis to various samples. This study aims to achieve a more fine-grained understanding of the structure of the Dutch language version of the WAIS-IV (WAIS-IV-NL) by applying an alternative analysis based on causal modeling in addition to confirmatory factor analysis (CFA). The Bayesian Constraint-based Causal Discovery (BCCD) algorithm learns underlying network structures directly from data and assesses more complex structures than is possible with factor analysis. WAIS-IV-NL profiles of two clinical samples of 202 patients (i.e. patients with temporal lobe epilepsy and a mixed psychiatric outpatient group) were analyzed and contrasted with a matched control group (N = 202) selected from the Dutch standardization sample of the WAIS-IV-NL to investigate internal structure by means of CFA and BCCD. With CFA, the four-factor structure as proposed by Wechsler demonstrates acceptable fit in all three subsamples. However, BCCD revealed three consistent clusters (verbal comprehension, visual processing, and processing speed) in all three subsamples. The combination of Arithmetic and Digit Span as a coherent working memory factor could not be verified, and Matrix Reasoning appeared to be isolated. With BCCD, some discrepancies from the proposed four-factor structure are exemplified. Furthermore, these results fit CHC theory of intelligence more clearly. Consistent clustering patterns indicate these results are robust. The structural causal discovery approach may be helpful in better interpreting existing tests, the development of new tests, and aid in diagnostic instruments.

Identification of chemical components of combustion emissions that affect pro-atherosclerotic vascular responses in mice

PubMed Central

Seilkop, Steven K.; Campen, Matthew J.; Lund, Amie K.; McDonald, Jacob D.; Mauderly, Joe L.

2012-01-01

Combustion emissions cause pro-atherosclerotic responses in apolipoprotein E-deficient (ApoE/−) mice, but the causal components of these complex mixtures are unresolved. In studies previously reported, ApoE−/− mice were exposed by inhalation 6 h/day for 50 consecutive days to multiple dilutions of diesel or gasoline exhaust, wood smoke, or simulated “downwind” coal emissions. In this study, the analysis of the combined four-study database using the Multiple Additive Regression Trees (MART) data mining approach to determine putative causal exposure components regardless of combustion source is reported. Over 700 physical–chemical components were grouped into 45 predictor variables. Response variables measured in aorta included endothelin-1, vascular endothelin growth factor, three matrix metalloproteinases (3, 7, 9), metalloproteinase inhibitor 2, heme-oxygenase-1, and thiobarbituric acid reactive substances. Two or three predictors typically explained most of the variation in response among the experimental groups. Overall, sulfur dioxide, ammonia, nitrogen oxides, and carbon monoxide were most highly predictive of responses, although their rankings differed among the responses. Consistent with the earlier finding that filtration of particles had little effect on responses, particulate components ranked third to seventh in predictive importance for the eight response variables. MART proved useful for identifying putative causal components, although the small number of pollution mixtures (4) can provide only suggestive evidence of causality. The potential independent causal contributions of these gases to the vascular responses, as well as possible interactions among them and other components of complex pollutant mixtures, warrant further evaluation. PMID:22486345

Identification of chemical components of combustion emissions that affect pro-atherosclerotic vascular responses in mice.

PubMed

Seilkop, Steven K; Campen, Matthew J; Lund, Amie K; McDonald, Jacob D; Mauderly, Joe L

2012-04-01

Combustion emissions cause pro-atherosclerotic responses in apolipoprotein E-deficient (ApoE/⁻) mice, but the causal components of these complex mixtures are unresolved. In studies previously reported, ApoE⁻/⁻ mice were exposed by inhalation 6 h/day for 50 consecutive days to multiple dilutions of diesel or gasoline exhaust, wood smoke, or simulated "downwind" coal emissions. In this study, the analysis of the combined four-study database using the Multiple Additive Regression Trees (MART) data mining approach to determine putative causal exposure components regardless of combustion source is reported. Over 700 physical-chemical components were grouped into 45 predictor variables. Response variables measured in aorta included endothelin-1, vascular endothelin growth factor, three matrix metalloproteinases (3, 7, 9), metalloproteinase inhibitor 2, heme-oxygenase-1, and thiobarbituric acid reactive substances. Two or three predictors typically explained most of the variation in response among the experimental groups. Overall, sulfur dioxide, ammonia, nitrogen oxides, and carbon monoxide were most highly predictive of responses, although their rankings differed among the responses. Consistent with the earlier finding that filtration of particles had little effect on responses, particulate components ranked third to seventh in predictive importance for the eight response variables. MART proved useful for identifying putative causal components, although the small number of pollution mixtures (4) can provide only suggestive evidence of causality. The potential independent causal contributions of these gases to the vascular responses, as well as possible interactions among them and other components of complex pollutant mixtures, warrant further evaluation.

Causal Attributions for Success and Failure at University Examinations

ERIC Educational Resources Information Center

Simon, J. G.; Feather, N. T.

1973-01-01

Male and female undergraduates rated their ability, amount of preparation, task difficulty, and their initial confidence (expectation) before they began an important examination. Subsequently they attributed causality for the examination outcome by rating the importance of factors involving ability, preparation, task difficulty, and luck as…

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

PubMed

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.

Essays on Causal Inference for Public Policy

ERIC Educational Resources Information Center

Zajonc, Tristan

2012-01-01

Effective policymaking requires understanding the causal effects of competing proposals. Relevant causal quantities include proposals' expected effect on different groups of recipients, the impact of policies over time, the potential trade-offs between competing objectives, and, ultimately, the optimal policy. This dissertation studies causal…

Bayesian networks improve causal environmental assessments for evidence-based policy

EPA Science Inventory

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 p...

Modeling the Perception of Audiovisual Distance: Bayesian Causal Inference and Other Models

PubMed Central

2016-01-01

Studies of audiovisual perception of distance are rare. Here, visual and auditory cue interactions in distance are tested against several multisensory models, including a modified causal inference model. In this causal inference model predictions of estimate distributions are included. In our study, the audiovisual perception of distance was overall better explained by Bayesian causal inference than by other traditional models, such as sensory dominance and mandatory integration, and no interaction. Causal inference resolved with probability matching yielded the best fit to the data. Finally, we propose that sensory weights can also be estimated from causal inference. The analysis of the sensory weights allows us to obtain windows within which there is an interaction between the audiovisual stimuli. We find that the visual stimulus always contributes by more than 80% to the perception of visual distance. The visual stimulus also contributes by more than 50% to the perception of auditory distance, but only within a mobile window of interaction, which ranges from 1 to 4 m. PMID:27959919

Measuring causal perception: connections to representational momentum?

PubMed

Choi, Hoon; Scholl, Brian J

2006-01-01

In a collision between two objects, we can perceive not only low-level properties, such as color and motion, but also the seemingly high-level property of causality. It has proven difficult, however, to measure causal perception in a quantitatively rigorous way which goes beyond perceptual reports. Here we focus on the possibility of measuring perceived causality using the phenomenon of representational momentum (RM). Recent studies suggest a relationship between causal perception and RM, based on the fact that RM appears to be attenuated for causally 'launched' objects. This is explained by appeal to the visual expectation that a 'launched' object is inert and thus should eventually cease its movement after a collision, without a source of self-propulsion. We first replicated these demonstrations, and then evaluated this alleged connection by exploring RM for different types of displays, including the contrast between causal launching and non-causal 'passing'. These experiments suggest that the RM-attenuation effect is not a pure measure of causal perception, but rather may reflect lower-level spatiotemporal correlates of only some causal displays. We conclude by discussing the strengths and pitfalls of various methods of measuring causal perception.

Principal Stratification — a Goal or a Tool?

PubMed Central

Pearl, Judea

2011-01-01

Principal stratification has recently become a popular tool to address certain causal inference questions, particularly in dealing with post-randomization factors in randomized trials. Here, we analyze the conceptual basis for this framework and invite response to clarify the value of principal stratification in estimating causal effects of interest. PMID:21556288

The Model Analyst’s Toolkit: Scientific Model Development, Analysis, and Validation

DTIC Science & Technology

2015-02-20

being integrated within MAT, including Granger causality. Granger causality tests whether a data series helps when predicting future values of another...relations by econometric models and cross-spectral methods. Econometrica: Journal of the Econometric Society, 424-438. Granger, C. W. (1980). Testing ... testing dataset. This effort is described in Section 3.2. 3.1. Improvements in Granger Causality User Interface Various metrics of causality are

How contrast situations affect the assignment of causality in symmetric physical settings.

PubMed

Beller, Sieghard; Bender, Andrea

2014-01-01

In determining the prime cause of a physical event, people often weight one of two entities in a symmetric physical relation as more important for bringing about the causal effect than the other. In a broad survey (Bender and Beller, 2011), we documented such weighting effects for different kinds of physical events and found that their direction and strength depended on a variety of factors. Here, we focus on one of those: adding a contrast situation that-while being formally irrelevant-foregrounds one of the factors and thus frames the task in a specific way. In two experiments, we generalize and validate our previous findings by using different stimulus material (in Experiment 1), by applying a different response format to elicit causal assignments, an analog rating scale instead of a forced-choice decision (in Experiment 2), and by eliciting explanations for the physical events in question (in both Experiments). The results generally confirm the contrast effects for both response formats; however, the effects were more pronounced with the force-choice format than with the rating format. People tended to refer to the given contrast in their explanations, which validates our manipulation. Finally, people's causal assignments are reflected in the type of explanation given in that contrast and property explanations were associated with biased causal assignments, whereas relational explanations were associated with unbiased assignments. In the discussion, we pick up the normative questions of whether or not these contrast effects constitute a bias in causal reasoning.

Aircraft Loss of Control Causal Factors and Mitigation Challenges

NASA Technical Reports Server (NTRS)

Jacobson, Steven R.

2010-01-01

Loss of control is the leading cause of jet fatalities worldwide. Aside from their frequency of occurrence, accidents resulting from loss of aircraft control seize the public s attention by yielding a large number of fatalities in a single event. In response to the rising threat to aviation safety, the NASA Aviation Safety Program has conducted a study of the loss of control problem. This study gathered four types of information pertaining to loss of control accidents: (1) statistical data; (2) individual accident reports that cite loss of control as a contributing factor; (3) previous meta-analyses of loss of control accidents; and (4) inputs solicited from aircraft manufacturers, air carriers, researchers, and other industry stakeholders. Using these information resources, the study team identified the causal factors that were cited in the greatest number of loss of control accidents, and which were emphasized most by industry stakeholders. This report describes the study approach, the key causal factors for aircraft loss of control, and recommended mitigation strategies to make near-term impacts, mid-term impacts, and Next Generation Air Transportation System impacts on the loss of control accident statistics

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

PubMed

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.

To what extent has climate change contributed to the recent epidemiology of tick-borne diseases?

PubMed

Randolph, Sarah E

2010-02-10

There is no doubt that all vector-borne diseases are very sensitive to climatic conditions. Many such diseases have shown marked increases in both distribution and incidence during the past few decades, just as human-induced climate change is thought to have exceeded random fluctuations. This coincidence has led to the general perception that climate change has driven disease emergence, but climate change is the inevitable backdrop for all recent events, without implying causality. Coincidence and causality can be disentangled using tick-borne encephalitis (TBE) as a test case, based on the excellent long-term data for this medically significant European disease system. Detailed analysis of climate records since 1970 has revealed abrupt temperature increases just prior to the dramatic upsurge in TBE incidence in many parts of central and eastern Europe. Furthermore, the seasonal patterns of this temperature change are such as might have favoured the transmission of TBE virus between co-feeding ticks. Nevertheless, the pattern of climate change is too uniform to explain the marked heterogeneity in the timing and degree of TBE upsurge, for example in different counties within each of the Baltic countries. Recent decreases as well as increases in TBE incidence must also be taken into account. Instead of a single cause, a network of interacting factors, acting synergistically but with differential force in space and time, would generate this epidemiological heterogeneity. From analysis of past and present events, it appears that human behavioural factors have played a more significant role than purely biological enzootic factors, although there is an explicit causal linkage from one to the other. This includes a range of abiotic and biotic environmental factors, together with human behaviour determined by socio-economic conditions. Many of the abrupt changes followed from the shift from planned to market economies with the fall of Soviet rule. Comparisons between eight countries have indeed revealed a remarkable correlation between poverty indicators and the relative degree of upsurge in TBE from 1993. Against this background of longer-term shifts in TBE incidence, sudden spikes in incidence appear to be due to exceptional weather conditions affecting people's behaviour, which have a differential impact depending on socio-economic factors. This new perspective may also help explain the epidemiology of Crimean-Congo haemorrhagic fever around the eastern Mediterranean region, including the current exceptional epidemic in Turkey.

Understanding environmental contributions to autism: Causal concepts and the state of science.

PubMed

Hertz-Picciotto, Irva; Schmidt, Rebecca J; Krakowiak, Paula

2018-04-01

The complexity of neurodevelopment, the rapidity of early neurogenesis, and over 100 years of research identifying environmental influences on neurodevelopment serve as backdrop to understanding factors that influence risk and severity of autism spectrum disorder (ASD). This Keynote Lecture, delivered at the May 2016 annual meeting of the International Society for Autism Research, describes concepts of causation, outlines the trajectory of research on nongenetic factors beginning in the 1960s, and briefly reviews the current state of this science. Causal concepts are introduced, including root causes; pitfalls in interpreting time trends as clues to etiologic factors; susceptible time windows for exposure; and implications of a multi-factorial model of ASD. An historical background presents early research into the origins of ASD. The epidemiologic literature from the last fifteen years is briefly but critically reviewed for potential roles of, for example, air pollution, pesticides, plastics, prenatal vitamins, lifestyle and family factors, and maternal obstetric and metabolic conditions during her pregnancy. Three examples from the case-control CHildhood Autism Risks from Genes and the Environment Study are probed to illustrate methodological approaches to central challenges in observational studies: capturing environmental exposure; causal inference when a randomized controlled clinical trial is either unethical or infeasible; and the integration of genetic, epigenetic, and environmental influences on development. We conclude with reflections on future directions, including exposomics, new technologies, the microbiome, gene-by-environment interaction in the era of -omics, and epigenetics as the interface of those two. As the environment is malleable, this research advances the goal of a productive and fulfilling life for all children, teen-agers and adults. Autism Res 2018, 11: 554-586. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. This Keynote Lecture, delivered at the 2016 meeting of the International Society for Autism Research, discusses evidence from human epidemiologic studies of prenatal factors contributing to autism, such as pesticides, maternal nutrition and her health. There is no single cause for autism. Examples highlight the features of a high-quality epidemiology study, and what comprises a compelling case for causation. Emergent research directions hold promise for identifying potential interventions to reduce disabilities, enhance giftedness, and improve lives of those with ASD. © 2018 International Society for Autism Research, Wiley Periodicals, Inc.

DNA methylation as a potential mediator of environmental risks in the development of childhood acute lymphoblastic leukemia

PubMed Central

Timms, Jessica A; Relton, Caroline L; Rankin, Judith; Strathdee, Gordon; McKay, Jill A

2016-01-01

5-year survival rate for childhood acute lymphoblastic leukemia (ALL) has risen to approximately 90%, yet the causal disease pathway is still poorly understood. Evidence suggests multiple ‘hits’ are required for disease progression; an initial genetic abnormality followed by additional secondary ‘hits’. It is plausible that environmental influences may trigger these secondary hits, and with the peak incidence of diagnosis between 2 and 5 years of age, early life exposures are likely to be key. DNA methylation can be modified by many environmental exposures and is dramatically altered in cancers, including childhood ALL. Here we explore the potential that DNA methylation may be involved in the causal pathway toward disease by acting as a mediator between established environmental factors and childhood ALL development. PMID:27035209

Causal discovery and inference: concepts and recent methodological advances.

PubMed

Spirtes, Peter; Zhang, Kun

This paper aims to give a broad coverage of central concepts and principles involved in automated causal inference and emerging approaches to causal discovery from i.i.d data and from time series. After reviewing concepts including manipulations, causal models, sample predictive modeling, causal predictive modeling, and structural equation models, we present the constraint-based approach to causal discovery, which relies on the conditional independence relationships in the data, and discuss the assumptions underlying its validity. We then focus on causal discovery based on structural equations models, in which a key issue is the identifiability of the causal structure implied by appropriately defined structural equation models: in the two-variable case, under what conditions (and why) is the causal direction between the two variables identifiable? We show that the independence between the error term and causes, together with appropriate structural constraints on the structural equation, makes it possible. Next, we report some recent advances in causal discovery from time series. Assuming that the causal relations are linear with nonGaussian noise, we mention two problems which are traditionally difficult to solve, namely causal discovery from subsampled data and that in the presence of confounding time series. Finally, we list a number of open questions in the field of causal discovery and inference.

Causal Factors and Adverse Conditions of Aviation Accidents and Incidents Related to Integrated Resilient Aircraft Control

NASA Technical Reports Server (NTRS)

Reveley, Mary S.; Briggs, Jeffrey L.; Evans, Joni K.; Sandifer, Carl E.; Jones, Sharon Monica

2010-01-01

The causal factors of accidents from the National Transportation Safety Board (NTSB) database and incidents from the Federal Aviation Administration (FAA) database associated with loss of control (LOC) were examined for four types of operations (i.e., Federal Aviation Regulation Part 121, Part 135 Scheduled, Part 135 Nonscheduled, and Part 91) for the years 1988 to 2004. In-flight LOC is a serious aviation problem. Well over half of the LOC accidents included at least one fatality (80 percent in Part 121), and roughly half of all aviation fatalities in the studied time period occurred in conjunction with LOC. An adverse events table was updated to provide focus to the technology validation strategy of the Integrated Resilient Aircraft Control (IRAC) Project. The table contains three types of adverse conditions: failure, damage, and upset. Thirteen different adverse condition subtypes were gleaned from the Aviation Safety Reporting System (ASRS), the FAA Accident and Incident database, and the NTSB database. The severity and frequency of the damage conditions, initial test conditions, and milestones references are also provided.

The natural history of substance use disorders.

PubMed

Sarvet, Aaron L; Hasin, Deborah

2016-07-01

Illicit drugs, alcohol, and tobacco use disorders contribute substantially to the global burden of disease. Knowledge about the major elements of the natural history of substance use disorders (incidence, remission, persistence, and relapse) is crucial to a broader understanding of the course and outcomes of substance use disorders. Prospective cohort studies in nonclinical samples indicate that externalizing psychopathology in earlier life, including early disordered substance use, delinquency, and personality disorders, are related to substance use disorders later in life and chronic course. Externalizing psychopathology may be initiated by early adverse experiences, for example, childhood maltreatment and stressful life events. After controlling for confounders, 'age at first use' as a causal factor for alcohol use disorder later in life and the 'drug substitution' hypothesis are not supported in general population data. Future research should focus on elaborating the causal framework that leads to the development and persistence of severe substance use disorders, with an emphasis on identifying modifiable factors for intervention by policy makers or health professionals. More research is needed on the natural history of substance use disorders in low-income and middle-income countries.

Evaluating the Impact of Implementation Factors on Family-Based Prevention Programming: Methods for Strengthening Causal Inference

PubMed Central

Crowley, D. Max; Coffman, Donna L.; Feinberg, Mark; Greenberg, Mark; Spoth, Richard

2013-01-01

Despite growing recognition of the important role implementation plays in successful prevention efforts, relatively little work has sought to demonstrate a causal relationship between implementation factors and participant outcomes. In turn, failure to explore the implementation-to-outcome link limits our understanding of the mechanisms essential to successful programming. This gap is partially due to the inability of current methodological procedures within prevention science to account for the multitude of confounders responsible for variation in implementation factors (i.e., selection bias). The current paper illustrates how propensity and marginal structural models can be used to improve causal inferences involving implementation factors not easily randomized (e.g., participant attendance). We first present analytic steps for simultaneously evaluating the impact of multiple implementation factors on prevention program outcome. Then we demonstrate this approach for evaluating the impact of enrollment and attendance in a family program, over and above the impact of a school-based program, within PROSPER, a large scale real-world prevention trial. Findings illustrate the capacity of this approach to successfully account for confounders that influence enrollment and attendance, thereby more accurately representing true causal relations. For instance, after accounting for selection bias, we observed a 5% reduction in the prevalence of 11th grade underage drinking for those who chose to receive a family program and school program compared to those who received only the school program. Further, we detected a 7% reduction in underage drinking for those with high attendance in the family program. PMID:23430578

What is the nature of causality in the brain? - Inherently probabilistic. Comment on "Foundational perspectives on causality in large-scale brain networks" by M. Mannino and S.L. Bressler

NASA Astrophysics Data System (ADS)

Dhamala, Mukesh

2015-12-01

Understanding cause-and-effect (causal) relations from observations concerns all sciences including neuroscience. Appropriately defining causality and its nature, though, has been a topic of active discussion for philosophers and scientists for centuries. Although brain research, particularly functional neuroimaging research, is now moving rapidly beyond identification of brain regional activations towards uncovering causal relations between regions, the nature of causality has not be been thoroughly described and resolved. In the current review article [1], Mannino and Bressler take us on a beautiful journey into the history of the work on causality and make a well-reasoned argument that the causality in the brain is inherently probabilistic. This notion is consistent with brain anatomy and functions, and is also inclusive of deterministic cases of inputs leading to outputs in the brain.

Causal-Explanatory Pluralism: How Intentions, Functions, and Mechanisms Influence Causal Ascriptions

ERIC Educational Resources Information Center

Lombrozo, Tania

2010-01-01

Both philosophers and psychologists have argued for the existence of distinct kinds of explanations, including teleological explanations that cite functions or goals, and mechanistic explanations that cite causal mechanisms. Theories of causation, in contrast, have generally been unitary, with dominant theories focusing either on counterfactual…

Using genetic data to strengthen causal inference in observational research.

PubMed

Pingault, Jean-Baptiste; O'Reilly, Paul F; Schoeler, Tabea; Ploubidis, George B; Rijsdijk, Frühling; Dudbridge, Frank

2018-06-05

Causal inference is essential across the biomedical, behavioural and social sciences.By progressing from confounded statistical associations to evidence of causal relationships, causal inference can reveal complex pathways underlying traits and diseases and help to prioritize targets for intervention. Recent progress in genetic epidemiology - including statistical innovation, massive genotyped data sets and novel computational tools for deep data mining - has fostered the intense development of methods exploiting genetic data and relatedness to strengthen causal inference in observational research. In this Review, we describe how such genetically informed methods differ in their rationale, applicability and inherent limitations and outline how they should be integrated in the future to offer a rich causal inference toolbox.

Causal uncertainty, claimed and behavioural self-handicapping.

PubMed

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.

Domain-specific perceptual causality in children depends on the spatio-temporal configuration, not motion onset

PubMed Central

Schlottmann, Anne; Cole, Katy; Watts, Rhianna; White, Marina

2013-01-01

Humans, even babies, perceive causality when one shape moves briefly and linearly after another. Motion timing is crucial in this and causal impressions disappear with short delays between motions. However, the role of temporal information is more complex: it is both a cue to causality and a factor that constrains processing. It affects ability to distinguish causality from non-causality, and social from mechanical causality. Here we study both issues with 3- to 7-year-olds and adults who saw two computer-animated squares and chose if a picture of mechanical, social or non-causality fit each event best. Prior work fit with the standard view that early in development, the distinction between the social and physical domains depends mainly on whether or not the agents make contact, and that this reflects concern with domain-specific motion onset, in particular, whether the motion is self-initiated or not. The present experiments challenge both parts of this position. In Experiments 1 and 2, we showed that not just spatial, but also animacy and temporal information affect how children distinguish between physical and social causality. In Experiments 3 and 4 we showed that children do not seem to use spatio-temporal information in perceptual causality to make inferences about self- or other-initiated motion onset. Overall, spatial contact may be developmentally primary in domain-specific perceptual causality in that it is processed easily and is dominant over competing cues, but it is not the only cue used early on and it is not used to infer motion onset. Instead, domain-specific causal impressions may be automatic reactions to specific perceptual configurations, with a complex role for temporal information. PMID:23874308

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

PubMed

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.

Education and coronary heart disease: mendelian randomisation study.

PubMed

Tillmann, Taavi; Vaucher, Julien; Okbay, Aysu; Pikhart, Hynek; Peasey, Anne; Kubinova, Ruzena; Pajak, Andrzej; Tamosiunas, Abdonas; Malyutina, Sofia; Hartwig, Fernando Pires; Fischer, Krista; Veronesi, Giovanni; Palmer, Tom; Bowden, Jack; Davey Smith, George; Bobak, Martin; Holmes, Michael V

2017-08-30

Objective  To determine whether educational attainment is a causal risk factor in the development of coronary heart disease. Design  Mendelian randomisation study, using genetic data as proxies for education to minimise confounding. Setting  The main analysis used genetic data from two large consortia (CARDIoGRAMplusC4D and SSGAC), comprising 112 studies from predominantly high income countries. Findings from mendelian randomisation analyses were then compared against results from traditional observational studies (164 170 participants). Finally, genetic data from six additional consortia were analysed to investigate whether longer education can causally alter the common cardiovascular risk factors. Participants  The main analysis was of 543 733 men and women (from CARDIoGRAMplusC4D and SSGAC), predominantly of European origin. Exposure  A one standard deviation increase in the genetic predisposition towards higher education (3.6 years of additional schooling), measured by 162 genetic variants that have been previously associated with education. Main outcome measure  Combined fatal and non-fatal coronary heart disease (63 746 events in CARDIoGRAMplusC4D). Results  Genetic predisposition towards 3.6 years of additional education was associated with a one third lower risk of coronary heart disease (odds ratio 0.67, 95% confidence interval 0.59 to 0.77; P=3×10 -8 ). This was comparable to findings from traditional observational studies (prevalence odds ratio 0.73, 0.68 to 0.78; incidence odds ratio 0.80, 0.76 to 0.83). Sensitivity analyses were consistent with a causal interpretation in which major bias from genetic pleiotropy was unlikely, although this remains an untestable possibility. Genetic predisposition towards longer education was additionally associated with less smoking, lower body mass index, and a favourable blood lipid profile. Conclusions  This mendelian randomisation study found support for the hypothesis that low education is a causal risk factor in the development of coronary heart disease. Potential mechanisms could include smoking, body mass index, and blood lipids. In conjunction with the results from studies with other designs, these findings suggest that increasing education may result in substantial health benefits.

Education and coronary heart disease: mendelian randomisation study

PubMed Central

Vaucher, Julien; Okbay, Aysu; Pikhart, Hynek; Peasey, Anne; Kubinova, Ruzena; Pajak, Andrzej; Tamosiunas, Abdonas; Malyutina, Sofia; Hartwig, Fernando Pires; Fischer, Krista; Veronesi, Giovanni; Palmer, Tom; Bowden, Jack; Davey Smith, George; Bobak, Martin; Holmes, Michael V

2017-01-01

Objective To determine whether educational attainment is a causal risk factor in the development of coronary heart disease. Design Mendelian randomisation study, using genetic data as proxies for education to minimise confounding. Setting The main analysis used genetic data from two large consortia (CARDIoGRAMplusC4D and SSGAC), comprising 112 studies from predominantly high income countries. Findings from mendelian randomisation analyses were then compared against results from traditional observational studies (164 170 participants). Finally, genetic data from six additional consortia were analysed to investigate whether longer education can causally alter the common cardiovascular risk factors. Participants The main analysis was of 543 733 men and women (from CARDIoGRAMplusC4D and SSGAC), predominantly of European origin. Exposure A one standard deviation increase in the genetic predisposition towards higher education (3.6 years of additional schooling), measured by 162 genetic variants that have been previously associated with education. Main outcome measure Combined fatal and non-fatal coronary heart disease (63 746 events in CARDIoGRAMplusC4D). Results Genetic predisposition towards 3.6 years of additional education was associated with a one third lower risk of coronary heart disease (odds ratio 0.67, 95% confidence interval 0.59 to 0.77; P=3×10−8). This was comparable to findings from traditional observational studies (prevalence odds ratio 0.73, 0.68 to 0.78; incidence odds ratio 0.80, 0.76 to 0.83). Sensitivity analyses were consistent with a causal interpretation in which major bias from genetic pleiotropy was unlikely, although this remains an untestable possibility. Genetic predisposition towards longer education was additionally associated with less smoking, lower body mass index, and a favourable blood lipid profile. Conclusions This mendelian randomisation study found support for the hypothesis that low education is a causal risk factor in the development of coronary heart disease. Potential mechanisms could include smoking, body mass index, and blood lipids. In conjunction with the results from studies with other designs, these findings suggest that increasing education may result in substantial health benefits. PMID:28855160

A methodology to model causal relationships on offshore safety assessment focusing on human and organizational factors.

PubMed

Ren, J; Jenkinson, I; Wang, J; Xu, D L; Yang, J B

2008-01-01

Focusing on people and organizations, this paper aims to contribute to offshore safety assessment by proposing a methodology to model causal relationships. The methodology is proposed in a general sense that it will be capable of accommodating modeling of multiple risk factors considered in offshore operations and will have the ability to deal with different types of data that may come from different resources. Reason's "Swiss cheese" model is used to form a generic offshore safety assessment framework, and Bayesian Network (BN) is tailored to fit into the framework to construct a causal relationship model. The proposed framework uses a five-level-structure model to address latent failures within the causal sequence of events. The five levels include Root causes level, Trigger events level, Incidents level, Accidents level, and Consequences level. To analyze and model a specified offshore installation safety, a BN model was established following the guideline of the proposed five-level framework. A range of events was specified, and the related prior and conditional probabilities regarding the BN model were assigned based on the inherent characteristics of each event. This paper shows that Reason's "Swiss cheese" model and BN can be jointly used in offshore safety assessment. On the one hand, the five-level conceptual model is enhanced by BNs that are capable of providing graphical demonstration of inter-relationships as well as calculating numerical values of occurrence likelihood for each failure event. Bayesian inference mechanism also makes it possible to monitor how a safety situation changes when information flow travel forwards and backwards within the networks. On the other hand, BN modeling relies heavily on experts' personal experiences and is therefore highly domain specific. "Swiss cheese" model is such a theoretic framework that it is based on solid behavioral theory and therefore can be used to provide industry with a roadmap for BN modeling and implications. A case study of the collision risk between a Floating Production, Storage and Offloading (FPSO) unit and authorized vessels caused by human and organizational factors (HOFs) during operations is used to illustrate an industrial application of the proposed methodology.

"Fundamental Causes" of Social Inequalities in Mortality: A Test of the Theory

ERIC Educational Resources Information Center

Phelan, Jo C.; Link, Bruce G.; Diez-Roux, Ana; Kawachi, Ichiro; Levin, Bruce

2004-01-01

Medicine and epidemiology currently dominate the study of the strong association between socioeconomic status and mortality. Socioeconomic status typically is viewed as a causally irrelevant "confounding variable" or as a less critical variable marking only the beginning of a causal chain in which intervening risk factors are given prominence. Yet…

Can Being Scared Cause Tummy Aches? Naive Theories, Ambiguous Evidence, and Preschoolers' Causal Inferences

ERIC Educational Resources Information Center

Schulz, Laura E.; Bonawitz, Elizabeth Baraff; Griffiths, Thomas L.

2007-01-01

Causal learning requires integrating constraints provided by domain-specific theories with domain-general statistical learning. In order to investigate the interaction between these factors, the authors presented preschoolers with stories pitting their existing theories against statistical evidence. Each child heard 2 stories in which 2 candidate…

Prediction versus aetiology: common pitfalls and how to avoid them.

PubMed

van Diepen, Merel; Ramspek, Chava L; Jager, Kitty J; Zoccali, Carmine; Dekker, Friedo W

2017-04-01

Prediction research is a distinct field of epidemiologic research, which should be clearly separated from aetiological research. Both prediction and aetiology make use of multivariable modelling, but the underlying research aim and interpretation of results are very different. Aetiology aims at uncovering the causal effect of a specific risk factor on an outcome, adjusting for confounding factors that are selected based on pre-existing knowledge of causal relations. In contrast, prediction aims at accurately predicting the risk of an outcome using multiple predictors collectively, where the final prediction model is usually based on statistically significant, but not necessarily causal, associations in the data at hand.In both scientific and clinical practice, however, the two are often confused, resulting in poor-quality publications with limited interpretability and applicability. A major problem is the frequently encountered aetiological interpretation of prediction results, where individual variables in a prediction model are attributed causal meaning. This article stresses the differences in use and interpretation of aetiological and prediction studies, and gives examples of common pitfalls. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

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

PubMed

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.

The good, the bad, and the timely: how temporal order and moral judgment influence causal selection

PubMed Central

Reuter, Kevin; Kirfel, Lara; van Riel, Raphael; Barlassina, Luca

2014-01-01

Causal selection is the cognitive process through which one or more elements in a complex causal structure are singled out as actual causes of a certain effect. In this paper, we report on an experiment in which we investigated the role of moral and temporal factors in causal selection. Our results are as follows. First, when presented with a temporal chain in which two human agents perform the same action one after the other, subjects tend to judge the later agent to be the actual cause. Second, the impact of temporal location on causal selection is almost canceled out if the later agent did not violate a norm while the former did. We argue that this is due to the impact that judgments of norm violation have on causal selection—even if the violated norm has nothing to do with the obtaining effect. Third, moral judgments about the effect influence causal selection even in the case in which agents could not have foreseen the effect and did not intend to bring it about. We discuss our findings in connection to recent theories of the role of moral judgment in causal reasoning, on the one hand, and to probabilistic models of temporal location, on the other. PMID:25477851

Latent structure modeling underlying theophylline tablet formulations using a Bayesian network based on a self-organizing map clustering.

PubMed

Yasuda, Akihito; Onuki, Yoshinori; Obata, Yasuko; Takayama, Kozo

2015-01-01

The "quality by design" concept in pharmaceutical formulation development requires the establishment of a science-based rationale and design space. In this article, we integrate thin-plate spline (TPS) interpolation, Kohonen's self-organizing map (SOM) and a Bayesian network (BN) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline tablets were prepared using a standard formulation. We measured the tensile strength and disintegration time as response variables and the compressibility, cohesion and dispersibility of the pretableting blend as latent variables. We predicted these variables quantitatively using nonlinear TPS, generated a large amount of data on pretableting blends and tablets and clustered these data into several clusters using a SOM. Our results show that we are able to predict the experimental values of the latent and response variables with a high degree of accuracy and are able to classify the tablet data into several distinct clusters. In addition, to visualize the latent structure between the causal and latent factors and the response variables, we applied a BN method to the SOM clustering results. We found that despite having inserted latent variables between the causal factors and response variables, their relation is equivalent to the results for the SOM clustering, and thus we are able to explain the underlying latent structure. Consequently, this technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline tablet formulation.

The temporal stability and predictive validity of pupils' causal attributions for difficult classroom behaviour.

PubMed

Lambert, Nathan; Miller, Andy

2010-12-01

Recent studies have investigated the causal attributions for difficult pupil behaviour made by teachers, pupils, and parents but none have investigated the temporal stability or predictive validity of these attributions. This study examines the causal attributions made for difficult classroom behaviour by students on two occasions 30 months apart. The longitudinal stability of these attributions is considered as is the predictive validity of the first set of attributions in relation to teachers' later judgments about individual students' behaviour. Two hundred and seventeen secondary school age pupils (114 males, 103 females) provided data on the two occasions. Teachers also rated each student's behaviour at the two times. A questionnaire listing 63 possible causes of classroom misbehaviour was delivered to pupils firstly when they were in Year 7 (aged 11-12) and then again, 30 months later. Responses were analysed through exploratory factor analysis (EFA). Additionally, teachers were asked to rate the standard of behaviour of each of the students on the two occasions. EFA of the Years 7 and 10 data indicated that pupils' attributions yielded broadly similar five-factor models with the perceived relative importance of these factors remaining the same. Analysis also revealed a predictive relationship between pupils' attributions regarding the factor named culture of misbehaviour in Year 7, and teachers' judgments of their standard of behaviour in Year 10. The present study suggests that young adolescents' causal attributions for difficult classroom behaviour remain stable over time and are predictive of teachers' later judgments about their behaviour.

Automated interviews on clinical case reports to elicit directed acyclic graphs.

PubMed

Luciani, Davide; Stefanini, Federico M

2012-05-01

Setting up clinical reports within hospital information systems makes it possible to record a variety of clinical presentations. Directed acyclic graphs (Dags) offer a useful way of representing causal relations in clinical problem domains and are at the core of many probabilistic models described in the medical literature, like Bayesian networks. However, medical practitioners are not usually trained to elicit Dag features. Part of the difficulty lies in the application of the concept of direct causality before selecting all the causal variables of interest for a specific patient. We designed an automated interview to tutor medical doctors in the development of Dags to represent their understanding of clinical reports. Medical notions were analyzed to find patterns in medical reasoning that can be followed by algorithms supporting the elicitation of causal Dags. Clinical relevance was defined to help formulate only relevant questions by driving an expert's attention towards variables causally related to nodes already inserted in the graph. Key procedural features of the proposed interview are described by four algorithms. The automated interview comprises questions on medical notions, phrased in medical terms. The first elicitation session produces questions concerning the patient's chief complaints and the outcomes related to diseases serving as diagnostic hypotheses, their observable manifestations and risk factors. The second session focuses on questions that refine the initial causal paths by considering syndromes, dysfunctions, pathogenic anomalies, biases and effect modifiers. A case study concerning a gastro-enterological problem and one dealing with an infected patient illustrate the output produced by the algorithms, depending on the answers provided by the doctor. The proposed elicitation framework is characterized by strong consistency with medical background and by a progressive introduction of relevant medical topics. Revision and testing of the subjectively elicited Dag is performed by matching the collected answers with the evidence included in accepted sources of biomedical knowledge. Copyright © 2011 Elsevier B.V. All rights reserved.

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

PubMed

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. Copyright 2010 Elsevier Ltd. All rights reserved.

Knowledge Representation Standards and Interchange Formats for Causal Graphs

NASA Technical Reports Server (NTRS)

Throop, David R.; Malin, Jane T.; Fleming, Land

2005-01-01

In many domains, automated reasoning tools must represent graphs of causally linked events. These include fault-tree analysis, probabilistic risk assessment (PRA), planning, procedures, medical reasoning about disease progression, and functional architectures. Each of these fields has its own requirements for the representation of causation, events, actors and conditions. The representations include ontologies of function and cause, data dictionaries for causal dependency, failure and hazard, and interchange formats between some existing tools. In none of the domains has a generally accepted interchange format emerged. The paper makes progress towards interoperability across the wide range of causal analysis methodologies. We survey existing practice and emerging interchange formats in each of these fields. Setting forth a set of terms and concepts that are broadly shared across the domains, we examine the several ways in which current practice represents them. Some phenomena are difficult to represent or to analyze in several domains. These include mode transitions, reachability analysis, positive and negative feedback loops, conditions correlated but not causally linked and bimodal probability distributions. We work through examples and contrast the differing methods for addressing them. We detail recent work in knowledge interchange formats for causal trees in aerospace analysis applications in early design, safety and reliability. Several examples are discussed, with a particular focus on reachability analysis and mode transitions. We generalize the aerospace analysis work across the several other domains. We also recommend features and capabilities for the next generation of causal knowledge representation standards.

Reconstructing constructivism: causal models, Bayesian learning mechanisms, and the theory theory.

PubMed

Gopnik, Alison; Wellman, Henry M

2012-11-01

We propose a new version of the "theory theory" grounded in the computational framework of probabilistic causal models and Bayesian learning. Probabilistic models allow a constructivist but rigorous and detailed approach to cognitive development. They also explain the learning of both more specific causal hypotheses and more abstract framework theories. We outline the new theoretical ideas, explain the computational framework in an intuitive and nontechnical way, and review an extensive but relatively recent body of empirical results that supports these ideas. These include new studies of the mechanisms of learning. Children infer causal structure from statistical information, through their own actions on the world and through observations of the actions of others. Studies demonstrate these learning mechanisms in children from 16 months to 4 years old and include research on causal statistical learning, informal experimentation through play, and imitation and informal pedagogy. They also include studies of the variability and progressive character of intuitive theory change, particularly theory of mind. These studies investigate both the physical and the psychological and social domains. We conclude with suggestions for further collaborative projects between developmental and computational cognitive scientists.

Evaluation of the causal framework used for setting national ambient air quality standards.

PubMed

Goodman, Julie E; Prueitt, Robyn L; Sax, Sonja N; Bailey, Lisa A; Rhomberg, Lorenz R

2013-11-01

Abstract A scientifically sound assessment of the potential hazards associated with a substance requires a systematic, objective and transparent evaluation of the weight of evidence (WoE) for causality of health effects. We critically evaluated the current WoE framework for causal determination used in the United States Environmental Protection Agency's (EPA's) assessments of the scientific data on air pollutants for the National Ambient Air Quality Standards (NAAQS) review process, including its methods for literature searches; study selection, evaluation and integration; and causal judgments. The causal framework used in recent NAAQS evaluations has many valuable features, but it could be more explicit in some cases, and some features are missing that should be included in every WoE evaluation. Because of this, it has not always been applied consistently in evaluations of causality, leading to conclusions that are not always supported by the overall WoE, as we demonstrate using EPA's ozone Integrated Science Assessment as a case study. We propose additions to the NAAQS causal framework based on best practices gleaned from a previously conducted survey of available WoE frameworks. A revision of the NAAQS causal framework so that it more closely aligns with these best practices and the full and consistent application of the framework will improve future assessments of the potential health effects of criteria air pollutants by making the assessments more thorough, transparent, and scientifically sound.

What matters most: quantifying an epidemiology of consequence

PubMed Central

Keyes, Katherine; Galea, Sandro

2015-01-01

Risk factor epidemiology has contributed to substantial public health success. In this essay, we argue, however, that the focus on risk factor epidemiology has led epidemiology to ever increasing focus on the estimation of precise causal effects of exposures on an outcome at the expense of engagement with the broader causal architecture that produces population health. To conduct an epidemiology of consequence, a systematic effort is needed to engage our science in a critical reflection both about how well and under what conditions or assumptions we can assess causal effects and also on what will truly matter most for changing population health. Such an approach changes the priorities and values of the discipline and requires reorientation of how we structure the questions we ask and the methods we use, as well as how we teach epidemiology to our emerging scholars. PMID:25749559

Model robustness as a confirmatory virtue: The case of climate science.

PubMed

Lloyd, Elisabeth A

2015-02-01

I propose a distinct type of robustness, which I suggest can support a confirmatory role in scientific reasoning, contrary to the usual philosophical claims. In model robustness, repeated production of the empirically successful model prediction or retrodiction against a background of independently-supported and varying model constructions, within a group of models containing a shared causal factor, may suggest how confident we can be in the causal factor and predictions/retrodictions, especially once supported by a variety of evidence framework. I present climate models of greenhouse gas global warming of the 20th Century as an example, and emphasize climate scientists' discussions of robust models and causal aspects. The account is intended as applicable to a broad array of sciences that use complex modeling techniques. Copyright © 2014 Elsevier Ltd. All rights reserved.

A review of protective factors and causal mechanisms that enhance the mental health of Indigenous Circumpolar youth.

PubMed

MacDonald, Joanna Petrasek; Ford, James D; Willox, Ashlee Cunsolo; Ross, Nancy A

2013-12-09

To review the protective factors and causal mechanisms which promote and enhance Indigenous youth mental health in the Circumpolar North. A systematic literature review of peer-reviewed English-language research was conducted to systematically examine the protective factors and causal mechanisms which promote and enhance Indigenous youth mental health in the Circumpolar North. This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, with elements of a realist review. From 160 records identified in the initial search of 3 databases, 15 met the inclusion criteria and were retained for full review. Data were extracted using a codebook to organize and synthesize relevant information from the articles. More than 40 protective factors at the individual, family, and community levels were identified as enhancing Indigenous youth mental health. These included practicing and holding traditional knowledge and skills, the desire to be useful and to contribute meaningfully to one's community, having positive role models, and believing in one's self. Broadly, protective factors at the family and community levels were identified as positively creating and impacting one's social environment, which interacts with factors at the individual level to enhance resilience. An emphasis on the roles of cultural and land-based activities, history, and language, as well as on the importance of social and family supports, also emerged throughout the literature. More than 40 protective factors at the individual, family, and community levels were identified as enhancing Indigenous youth mental health. These included practicing and holding traditional knowledge and skills, the desire to be useful and to contribute meaningfully to one's community, having positive role models, and believing in one's self. Broadly, protective factors at the family and community levels were identified as positively creating and impacting one's social environment, which interacts with factors at the individual level to enhance resilience. An emphasis on the roles of cultural and land-based activities, history, and language, as well as on the importance of social and family supports, also emerged throughout the literature. Healthy communities and families foster and support youth who are resilient to mental health challenges and able to adapt and cope with multiple stressors, be they social, economic, or environmental. Creating opportunities and environments where youth can successfully navigate challenges and enhance their resilience can in turn contribute to fostering healthy Circumpolar communities. Looking at the role of new social media in the way youth communicate and interact is one way of understanding how to create such opportunities. Youth perspectives of mental health programmes are crucial to developing appropriate mental health support and meaningful engagement of youth can inform locally appropriate and culturally relevant mental health resources, programmes and community resilience strategies.

A review of protective factors and causal mechanisms that enhance the mental health of Indigenous Circumpolar youth

PubMed Central

MacDonald, Joanna Petrasek; Ford, James D.; Willox, Ashlee Cunsolo; Ross, Nancy A.

2013-01-01

Objectives To review the protective factors and causal mechanisms which promote and enhance Indigenous youth mental health in the Circumpolar North. Study design A systematic literature review of peer-reviewed English-language research was conducted to systematically examine the protective factors and causal mechanisms which promote and enhance Indigenous youth mental health in the Circumpolar North. Methods This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, with elements of a realist review. From 160 records identified in the initial search of 3 databases, 15 met the inclusion criteria and were retained for full review. Data were extracted using a codebook to organize and synthesize relevant information from the articles. Results More than 40 protective factors at the individual, family, and community levels were identified as enhancing Indigenous youth mental health. These included practicing and holding traditional knowledge and skills, the desire to be useful and to contribute meaningfully to one's community, having positive role models, and believing in one's self. Broadly, protective factors at the family and community levels were identified as positively creating and impacting one's social environment, which interacts with factors at the individual level to enhance resilience. An emphasis on the roles of cultural and land-based activities, history, and language, as well as on the importance of social and family supports, also emerged throughout the literature. More than 40 protective factors at the individual, family, and community levels were identified as enhancing Indigenous youth mental health. These included practicing and holding traditional knowledge and skills, the desire to be useful and to contribute meaningfully to one's community, having positive role models, and believing in one's self. Broadly, protective factors at the family and community levels were identified as positively creating and impacting one's social environment, which interacts with factors at the individual level to enhance resilience. An emphasis on the roles of cultural and land-based activities, history, and language, as well as on the importance of social and family supports, also emerged throughout the literature. Conclusions Healthy communities and families foster and support youth who are resilient to mental health challenges and able to adapt and cope with multiple stressors, be they social, economic, or environmental. Creating opportunities and environments where youth can successfully navigate challenges and enhance their resilience can in turn contribute to fostering healthy Circumpolar communities. Looking at the role of new social media in the way youth communicate and interact is one way of understanding how to create such opportunities. Youth perspectives of mental health programmes are crucial to developing appropriate mental health support and meaningful engagement of youth can inform locally appropriate and culturally relevant mental health resources, programmes and community resilience strategies. PMID:24350066

Determining Directional Dependency in Causal Associations

ERIC Educational Resources Information Center

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…

Programs as Causal Models: Speculations on Mental Programs and Mental Representation

ERIC Educational Resources Information Center

Chater, Nick; Oaksford, Mike

2013-01-01

Judea Pearl has argued that counterfactuals and causality are central to intelligence, whether natural or artificial, and has helped create a rich mathematical and computational framework for formally analyzing causality. Here, we draw out connections between these notions and various current issues in cognitive science, including the nature of…

Verification of Causal Influences of Reasoning Skills and Epistemology on Physics Conceptual Learning

ERIC Educational Resources Information Center

Ding, Lin

2014-01-01

This study seeks to test the causal influences of reasoning skills and epistemologies on student conceptual learning in physics. A causal model, integrating multiple variables that were investigated separately in the prior literature, is proposed and tested through path analysis. These variables include student preinstructional reasoning skills…

The Relationship of Self-Concept to Causal Attributions.

ERIC Educational Resources Information Center

Shaha, Steven H.

When people experience failures they search for an explanation of why the failure occurred. The process of seeking an explanatory cause is the basis of attribution theory. Causal attributions include the dimensions of locus of causality (internal or external), stability of the cause over time, and the degree of personal control over the outcome.…

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

PubMed Central

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

Factors Influencing the Sahelian Paradox at the Local Watershed Scale: Causal Inference Insights

NASA Astrophysics Data System (ADS)

Van Gordon, M.; Groenke, A.; Larsen, L.

2017-12-01

While the existence of paradoxical rainfall-runoff and rainfall-groundwater correlations are well established in the West African Sahel, the hydrologic mechanisms involved are poorly understood. In pursuit of mechanistic explanations, we perform a causal inference analysis on hydrologic variables in three watersheds in Benin and Niger. Using an ensemble of techniques, we compute the strength of relationships between observational soil moisture, runoff, precipitation, and temperature data at seasonal and event timescales. Performing analysis over a range of time lags allows dominant time scales to emerge from the relationships between variables. By determining the time scales of hydrologic connectivity over vertical and lateral space, we show differences in the importance of overland and subsurface flow over the course of the rainy season and between watersheds. While previous work on the paradoxical hydrologic behavior in the Sahel focuses on surface processes and infiltration, our results point toward the importance of subsurface flow to rainfall-runoff relationships in these watersheds. The hypotheses generated from our ensemble approach suggest that subsequent explorations of mechanistic hydrologic processes in the region include subsurface flow. Further, this work highlights how an ensemble approach to causal analysis can reveal nuanced relationships between variables even in poorly understood hydrologic systems.

Causal Factors of Corruption in Construction Project Management: An Overview.

PubMed

Owusu, Emmanuel Kingsford; Chan, Albert P C; Shan, Ming

2017-11-11

The development of efficient and strategic anti-corruption measures can be better achieved if a deeper understanding and identification of the causes of corruption are established. Over the past years, many studies have been devoted to the research of corruption in construction management (CM). This has resulted in a significant increase in the body of knowledge on the subject matter, including the causative factors triggering these corrupt practices. However, an apropos systematic assessment of both past and current studies on the subject matter which is needful for the future endeavor is lacking. Moreover, there is an absence of unified view of the causative factors of corruption identified in construction project management (CPM). This paper, therefore, presents a comprehensive review of the causes of corruption from selected articles in recognized construction management journals to address the mentioned gaps. A total number of 44 causes of corruption were identified from 37 publications and analyzed in terms of existing causal factors of corruption, annual trend of publications and the thematic categorization of the identified variables. The most identifiable causes were over close relationships, poor professional ethical standards, negative industrial and working conditions, negative role models and inadequate sanctions. A conceptual framework of causes of corruption was established, after categorizing the 44 variables into five unique categories. In descending order, the five constructs are Psychosocial-Specific Causes, Organizational-Specific Causes, Regulatory-Specific Causes, Project-Specific Causes and Statutory-Specific Causes. This study extends the current literature of corruption research in construction management and contributes to a deepened understanding of the causal instigators of corruption identified in CPM. The findings from this study provide valuable information and extended knowledge to industry practitioners and policymakers as well as anti-corruption agencies in the formulation and direction of anti-corruption measures. To corruption researchers in CM, this study is vital for further research.

Do material, psychosocial and behavioural factors mediate the relationship between disability acquisition and mental health? A sequential causal mediation analysis.

PubMed

Aitken, Zoe; Simpson, Julie Anne; Gurrin, Lyle; Bentley, Rebecca; Kavanagh, Anne Marie

2018-01-29

There is evidence of a causal relationship between disability acquisition and poor mental health; however, the mechanism by which disability affects mental health is poorly understood. This gap in understanding limits the development of effective interventions to improve the mental health of people with disabilities. We used four waves of data from the Household, Income and Labour Dynamics in Australia Survey (2011-14) to compare self-reported mental health between individuals who acquired any disability (n=387) and those who remained disability-free (n=7936). We tested three possible pathways from disability acquisition to mental health, examining the effect of material, psychosocial and behavioural mediators. The effect was partitioned into natural direct and indirect effects through the mediators using a sequential causal mediation analysis approach. Multiple imputation using chained equations was used to assess the impact of missing data. Disability acquisition was estimated to cause a five-point decline in mental health [estimated mean difference: -5.3, 95% confidence interval (CI) -6.8, -3.7]. The indirect effect through material factors was estimated to be a 1.7-point difference (-1.7, 95% CI -2.8, -0.6), explaining 32% of the total effect, with a negligible proportion of the effect explained by the addition of psychosocial characteristics (material and psychosocial: -1.7, 95% CI -3.0, -0.5) and a further 5% by behavioural factors (material-psychosocial-behavioural: -2.0, 95% CI -3.4, -0.6). The finding that the effect of disability acquisition on mental health operates predominantly through material rather than psychosocial and behavioural factors has important implications. The results highlight the need for better social protection, including income support, employment and education opportunities, and affordable housing for people who acquire a disability. © The Author(s) 2018; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association

Molecular mechanisms of maternal vascular dysfunction in preeclampsia.

PubMed

Goulopoulou, Styliani; Davidge, Sandra T

2015-02-01

In preeclampsia, as a heterogeneous syndrome, multiple pathways have been proposed for both the causal as well as the perpetuating factors leading to maternal vascular dysfunction. Postulated mechanisms include imbalance in the bioavailability and activity of endothelium-derived contracting and relaxing factors and oxidative stress. Studies have shown that placenta-derived factors [antiangiogenic factors, microparticles (MPs), cell-free nucleic acids] are released into the maternal circulation and act on the vascular wall to modify the secretory capacity of endothelial cells and alter the responsiveness of vascular smooth muscle cells to constricting and relaxing stimuli. These molecules signal their deleterious effects on the maternal vascular wall via pathways that provide the molecular basis for novel and effective therapeutic interventions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Risk Factors of Periodontal Disease: Review of the Literature

PubMed Central

AlJehani, Yousef A.

2014-01-01

Objectives. This paper aims to review the evidence on the potential roles of modifiable and nonmodifiable risk factors associated with periodontal disease. Data. Original articles that reported on the risk factors for periodontal disease were included. Sources. MEDLINE (1980 to Jan 2014), PubMed (using medical subject headings), and Google Scholar were searched using the following terms in different combinations: “periodontal disease,” “periodontitis,” “risk factors,” and “causal.” This was supplemented by hand-searching in peer-reviewed journals and cross-referenced with the articles accessed. Conclusions. It is important to understand the etiological factors and the pathogenesis of periodontal disease to recognize and appreciate the associated risk factors. As periodontal disease is multifactorial, effective disease management requires a clear understanding of all the associated risk factors. PMID:24963294

Subjective spacetime derived from a causal histories approach

NASA Astrophysics Data System (ADS)

Gunji, Yukio-Pegio; Haruna, Taichi; Uragami, Daisuke; Nishikawa, Asaki

2009-10-01

The internal description of spacetime can reveal ambiguity regarding an observer’s perception of the present, where an observer can refer to the present as if he were outside spacetime while actually existing in the present. This ambiguity can be expressed as the compatibility between an element and a set, and is here called a/{a}-compatibility. We describe a causal set as a lattice and a causal history as a quotient lattice, and implement the a/{a}-compatibility in the framework of a causal histories approach. This leads to a perpetual change of a pair of causal set and causal history, and can be used to describe subjective spacetime including the déjà vu experience and/or schizophrenic time.

Agency, time, and causality

PubMed Central

Widlok, Thomas

2014-01-01

Cognitive Scientists interested in causal cognition increasingly search for evidence from non-Western Educational Industrial Rich Democratic 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. PMID:25414683

Etiology in psychiatry: embracing the reality of poly‐gene‐environmental causation of mental illness

PubMed Central

Uher, Rudolf; Zwicker, Alyson

2017-01-01

Intriguing findings on genetic and environmental causation suggest a need to reframe the etiology of mental disorders. Molecular genetics shows that thousands of common and rare genetic variants contribute to mental illness. Epidemiological studies have identified dozens of environmental exposures that are associated with psychopathology. The effect of environment is likely conditional on genetic factors, resulting in gene‐environment interactions. The impact of environmental factors also depends on previous exposures, resulting in environment‐environment interactions. Most known genetic and environmental factors are shared across multiple mental disorders. Schizophrenia, bipolar disorder and major depressive disorder, in particular, are closely causally linked. Synthesis of findings from twin studies, molecular genetics and epidemiological research suggests that joint consideration of multiple genetic and environmental factors has much greater explanatory power than separate studies of genetic or environmental causation. Multi‐factorial gene‐environment interactions are likely to be a generic mechanism involved in the majority of cases of mental illness, which is only partially tapped by existing gene‐environment studies. Future research may cut across psychiatric disorders and address poly‐causation by considering multiple genetic and environmental measures across the life course with a specific focus on the first two decades of life. Integrative analyses of poly‐causation including gene‐environment and environment‐environment interactions can realize the potential for discovering causal types and mechanisms that are likely to generate new preventive and therapeutic tools. PMID:28498595

Assessing Command and Control System Vulnerabilities in Underdeveloped, Degraded and Denied Operational Environments

DTIC Science & Technology

2013-06-01

simulation of complex systems (Sterman 2000, Meadows 2008): a) Causal Loop Diagrams. A Causal Loop Diagram ( CLD ) is used to represent the feedback...structure of the dynamic system. CLDs consist of variables in the system being connected by arrows to show their causal influences and relationships. It is...distribution of orders will be included in the model. 6.4.2 Causal Loop Diagrams The CLD , as seen in Figure 5, is derived from the WDA constructs for the

Abilities of 4-7 Years Old Children to Provide Independent Explanations and Generalisations of Causality

ERIC Educational Resources Information Center

Daugirdiene, Ausra; Petrulyte, Aiste; Brandisauskiene, Agne

2018-01-01

The understanding and generalisation of causality are important thinking abilities, as they form the basis for a person's activity. Researchers exploring these abilities do not have a unified opinion regarding the age of children when they develop causative understanding and its determinant factors (e.g. age, prior knowledge, the content of a…

Development and Coherence of Beliefs Regarding Disease Causality and Prevention

ERIC Educational Resources Information Center

Sigelman, Carol K.

2014-01-01

Guided by a naïve theories perspective on the development of thinking about disease, this study of 188 children aged 6 to 18 examined knowledge of HIV/AIDS causality and prevention using parallel measures derived from open-ended and structured interviews. Knowledge of both risk factors and prevention rules, as well as conceptual understanding of…

What Does Quantum Physics Have to Do with Behavior Disorders?

ERIC Educational Resources Information Center

Center, David B.

This paper argues that human agency as a causal factor in behavior must be considered in any model of behavior and behavior disorders. Since human agency is historically tied to the issue of consciousness, to argue that consciousness plays a causal role in behavior requires a plausible explanation of consciousness. This paper proposes that…

University Students' Causal Conceptions about Social Mobility: Diverging Pathways for Believers in Personal Merit and Luck

ERIC Educational Resources Information Center

Shane, Jacob; Heckhausen, Jutta

2013-01-01

Many college students hold ambitious goals for upward social mobility via post-college careers. However, in the current economic recession such optimistic expectations are not a given. The present study examines how college students' current social status and beliefs in causal factors for socioeconomic status (SES) attainment lead to diverging…

Effects of Age, Gender, and Causality on Perceptions of Persons with Mental Retardation

ERIC Educational Resources Information Center

Panek, Paul E.; Jungers, Melissa K.

2008-01-01

The present study examined the effects of age, gender, and causality on the perceptions of persons with mental retardation. Participants rated individuals with mental retardation using a semantic differential scale with three factors: activity, evaluation, and potency. Target individuals in each scenario varied on the variables of age (8, 20, 45),…

A Causal Model of Career Development and Quality of Life of College Students with Disabilities

ERIC Educational Resources Information Center

Chun, Jina

2017-01-01

Researchers have assumed that social cognitive factors play significant roles in the career development of transition youth and young adults with disabilities and those without disabilities. However, research on the influence of the career decision-making process as a primary causal agent in one's psychosocial outcomes such as perceived level of…

Feedback Both Helps and Hinders Learning: The Causal Role of Prior Knowledge

ERIC Educational Resources Information Center

Fyfe, Emily R.; Rittle-Johnson, Bethany

2016-01-01

Feedback can be a powerful learning tool, but its effects vary widely. Research has suggested that learners' prior knowledge may moderate the effects of feedback; however, no causal link has been established. In Experiment 1, we randomly assigned elementary school children (N = 108) to a condition based on a crossing of 2 factors: induced strategy…

Quantum correlations with no causal order

PubMed Central

Oreshkov, Ognyan; Costa, Fabio; Brukner, Časlav

2012-01-01

The idea that events obey a definite causal order is deeply rooted in our understanding of the world and at the basis of the very notion of time. But where does causal order come from, and is it a necessary property of nature? Here, we address these questions from the standpoint of quantum mechanics in a new framework for multipartite correlations that does not assume a pre-defined global causal structure but only the validity of quantum mechanics locally. All known situations that respect causal order, including space-like and time-like separated experiments, are captured by this framework in a unified way. Surprisingly, we find correlations that cannot be understood in terms of definite causal order. These correlations violate a 'causal inequality' that is satisfied by all space-like and time-like correlations. We further show that in a classical limit causal order always arises, which suggests that space-time may emerge from a more fundamental structure in a quantum-to-classical transition. PMID:23033068

The "Mevalonate hypothesis": a cholesterol-independent alternative for the etiology of atherosclerosis.

PubMed

Keizer, Hiskias G

2012-11-05

The "cholesterol hypothesis" is the leading theory to explain the cause of atherosclerosis. The "cholesterol hypothesis" assumes that plasma (LDL) cholesterol is an important causal factor for atherosclerosis.However, data of at least seven placebo controlled randomized prospective trials with various cholesterol lowering drugs show that plasma cholesterol lowering does not necessarily lead to protection against cardiovascular disease. Therefore an alternative hypothesis for the etiology of cardiovascular disease is formulated. This alternative hypothesis, the "mevalonate hypothesis", assumes that after stimulation of the mevalonate pathway in endothelial cells by inflammatory factors, these cells start producing cholesterol and free radicals. In this hypothesis, only the latter play a role in the etiology of atherosclerosis by contributing to the formation of oxidized cholesterol which is a widely accepted causal factor for atherosclerosis.Regardless of how the mevalonate pathway is activated (by withdrawal of statin drugs, by inflammatory factors or indirectly by reduced intracellular cholesterol levels) in all these cases free radical production is observed as well as cardiovascular disease. Since in the "mevalonate hypothesis" cholesterol is produced at the same time as the free radicals causing atherosclerosis, this hypothesis provides an explanation for the correlation which exists between cardiovascular disease and plasma cholesterol levels. From an evolutionary perspective, concomitant cholesterol production and free radical production in response to inflammatory factors makes sense if one realizes that both activities potentially protect cells and organisms from infection by gram-negative bacteria.In conclusion, data have been collected which suggest that activation of the mevalonate pathway in endothelial cells is likely to be a causal factor for atherosclerosis. This "mevalonate hypothesis" provides a better explanation for results obtained from recent clinical studies with cholesterol lowering drugs than the "cholesterol hypothesis". Furthermore, this hypothesis explains how cholesterol can be correlated with cardiovascular disease without being a causal factor for it. Finally it provides a logical explanation for the etiology of this disease.

Determinants of Judgments of Explanatory Power: Credibility, Generality, and Statistical Relevance.

PubMed

Colombo, Matteo; Bucher, Leandra; Sprenger, Jan

2017-01-01

Explanation is a central concept in human psychology. Drawing upon philosophical theories of explanation, psychologists have recently begun to examine the relationship between explanation, probability and causality. Our study advances this growing literature at the intersection of psychology and philosophy of science by systematically investigating how judgments of explanatory power are affected by (i) the prior credibility of an explanatory hypothesis, (ii) the causal framing of the hypothesis, (iii) the perceived generalizability of the explanation, and (iv) the relation of statistical relevance between hypothesis and evidence. Collectively, the results of our five experiments support the hypothesis that the prior credibility of a causal explanation plays a central role in explanatory reasoning: first, because of the presence of strong main effects on judgments of explanatory power, and second, because of the gate-keeping role it has for other factors. Highly credible explanations are not susceptible to causal framing effects, but they are sensitive to the effects of normatively relevant factors: the generalizability of an explanation, and its statistical relevance for the evidence. These results advance current literature in the philosophy and psychology of explanation in three ways. First, they yield a more nuanced understanding of the determinants of judgments of explanatory power, and the interaction between these factors. Second, they show the close relationship between prior beliefs and explanatory power. Third, they elucidate the nature of abductive reasoning.

Determinants of Judgments of Explanatory Power: Credibility, Generality, and Statistical Relevance

PubMed Central

Colombo, Matteo; Bucher, Leandra; Sprenger, Jan

2017-01-01

Explanation is a central concept in human psychology. Drawing upon philosophical theories of explanation, psychologists have recently begun to examine the relationship between explanation, probability and causality. Our study advances this growing literature at the intersection of psychology and philosophy of science by systematically investigating how judgments of explanatory power are affected by (i) the prior credibility of an explanatory hypothesis, (ii) the causal framing of the hypothesis, (iii) the perceived generalizability of the explanation, and (iv) the relation of statistical relevance between hypothesis and evidence. Collectively, the results of our five experiments support the hypothesis that the prior credibility of a causal explanation plays a central role in explanatory reasoning: first, because of the presence of strong main effects on judgments of explanatory power, and second, because of the gate-keeping role it has for other factors. Highly credible explanations are not susceptible to causal framing effects, but they are sensitive to the effects of normatively relevant factors: the generalizability of an explanation, and its statistical relevance for the evidence. These results advance current literature in the philosophy and psychology of explanation in three ways. First, they yield a more nuanced understanding of the determinants of judgments of explanatory power, and the interaction between these factors. Second, they show the close relationship between prior beliefs and explanatory power. Third, they elucidate the nature of abductive reasoning. PMID:28928679

Experimental test of nonlocal causality

PubMed Central

Ringbauer, Martin; Giarmatzi, Christina; Chaves, Rafael; Costa, Fabio; White, Andrew G.; Fedrizzi, Alessandro

2016-01-01

Explaining observations in terms of causes and effects is central to empirical science. However, correlations between entangled quantum particles seem to defy such an explanation. This implies that some of the fundamental assumptions of causal explanations have to give way. We consider a relaxation of one of these assumptions, Bell’s local causality, by allowing outcome dependence: a direct causal influence between the outcomes of measurements of remote parties. We use interventional data from a photonic experiment to bound the strength of this causal influence in a two-party Bell scenario, and observational data from a Bell-type inequality test for the considered models. Our results demonstrate the incompatibility of quantum mechanics with a broad class of nonlocal causal models, which includes Bell-local models as a special case. Recovering a classical causal picture of quantum correlations thus requires an even more radical modification of our classical notion of cause and effect. PMID:27532045

Experimental test of nonlocal causality.

PubMed

Ringbauer, Martin; Giarmatzi, Christina; Chaves, Rafael; Costa, Fabio; White, Andrew G; Fedrizzi, Alessandro

2016-08-01

Explaining observations in terms of causes and effects is central to empirical science. However, correlations between entangled quantum particles seem to defy such an explanation. This implies that some of the fundamental assumptions of causal explanations have to give way. We consider a relaxation of one of these assumptions, Bell's local causality, by allowing outcome dependence: a direct causal influence between the outcomes of measurements of remote parties. We use interventional data from a photonic experiment to bound the strength of this causal influence in a two-party Bell scenario, and observational data from a Bell-type inequality test for the considered models. Our results demonstrate the incompatibility of quantum mechanics with a broad class of nonlocal causal models, which includes Bell-local models as a special case. Recovering a classical causal picture of quantum correlations thus requires an even more radical modification of our classical notion of cause and effect.

Beliefs of people taking antidepressants about causes of depression and reasons for increased prescribing rates.

PubMed

Read, John; Cartwright, Claire; Gibson, Kerry; Shiels, Christopher; Haslam, Nicholas

2014-10-01

Public beliefs about the causes of mental health problems are related to desire for distance and pessimism about recovery, and are therefore frequently studied. The beliefs of people receiving treatment are researched less often. An online survey on causal beliefs about depression and experiences with antidepressants was completed by 1829 New Zealand adults prescribed anti-depressants in the preceding five years, 97.4% of whom proceeded to take antidepressants. The most frequently endorsed of 17 causal beliefs were family stress, relationship problems, loss of loved one, financial problems, isolation, and abuse or neglect in childhood. Factor analysis produced three factors: 'bio-genetic', 'adulthood stress' and 'childhood adversity'. The most strongly endorsed explanations for increases in antidepressant prescribing invoked improved identification, reduced stigma and drug company marketing. The least strongly endorsed was 'Anti-depressants are the best treatment'. Regression analyses revealed that self-reported efficacy of the antidepressants was positively associated with bio-genetic causal beliefs, negatively associated with childhood adversity beliefs and unrelated to adulthood stress beliefs. The belief that 'People cannot׳ get better by themselves even if they try' was positively associated with bio-genetic beliefs. The convenience sample may have been biased towards a favourable view of bio-genetic explanations, since 83% reported that the medication reduced their depression. Clinicians׳ should consider exploring patients׳ causal beliefs. The public, even when taking antidepressants, continues to hold a multi-factorial causal model of depression with a primary emphasis on psycho-social causes. A three factor model of those beliefs may lead to more sophisticated understandings of relationships with stigma variables. Copyright © 2014 Elsevier B.V. All rights reserved.

Air Pollution, Oxidative Stress, and Alzheimer's Disease

PubMed Central

Moulton, Paula Valencia; Yang, Wei

2012-01-01

Alzheimer's disease (AD) is the most common form of dementia affecting millions of people worldwide and will continue to affect millions more with population aging on the rise. AD causality is multifactorial. Known causal factors include genetic predisposition, age, and sex. Environmental toxins such as air pollution (AP) have also been implicated in AD causation. Exposure to AP can lead to chronic oxidative stress (OS), which is involved in the pathogenesis of AD. Whereas AP plays a role in AD pathology, the epidemiological evidence for this association is limited. Given the significant prevalence of AP exposure combined with increased population aging, epidemiological evidence for this link is important to consider. In this paper, we examine the existing evidence supporting the relationship between AP, OS, and AD and provide recommendations for future research on the population level, which will provide evidence in support of public health interventions. PMID:22523504

A Causal Relationship of Occupational Stress among University Employees.

PubMed

Kaewanuchit, Chonticha; Muntaner, Carles; Isha, Nizam

2015-07-01

Occupational stress is a psychosocial dimension of occupational health concept on social determinants of health, especially, job & environmental condition. Recently, staff network of different government universities of Thailand have called higher education commission, and Ministry of Education, Thailand to resolve the issue of government education policy (e.g. wage inequity, poor welfare, law, and job & environment condition) that leads to their job insecurity, physical and mental health problems from occupational stress. The aim of this study was to investigate a causal relationship of occupational stress among the academic university employees. This cross sectional research was conducted in 2014 among 2,000 academic university employees at Thai government universities using stratified random sampling. Independent variables were wage, family support, periods of duty, and job & environmental condition. Dependent variable was stress. Job & environmental condition, as social and environmental factor, and periods of duty as individual factor had direct effect to stress (P< 0.05). Family support, as family factor, and wage, as individual factor had direct effect to stress (P < 0.05). Both family support and wage were the causal endogenous variables. Job & environmental condition and periods of duty were increased so that it associated with occupational stress among academic university employees at moderate level.

Non-parametric causality detection: An application to social media and financial data

NASA Astrophysics Data System (ADS)

Tsapeli, Fani; Musolesi, Mirco; Tino, Peter

2017-10-01

According to behavioral finance, stock market returns are influenced by emotional, social and psychological factors. Several recent works support this theory by providing evidence of correlation between stock market prices and collective sentiment indexes measured using social media data. However, a pure correlation analysis is not sufficient to prove that stock market returns are influenced by such emotional factors since both stock market prices and collective sentiment may be driven by a third unmeasured factor. Controlling for factors that could influence the study by applying multivariate regression models is challenging given the complexity of stock market data. False assumptions about the linearity or non-linearity of the model and inaccuracies on model specification may result in misleading conclusions. In this work, we propose a novel framework for causal inference that does not require any assumption about a particular parametric form of the model expressing statistical relationships among the variables of the study and can effectively control a large number of observed factors. We apply our method in order to estimate the causal impact that information posted in social media may have on stock market returns of four big companies. Our results indicate that social media data not only correlate with stock market returns but also influence them.

Formulating and Answering High-Impact Causal Questions in Physiologic Childbirth Science: Concepts and Assumptions.

PubMed

Snowden, Jonathan M; Tilden, Ellen L; Odden, Michelle C

2018-06-08

In this article, we conclude our 3-part series by focusing on several concepts that have proven useful for formulating causal questions and inferring causal effects. The process of causal inference is of key importance for physiologic childbirth science, so each concept is grounded in content related to women at low risk for perinatal complications. A prerequisite to causal inference is determining that the question of interest is causal rather than descriptive or predictive. Another critical step in defining a high-impact causal question is assessing the state of existing research for evidence of causality. We introduce 2 causal frameworks that are useful for this undertaking, Hill's causal considerations and the sufficient-component cause model. We then provide 3 steps to aid perinatal researchers in inferring causal effects in a given study. First, the researcher should formulate a rigorous and clear causal question. We introduce an example of epidural analgesia and labor progression to demonstrate this process, including the central role of temporality. Next, the researcher should assess the suitability of the given data set to answer this causal question. In randomized controlled trials, data are collected with the express purpose of answering the causal question. Investigators using observational data should also ensure that their chosen causal question is answerable with the available data. Finally, investigators should design an analysis plan that targets the causal question of interest. Some data structures (eg, time-dependent confounding by labor progress when estimating the effect of epidural analgesia on postpartum hemorrhage) require specific analytical tools to control for bias and estimate causal effects. The assumptions of consistency, exchangeability, and positivity may be especially useful in carrying out these steps. Drawing on appropriate causal concepts and considering relevant assumptions strengthens our confidence that research has reduced the likelihood of alternative explanations (eg bias, chance) and estimated a causal effect. © 2018 by the American College of Nurse-Midwives.

A Bayesian Theory of Sequential Causal Learning and Abstract Transfer.

PubMed

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 Cognitive Science Society, Inc.

A systematic review of the etiopathogenesis of Kienböck's disease and a critical appraisal of its recognition as an occupational disease related to hand-arm vibration

PubMed Central

2012-01-01

Background We systematically reviewed etiological factors of Kienböck’s disease (osteonecrosis of the lunate) discussed in the literature in order to examine the justification for including Kienböck’s disease (KD) in the European Listing of Occupational Diseases. Methods We searched the Ovid/Medline and the Cochrane Library for articles discussing the etiology of osteonecrosis of the lunate published since the first description of KD in 1910 and up until July 2012 in English, French or German. Literature was classified by the level of evidence presented, the etiopathological hypothesis discussed, and the author's conclusion about the role of the etiopathological hypothesis. The causal relationship between KD and hand-arm vibration was elucidated by the Bradford Hill criteria. Results A total of 220 references was found. Of the included 152 articles, 140 (92%) reached the evidence level IV (case series). The four most frequently discussed factors were negative ulnar variance (n=72; 47%), primary arterial ischemia of the lunate (n=63; 41%), trauma (n=63; 41%) and hand-arm vibration (n=53; 35%). The quality of the cohort studies on hand-arm vibration did not permit a meta-analysis to evaluate the strength of an association to KD. Evidence for the lack of consistency, plausibility and coherence of the 4 most frequently discussed etiopathologies was found. No evidence was found to support any of the nine Bradford Hill criteria for a causal relationship between KD and hand-arm vibration. Conclusions A systematic review of 220 articles on the etiopathology of KD and the application of the Bradford Hill criteria does not provide sufficient scientific evidence to confirm or refute a causal relationship between KD and hand-arm vibration. This currently suggests that, KD does not comply with the criteria of the International Labour Organization determining occupational diseases. However, research with a higher level of evidence is required to further determine if hand-arm vibration is a risk factor for KD. PMID:23171057

Risk factors for neck and upper extremity disorders among computers users and the effect of interventions: an overview of systematic reviews.

PubMed

Andersen, Johan H; Fallentin, Nils; Thomsen, Jane F; Mikkelsen, Sigurd

2011-05-12

To summarize systematic reviews that 1) assessed the evidence for causal relationships between computer work and the occurrence of carpal tunnel syndrome (CTS) or upper extremity musculoskeletal disorders (UEMSDs), or 2) reported on intervention studies among computer users/or office workers. PubMed, Embase, CINAHL and Web of Science were searched for reviews published between 1999 and 2010. Additional publications were provided by content area experts. The primary author extracted all data using a purpose-built form, while two of the authors evaluated the quality of the reviews using recommended standard criteria from AMSTAR; disagreements were resolved by discussion. The quality of evidence syntheses in the included reviews was assessed qualitatively for each outcome and for the interventions. Altogether, 1,349 review titles were identified, 47 reviews were retrieved for full text relevance assessment, and 17 reviews were finally included as being relevant and of sufficient quality. The degrees of focus and rigorousness of these 17 reviews were highly variable. Three reviews on risk factors for carpal tunnel syndrome were rated moderate to high quality, 8 reviews on risk factors for UEMSDs ranged from low to moderate/high quality, and 6 reviews on intervention studies were of moderate to high quality. The quality of the evidence for computer use as a risk factor for CTS was insufficient, while the evidence for computer use and UEMSDs was moderate regarding pain complaints and limited for specific musculoskeletal disorders. From the reviews on intervention studies no strong evidence based recommendations could be given. Computer use is associated with pain complaints, but it is still not very clear if this association is causal. The evidence for specific disorders or diseases is limited. No effective interventions have yet been documented.

Paradoxical Behavior of Granger Causality

NASA Astrophysics Data System (ADS)

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

A review of causal inference for biomedical informatics

PubMed Central

Kleinberg, Samantha; Hripcsak, George

2011-01-01

Causality is an important concept throughout the health sciences and is particularly vital for informatics work such as finding adverse drug events or risk factors for disease using electronic health records. While philosophers and scientists working for centuries on formalizing what makes something a cause have not reached a consensus, new methods for inference show that we can make progress in this area in many practical cases. This article reviews core concepts in understanding and identifying causality and then reviews current computational methods for inference and explanation, focusing on inference from large-scale observational data. While the problem is not fully solved, we show that graphical models and Granger causality provide useful frameworks for inference and that a more recent approach based on temporal logic addresses some of the limitations of these methods. PMID:21782035

Cancer risk and the complexity of the interactions between environmental and host factors: HENVINET interactive diagrams as simple tools for exploring and understanding the scientific evidence.

PubMed

Merlo, Domenico F; Filiberti, Rosangela; Kobernus, Michael; Bartonova, Alena; Gamulin, Marija; Ferencic, Zeljko; Dusinska, Maria; Fucic, Aleksandra

2012-06-28

Development of graphical/visual presentations of cancer etiology caused by environmental stressors is a process that requires combining the complex biological interactions between xenobiotics in living and occupational environment with genes (gene-environment interaction) and genomic and non-genomic based disease specific mechanisms in living organisms. Traditionally, presentation of causal relationships includes the statistical association between exposure to one xenobiotic and the disease corrected for the effect of potential confounders. Within the FP6 project HENVINET, we aimed at considering together all known agents and mechanisms involved in development of selected cancer types. Selection of cancer types for causal diagrams was based on the corpus of available data and reported relative risk (RR). In constructing causal diagrams the complexity of the interactions between xenobiotics was considered a priority in the interpretation of cancer risk. Additionally, gene-environment interactions were incorporated such as polymorphisms in genes for repair and for phase I and II enzymes involved in metabolism of xenobiotics and their elimination. Information on possible age or gender susceptibility is also included. Diagrams are user friendly thanks to multistep access to information packages and the possibility of referring to related literature and a glossary of terms. Diagrams cover both chemical and physical agents (ionizing and non-ionizing radiation) and provide basic information on the strength of the association between type of exposure and cancer risk reported by human studies and supported by mechanistic studies. Causal diagrams developed within HENVINET project represent a valuable source of information for professionals working in the field of environmental health and epidemiology, and as educational material for students. Cancer risk results from a complex interaction of environmental exposures with inherited gene polymorphisms, genetic burden collected during development and non genomic capacity of response to environmental insults. In order to adopt effective preventive measures and the associated regulatory actions, a comprehensive investigation of cancer etiology is crucial. Variations and fluctuations of cancer incidence in human populations do not necessarily reflect environmental pollution policies or population distribution of polymorphisms of genes known to be associated with increased cancer risk. Tools which may be used in such a comprehensive research, including molecular biology applied to field studies, require a methodological shift from the reductionism that has been used until recently as a basic axiom in interpretation of data. The complexity of the interactions between cells, genes and the environment, i.e. the resonance of the living matter with the environment, can be synthesized by systems biology. Within the HENVINET project such philosophy was followed in order to develop interactive causal diagrams for the investigation of cancers with possible etiology in environmental exposure. Causal diagrams represent integrated knowledge and seed tool for their future development and development of similar diagrams for other environmentally related diseases such as asthma or sterility. In this paper development and application of causal diagrams for cancer are presented and discussed.

What matters most: quantifying an epidemiology of consequence.

PubMed

Keyes, Katherine; Galea, Sandro

2015-05-01

Risk factor epidemiology has contributed to substantial public health success. In this essay, we argue, however, that the focus on risk factor epidemiology has led epidemiology to ever increasing focus on the estimation of precise causal effects of exposures on an outcome at the expense of engagement with the broader causal architecture that produces population health. To conduct an epidemiology of consequence, a systematic effort is needed to engage our science in a critical reflection both about how well and under what conditions or assumptions we can assess causal effects and also on what will truly matter most for changing population health. Such an approach changes the priorities and values of the discipline and requires reorientation of how we structure the questions we ask and the methods we use, as well as how we teach epidemiology to our emerging scholars. Copyright © 2015 Elsevier Inc. All rights reserved.

THE ORIGINS OF COGNITIVE DEFICITS IN VICTIMIZED CHILDREN: IMPLICATIONS FOR NEUROSCIENTISTS AND CLINICIANS

PubMed Central

Danese, Andrea; Moffitt, Terrie E; Arseneault, Louise; Bleiberg, Ben A; Dinardo, Perry B; Gandelman, Stephanie B; Houts, Renate; Ambler, Antony; Fisher, Helen; Poulton, Richie; Caspi, Avshalom

2016-01-01

OBJECTIVE Individuals reporting a history of childhood violence victimization have impaired brain function. However, the clinical significance, reproducibility, and causality of these findings are disputed. We directly tested these research gaps. METHOD We tested the association between prospectively-collected measures of childhood violence victimization and cognitive functions in childhood, adolescence, and adulthood among 2,232 members of the UK E-Risk Study and 1,037 members of the New Zealand Dunedin Study, who were followed-up from birth until ages 18 and 38 years, respectively. We used multiple measures of victimization and cognition, and included comparisons of cognitive scores for twins discordant for victimization. RESULTS We found that individuals exposed to childhood victimization had pervasive impairments in clinically-relevant cognitive functions including general intelligence, executive function, processing speed, memory, perceptual reasoning, and verbal comprehension in adolescence and adulthood. However, the observed cognitive deficits in victimized individuals were largely explained by cognitive deficits that predated childhood victimization and by confounding genetic and environmental risks. CONCLUSIONS Findings from two population-representative birth cohorts totaling more than 3,000 individuals and born 20 years and 20,000 kilometers apart suggest that the association between childhood violence victimization and later cognition is largely non-causal, in contrast to conventional interpretations. These findings urge adopting a more circumspect approach to causal inference in the neuroscience of stress. Clinically, cognitive deficits should be conceptualized as individual risk factors for victimization as well as potential complicating features during treatment. PMID:27794691

Disease causality extraction based on lexical semantics and document-clause frequency from biomedical literature.

PubMed

Lee, Dong-Gi; Shin, Hyunjung

2017-05-18

Recently, research on human disease network has succeeded and has become an aid in figuring out the relationship between various diseases. In most disease networks, however, the relationship between diseases has been simply represented as an association. This representation results in the difficulty of identifying prior diseases and their influence on posterior diseases. In this paper, we propose a causal disease network that implements disease causality through text mining on biomedical literature. To identify the causality between diseases, the proposed method includes two schemes: the first is the lexicon-based causality term strength, which provides the causal strength on a variety of causality terms based on lexicon analysis. The second is the frequency-based causality strength, which determines the direction and strength of causality based on document and clause frequencies in the literature. We applied the proposed method to 6,617,833 PubMed literature, and chose 195 diseases to construct a causal disease network. From all possible pairs of disease nodes in the network, 1011 causal pairs of 149 diseases were extracted. The resulting network was compared with that of a previous study. In terms of both coverage and quality, the proposed method showed outperforming results; it determined 2.7 times more causalities and showed higher correlation with associated diseases than the existing method. This research has novelty in which the proposed method circumvents the limitations of time and cost in applying all possible causalities in biological experiments and it is a more advanced text mining technique by defining the concepts of causality term strength.

Reconstructing constructivism: Causal models, Bayesian learning mechanisms and the theory theory

PubMed Central

Gopnik, Alison; Wellman, Henry M.

2012-01-01

We propose a new version of the “theory theory” grounded in the computational framework of probabilistic causal models and Bayesian learning. Probabilistic models allow a constructivist but rigorous and detailed approach to cognitive development. They also explain the learning of both more specific causal hypotheses and more abstract framework theories. We outline the new theoretical ideas, explain the computational framework in an intuitive and non-technical way, and review an extensive but relatively recent body of empirical results that supports these ideas. These include new studies of the mechanisms of learning. Children infer causal structure from statistical information, through their own actions on the world and through observations of the actions of others. Studies demonstrate these learning mechanisms in children from 16 months to 4 years old and include research on causal statistical learning, informal experimentation through play, and imitation and informal pedagogy. They also include studies of the variability and progressive character of intuitive theory change, particularly theory of mind. These studies investigate both the physical and psychological and social domains. We conclude with suggestions for further collaborative projects between developmental and computational cognitive scientists. PMID:22582739

Driver crash risk factors and prevalence evaluation using naturalistic driving data.

PubMed

Dingus, Thomas A; Guo, Feng; Lee, Suzie; Antin, Jonathan F; Perez, Miguel; Buchanan-King, Mindy; Hankey, Jonathan

2016-03-08

The accurate evaluation of crash causal factors can provide fundamental information for effective transportation policy, vehicle design, and driver education. Naturalistic driving (ND) data collected with multiple onboard video cameras and sensors provide a unique opportunity to evaluate risk factors during the seconds leading up to a crash. This paper uses a National Academy of Sciences-sponsored ND dataset comprising 905 injurious and property damage crash events, the magnitude of which allows the first direct analysis (to our knowledge) of causal factors using crashes only. The results show that crash causation has shifted dramatically in recent years, with driver-related factors (i.e., error, impairment, fatigue, and distraction) present in almost 90% of crashes. The results also definitively show that distraction is detrimental to driver safety, with handheld electronic devices having high use rates and risk.

Driver crash risk factors and prevalence evaluation using naturalistic driving data

PubMed Central

Dingus, Thomas A.; Guo, Feng; Lee, Suzie; Antin, Jonathan F.; Perez, Miguel; Buchanan-King, Mindy; Hankey, Jonathan

2016-01-01

The accurate evaluation of crash causal factors can provide fundamental information for effective transportation policy, vehicle design, and driver education. Naturalistic driving (ND) data collected with multiple onboard video cameras and sensors provide a unique opportunity to evaluate risk factors during the seconds leading up to a crash. This paper uses a National Academy of Sciences-sponsored ND dataset comprising 905 injurious and property damage crash events, the magnitude of which allows the first direct analysis (to our knowledge) of causal factors using crashes only. The results show that crash causation has shifted dramatically in recent years, with driver-related factors (i.e., error, impairment, fatigue, and distraction) present in almost 90% of crashes. The results also definitively show that distraction is detrimental to driver safety, with handheld electronic devices having high use rates and risk. PMID:26903657

Causal explanations for class inequality in health--an empirical analysis.

PubMed

Lundberg, O

1991-01-01

One of the most important issues for research on social class inequalities in health are the causes behind such differences. So far, the debate on class inequalities in health has mainly been centred around hypotheses on artefactual and selectional processes. Although most contributors to this branch of research have argued in favour of causal explanations, these have gained very little systematic scrutiny. In this article, several possible causal factors are singled out for empirical testing. The effect of these factors on class differences in physical and mental illness is studied by means of logit regressions. On the basis of these analyses, it is shown that physical working conditions are the prime source of class inequality in physical illness, although economic hardship during upbringing and health related behaviours also contribute. For class inequality in mental illness these three factors plus weak social network are important. In sum, a large part of the class differences in physical as well as mental illness can be understood as a result of systematic differences between classes in living conditions, primarily differences in working conditions.

Causal Relationships between Communication Confidence, Beliefs about Group Work, and Willingness to Communicate in Foreign Language Group Work

ERIC Educational Resources Information Center

Fushino, Kumiko

2010-01-01

This article reports on the causal relationships between three factors in second language (L2) group work settings: communication confidence (i.e., confidence in one's ability to communicate), beliefs about group work, and willingness to communicate (WTC). A questionnaire was administered to 729 first-year university students in Japan. A model…

Applying a Multiple Group Causal Indicator Modeling Framework to the Reading Comprehension Skills of Third, Seventh, and Tenth Grade Students

ERIC Educational Resources Information Center

Tighe, Elizabeth L.; Wagner, Richard K.; Schatschneider, Christopher

2015-01-01

This study demonstrates the utility of applying a causal indicator modeling framework to investigate important predictors of reading comprehension in third, seventh, and tenth grade students. The results indicated that a 4-factor multiple indicator multiple indicator cause (MIMIC) model of reading comprehension provided adequate fit at each grade…

The Impact of Letter Grades on Student Effort, Course Selection, and Major Choice: A Regression-Discontinuity Analysis

ERIC Educational Resources Information Center

Main, Joyce B.; Ost, Ben

2014-01-01

The authors apply a regression-discontinuity design to identify the causal impact of letter grades on student effort within a course, subsequent credit hours taken, and the probability of majoring in economics. Their methodology addresses key issues in identifying the causal impact of letter grades: correlation with unobservable factors, such as…

Obesity and infection: reciprocal causality.

PubMed

Hainer, V; Zamrazilová, H; Kunešová, M; Bendlová, B; Aldhoon-Hainerová, I

2015-01-01

Associations between different infectious agents and obesity have been reported in humans for over thirty years. In many cases, as in nosocomial infections, this relationship reflects the greater susceptibility of obese individuals to infection due to impaired immunity. In such cases, the infection is not related to obesity as a causal factor but represents a complication of obesity. In contrast, several infections have been suggested as potential causal factors in human obesity. However, evidence of a causal linkage to human obesity has only been provided for adenovirus 36 (Adv36). This virus activates lipogenic and proinflammatory pathways in adipose tissue, improves insulin sensitivity, lipid profile and hepatic steatosis. The E4orf1 gene of Adv36 exerts insulin senzitizing effects, but is devoid of its pro-inflammatory modalities. The development of a vaccine to prevent Adv36-induced obesity or the use of E4orf1 as a ligand for novel antidiabetic drugs could open new horizons in the prophylaxis and treatment of obesity and diabetes. More experimental and clinical studies are needed to elucidate the mutual relations between infection and obesity, identify additional infectious agents causing human obesity, as well as define the conditions that predispose obese individuals to specific infections.

Fusobacterium and colorectal cancer: causal factor or passenger? Results from a large colorectal cancer screening study.

PubMed

Amitay, Efrat L; Werner, Simone; Vital, Marius; Pieper, Dietmar H; Höfler, Daniela; Gierse, Indra-Jasmin; Butt, Julia; Balavarca, Yesilda; Cuk, Katarina; Brenner, Hermann

2017-08-01

Colorectal cancer is a leading cause of morbidity and mortality worldwide in both men and women. The gut microbiome is increasingly recognized as having an important role in human health and disease. Fusobacterium has been identified in former studies as a leading gut bacterium associated with colorectal cancer, but it is still not clear if it plays an oncogenic role. In the current study, fecal samples were collected prior to bowel preparation from participants of screening colonoscopy in the German BliTz study. Using 16S rRNA gene analysis, we examined the presence and relative abundance of Fusobacterium in fecal samples from 500 participants, including 46, 113, 110 and 231 individuals with colorectal cancer, advanced adenomas, non-advanced adenomas and without any neoplasms, respectively. We found that the abundance of Fusobacterium in feces was strongly associated with the presence of colorectal cancer (P-value < 0.0001). This was confirmed by PCR at the species level for Fusobacterium nucleatum. However, no association was seen with the presence of advanced adenomas (P-value = 0.80) or non-advanced adenomas (P-value = 0.80), nor were there any associations observed with dietary or lifestyle habits. Although a causal role cannot be ruled out, our observations, based on fecal microbiome, support the hypothesis that Fusobacterium is a passenger that multiplies in the more favorable conditions caused by the malignant tumor rather than a causal factor in colorectal cancer development. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Effects of cognitive training on the structure of intelligence.

PubMed

Protzko, John

2017-08-01

Targeted cognitive training, such as n-back or speed of processing training, in the hopes of raising intelligence is of great theoretical and practical importance. The most important theoretical contribution, however, is not about the malleability of intelligence. Instead, I argue the most important and novel theoretical contribution is understanding the causal structure of intelligence. The structure of intelligence, most often taken as a hierarchical factor structure, necessarily prohibits transfer from subfactors back up to intelligence. If this is the true structure, targeted cognitive training interventions will fail to increase intelligence not because intelligence is immutable, but simply because there is no causal connection between, say, working memory and intelligence. Seeing the structure of intelligence for what it is, a causal measurement model, allows us to focus testing on the presence and absence of causal links. If we can increase subfactors without transfer to other facets, we may be confirming the correct causal structure more than testing malleability. Such a blending into experimental psychometrics is a strong theoretical pursuit.

Neurocognitive and Neuroplastic Mechanisms of Novel Clinical Signs in CRPS.

PubMed

Kuttikat, Anoop; Noreika, Valdas; Shenker, Nicholas; Chennu, Srivas; Bekinschtein, Tristan; Brown, Christopher Andrew

2016-01-01

Complex regional pain syndrome (CRPS) is a chronic, debilitating pain condition that usually arises after trauma to a limb, but its precise etiology remains elusive. Novel clinical signs based on body perceptual disturbances have been reported, but their pathophysiological mechanisms remain poorly understood. Investigators have used functional neuroimaging techniques (including MEG, EEG, fMRI, and PET) to study changes mainly within the somatosensory and motor cortices. Here, we provide a focused review of the neuroimaging research findings that have generated insights into the potential neurocognitive and neuroplastic mechanisms underlying perceptual disturbances in CRPS. Neuroimaging findings, particularly with regard to somatosensory processing, have been promising but limited by a number of technique-specific factors (such as the complexity of neuroimaging investigations, poor spatial resolution of EEG/MEG, and use of modeling procedures that do not draw causal inferences) and more general factors including small samples sizes and poorly characterized patients. These factors have led to an underappreciation of the potential heterogeneity of pathophysiology that may underlie variable clinical presentation in CRPS. Also, until now, neurological deficits have been predominantly investigated separately from perceptual and cognitive disturbances. Here, we highlight the need to identify neurocognitive phenotypes of patients with CRPS that are underpinned by causal explanations for perceptual disturbances. We suggest that a combination of larger cohorts, patient phenotyping, the use of both high temporal, and spatial resolution neuroimaging methods, and the identification of simplified biomarkers is likely to be the most fruitful approach to identifying neurocognitive phenotypes in CRPS. Based on our review, we explain how such phenotypes could be characterized in terms of hierarchical models of perception and corresponding disturbances in recurrent processing involving the somatosensory, salience and executive brain networks. We also draw attention to complementary neurological factors that may explain some CRPS symptoms, including the possibility of central neuroinflammation and neuronal atrophy, and how these phenomena may overlap but be partially separable from neurocognitive deficits.

Neurocognitive and Neuroplastic Mechanisms of Novel Clinical Signs in CRPS

PubMed Central

Kuttikat, Anoop; Noreika, Valdas; Shenker, Nicholas; Chennu, Srivas; Bekinschtein, Tristan; Brown, Christopher Andrew

2016-01-01

Complex regional pain syndrome (CRPS) is a chronic, debilitating pain condition that usually arises after trauma to a limb, but its precise etiology remains elusive. Novel clinical signs based on body perceptual disturbances have been reported, but their pathophysiological mechanisms remain poorly understood. Investigators have used functional neuroimaging techniques (including MEG, EEG, fMRI, and PET) to study changes mainly within the somatosensory and motor cortices. Here, we provide a focused review of the neuroimaging research findings that have generated insights into the potential neurocognitive and neuroplastic mechanisms underlying perceptual disturbances in CRPS. Neuroimaging findings, particularly with regard to somatosensory processing, have been promising but limited by a number of technique-specific factors (such as the complexity of neuroimaging investigations, poor spatial resolution of EEG/MEG, and use of modeling procedures that do not draw causal inferences) and more general factors including small samples sizes and poorly characterized patients. These factors have led to an underappreciation of the potential heterogeneity of pathophysiology that may underlie variable clinical presentation in CRPS. Also, until now, neurological deficits have been predominantly investigated separately from perceptual and cognitive disturbances. Here, we highlight the need to identify neurocognitive phenotypes of patients with CRPS that are underpinned by causal explanations for perceptual disturbances. We suggest that a combination of larger cohorts, patient phenotyping, the use of both high temporal, and spatial resolution neuroimaging methods, and the identification of simplified biomarkers is likely to be the most fruitful approach to identifying neurocognitive phenotypes in CRPS. Based on our review, we explain how such phenotypes could be characterized in terms of hierarchical models of perception and corresponding disturbances in recurrent processing involving the somatosensory, salience and executive brain networks. We also draw attention to complementary neurological factors that may explain some CRPS symptoms, including the possibility of central neuroinflammation and neuronal atrophy, and how these phenomena may overlap but be partially separable from neurocognitive deficits. PMID:26858626

Causal modelling applied to the risk assessment of a wastewater discharge.

PubMed

Paul, Warren L; Rokahr, Pat A; Webb, Jeff M; Rees, Gavin N; Clune, Tim S

2016-03-01

Bayesian networks (BNs), or causal Bayesian networks, have become quite popular in ecological risk assessment and natural resource management because of their utility as a communication and decision-support tool. Since their development in the field of artificial intelligence in the 1980s, however, Bayesian networks have evolved and merged with structural equation modelling (SEM). Unlike BNs, which are constrained to encode causal knowledge in conditional probability tables, SEMs encode this knowledge in structural equations, which is thought to be a more natural language for expressing causal information. This merger has clarified the causal content of SEMs and generalised the method such that it can now be performed using standard statistical techniques. As it was with BNs, the utility of this new generation of SEM in ecological risk assessment will need to be demonstrated with examples to foster an understanding and acceptance of the method. Here, we applied SEM to the risk assessment of a wastewater discharge to a stream, with a particular focus on the process of translating a causal diagram (conceptual model) into a statistical model which might then be used in the decision-making and evaluation stages of the risk assessment. The process of building and testing a spatial causal model is demonstrated using data from a spatial sampling design, and the implications of the resulting model are discussed in terms of the risk assessment. It is argued that a spatiotemporal causal model would have greater external validity than the spatial model, enabling broader generalisations to be made regarding the impact of a discharge, and greater value as a tool for evaluating the effects of potential treatment plant upgrades. Suggestions are made on how the causal model could be augmented to include temporal as well as spatial information, including suggestions for appropriate statistical models and analyses.

A Complex Systems Approach to Causal Discovery in Psychiatry.

PubMed

Saxe, Glenn N; Statnikov, Alexander; Fenyo, David; Ren, Jiwen; Li, Zhiguo; Prasad, Meera; Wall, Dennis; Bergman, Nora; Briggs, Ernestine C; Aliferis, Constantin

2016-01-01

Conventional research methodologies and data analytic approaches in psychiatric research are unable to reliably infer causal relations without experimental designs, or to make inferences about the functional properties of the complex systems in which psychiatric disorders are embedded. This article describes a series of studies to validate a novel hybrid computational approach--the Complex Systems-Causal Network (CS-CN) method-designed to integrate causal discovery within a complex systems framework for psychiatric research. The CS-CN method was first applied to an existing dataset on psychopathology in 163 children hospitalized with injuries (validation study). Next, it was applied to a much larger dataset of traumatized children (replication study). Finally, the CS-CN method was applied in a controlled experiment using a 'gold standard' dataset for causal discovery and compared with other methods for accurately detecting causal variables (resimulation controlled experiment). The CS-CN method successfully detected a causal network of 111 variables and 167 bivariate relations in the initial validation study. This causal network had well-defined adaptive properties and a set of variables was found that disproportionally contributed to these properties. Modeling the removal of these variables resulted in significant loss of adaptive properties. The CS-CN method was successfully applied in the replication study and performed better than traditional statistical methods, and similarly to state-of-the-art causal discovery algorithms in the causal detection experiment. The CS-CN method was validated, replicated, and yielded both novel and previously validated findings related to risk factors and potential treatments of psychiatric disorders. The novel approach yields both fine-grain (micro) and high-level (macro) insights and thus represents a promising approach for complex systems-oriented research in psychiatry.

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

PubMed Central

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 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 analyzed 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. PMID:25505432

Stratified exact tests for the weak causal null hypothesis in randomized trials with a binary outcome.

PubMed

Chiba, Yasutaka

2017-09-01

Fisher's exact test is commonly used to compare two groups when the outcome is binary in randomized trials. In the context of causal inference, this test explores the sharp causal null hypothesis (i.e. the causal effect of treatment is the same for all subjects), but not the weak causal null hypothesis (i.e. the causal risks are the same in the two groups). Therefore, in general, rejection of the null hypothesis by Fisher's exact test does not mean that the causal risk difference is not zero. Recently, Chiba (Journal of Biometrics and Biostatistics 2015; 6: 244) developed a new exact test for the weak causal null hypothesis when the outcome is binary in randomized trials; the new test is not based on any large sample theory and does not require any assumption. In this paper, we extend the new test; we create a version of the test applicable to a stratified analysis. The stratified exact test that we propose is general in nature and can be used in several approaches toward the estimation of treatment effects after adjusting for stratification factors. The stratified Fisher's exact test of Jung (Biometrical Journal 2014; 56: 129-140) tests the sharp causal null hypothesis. This test applies a crude estimator of the treatment effect and can be regarded as a special case of our proposed exact test. Our proposed stratified exact test can be straightforwardly extended to analysis of noninferiority trials and to construct the associated confidence interval. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Influence of climate cycles on grapevine domestication and ancient migrations in Eurasia.

PubMed

Mariani, Luigi; Cola, Gabriele; Maghradze, David; Failla, Osvaldo; Zavatti, Franco

2018-09-01

The objective of this work is to investigate the Holocenic climate cycles that may have influenced the domestication of grapevine in the Subcaucasian area and its subsequent spread in Eurasia. The analysis covered the longitudinal belt ranging from the Iberian Peninsula to Japan, seen as the preferential pathway for the Holocenic spread of grapevine and many other crops in Eurasia. Spectral analysis was considered as the criterion of investigation and the Holocenic cycles were analyzed considering different geochemical and biological proxies, of which seven are directly referred to vine. In this context the relation of the abovementioned proxies with spectral peaks of possible causal factors like Solar activity (SA), North Atlantic oceanic factors (Atlantic Multidecadal Oscillation - AMO and North Atlantic Oscillation - NAO), and subtropical oceanic factors (El Nino Southern Oscillation - ENSO) was also analyzed. In order to acquire a sufficiently wide number of proxies sensitive to the causal factors, we referred to a latitudinal belt wider than the one colonized by vine, also acquiring proxy from the Scandinavian area, notoriously susceptible to North Atlantic forcings. The analysis of the proxy spectral peaks, considering 20 classes with a 50-years step in the 0-1000 years range, showed that the 50% of the classes have a higher frequency of peaks at East than West, the 20% a higher frequency at West than East and the 10% an equal frequency, showing the efficiency of the propagation of Western signals towards the center of Eurasia. The search of the causal factors spectral peaks in the proxy series showed that AMO, NAO and SA acted with a certain regularity on the entire belt investigated both latitudinally and longitudinally, while spectral peaks linked to ENSO underwent a considerable attenuation moving northward. Finally, the specific analysis on viticultural proxies showed common peaks with causal factors. Copyright © 2018 Elsevier B.V. All rights reserved.

Weather Information Communications (WINCOMM) Project: Dissemination of Weather Information for the Reduction of Aviation Weather-Related Accident Causal Factors

NASA Technical Reports Server (NTRS)

Jarrell, Michael; Tanger, Thomas

2004-01-01

Weather Information Communications (WINCOMM) is part of the Weather Accident Prevention (WxAP) Project, which is part of the NASA's Aviation Safety and Security Program. The goals of WINCOMM are to facilitate the exchange of tactical and strategic weather information between air and ground. This viewgraph presentation provides information on data link decision factors, architectures, validation goals. WINCOMM is capable of providing en-route communication air-to-ground, ground-to-air, and air-to-air, even on international or intercontinental flights. The presentation also includes information on the capacity, cost, and development of data links.

Causal inference, probability theory, and graphical insights.

PubMed

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.

New Insights into Signed Path Coefficient Granger Causality Analysis.

PubMed

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.

Non-Gaussian Methods for Causal Structure Learning.

PubMed

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.

Anatomy of an incident

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cournoyer, Michael E.; Trujillo, Stanley; Lawton, Cindy M.

A traditional view of incidents is that they are caused by shortcomings in human competence, attention, or attitude. It may be under the label of “loss of situational awareness,” procedure “violation,” or “poor” management. A different view is that human error is not the cause of failure, but a symptom of failure – trouble deeper inside the system. In this perspective, human error is not the conclusion, but rather the starting point of investigations. During an investigation, three types of information are gathered: physical, documentary, and human (recall/experience). Through the causal analysis process, apparent cause or apparent causes are identifiedmore » as the most probable cause or causes of an incident or condition that management has the control to fix and for which effective recommendations for corrective actions can be generated. A causal analysis identifies relevant human performance factors. In the following presentation, the anatomy of a radiological incident is discussed, and one case study is presented. We analyzed the contributing factors that caused a radiological incident. When underlying conditions, decisions, actions, and inactions that contribute to the incident are identified. This includes weaknesses that may warrant improvements that tolerate error. Measures that reduce consequences or likelihood of recurrence are discussed.« less

Water quality and non-point sources of risk: the Jiulong River Watershed, P. R. of China.

PubMed

Zhang, Jingjing; Zhang, Luoping; Ricci, Paolo F

2012-01-01

Retrospective water quality assessment plays an essential role in identifying trends and causal associations between exposures and risks, thus it can be a guide for water resources management. We have developed empirical relationships between several time-varying social and economic factors of economic development, water quality variables such as nitrate-nitrogen, COD(Mn), BOD(5), and DO, in the Jiulong River Watershed and its main tributary, the West River. Our analyses used alternative statistical methods to reduce the dimensionality of the analysis first and then strengthen the study's causal associations. The statistical methods included: factor analysis (FA), trend analysis, Monte Carlo/bootstrap simulations, robust regressions and a coupled equations model, integrated into a framework that allows an investigation and resolution of the issues that may affect the estimated results. After resolving these, we found that the concentrations of nitrogen compounds increased over time in the West River region, and that fertilizer used in agricultural fruit crops was the main risk with regard to nitrogen pollution. The relationships we developed can identify hazards and explain the impact of sources of different types of pollution, such as urbanization, and agriculture.

Anatomy of an incident

DOE PAGES

Cournoyer, Michael E.; Trujillo, Stanley; Lawton, Cindy M.; ...

2016-03-23

A traditional view of incidents is that they are caused by shortcomings in human competence, attention, or attitude. It may be under the label of “loss of situational awareness,” procedure “violation,” or “poor” management. A different view is that human error is not the cause of failure, but a symptom of failure – trouble deeper inside the system. In this perspective, human error is not the conclusion, but rather the starting point of investigations. During an investigation, three types of information are gathered: physical, documentary, and human (recall/experience). Through the causal analysis process, apparent cause or apparent causes are identifiedmore » as the most probable cause or causes of an incident or condition that management has the control to fix and for which effective recommendations for corrective actions can be generated. A causal analysis identifies relevant human performance factors. In the following presentation, the anatomy of a radiological incident is discussed, and one case study is presented. We analyzed the contributing factors that caused a radiological incident. When underlying conditions, decisions, actions, and inactions that contribute to the incident are identified. This includes weaknesses that may warrant improvements that tolerate error. Measures that reduce consequences or likelihood of recurrence are discussed.« less

Spatial distribution of a population at risk: an important factor for understanding the recent rise in tick-borne diseases (Lyme borreliosis and tick-borne encephalitis in the Czech Republic).

PubMed

Zeman, Petr; Benes, Cestmir

2013-12-01

Recent rise in tick-borne diseases in many parts of Europe is a phenomenon in need of an explanation. We analyzed temporal trends in spatial distribution of a population at risk of Lyme borreliosis, tick-borne encephalitis, and as a control, also of a 'non-tick-borne disease' in the Czech Republic in 1997-2010. Analysis revealed that the population's exposure had been increasingly confined to the nearest surroundings of residences or in totally residential locations and that the incidence of the diseases depended in some causal way on how close to residences people exposed themselves to the risk. The rise in Lyme borreliosis and tick-borne encephalitis was solely due to infections acquired at or near patients' homes (<5 km), while the number of cases acquired further away was decreasing. The detected patterns in the data question some of the hypotheses which may be applicable in explaining the rise in disease incidences in the Czech Republic including the effect of climate change. Potentially causal factors are discussed. Copyright © 2013 Elsevier GmbH. All rights reserved.

Birth weight and mortality: causality or confounding?

PubMed

Basso, Olga; Wilcox, Allen J; Weinberg, Clarice R

2006-08-15

The association between birth weight and mortality is among the strongest seen in epidemiology. While preterm delivery causes both small babies and high mortality, it does not explain this association. Fetal growth restriction has also been proposed, although its features are unclear because it lacks a definition independent of weight. If, as some postulate, birth weight is not itself on the causal path to mortality, its relation with mortality would have to be explained by confounding factors that decrease birth weight and increase mortality. In this paper, the authors explore the characteristics such confounders would require in order to achieve the observed association between birth weight and mortality. Through a simple simulation, they found that the observed steep gradient of risk for small babies at term can be produced by a rare condition or conditions (with a total prevalence of 0.5%) having profound effects on both fetal growth (-1.7 standard deviations) and mortality (relative risk = 160). Candidate conditions might include malformations, fetal or placental aneuploidy, infections, or imprinting disorders. If such rare factors underlie the association of birth weight with mortality, it would have broad implications for the study of fetal growth restriction and birth weight, and for the prevention of infant mortality.

Understanding how pain education causes changes in pain and disability: protocol for a causal mediation analysis of the PREVENT trial.

PubMed

Lee, Hopin; Moseley, G Lorimer; Hübscher, Markus; Kamper, Steven J; Traeger, Adrian C; Skinner, Ian W; McAuley, James H

2015-07-01

Pain education is a complex intervention developed to help clinicians manage low back pain. Although complex interventions are usually evaluated by their effects on outcomes, such as pain or disability, most do not directly target these outcomes; instead, they target intermediate factors that are presumed to be associated with the outcomes. The mechanisms underlying treatment effects, or the effect of an intervention on an intermediate factor and its subsequent effect on outcome, are rarely investigated in clinical trials. This leaves a gap in the evidence for understanding how treatments exert their effects on outcomes. Mediation analysis provides a method for identifying and quantifying the mechanisms that underlie interventions. To determine whether the effect of pain education on pain and disability is mediated by changes in self-efficacy, catastrophisation and back pain beliefs. Causal mediation analysis of the PREVENT randomised controlled trial. Two hundred and two participants with acute low back pain from primary care clinics in the Sydney metropolitan area. Participants will be randomised to receive either 'pain education' (intervention group) or 'sham education' (control group). All outcome measures (including patient characteristics), primary outcome measures (pain and disability), and putative mediating variables (self-efficacy, catastrophisation and back pain beliefs) will be measured prior to randomisation. Putative mediators and primary outcome measures will be measured 1 week after the intervention, and primary outcome measures will be measured 3 months after the onset of low back pain. Causal mediation analysis under the potential outcomes framework will be used to test single and multiple mediator models. A sensitivity analysis will be conducted to evaluate the robustness of the estimated mediation effects on the influence of violating sequential ignorability--a critical assumption for causal inference. Mediation analysis of clinical trials can estimate how much the total effect of the treatment on the outcome is carried through an indirect path. Using mediation analysis to understand these mechanisms can generate evidence that can be used to tailor treatments and optimise treatment effects. In this study, the causal mediation effects of a pain education intervention for acute non-specific low back pain will be estimated. This knowledge is critical for further development and refinement of interventions for conditions such as low back pain. Copyright © 2015 Australian Physiotherapy Association. Published by Elsevier B.V. All rights reserved.

Too much sitting and all-cause mortality: is there a causal link?

PubMed

Biddle, Stuart J H; Bennie, Jason A; Bauman, Adrian E; Chau, Josephine Y; Dunstan, David; Owen, Neville; Stamatakis, Emmanuel; van Uffelen, Jannique G Z

2016-07-26

Sedentary behaviours (time spent sitting, with low energy expenditure) are associated with deleterious health outcomes, including all-cause mortality. Whether this association can be considered causal has yet to be established. Using systematic reviews and primary studies from those reviews, we drew upon Bradford Hill's criteria to consider the likelihood that sedentary behaviour in epidemiological studies is likely to be causally related to all-cause (premature) mortality. Searches for systematic reviews on sedentary behaviours and all-cause mortality yielded 386 records which, when judged against eligibility criteria, left eight reviews (addressing 17 primary studies) for analysis. Exposure measures included self-reported total sitting time, TV viewing time, and screen time. Studies included comparisons of a low-sedentary reference group with several higher sedentary categories, or compared the highest versus lowest sedentary behaviour groups. We employed four Bradford Hill criteria: strength of association, consistency, temporality, and dose-response. Evidence supporting causality at the level of each systematic review and primary study was judged using a traffic light system depicting green for causal evidence, amber for mixed or inconclusive evidence, and red for no evidence for causality (either evidence of no effect or no evidence reported). The eight systematic reviews showed evidence for consistency (7 green) and temporality (6 green), and some evidence for strength of association (4 green). There was no evidence for a dose-response relationship (5 red). Five reviews were rated green overall. Twelve (67 %) of the primary studies were rated green, with evidence for strength and temporality. There is reasonable evidence for a likely causal relationship between sedentary behaviour and all-cause mortality based on the epidemiological criteria of strength of association, consistency of effect, and temporality.

Assessment of causal associations between illness and criminal acts in those who are acquitted by reason of insanity.

PubMed

Skeie, Christian Aarup; Rasmussen, Kirsten

2015-02-24

The court proceedings after the terrorist attacks on 22 July 2011 reignited the debate on the justification for having a rule that regulates the insanity defence exclusively on the basis of a medical condition – the medical principle. The psychological principle represents an alternative that requires a causal relationship between the psychosis and the acts committed. In this article we investigate rulings made by the courts of appeal where the accused have been found legally insane at the time of the act, and elucidate the extent to which a causal relationship between the illness and the act appears to be in evidence. Data have been retrieved from rulings by the courts of appeal published at lovdata.no, which include anonymised rulings. Searches were made for cases under Section 39 (verdict of special sanctions) and Section 44 (acquittal by reason of insanity) of the General Civil Penal Code. Court rulings in which a possible causal relationship could be considered were included. The included rulings were carefully assessed with regard to whether a causal relationship existed between the mental disorder of the accused at the time and the criminal act. The search returned a total of 373 rulings, of which 75 were included. The vast majority of the charges referred to serious crimes. Diagnoses under ICD-10 category codes F20-29 (schizophrenia, schizotypal and delusional disorders) were the most frequently occurring type. In 17 of the 75 rulings (23%), it was judged that no causal relationship between the illness and the act existed. In 25 of 26 cases that involved homicide, a causal relationship between the illness and the act was judged to be evident. The data may indicate that the medical principle results in impunity in a considerable number of rulings where the illness of the accused apparently has had no effect on the acts committed.

Universal behavior of generalized causal set d’Alembertians in curved spacetime

NASA Astrophysics Data System (ADS)

Belenchia, Alessio

2016-07-01

Causal set non-local wave operators allow both for the definition of an action for causal set theory and the study of deviations from local physics that may have interesting phenomenological consequences. It was previously shown that, in all dimensions, the (unique) minimal discrete operators give averaged continuum non-local operators that reduce to \\square -R/2 in the local limit. Recently, dropping the constraint of minimality, it was shown that there exist an infinite number of discrete operators satisfying basic physical requirements and with the right local limit in flat spacetime. In this work, we consider this entire class of generalized causal set d’Alembertins in curved spacetimes and extend to them the result about the universality of the -R/2 factor. Finally, we comment on the relation of this result to the Einstein equivalence principle.

Political Attitudes Develop Independently of Personality Traits

PubMed Central

Hatemi, Peter K.; Verhulst, Brad

2015-01-01

The primary assumption within the recent personality and political orientations literature is that personality traits cause people to develop political attitudes. In contrast, research relying on traditional psychological and developmental theories suggests the relationship between most personality dimensions and political orientations are either not significant or weak. Research from behavioral genetics suggests the covariance between personality and political preferences is not causal, but due to a common, latent genetic factor that mutually influences both. The contradictory assumptions and findings from these research streams have yet to be resolved. This is in part due to the reliance on cross-sectional data and the lack of longitudinal genetically informative data. Here, using two independent longitudinal genetically informative samples, we examine the joint development of personality traits and attitude dimensions to explore the underlying causal mechanisms that drive the relationship between these features and provide a first step in resolving the causal question. We find change in personality over a ten-year period does not predict change in political attitudes, which does not support a causal relationship between personality traits and political attitudes as is frequently assumed. Rather, political attitudes are often more stable than the key personality traits assumed to be predicting them. Finally, the results from our genetic models find that no additional variance is accounted for by the causal pathway from personality traits to political attitudes. Our findings remain consistent with the original construction of the five-factor model of personality and developmental theories on attitude formation, but challenge recent work in this area. PMID:25734580

Political attitudes develop independently of personality traits.

PubMed

Hatemi, Peter K; Verhulst, Brad

2015-01-01

The primary assumption within the recent personality and political orientations literature is that personality traits cause people to develop political attitudes. In contrast, research relying on traditional psychological and developmental theories suggests the relationship between most personality dimensions and political orientations are either not significant or weak. Research from behavioral genetics suggests the covariance between personality and political preferences is not causal, but due to a common, latent genetic factor that mutually influences both. The contradictory assumptions and findings from these research streams have yet to be resolved. This is in part due to the reliance on cross-sectional data and the lack of longitudinal genetically informative data. Here, using two independent longitudinal genetically informative samples, we examine the joint development of personality traits and attitude dimensions to explore the underlying causal mechanisms that drive the relationship between these features and provide a first step in resolving the causal question. We find change in personality over a ten-year period does not predict change in political attitudes, which does not support a causal relationship between personality traits and political attitudes as is frequently assumed. Rather, political attitudes are often more stable than the key personality traits assumed to be predicting them. Finally, the results from our genetic models find that no additional variance is accounted for by the causal pathway from personality traits to political attitudes. Our findings remain consistent with the original construction of the five-factor model of personality and developmental theories on attitude formation, but challenge recent work in this area.

Attention Deficit Hyperactivity Disorder Symptoms and Low Educational Achievement: Evidence Supporting A Causal Hypothesis.

PubMed

de Zeeuw, Eveline L; van Beijsterveldt, Catharina E M; Ehli, Erik A; de Geus, Eco J C; Boomsma, Dorret I

2017-05-01

Attention Deficit Hyperactivity Disorder (ADHD) and educational achievement are negatively associated in children. Here we test the hypothesis that there is a direct causal effect of ADHD on educational achievement. The causal effect is tested in a genetically sensitive design to exclude the possibility of confounding by a third factor (e.g. genetic pleiotropy) and by comparing educational achievement and secondary school career in children with ADHD who take or do not take methylphenidate. Data on ADHD symptoms, educational achievement and methylphenidate usage were available in a primary school sample of ~10,000 12-year-old twins from the Netherlands Twin Register. A substantial group also had longitudinal data at ages 7-12 years. ADHD symptoms were cross-sectionally and longitudinally, associated with lower educational achievement at age 12. More ADHD symptoms predicted a lower-level future secondary school career at age 14-16. In both the cross-sectional and longitudinal analyses, testing the direct causal effect of ADHD on educational achievement, while controlling for genetic and environmental factors, revealed an association between ADHD symptoms and educational achievement independent of genetic and environmental pleiotropy. These findings were confirmed in MZ twin intra-pair differences models, twins with more ADHD symptoms scored lower on educational achievement than their co-twins. Furthermore, children with ADHD medication, scored significantly higher on the educational achievement test than children with ADHD who did not use medication. Taken together, the results are consistent with a direct causal effect of ADHD on educational achievement.

Good research practices for comparative effectiveness research: approaches to mitigate bias and confounding in the design of nonrandomized studies of treatment effects using secondary data sources: the International Society for Pharmacoeconomics and Outcomes Research Good Research Practices for Retrospective Database Analysis Task Force Report--Part II.

PubMed

Cox, Emily; Martin, Bradley C; Van Staa, Tjeerd; Garbe, Edeltraut; Siebert, Uwe; Johnson, Michael L

2009-01-01

The goal of comparative effectiveness analysis is to examine the relationship between two variables, treatment, or exposure and effectiveness or outcome. Unlike data obtained through randomized controlled trials, researchers face greater challenges with causal inference with observational studies. Recognizing these challenges, a task force was formed to develop a guidance document on methodological approaches to addresses these biases. The task force was commissioned and a Chair was selected by the International Society for Pharmacoeconomics and Outcomes Research Board of Directors in October 2007. This report, the second of three reported in this issue of the Journal, discusses the inherent biases when using secondary data sources for comparative effectiveness analysis and provides methodological recommendations to help mitigate these biases. The task force report provides recommendations and tools for researchers to mitigate threats to validity from bias and confounding in measurement of exposure and outcome. Recommendations on design of study included: the need for data analysis plan with causal diagrams; detailed attention to classification bias in definition of exposure and clinical outcome; careful and appropriate use of restriction; extreme care to identify and control for confounding factors, including time-dependent confounding. Design of nonrandomized studies of comparative effectiveness face several daunting issues, including measurement of exposure and outcome challenged by misclassification and confounding. Use of causal diagrams and restriction are two techniques that can improve the theoretical basis for analyzing treatment effects in study populations of more homogeneity, with reduced loss of generalizability.

MIIC online: a web server to reconstruct causal or non-causal networks from non-perturbative data.

PubMed

Sella, Nadir; Verny, Louis; Uguzzoni, Guido; Affeldt, Séverine; Isambert, Hervé

2018-07-01

We present a web server running the MIIC algorithm, a network learning method combining constraint-based and information-theoretic frameworks to reconstruct causal, non-causal or mixed networks from non-perturbative data, without the need for an a priori choice on the class of reconstructed network. Starting from a fully connected network, the algorithm first removes dispensable edges by iteratively subtracting the most significant information contributions from indirect paths between each pair of variables. The remaining edges are then filtered based on their confidence assessment or oriented based on the signature of causality in observational data. MIIC online server can be used for a broad range of biological data, including possible unobserved (latent) variables, from single-cell gene expression data to protein sequence evolution and outperforms or matches state-of-the-art methods for either causal or non-causal network reconstruction. MIIC online can be freely accessed at https://miic.curie.fr. Supplementary data are available at Bioinformatics online.

The Pattern of Road Traffic Crashes in South East Iran

PubMed Central

Rad, Mahdieh; Martiniuk, Alexandra LC.; Ansari-Moghaddam, Alireza; Mohammadi, Mahdi; Rashedi, Fariborz; Ghasemi, Ardavan

2016-01-01

Background: In the present study, the epidemiologic aspects of road traffic crashes in South East of Iran are described. Methods: This cross-sectional study included the profile of 2398 motor vehicle crashes recorded in the police office in one Year in South East of Iran. Data collected included: demographics, the type of crash, type of involved vehicle, location of crash and factors contributing to the crash. Descriptive statistics were used for data analysis. Results: Collisions with other vehicles or objects contributed the highest proportion (62.4%) of motor vehicle crashes. Human factors including careless driving, violating traffic laws, speeding, and sleep deprivation/fatigue were the most important causal factors accounting for 90% of road crashes. Data shows that 41% of drivers were not using a seat belt at the time of crash. One- third of the crashes resulted in injury (25%) or death (5%). Conclusions: Reckless driving such as speeding and violation of traffic laws are major risk factors for crashes in the South East of Iran. This highlights the need for education along with traffic law enforcement to reduce motor vehicle crashes in future. PMID:27157159

The Pattern of Road Traffic Crashes in South East Iran.

PubMed

Rad, Mahdieh; Martiniuk, Alexandra Lc; Ansari-Moghaddam, Alireza; Mohammadi, Mahdi; Rashedi, Fariborz; Ghasemi, Ardavan

2016-09-01

In the present study, the epidemiologic aspects of road traffic crashes in South East of Iran are described. This cross-sectional study included the profile of 2398 motor vehicle crashes recorded in the police office in one Year in South East of Iran. Data collected included: demographics, the type of crash, type of involved vehicle, location of crash and factors contributing to the crash. Descriptive statistics were used for data analysis. Collisions with other vehicles or objects contributed the highest proportion (62.4%) of motor vehicle crashes. Human factors including careless driving, violating traffic laws, speeding, and sleep deprivation/fatigue were the most important causal factors accounting for 90% of road crashes. Data shows that 41% of drivers were not using a seat belt at the time of crash. One- third of the crashes resulted in injury (25%) or death (5%). Reckless driving such as speeding and violation of traffic laws are major risk factors for crashes in the South East of Iran. This highlights the need for education along with traffic law enforcement to reduce motor vehicle crashes in future.

Using HFACS-Healthcare to Identify Systemic Vulnerabilities During Surgery.

PubMed

Cohen, Tara N; Francis, Sarah E; Wiegmann, Douglas A; Shappell, Scott A; Gewertz, Bruce L

2018-03-01

The Human Factors Analysis and Classification System for Healthcare (HFACS-Healthcare) was used to classify surgical near miss events reported via a hospital's event reporting system over the course of 1 year. Two trained analysts identified causal factors within each event narrative and subsequently categorized the events using HFACS-Healthcare. Of 910 original events, 592 could be analyzed further using HFACS-Healthcare, resulting in the identification of 726 causal factors. Most issues (n = 436, 60.00%) involved preconditions for unsafe acts, followed by unsafe acts (n = 257, 35.39%), organizational influences (n = 27, 3.72%), and supervisory factors (n = 6, 0.82%). These findings go beyond the traditional methods of trending incident data that typically focus on documenting the frequency of their occurrence. Analyzing near misses based on their underlying contributing human factors affords a greater opportunity to develop process improvements to reduce reoccurrence and better provide patient safety approaches.

New Onset Autoimmune Hepatitis during Anti-Tumor Necrosis Factor-Alpha Treatment in Children.

PubMed

Ricciuto, Amanda; Kamath, Binita M; Walters, Thomas D; Frost, Karen; Carman, Nicholas; Church, Peter C; Ling, Simon C; Griffiths, Anne M

2018-03-01

To evaluate a large anti-tumor necrosis factor (TNF)-treated pediatric inflammatory bowel disease cohort for drug-induced liver injury (DILI) following presentation of an index case with suspected DILI with autoimmune features after infliximab exposure. To characterize the incidence, natural history, and risk factors for liver enzyme elevation with anti-TNF use. We reviewed the index case and performed a retrospective cohort study of 659 children receiving anti-TNF therapy between 2000 and 2015 at a tertiary pediatric inflammatory bowel disease center. Patients with alanine aminotransferase (ALT) ≥×2 the upper limit of normal were included. The incidence, evolution, and risk factors for liver injury were examined with univariate and multivariable proportional hazards regression. Causality was assessed using the Roussel-Uclaf Causality Assessment Method. The index case, a teenage girl with Crohn's disease, developed elevated liver enzymes and features of autoimmune hepatitis on liver biopsy 23 weeks after starting infliximab. The injury resolved entirely within 4 months of withdrawing infliximab without additional therapy. Overall, 7.7% of our cohort developed new ALT elevations while on anti-TNF. Most ALT elevations were mild and transient and attributable to alternate etiologies. No additional clear cases of autoimmune hepatitis were identified. Transient liver enzyme abnormalities are relatively common among anti-TNF-treated children. Anti-TNF-related DILI with autoimmune features is rare but must be recognized so that therapy can be stopped. Copyright © 2017 Elsevier Inc. All rights reserved.

The Pervasive Problem With Placebos in Psychology: Why Active Control Groups Are Not Sufficient to Rule Out Placebo Effects.

PubMed

Boot, Walter R; Simons, Daniel J; Stothart, Cary; Stutts, Cassie

2013-07-01

To draw causal conclusions about the efficacy of a psychological intervention, researchers must compare the treatment condition with a control group that accounts for improvements caused by factors other than the treatment. Using an active control helps to control for the possibility that improvement by the experimental group resulted from a placebo effect. Although active control groups are superior to "no-contact" controls, only when the active control group has the same expectation of improvement as the experimental group can we attribute differential improvements to the potency of the treatment. Despite the need to match expectations between treatment and control groups, almost no psychological interventions do so. This failure to control for expectations is not a minor omission-it is a fundamental design flaw that potentially undermines any causal inference. We illustrate these principles with a detailed example from the video-game-training literature showing how the use of an active control group does not eliminate expectation differences. The problem permeates other interventions as well, including those targeting mental health, cognition, and educational achievement. Fortunately, measuring expectations and adopting alternative experimental designs makes it possible to control for placebo effects, thereby increasing confidence in the causal efficacy of psychological interventions. © The Author(s) 2013.

Molecular epidemiology of acute leukemia in children: causal model, interaction of three factors-susceptibility, environmental exposure and vulnerability period.

PubMed

Mejía-Aranguré, Juan Manuel

Acute leukemias have a huge morphological, cytogenetic and molecular heterogeneity and genetic polymorphisms associated with susceptibility. Every leukemia presents causal factors associated with the development of the disease. Particularly, when three factors are present, they result in the development of acute leukemia. These phenomena are susceptibility, environmental exposure and a period that, for this model, has been called the period of vulnerability. This framework shows how the concepts of molecular epidemiology have established a reference from which it is more feasible to identify the environmental factors associated with the development of leukemia in children. Subsequently, the arguments show that only susceptible children are likely to develop leukemia once exposed to an environmental factor. For additional exposure, if the child is not susceptible to leukemia, the disease does not develop. In addition, this exposure should occur during a time window when hematopoietic cells and their environment are more vulnerable to such interaction, causing the development of leukemia. This model seeks to predict the time when the leukemia develops and attempts to give a context in which the causality of childhood leukemia should be studied. This information can influence and reduce the risk of a child developing leukemia. Copyright © 2016 Hospital Infantil de México Federico Gómez. Publicado por Masson Doyma México S.A. All rights reserved.

Multiple mechanisms influencing the relationship between alcohol consumption and peer alcohol use.

PubMed

Edwards, Alexis C; Maes, Hermine H; Prescott, Carol A; Kendler, Kenneth S

2015-02-01

Alcohol consumption is typically correlated with the alcohol use behaviors of one's peers. Previous research has suggested that this positive relationship could be due to social selection, social influence, or a combination of both processes. However, few studies have considered the role of shared genetic and environmental influences in conjunction with causal processes. This study uses data from a sample of male twins (N = 1,790) who provided retrospective reports of their own alcohol consumption and their peers' alcohol-related behaviors, from adolescence into young adulthood (ages 12 to 25). Structural equation modeling was employed to compare 3 plausible models of genetic and environmental influences on the relationship between phenotypes over time. Model fitting indicated that one's own alcohol consumption and the alcohol use of one's peers are related through both genetic and shared environmental factors and through unique environmental causal influences. The relative magnitude of these factors, and their contribution to covariation, changed over time, with genetic factors becoming more meaningful later in development. Peers' alcohol use behaviors and one's own alcohol consumption are related through a complex combination of genetic and environmental factors that act via correlated factors and the complementary causal mechanisms of social selection and influence. Understanding these processes can inform risk assessment as well as improve our ability to model the development of alcohol use. Copyright © 2015 by the Research Society on Alcoholism.

Multiple mechanisms influencing the relationship between alcohol consumption and peer alcohol use

PubMed Central

Edwards, Alexis C.; Maesr, Hermine H.; Prescott, Carol A.; Kendler, Kenneth S.

2014-01-01

Background Alcohol consumption is typically correlated with the alcohol use behaviors of one’s peers. Previous research has suggested that this positive relationship could be due to social selection, social influence, or a combination of both processes. However, few studies have considered the role of shared genetic and environmental influences in conjunction with causal processes. Methods The current study uses data from a sample of male twins (N=1790) who provided retrospective reports of their own alcohol consumption and their peers’ alcohol related behaviors, from adolescence into young adulthood (ages 12–25). Structural equation modeling was employed to compare three plausible models of genetic and environmental influences on the relationship between phenotypes over time. Results Model fitting indicated that one’s own alcohol consumption and the alcohol use of one’s peers are related through both genetic and shared environmental factors and through unique environmental causal influences. The relative magnitude of these factors, and their contribution to covariation, changed over time, with genetic factors becoming more meaningful later in development. Conclusions Peers’ alcohol use behaviors and one’s own alcohol consumption are related through a complex combination of genetic and environmental factors that act via correlated factors and the complementary causal mechanisms of social selection and influence. Understanding these processes can inform risk assessment as well as improve our ability to model the development of alcohol use. PMID:25597346

Safety compliance and safety climate: A repeated cross-sectional study in the oil and gas industry.

PubMed

Kvalheim, Sverre A; Dahl, Øyvind

2016-12-01

Violations of safety rules and procedures are commonly identified as a causal factor in accidents in the oil and gas industry. Extensive knowledge on effective management practices related to improved compliance with safety procedures is therefore needed. Previous studies of the causal relationship between safety climate and safety compliance demonstrate that the propensity to act in accordance with prevailing rules and procedures is influenced to a large degree by workers' safety climate. Commonly, the climate measures employed differ from one study to another and identical measures of safety climate are seldom tested repeatedly over extended periods of time. This research gap is addressed in the present study. The study is based on a survey conducted four times among sharp-end workers of the Norwegian oil and gas industry (N=31,350). This is done by performing multiple tests (regression analysis) over a period of 7years of the causal relationship between safety climate and safety compliance. The safety climate measure employed is identical across the 7-year period. Taking all periods together, the employed safety climate model explained roughly 27% of the variance in safety compliance. The causal relationship was found to be stable across the period, thereby increasing the reliability and the predictive validity of the factor structure. The safety climate factor that had the most powerful effect on safety compliance was work pressure. The factor structure employed shows high predictive validity and should therefore be relevant to organizations seeking to improve safety in the petroleum sector. The findings should also be relevant to other high-hazard industries where safety rules and procedures constitute a central part of the approach to managing safety. Copyright © 2016 Elsevier Ltd and National Safety Council. All rights reserved.

A Causal Relationship of Occupational Stress among University Employees

PubMed Central

KAEWANUCHIT, Chonticha; MUNTANER, Carles; ISHA, Nizam

2015-01-01

Background: Occupational stress is a psychosocial dimension of occupational health concept on social determinants of health, especially, job & environmental condition. Recently, staff network of different government universities of Thailand have called higher education commission, and Ministry of Education, Thailand to resolve the issue of government education policy (e.g. wage inequity, poor welfare, law, and job & environment condition) that leads to their job insecurity, physical and mental health problems from occupational stress. The aim of this study was to investigate a causal relationship of occupational stress among the academic university employees. Methods: This cross sectional research was conducted in 2014 among 2,000 academic university employees at Thai government universities using stratified random sampling. Independent variables were wage, family support, periods of duty, and job & environmental condition. Dependent variable was stress. Results: Job & environmental condition, as social and environmental factor, and periods of duty as individual factor had direct effect to stress (P< 0.05). Family support, as family factor, and wage, as individual factor had direct effect to stress (P < 0.05). Both family support and wage were the causal endogenous variables. Conclusion: Job & environmental condition and periods of duty were increased so that it associated with occupational stress among academic university employees at moderate level. PMID:26576371

Mastitis in sheep--The last 10 years and the future of research.

PubMed

Gelasakis, A I; Mavrogianni, V S; Petridis, I G; Vasileiou, N G C; Fthenakis, G C

2015-12-14

Bacterial mastitis is a significant welfare and financial problem in sheep flocks. This paper reviews the recently published literature, including publications that highlight the significance and virulence factors of the causal agents, especially Staphylococcus aureus and Mannheimia haemolytica, the primary causes of the disease. Research has also contributed to the understanding of risk factors, including genetic susceptibility of animals to infections, supporting future strategies for sustainable disease control. Pathogenetic mechanisms, including the role of the local defenses in the teat, have also been described and can assist formulation of strategies that induce local immune responses in the teat of ewes. Further to well-established diagnostic techniques, i.e., bacteriological tests and somatic cell counting, advanced methodologies, e.g., proteomics technologies, will likely contribute to more rapid and accurate diagnostics, in turn enhancing mastitis control efforts. Copyright © 2015 Elsevier B.V. All rights reserved.

Do Selective Serotonin Reuptake Inhibitors (SSRIs) Cause Fractures?

PubMed

Warden, Stuart J; Fuchs, Robyn K

2016-10-01

Recent meta-analyses report a 70 % increase in fracture risk in selective serotonin reuptake inhibitor (SSRI) users compared to non-users; however, included studies were observational and limited in their ability to establish causality. Here, we use the Bradford Hill criteria to explore causality between SSRIs and fractures. We found a strong, consistent, and temporal relationship between SSRIs and fractures, which appears to follow a biological gradient. However, specificity and biological plausibility remain concerns. In terms of specificity, the majority of available data have limitations due to either confounding by indication or channeling bias. Self-controlled case series address some of these limitations and provide relatively strong observational evidence for a causal relationship between SSRIs and fracture. In doing so, they suggest that falls contribute to fractures in SSRI users. Whether there are also underlying changes in skeletal properties remains unresolved. Initial studies provide some evidence for skeletal effects of SSRIs; however, the pathways involved need to be established before biological plausibility can be accepted. As the link between SSRIs and fractures is based on observational data and not evidence from prospective trials, there is insufficient evidence to definitively determine a causal relationship and it appears premature to label SSRIs as a secondary cause of osteoporosis. SSRIs appear to contribute to fracture-inducing falls, and addressing any fall risk associated with SSRIs may be an efficient approach to reducing SSRI-related fractures. As fractures stemming from SSRI-induced falls are more likely in individuals with compromised bone health, it is worth considering bone density testing and intervention for those presenting with risk factors for osteoporosis.

Quantum-coherent mixtures of causal relations

NASA Astrophysics Data System (ADS)

Maclean, Jean-Philippe W.; Ried, Katja; Spekkens, Robert W.; Resch, Kevin J.

2017-05-01

Understanding the causal influences that hold among parts of a system is critical both to explaining that system's natural behaviour and to controlling it through targeted interventions. In a quantum world, understanding causal relations is equally important, but the set of possibilities is far richer. The two basic ways in which a pair of time-ordered quantum systems may be causally related are by a cause-effect mechanism or by a common-cause acting on both. Here we show a coherent mixture of these two possibilities. We realize this nonclassical causal relation in a quantum optics experiment and derive a set of criteria for witnessing the coherence based on a quantum version of Berkson's effect, whereby two independent causes can become correlated on observation of their common effect. The interplay of causality and quantum theory lies at the heart of challenging foundational puzzles, including Bell's theorem and the search for quantum gravity.

Quantum-coherent mixtures of causal relations

PubMed Central

MacLean, Jean-Philippe W.; Ried, Katja; Spekkens, Robert W.; Resch, Kevin J.

2017-01-01

Understanding the causal influences that hold among parts of a system is critical both to explaining that system's natural behaviour and to controlling it through targeted interventions. In a quantum world, understanding causal relations is equally important, but the set of possibilities is far richer. The two basic ways in which a pair of time-ordered quantum systems may be causally related are by a cause-effect mechanism or by a common-cause acting on both. Here we show a coherent mixture of these two possibilities. We realize this nonclassical causal relation in a quantum optics experiment and derive a set of criteria for witnessing the coherence based on a quantum version of Berkson's effect, whereby two independent causes can become correlated on observation of their common effect. The interplay of causality and quantum theory lies at the heart of challenging foundational puzzles, including Bell's theorem and the search for quantum gravity. PMID:28485394

Quantum-coherent mixtures of causal relations.

PubMed

MacLean, Jean-Philippe W; Ried, Katja; Spekkens, Robert W; Resch, Kevin J

2017-05-09

Understanding the causal influences that hold among parts of a system is critical both to explaining that system's natural behaviour and to controlling it through targeted interventions. In a quantum world, understanding causal relations is equally important, but the set of possibilities is far richer. The two basic ways in which a pair of time-ordered quantum systems may be causally related are by a cause-effect mechanism or by a common-cause acting on both. Here we show a coherent mixture of these two possibilities. We realize this nonclassical causal relation in a quantum optics experiment and derive a set of criteria for witnessing the coherence based on a quantum version of Berkson's effect, whereby two independent causes can become correlated on observation of their common effect. The interplay of causality and quantum theory lies at the heart of challenging foundational puzzles, including Bell's theorem and the search for quantum gravity.

Kernel canonical-correlation Granger causality for multiple time series

NASA Astrophysics Data System (ADS)

Wu, Guorong; Duan, Xujun; Liao, Wei; Gao, Qing; Chen, Huafu

2011-04-01

Canonical-correlation analysis as a multivariate statistical technique has been applied to multivariate Granger causality analysis to infer information flow in complex systems. It shows unique appeal and great superiority over the traditional vector autoregressive method, due to the simplified procedure that detects causal interaction between multiple time series, and the avoidance of potential model estimation problems. However, it is limited to the linear case. Here, we extend the framework of canonical correlation to include the estimation of multivariate nonlinear Granger causality for drawing inference about directed interaction. Its feasibility and effectiveness are verified on simulated data.

Analogical and category-based inference: a theoretical integration with Bayesian causal models.

PubMed

Holyoak, Keith J; Lee, Hee Seung; Lu, Hongjing

2010-11-01

A fundamental issue for theories of human induction is to specify constraints on potential inferences. For inferences based on shared category membership, an analogy, and/or a relational schema, it appears that the basic goal of induction is to make accurate and goal-relevant inferences that are sensitive to uncertainty. People can use source information at various levels of abstraction (including both specific instances and more general categories), coupled with prior causal knowledge, to build a causal model for a target situation, which in turn constrains inferences about the target. We propose a computational theory in the framework of Bayesian inference and test its predictions (parameter-free for the cases we consider) in a series of experiments in which people were asked to assess the probabilities of various causal predictions and attributions about a target on the basis of source knowledge about generative and preventive causes. The theory proved successful in accounting for systematic patterns of judgments about interrelated types of causal inferences, including evidence that analogical inferences are partially dissociable from overall mapping quality.

Update on Multiple Ovulations in Dairy Cattle

PubMed Central

Macmillan, Kira; Kastelic, John P.

2018-01-01

Simple Summary Multiple ovulations (MOV) in cattle can lead to twin pregnancies, which negatively affects the health, production, and reproduction of cows. Despite many studies, the causal mechanisms behind MOV are still not well understood. There is a general agreement that MOV are more likely during periods of low progesterone (P4), which may increase the luteinizing hormone (LH) release at the time of selection, resulting in more than one follicle becoming dominant. The MOV rate also increases in older cows and when the selection of a dominant follicle occurs concurrently with a high milk yield. Additional risk factors for MOV are ovarian cysts, diet, season, and genetics. A better understanding of the mechanisms underlying MOV may help to mitigate twinning, perhaps through the appropriate reproductive management protocols or genetic selection. Abstract This review updates the causal mechanisms and risk factors for multiple ovulations (MOV) in cattle. Clearly, MOV can lead to twin pregnancies, which negatively affects the health, production, and reproduction of cows. Therefore, a better understanding of the factors causing MOV may help to reduce twinning. Multiple ovulations occur after two or more follicles deviate and achieve codominance. The MOV rate is influenced by a complex network of hormones. For example, MOV is more common during periods of low progesterone (P4), that is, in anovulatory cattle or when luteolysis coincides with the selection of the future ovulatory follicle. There is also strong evidence for the luteinizing hormone (LH) being the primary factor leading to codominance, as high P4 concentrations suppress the transient LH surges and can reduce the ovulation rate in cattle or even inhibit deviation. Rates of MOV are increased in older and higher-producing dairy cows. Increased milk production and dry matter intake (DMI) increases hormone clearance, including P4; however, the association between milk yield and MOV has not been consistent. Additional risk factors for MOV include ovarian cysts, diet, season, and genetics. PMID:29695075

Do individuals with asthma experience airway hyper-responsiveness after exposure to nitrogen dioxide?

PubMed

Goodman, Julie E; Kennedy, Erin M; Seeley, Mara

2017-10-01

The current 100 ppb short-term National Ambient Air Quality Standard for NO 2 , and EPA's determination of a causal association for respiratory effects, are based in part on controlled human exposure studies evaluating airway hyper-responsiveness (AHR). A meta-analysis by Goodman et al. (2009) found increased AHR at 100 ppb NO 2 but no clear concentration-response relationship up to 600 ppb, and an overall lack of an AHR effect for studies involving exercise or exposure to allergens. Several factors have been suggested to explain why effects on AHR are observed while people are at rest, but not during exercise or after exposure to allergens. These include an exercise-induced refractory period; partial reversal of bronchospasm from use of forced expiration maneuvers; and greater airway responsiveness of participants exposed to NO 2 at rest. We reviewed the scientific evidence to determine whether there is biological support for these factors and found that none sufficiently explained the lack of an effect during exercise or after exposure to allergens. In the absence of either a consistent concentration-response or a plausible explanation for the paradoxical AHR findings, the biological significance of these findings is uncertain and provides equivocal support for NO 2 as a causal factor of AHR at these exposure levels. Copyright © 2017 Gradient. Published by Elsevier Inc. All rights reserved.

Disease ecology and the global emergence of zoonotic pathogens.

PubMed

Wilcox, Bruce A; Gubler, Duane J

2005-09-01

The incidence and frequency of epidemic transmission of zoonotic diseases, both known and newly recognized, has increased dramatically in the past 30 years. It is thought that this dramatic disease emergence is primarily the result of the social, demographic, and environmental transformation that has occurred globally since World War II. However, the causal linkages have not been elucidated. Investigating emerging zoonotic pathogens as an ecological phenomenon can provide significant insights as to why some of these pathogens have jumped species and caused major epidemics in humans. A review of concepts and theory from biological ecology and of causal factors in disease emergence previously described suggests a general model of global zoonotic disease emergence. The model links demographic and societal factors to land use and land cover change whose associated ecological factors help explain disease emergence. The scale and magnitude of these changes are more significant than those associated with climate change, the effects of which are largely not yet understood. Unfortunately, the complex character and non-linear behavior of the human-natural systems in which host-pathogen systems are embedded makes specific incidences of disease emergence or epidemics inherently difficult to predict. Employing a complex systems analytical approach, however, may show how a few key ecological variables and system properties, including the adaptive capacity of institutions, explains the emergence of infectious diseases and how an integrated, multi-level approach to zoonotic disease control can reduce risk.

Inferring causal relationships between phenotypes using summary statistics from genome-wide association studies.

PubMed

Meng, Xiang-He; Shen, Hui; Chen, Xiang-Ding; Xiao, Hong-Mei; Deng, Hong-Wen

2018-03-01

Genome-wide association studies (GWAS) have successfully identified numerous genetic variants associated with diverse complex phenotypes and diseases, and provided tremendous opportunities for further analyses using summary association statistics. Recently, Pickrell et al. developed a robust method for causal inference using independent putative causal SNPs. However, this method may fail to infer the causal relationship between two phenotypes when only a limited number of independent putative causal SNPs identified. Here, we extended Pickrell's method to make it more applicable for the general situations. We extended the causal inference method by replacing the putative causal SNPs with the lead SNPs (the set of the most significant SNPs in each independent locus) and tested the performance of our extended method using both simulation and empirical data. Simulations suggested that when the same number of genetic variants is used, our extended method had similar distribution of test statistic under the null model as well as comparable power under the causal model compared with the original method by Pickrell et al. But in practice, our extended method would generally be more powerful because the number of independent lead SNPs was often larger than the number of independent putative causal SNPs. And including more SNPs, on the other hand, would not cause more false positives. By applying our extended method to summary statistics from GWAS for blood metabolites and femoral neck bone mineral density (FN-BMD), we successfully identified ten blood metabolites that may causally influence FN-BMD. We extended a causal inference method for inferring putative causal relationship between two phenotypes using summary statistics from GWAS, and identified a number of potential causal metabolites for FN-BMD, which may provide novel insights into the pathophysiological mechanisms underlying osteoporosis.

UNRECOGNIZED OR POTENTIAL RISK FACTORS FOR CHILDHOOD CANCER

EPA Science Inventory

Traditional epidemiological studies suggest that the contribution of environmental agents to childhood cancer may be minor. However, epidemiological methods can only seldom identify causal factors associated with a relative risk of less than a factor of one and a half to two. App...

A Framework for Estimating Causal Effects in Latent Class Analysis: Is There a Causal Link Between Early Sex and Subsequent Profiles of Delinquency?

PubMed Central

Lanza, Stephanie T.; Coffman, Donna L.

2013-01-01

Prevention scientists use latent class analysis (LCA) with increasing frequency to characterize complex behavior patterns and profiles of risk. Often, the most important research questions in these studies involve establishing characteristics that predict membership in the latent classes, thus describing the composition of the subgroups and suggesting possible points of intervention. More recently, prevention scientists have begun to adopt modern methods for drawing causal inference from observational data because of the bias that can be introduced by confounders. This same issue of confounding exists in any analysis of observational data, including prediction of latent class membership. This study demonstrates a straightforward approach to causal inference in LCA that builds on propensity score methods. We demonstrate this approach by examining the causal effect of early sex on subsequent delinquency latent classes using data from 1,890 adolescents in 11th and 12th grade from wave I of the National Longitudinal Study of Adolescent Health. Prior to the statistical adjustment for potential confounders, early sex was significantly associated with delinquency latent class membership for both genders (p=0.02). However, the propensity score adjusted analysis indicated no evidence for a causal effect of early sex on delinquency class membership (p=0.76) for either gender. Sample R and SAS code is included in an Appendix in the ESM so that prevention scientists may adopt this approach to causal inference in LCA in their own work. PMID:23839479

A framework for estimating causal effects in latent class analysis: is there a causal link between early sex and subsequent profiles of delinquency?

PubMed

Butera, Nicole M; Lanza, Stephanie T; Coffman, Donna L

2014-06-01

Prevention scientists use latent class analysis (LCA) with increasing frequency to characterize complex behavior patterns and profiles of risk. Often, the most important research questions in these studies involve establishing characteristics that predict membership in the latent classes, thus describing the composition of the subgroups and suggesting possible points of intervention. More recently, prevention scientists have begun to adopt modern methods for drawing causal inference from observational data because of the bias that can be introduced by confounders. This same issue of confounding exists in any analysis of observational data, including prediction of latent class membership. This study demonstrates a straightforward approach to causal inference in LCA that builds on propensity score methods. We demonstrate this approach by examining the causal effect of early sex on subsequent delinquency latent classes using data from 1,890 adolescents in 11th and 12th grade from wave I of the National Longitudinal Study of Adolescent Health. Prior to the statistical adjustment for potential confounders, early sex was significantly associated with delinquency latent class membership for both genders (p = 0.02). However, the propensity score adjusted analysis indicated no evidence for a causal effect of early sex on delinquency class membership (p = 0.76) for either gender. Sample R and SAS code is included in an Appendix in the ESM so that prevention scientists may adopt this approach to causal inference in LCA in their own work.

Learning about causes from people and about people as causes: probabilistic models and social causal reasoning.

PubMed

Buchsbaum, Daphna; Seiver, Elizabeth; Bridgers, Sophie; Gopnik, Alison

2012-01-01

A major challenge children face is uncovering the causal structure of the world around them. Previous research on children's causal inference has demonstrated their ability to learn about causal relationships in the physical environment using probabilistic evidence. However, children must also learn about causal relationships in the social environment, including discovering the causes of other people's behavior, and understanding the causal relationships between others' goal-directed actions and the outcomes of those actions. In this chapter, we argue that social reasoning and causal reasoning are deeply linked, both in the real world and in children's minds. Children use both types of information together and in fact reason about both physical and social causation in fundamentally similar ways. We suggest that children jointly construct and update causal theories about their social and physical environment and that this process is best captured by probabilistic models of cognition. We first present studies showing that adults are able to jointly infer causal structure and human action structure from videos of unsegmented human motion. Next, we describe how children use social information to make inferences about physical causes. We show that the pedagogical nature of a demonstrator influences children's choices of which actions to imitate from within a causal sequence and that this social information interacts with statistical causal evidence. We then discuss how children combine evidence from an informant's testimony and expressed confidence with evidence from their own causal observations to infer the efficacy of different potential causes. We also discuss how children use these same causal observations to make inferences about the knowledge state of the social informant. Finally, we suggest that psychological causation and attribution are part of the same causal system as physical causation. We present evidence that just as children use covariation between physical causes and their effects to learn physical causal relationships, they also use covaration between people's actions and the environment to make inferences about the causes of human behavior.

Draft Genome Sequences of Two Isolates of Colletotrichum lindemuthianum, the Causal Agent of Anthracnose in Common Beans.

PubMed

de Queiroz, Casley Borges; Correia, Hilberty L Nunes; Menicucci, Renato Pedrozo; Vidigal, Pedro M Pereira; de Queiroz, Marisa Vieira

2017-05-04

Colletotrichum lindemuthianum is the causal agent of anthracnose in common beans, one of the main limiting factors of their culture. Here, we report for the first time, to our knowledge, a draft of the complete genome sequences of two isolates belonging to 83.501 and 89 A 2 2-3 of C. lindemutuianum . Copyright © 2017 de Queiroz et al.

Modelling cointegration and Granger causality network to detect long-term equilibrium and diffusion paths in the financial system.

PubMed

Gao, Xiangyun; Huang, Shupei; Sun, Xiaoqi; Hao, Xiaoqing; An, Feng

2018-03-01

Microscopic factors are the basis of macroscopic phenomena. We proposed a network analysis paradigm to study the macroscopic financial system from a microstructure perspective. We built the cointegration network model and the Granger causality network model based on econometrics and complex network theory and chose stock price time series of the real estate industry and its upstream and downstream industries as empirical sample data. Then, we analysed the cointegration network for understanding the steady long-term equilibrium relationships and analysed the Granger causality network for identifying the diffusion paths of the potential risks in the system. The results showed that the influence from a few key stocks can spread conveniently in the system. The cointegration network and Granger causality network are helpful to detect the diffusion path between the industries. We can also identify and intervene in the transmission medium to curb risk diffusion.

Modelling cointegration and Granger causality network to detect long-term equilibrium and diffusion paths in the financial system

PubMed Central

Huang, Shupei; Sun, Xiaoqi; Hao, Xiaoqing; An, Feng

2018-01-01

Microscopic factors are the basis of macroscopic phenomena. We proposed a network analysis paradigm to study the macroscopic financial system from a microstructure perspective. We built the cointegration network model and the Granger causality network model based on econometrics and complex network theory and chose stock price time series of the real estate industry and its upstream and downstream industries as empirical sample data. Then, we analysed the cointegration network for understanding the steady long-term equilibrium relationships and analysed the Granger causality network for identifying the diffusion paths of the potential risks in the system. The results showed that the influence from a few key stocks can spread conveniently in the system. The cointegration network and Granger causality network are helpful to detect the diffusion path between the industries. We can also identify and intervene in the transmission medium to curb risk diffusion. PMID:29657804

Prenatal nutrition, epigenetics and schizophrenia risk: can we test causal effects?

PubMed

Kirkbride, James B; Susser, Ezra; Kundakovic, Marija; Kresovich, Jacob K; Davey Smith, George; Relton, Caroline L

2012-06-01

We posit that maternal prenatal nutrition can influence offspring schizophrenia risk via epigenetic effects. In this article, we consider evidence that prenatal nutrition is linked to epigenetic outcomes in offspring and schizophrenia in offspring, and that schizophrenia is associated with epigenetic changes. We focus upon one-carbon metabolism as a mediator of the pathway between perturbed prenatal nutrition and the subsequent risk of schizophrenia. Although post-mortem human studies demonstrate DNA methylation changes in brains of people with schizophrenia, such studies cannot establish causality. We suggest a testable hypothesis that utilizes a novel two-step Mendelian randomization approach, to test the component parts of the proposed causal pathway leading from prenatal nutritional exposure to schizophrenia. Applied here to a specific example, such an approach is applicable for wider use to strengthen causal inference of the mediating role of epigenetic factors linking exposures to health outcomes in population-based studies.

Multivariate co-integration analysis of the Kaya factors in Ghana.

PubMed

Asumadu-Sarkodie, Samuel; Owusu, Phebe Asantewaa

2016-05-01

The fundamental goal of the Government of Ghana's development agenda as enshrined in the Growth and Poverty Reduction Strategy to grow the economy to a middle income status of US$1000 per capita by the end of 2015 could be met by increasing the labour force, increasing energy supplies and expanding the energy infrastructure in order to achieve the sustainable development targets. In this study, a multivariate co-integration analysis of the Kaya factors namely carbon dioxide, total primary energy consumption, population and GDP was investigated in Ghana using vector error correction model with data spanning from 1980 to 2012. Our research results show an existence of long-run causality running from population, GDP and total primary energy consumption to carbon dioxide emissions. However, there is evidence of short-run causality running from population to carbon dioxide emissions. There was a bi-directional causality running from carbon dioxide emissions to energy consumption and vice versa. In other words, decreasing the primary energy consumption in Ghana will directly reduce carbon dioxide emissions. In addition, a bi-directional causality running from GDP to energy consumption and vice versa exists in the multivariate model. It is plausible that access to energy has a relationship with increasing economic growth and productivity in Ghana.

Nonlinear parametric model for Granger causality of time series

NASA Astrophysics Data System (ADS)

Marinazzo, Daniele; Pellicoro, Mario; Stramaglia, Sebastiano

2006-06-01

The notion of Granger causality between two time series examines if the prediction of one series could be improved by incorporating information of the other. In particular, if the prediction error of the first time series is reduced by including measurements from the second time series, then the second time series is said to have a causal influence on the first one. We propose a radial basis function approach to nonlinear Granger causality. The proposed model is not constrained to be additive in variables from the two time series and can approximate any function of these variables, still being suitable to evaluate causality. Usefulness of this measure of causality is shown in two applications. In the first application, a physiological one, we consider time series of heart rate and blood pressure in congestive heart failure patients and patients affected by sepsis: we find that sepsis patients, unlike congestive heart failure patients, show symmetric causal relationships between the two time series. In the second application, we consider the feedback loop in a model of excitatory and inhibitory neurons: we find that in this system causality measures the combined influence of couplings and membrane time constants.

New Insights into Signed Path Coefficient Granger Causality Analysis

PubMed Central

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. PMID:27833547

Causality in medicine: the case of tumours and viruses.

PubMed Central

Vonka, V

2000-01-01

Clarification of the aetiology of chronic human diseases such as atherosclerosis or cancer is one of the dominant topics in contemporary medical research. It is believed that identification of the causal factors will enable more efficient prevention and diagnosis of these diseases and, in some instances, also permit more effective therapy. The task is difficult because of the multistep and multifactorial origin of these diseases. A special case in contemporary aetiological studies is definition of the role of viruses in the pathogenesis of human cancer. Virus-associated cancer develops only in a small minority of infected subjects, which implies that, if the virus does play a role in the pathogenesis of the malignancy, other factors must also be involved. In this paper the author attempts to review the present methodological approaches to aetiological studies of chronic diseases, discusses the role of criteria for identifying causal relationships and proposes guidelines that might help to determine the role of viruses in human cancer. PMID:11205344

Supporting inquiry learning by promoting normative understanding of multivariable causality

NASA Astrophysics Data System (ADS)

Keselman, Alla

2003-11-01

Early adolescents may lack the cognitive and metacognitive skills necessary for effective inquiry learning. In particular, they are likely to have a nonnormative mental model of multivariable causality in which effects of individual variables are neither additive nor consistent. Described here is a software-based intervention designed to facilitate students' metalevel and performance-level inquiry skills by enhancing their understanding of multivariable causality. Relative to an exploration-only group, sixth graders who practiced predicting an outcome (earthquake risk) based on multiple factors demonstrated increased attention to evidence, improved metalevel appreciation of effective strategies, and a trend toward consistent use of a controlled comparison strategy. Sixth graders who also received explicit instruction in making predictions based on multiple factors showed additional improvement in their ability to compare multiple instances as a basis for inferences and constructed the most accurate knowledge of the system. Gains were maintained in transfer tasks. The cognitive skills and metalevel understanding examined here are essential to inquiry learning.

The social determinants of oral health: new approaches to conceptualizing and researching complex causal networks.

PubMed

Newton, J Timothy; Bower, Elizabeth J

2005-02-01

Oral epidemiological research into the social determinants of oral health has been limited by the absence of a theoretical framework which reflects the complexity of real life social processes and the network of causal pathways between social structure and oral health and disease. In the absence of such a framework, social determinants are treated as isolated risk factors, attributable to the individual, having a direct impact on oral health. There is little sense of how such factors interrelate over time and place and the pathways between the factors and oral health. Features of social life which impact on individuals' oral health but are not reducible to the individual remain under-researched. A conceptual framework informing mainstream epidemiological research into the social determinants of health is applied to oral epidemiology. The framework suggests complex causal pathways between social structure and health via interlinking material, psychosocial and behavioural pathways. Methodological implications for oral epidemiological research informed by the framework, such as the use of multilevel modelling, path analysis and structural equation modelling, combining qualitative and quantitative research methods, and collaborative research, are discussed. Copyright Blackwell Munksgaard, 2005.

Acausal measurement-based quantum computing

NASA Astrophysics Data System (ADS)

Morimae, Tomoyuki

2014-07-01

In measurement-based quantum computing, there is a natural "causal cone" among qubits of the resource state, since the measurement angle on a qubit has to depend on previous measurement results in order to correct the effect of by-product operators. If we respect the no-signaling principle, by-product operators cannot be avoided. Here we study the possibility of acausal measurement-based quantum computing by using the process matrix framework [Oreshkov, Costa, and Brukner, Nat. Commun. 3, 1092 (2012), 10.1038/ncomms2076]. We construct a resource process matrix for acausal measurement-based quantum computing restricting local operations to projective measurements. The resource process matrix is an analog of the resource state of the standard causal measurement-based quantum computing. We find that if we restrict local operations to projective measurements the resource process matrix is (up to a normalization factor and trivial ancilla qubits) equivalent to the decorated graph state created from the graph state of the corresponding causal measurement-based quantum computing. We also show that it is possible to consider a causal game whose causal inequality is violated by acausal measurement-based quantum computing.

Factors influencing nanotechnology commercialization: an empirical analysis of nanotechnology firms in South Korea

NASA Astrophysics Data System (ADS)

Lee, Cheol-Ju; Lee, SuKap; Jhon, Myung S.; Shin, Juneseuk

2013-02-01

Nanotechnology is a representative emerging technology in an embryonic stage. Due to the continuous support provided by both the public and private sectors of many countries, nanotechnologies have increasingly been commercialized in a wide array of industries, but also produce many commercialization failures. Tackling this problem, we investigate key factors affecting the commercialization of nanotechnologies. Identifying key factors of nanotechnology commercialization through literature review and interview with CEOs, we collected data of 206 Korean nanotechnology-based companies, and analyzed the causal relationship between key factors and financial performance. Logistic and Tobit regression models are used. Overall, companies achieving successful commercialization hold some common characteristics including consistent exploratory R&D, governmental funding, and nano-instrument/energy/environment-related products. Also, the use of potentially toxic materials makes commercialization difficult even if the products are not toxic.

Young adults' reactions to infant crying.

PubMed

Cohen-Bendahan, C C C; van Doornen, L J P; de Weerth, C

2014-02-01

An infant's optimal development is determined to a great extent by the adequate and sensitive responses of the caregiver. The adequacy and sensitivity of a reaction to an infant in distress (i.e. crying) will partly depend on the causal attributions of the crying and on the individual's sympathy for the infant. Being female, prior caring experiences, and multiparity have shown to be linked to more sympathetic, tolerant and less hostile emotional responses to crying. However, little is known about other factors explaining inexperienced future caregivers' reactions to infant crying. The present paper's goal is to shed more light on the subject by looking at how personality factors, caregiving interest, sex, promptness of the reaction, and gender identity are related to emotional reactions and causal attributions to crying in a population of young adults without children. One hundred and ninety-one childless university students participated (126 females; ages 18-35 years). The participants completed questionnaires on personality, gender identity and caregiving interest, and listened to an audio sample of an infant crying, reporting their emotions and their causal attributions to the crying. The results showed that experiencing anger was associated with more child-blaming attributions to the crying, while quickness of response and feelings of sympathy predicted more child-oriented attributions. The latter was stronger in males. Explicit care interest decreased child-blaming causal attributions more for men than for the women. Interestingly, solely in the females' personality factors neuroticism and conscientiousness played a role in child blaming attributions together with anger. These findings suggest that the motives that young adults attribute to a crying infant depend in males on the emotions triggered by the crying, responsiveness and care interest. While in females, emotions, responsiveness and personality affect the causal attribution to the crying. Future research is needed in order to determine whether these attributions are also linked to young adults' actual behaviour towards a crying infant. Copyright © 2013 Elsevier Inc. All rights reserved.

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

PubMed

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.

[Medication errors in a neonatal unit: One of the main adverse events].

PubMed

Esqué Ruiz, M T; Moretones Suñol, M G; Rodríguez Miguélez, J M; Sánchez Ortiz, E; Izco Urroz, M; de Lamo Camino, M; Figueras Aloy, J

2016-04-01

Neonatal units are one of the hospital areas most exposed to the committing of treatment errors. A medication error (ME) is defined as the avoidable incident secondary to drug misuse that causes or may cause harm to the patient. The aim of this paper is to present the incidence of ME (including feeding) reported in our neonatal unit and its characteristics and possible causal factors. A list of the strategies implemented for prevention is presented. An analysis was performed on the ME declared in a neonatal unit. A total of 511 MEs have been reported over a period of seven years in the neonatal unit. The incidence in the critical care unit was 32.2 per 1000 hospital days or 20 per 100 patients, of which 0.22 per 1000 days had serious repercussions. The ME reported were, 39.5% prescribing errors, 68.1% administration errors, 0.6% were adverse drug reactions. Around two-thirds (65.4%) were produced by drugs, with 17% being intercepted. The large majority (89.4%) had no impact on the patient, but 0.6% caused permanent damage or death. Nurses reported 65.4% of MEs. The most commonly implicated causal factor was distraction (59%). Simple corrective action (alerts), and intermediate (protocols, clinical sessions and courses) and complex actions (causal analysis, monograph) were performed. It is essential to determine the current state of ME, in order to establish preventive measures and, together with teamwork and good practices, promote a climate of safety. Copyright © 2015 Asociación Española de Pediatría. Published by Elsevier España, S.L.U. All rights reserved.

Smoking and caffeine consumption: a genetic analysis of their association

PubMed Central

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.

2016-01-01

Abstract 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. PMID:27027469

How do environmental factors influence life cycles and development? An experimental framework for early-diverging metazoans

PubMed Central

Bosch, Thomas C. G.; Adamska, Maja; Augustin, René; Domazet-Loso, Tomislav; Foret, Sylvain; Fraune, Sebastian; Funayama, Noriko; Grasis, Juris; Hamada, Mayuko; Hatta, Masayuki; Hobmayer, Bert; Kawai, Kotoe; Klimovich, Alexander; Manuel, Michael; Shinzato, Chuya; Technau, Uli; Yum, Seungshic; Miller, David J.

2014-01-01

Ecological developmental biology (eco-devo) explores the mechanistic relationships between the processes of individual development and environmental factors. Recent studies imply that some of these relationships have deep evolutionary origins, and may even predate the divergences of the simplest extant animals, including cnidarians and sponges. Development of these early diverging metazoans is often sensitive to environmental factors, and these interactions occur in the context of conserved signaling pathways and mechanisms of tissue homeostasis whose detailed molecular logic remain elusive. Efficient methods for transgenesis in cnidarians together with the ease of experimental manipulation in cnidarians and sponges make them ideal models for understanding causal relationships between environmental factors and developmental mechanisms. Here, we identify major questions at the interface between animal evolution and development and outline a road map for research aimed at identifying the mechanisms that link environmental factors to developmental mechanisms in early diverging metazoans. PMID:25205353

Causality

NASA Astrophysics Data System (ADS)

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.

Questions on causality and responsibility arising from an outbreak of Pseudomonas aeruginosa infections in Norway

PubMed Central

Iversen, Bjørn G; Hofmann, Bjørn; Aavitsland, Preben

2008-01-01

In 2002, Norway experienced a large outbreak of Pseudomonas aeruginosa infections in hospitals with 231 confirmed cases. This fuelled intense public and professional debates on what were the causes and who were responsible. In epidemiology, other sciences, in philosophy and in law there is a long tradition of discussing the concept of causality. We use this outbreak as a case; apply various theories of causality from different disciplines to discuss the roles and responsibilities of some of the parties involved. Mackie's concept of INUS conditions, Hill's nine viewpoints to study association for claiming causation, deterministic and probabilistic ways of reasoning, all shed light on the issues of causality in this outbreak. Moreover, applying legal theories of causation (counterfactual reasoning and the "but-for" test and the NESS test) proved especially useful, but the case also illustrated the weaknesses of the various theories of causation. We conclude that many factors contributed to causing the outbreak, but that contamination of a medical device in the production facility was the major necessary condition. The reuse of the medical device in hospitals contributed primarily to the size of the outbreak. The unintended error by its producer – and to a minor extent by the hospital practice – was mainly due to non-application of relevant knowledge and skills, and appears to constitute professional negligence. Due to criminal procedure laws and other factors outside the discourse of causality, no one was criminally charged for the outbreak which caused much suffering and shortening the life of at least 34 people. PMID:18947429

Post-traumatic stress disorder and cardiometabolic disease: improving causal inference to inform practice.

PubMed

Koenen, K C; Sumner, J A; Gilsanz, P; Glymour, M M; Ratanatharathorn, A; Rimm, E B; Roberts, A L; Winning, A; Kubzansky, L D

2017-01-01

Post-traumatic stress disorder (PTSD) has been declared 'a life sentence' based on evidence that the disorder leads to a host of physical health problems. Some of the strongest empirical research - in terms of methodology and findings - has shown that PTSD predicts higher risk of cardiometabolic diseases, specifically cardiovascular disease (CVD) and type 2 diabetes (T2D). Despite mounting evidence, PTSD is not currently acknowledged as a risk factor by cardiovascular or endocrinological medicine. This view is unlikely to change absent compelling evidence that PTSD causally contributes to cardiometabolic disease. This review suggests that with developments in methods for epidemiological research and the rapidly expanding knowledge of the behavioral and biological effects of PTSD the field is poised to provide more definitive answers to questions of causality. First, we discuss methods to improve causal inference using the observational data most often used in studies of PTSD and health, with particular reference to issues of temporality and confounding. Second, we consider recent work linking PTSD with specific behaviors and biological processes, and evaluate whether these may plausibly serve as mechanisms by which PTSD leads to cardiometabolic disease. Third, we evaluate how looking more comprehensively into the PTSD phenotype provides insight into whether specific aspects of PTSD phenomenology are particularly relevant to cardiometabolic disease. Finally, we discuss new areas of research that are feasible and could enhance understanding of the PTSD-cardiometabolic relationship, such as testing whether treatment of PTSD can halt or even reverse the cardiometabolic risk factors causally related to CVD and T2D.

Efficient and accurate causal inference with hidden confounders from genome-transcriptome variation data

PubMed Central

2017-01-01

Mapping gene expression as a quantitative trait using whole genome-sequencing and transcriptome analysis allows to discover the functional consequences of genetic variation. We developed a novel method and ultra-fast software Findr for higly accurate causal inference between gene expression traits using cis-regulatory DNA variations as causal anchors, which improves current methods by taking into consideration hidden confounders and weak regulations. Findr outperformed existing methods on the DREAM5 Systems Genetics challenge and on the prediction of microRNA and transcription factor targets in human lymphoblastoid cells, while being nearly a million times faster. Findr is publicly available at https://github.com/lingfeiwang/findr. PMID:28821014

Causal attributions in Brazilian children's reasoning about health and illness.

PubMed

Boruchovitch, E; Mednick, B R

2000-10-01

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. 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. 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. 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.

Globally conditioned Granger causality in brain–brain and brain–heart interactions: a combined heart rate variability/ultra-high-field (7 T) functional magnetic resonance imaging study

PubMed Central

Passamonti, Luca; Wald, Lawrence L.; Barbieri, Riccardo

2016-01-01

The causal, directed interactions between brain regions at rest (brain–brain networks) and between resting-state brain activity and autonomic nervous system (ANS) outflow (brain–heart links) have not been completely elucidated. We collected 7 T resting-state functional magnetic resonance imaging (fMRI) data with simultaneous respiration and heartbeat recordings in nine healthy volunteers to investigate (i) the causal interactions between cortical and subcortical brain regions at rest and (ii) the causal interactions between resting-state brain activity and the ANS as quantified through a probabilistic, point-process-based heartbeat model which generates dynamical estimates for sympathetic and parasympathetic activity as well as sympathovagal balance. Given the high amount of information shared between brain-derived signals, we compared the results of traditional bivariate Granger causality (GC) with a globally conditioned approach which evaluated the additional influence of each brain region on the causal target while factoring out effects concomitantly mediated by other brain regions. The bivariate approach resulted in a large number of possibly spurious causal brain–brain links, while, using the globally conditioned approach, we demonstrated the existence of significant selective causal links between cortical/subcortical brain regions and sympathetic and parasympathetic modulation as well as sympathovagal balance. In particular, we demonstrated a causal role of the amygdala, hypothalamus, brainstem and, among others, medial, middle and superior frontal gyri, superior temporal pole, paracentral lobule and cerebellar regions in modulating the so-called central autonomic network (CAN). In summary, we show that, provided proper conditioning is employed to eliminate spurious causalities, ultra-high-field functional imaging coupled with physiological signal acquisition and GC analysis is able to quantify directed brain–brain and brain–heart interactions reflecting central modulation of ANS outflow. PMID:27044985

What do we know about developing patient portals? a systematic literature review.

PubMed

Otte-Trojel, Terese; de Bont, Antoinette; Rundall, Thomas G; van de Klundert, Joris

2016-04-01

Numerous articles have reported on the development of patient portals, including development problems and solutions. We review these articles to inform future patient portal development efforts and to provide a summary of the evidence base that can guide future research. We performed a systematic review of relevant literature to answer 5 questions: (1) What categories of problems related to patient portal development have been defined? (2) What causal factors have been identified by problem analysis and diagnosis? (3) What solutions have been proposed to ameliorate these causal factors? (4) Which proposed solutions have been implemented and in which organizational contexts? (5) Have implemented solutions been evaluated and what learning has been generated? Through searches on PubMed, ScienceDirect and LISTA, we included 109 articles. We identified 5 main problem categories: achieving patient engagement, provider engagement, appropriate data governance, security and interoperability, and a sustainable business model. Further, we identified key factors contributing to these problems as well as solutions proposed to ameliorate them. While about half (45) of the 109 articles proposed solutions, fewer than half of these solutions (18) were implemented, and even fewer (5) were evaluated to generate learning about their effects. Few studies systematically report on the patient portal development processes. As a result, the review does not provide an evidence base for portal development. Our findings support a set of recommendations for advancement of the evidence base: future research should build on existing evidence, draw on principles from design sciences conveyed in the problem-solving cycle, and seek to produce evidence within various different organizational contexts. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Educational attainment and cigarette smoking: a causal association?†

PubMed Central

Gilman, Stephen E; Martin, Laurie T; Abrams, David B; Kawachi, Ichiro; Kubzansky, Laura; Loucks, Eric B; Rende, Richard; Rudd, Rima; Buka, Stephen L

2016-01-01

Background Despite abundant evidence that lower education is associated with a higher risk of smoking, whether the association is causal has not been convincingly established. Methods We investigated the association between education and lifetime smoking patterns in a birth cohort established in 1959 and followed through adulthood (n = 1311). We controlled for a wide range of potential confounders that were measured prior to school entry, and also estimated sibling fixed effects models to control for unmeasured familial vulnerability to smoking. Results In the full sample of participants, regression analyses adjusting for multiple childhood factors (including socioeconomic status, IQ, behavioural problems, and medical conditions) indicated that the number of pack-years smoked was higher among individuals with less than high school education [rate ratio (RR) = 1.58, confidence interval (CI) = 1.31, 1.91]. However, in the sibling fixed effects analysis the RR was 1.23 (CI = 0.80, 1.93). Similarly, adjusted models estimated in the full sample showed that individuals with less than high school education had fewer short-term (RR = 0.40; CI = 0.23, 0.69) and long-term (RR = 0.59; CI = 0.42, 0.83) quit attempts, and were less likely to quit smoking (odds ratio = 0.34; CI = 0.19, 0.62). The effects of education on quitting smoking were attenuated in the sibling fixed effects models that controlled for familial vulnerability to smoking. Conclusions A substantial portion of the education differential in smoking that has been repeatedly observed is attributable to factors shared by siblings that contribute to shortened educational careers and to lifetime smoking trajectories. Reducing disparities in cigarette smoking, including educational disparities, may therefore require approaches that focus on factors early in life that influence smoking risk over the adult life span. PMID:18180240

What do we know about developing patient portals? a systematic literature review

PubMed Central

de Bont, Antoinette; Rundall, Thomas G; van de Klundert, Joris

2016-01-01

Objective Numerous articles have reported on the development of patient portals, including development problems and solutions. We review these articles to inform future patient portal development efforts and to provide a summary of the evidence base that can guide future research. Materials and Methods We performed a systematic review of relevant literature to answer 5 questions: (1) What categories of problems related to patient portal development have been defined? (2) What causal factors have been identified by problem analysis and diagnosis? (3) What solutions have been proposed to ameliorate these causal factors? (4) Which proposed solutions have been implemented and in which organizational contexts? (5) Have implemented solutions been evaluated and what learning has been generated? Through searches on PubMed, ScienceDirect and LISTA, we included 109 articles. Results We identified 5 main problem categories: achieving patient engagement, provider engagement, appropriate data governance, security and interoperability, and a sustainable business model. Further, we identified key factors contributing to these problems as well as solutions proposed to ameliorate them. While about half (45) of the 109 articles proposed solutions, fewer than half of these solutions (18) were implemented, and even fewer (5) were evaluated to generate learning about their effects. Discussion Few studies systematically report on the patient portal development processes. As a result, the review does not provide an evidence base for portal development. Conclusion Our findings support a set of recommendations for advancement of the evidence base: future research should build on existing evidence, draw on principles from design sciences conveyed in the problem-solving cycle, and seek to produce evidence within various different organizational contexts. PMID:26335985

Inflammatory pathways in cervical cancer - the UCT contribution.

PubMed

Sales, Kurt Jason; Katz, Arieh Anthony

2012-03-23

Cervical cancer is the leading gynaecological malignancy in Southern Africa. The main causal factor for development of the disease is infection of the cervix with human papillomavirus. It is a multi-step disease with several contributing co-factors including multiple sexual partners, a compromised immune system and cervical inflammation caused by infections with Chlamydia trachomatis or Neisseria gonorrhoeae. Inflammation involves extensive tissue remodelling events which are orchestrated by complex networks of cytokines, chemokines and bio-active lipids working across multiple cellular compartments to maintain tissue homeostasis. Many pathological disorders or diseases, including cervical cancer, are characterised by the exacerbated activation and maintenance of inflammatory pathways. In this review we highlight our findings pertaining to activation of inflammatory pathways in cervical cancers, addressing their potential role in pathological changes of the cervix and the significance of these findings for intervention strategies.

Strategic environmental assessment performance factors and their interaction: An empirical study in China

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Tianwei, E-mail: li.tianwei@mep.gov.cn; Wang, Huizhi, E-mail: huizhiwangnk@163.com; Deng, Baole, E-mail: dengbaolekobe@126.com

Strategic Environmental Assessment (SEA) has been seen as a preventive and participatory environmental management tool designed to integrate environmental protection into the decision-making process. However, the debate about SEA performance and effectiveness has increased in recent decades. Two main challenges exist in relation to this issue. The first is identifying the key influencing factors that affect SEA effectiveness, and the second is analyzing the relationship between SEA and these influencing factors. In this study, influencing factors were investigated through questionnaire surveys in the Chinese context, and then a Structural Equation Model (SEM) was developed and tested to identify potential linksmore » and causal relationships among factors. The associations between the independent factors were divided into direct and indirect causal associations. The results indicate that the decision-making process and policy context directly affect SEA implementation, while information and data sharing, public participation, expertise and SEA institutions are indirectly related with SEA. The results also suggest that a lack of cooperation between different sectors is an obstacle to the implementation of SEA. These findings could potentially contribute to the future management and implementation of SEA or enhance existing knowledge of SEA. The results show that the proposed model has a degree of feasibility and applicability. - Highlights: • Influencing factors were identified and investigated through questionnaire surveys. • Structural Equation Model (SEM) was developed and tested to identify potential links and causal relationships among factors. • Decision-making process and policy context directly affect SEA implementation. • Lack of cooperation among different sectors is an obstacle to the implementation of SEA. • The proposed model has a degree of feasibility and applicability.« less

Spectral factorization of wavefields and wave operators

NASA Astrophysics Data System (ADS)

Rickett, James Edward

Spectral factorization is the problem of finding a minimum-phase function with a given power spectrum. Minimum phase functions have the property that they are causal with a causal (stable) inverse. In this thesis, I factor multidimensional systems into their minimum-phase components. Helical boundary conditions resolve any ambiguities over causality, allowing me to factor multi-dimensional systems with conventional one-dimensional spectral factorization algorithms. In the first part, I factor passive seismic wavefields recorded in two-dimensional spatial arrays. The result provides an estimate of the acoustic impulse response of the medium that has higher bandwidth than autocorrelation-derived estimates. Also, the function's minimum-phase nature mimics the physics of the system better than the zero-phase autocorrelation model. I demonstrate this on helioseismic data recorded by the satellite-based Michelson Doppler Imager (MDI) instrument, and shallow seismic data recorded at Long Beach, California. In the second part of this thesis, I take advantage of the stable-inverse property of minimum-phase functions to solve wave-equation partial differential equations. By factoring multi-dimensional finite-difference stencils into minimum-phase components, I can invert them efficiently, facilitating rapid implicit extrapolation without the azimuthal anisotropy that is observed with splitting approximations. The final part of this thesis describes how to calculate diagonal weighting functions that approximate the combined operation of seismic modeling and migration. These weighting functions capture the effects of irregular subsurface illumination, which can be the result of either the surface-recording geometry, or focusing and defocusing of the seismic wavefield as it propagates through the earth. Since they are diagonal, they can be easily both factored and inverted to compensate for uneven subsurface illumination in migrated images. Experimental results show that applying these weighting functions after migration leads to significantly improved estimates of seismic reflectivity.

Environmental risk factors for cancers of the brain and nervous system: the use of ecological data to generate hypotheses.

PubMed

de Vocht, Frank; Hannam, Kimberly; Buchan, Iain

2013-05-01

There is a public health need to balance timely generation of hypotheses with cautious causal inference. For rare cancers this is particularly challenging because standard epidemiological study designs may not be able to elucidate causal factors in an early period of newly emerging risks. Alternative methodologies need to be considered for generating and shaping hypotheses prior to definitive investigation. To evaluate whether open-access databases can be used to explore links between potential risk factors and cancers at an ecological level, using the case study of brain and nervous system cancers as an example. National age-adjusted cancer incidence rates were obtained from the GLOBOCAN 2008 resource and combined with data from the United Nations Development Report and the World Bank list of development indicators. Data were analysed using multivariate regression models. Cancer rates, potential confounders and environmental risk factors were available for 165 of 208 countries. 2008 national incidences of brain and nervous system cancers were associated with continent, gross national income in 2008 and Human Development Index Score. The only exogenous risk factor consistently associated with higher incidence was the penetration rate of mobile/cellular telecommunications subscriptions, although other factors were highlighted. According to these ecological results the latency period is at least 11-12 years, but probably more than 20 years. Missing data on cancer incidence and for other potential risk factors prohibit more detailed investigation of exposure-response associations and/or explore other hypotheses. Readily available ecological data may be underused, particularly for the study of risk factors for rare diseases and those with long latencies. The results of ecological analyses in general should not be overinterpreted in causal inference, but equally they should not be ignored where alternative signals of aetiology are lacking.

Assessing the association between homocysteine and cognition: reflections on Bradford Hill, meta-analyses, and causality.

PubMed

McCaddon, Andrew; Miller, Joshua W

2015-10-01

Hyperhomocysteinemia is a recognized risk factor for cognitive decline and incident dementia in older adults. Two recent reports addressed the cumulative epidemiological evidence for this association but expressed conflicting opinions. Here, the evidence is reviewed in relation to Sir Austin Bradford Hill's criteria for assessing "causality," and the latest meta-analysis of the effects of homocysteine-lowering on cognitive function is critically examined. The meta-analysis included 11 trials, collectively assessing 22,000 individuals, that examined the effects of B vitamin supplements (folic acid, vitamin B12, vitamin B6) on global or domain-specific cognitive decline. It concluded that homocysteine-lowering with B vitamin supplements has no significant effect on cognitive function. However, careful examination of the trials in the meta-analysis indicates that no conclusion can be made regarding the effects of homocysteine-lowering on cognitive decline, since the trials typically did not include individuals who were experiencing such decline. Further definitive trials in older adults experiencing cognitive decline are still urgently needed. © The Author(s) 2015. Published by Oxford University Press on behalf of the International Life Sciences Institute. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Genetic variants associated with altered plasma levels of C-reactive protein are not associated with late-life cognitive ability in four Scottish samples.

PubMed

Marioni, Riccardo E; Deary, Ian J; Murray, Gordon D; Lowe, Gordon D O; Rafnsson, Snorri B; Strachan, Mark W J; Luciano, Michelle; Houlihan, Lorna M; Gow, Alan J; Harris, Sarah E; Stewart, Marlene C; Rumley, Ann; Fowkes, F Gerry R; Price, Jackie F

2010-01-01

It is unknown whether the relationship between raised inflammatory biomarker levels and late-life cognitive ability is causal. We explored this issue by testing the association between genetic regulators of plasma C-reactive protein (CRP) and cognition. Data were analysed from four cohorts based in central Scotland (Total N = 4,782). Associations were tested between variants in the CRP gene and both plasma CRP levels and a battery of neuropsychological tests, including a vocabulary-based estimate of peak prior cognitive ability and a general (summary) cognitive factor score, or 'g'. CRP levels were associated with a number of variants in the CRP gene (SNPs), including rs1205, rs1130864, rs1800947, and rs1417938 (P range 4.2e-06 to 0.041). Higher CRP levels were also associated with vocabulary-adjusted cognitive ability, used here to estimate lifetime cognitive change (P range 1.7e-04 to 0.038). After correction for multiple testing and adjustment for age and sex, no statistically significant associations were found between the SNPs and cognition. CRP is unlikely to be a causal determinant of late-life cognitive ability.

Distribution of Causes in Selected US Aviation Accident Reports Between 1996 and 2003

NASA Technical Reports Server (NTRS)

Holloway, C. M.; Johnson, C. W.

2004-01-01

This paper describes the results of an independent analysis of the probable and contributory causes of selected aviation accidents in the United States between 1996 and 2003. The purpose of the study was to assess the comparative frequency of a variety of causal factors in the reporting of these adverse events. Although our results show that more of these high consequence accidents were attributed to human error than to any other single factor, a large number of reports also mentioned wider systemic issues, including the managerial and regulatory context of aviation operations. These wider issues are more likely to appear as contributory rather than primary causes in this set of accident reports.

Global amphibian declines: perspectives from the United States and beyond

USGS Publications Warehouse

Densmore, Christine L.; Cipriano, R.C.; Bruckner, A.W.; Shchelkunov, I.S.

2011-01-01

Over recent decades, amphibians have experienced population declines, extirpations and species-level extinctions at an alarming rate. Numerous potential etiologies for amphibian declines have been postulated including climate and habitat degradation. Other potential anthropogenic causes including overexploitation and the frequent introductions of invasive predatory species have also been blamed for amphibian declines. Still other underlying factors may include infectious diseases caused by the chytrid fungus Batrachochytrium dendrobatidis, pathogenic viruses (Ranavirus), and other agents. It is nearly certain that more than one etiology is to blame for the majority of the global amphibian declines, and that these causal factors include some combination of climatological or physical habitat destabilization and infectious disease, most notably chytridiomycosis. Scientific research efforts are aimed at elucidating these etiologies on local, regional, and global scales that we might better understand and counteract the driving forces behind amphibian declines. Conservation efforts as outlined in the Amphibian Conservation Action Plan of 2005 are also being made to curtail losses and prevent further extinctions wherever possible.

[Eco-epidemiology: towards epidemiology of complexity].

PubMed

Bizouarn, Philippe

2016-05-01

In order to solve public health problems posed by the epidemiology of risk factors centered on the individual and neglecting the causal processes linking the risk factors with the health outcomes, Mervyn Susser proposed a multilevel epidemiology called eco-epidemiology, addressing the interdependence of individuals and their connection with molecular, individual, societal, environmental levels of organization participating in the causal disease processes. The aim of this epidemiology is to integrate more than a level of organization in design, analysis and interpretation of health problems. After presenting the main criticisms of risk-factor epidemiology focused on the individual, we will try to show how eco-epidemiology and its development could help to understand the need for a broader and integrative epidemiology, in which studies designed to identify risk factors would be balanced by studies designed to answer other questions equally vital to public health. © 2016 médecine/sciences – Inserm.

Occupational Factors, Fatigue, and Cardiovascular Disease

PubMed Central

2009-01-01

Purpose: Briefly identify the epidemiological evidence, propose pertinent mechanisms, and discuss physical therapy practice as well as research implications of a causal association between occupational factors and cardiovascular disease. Summary of Key Points: There is evidence that occupational metabolic demands and work organizations characterized by reduced worker control are associated with increased risk of cardiovascular disease. It is biologically plausible that these two factors interact to create a preclinical, intermediate state of fatigue (burnout) that is a critical component in the causal path from occupational factors to CVD. Physical therapists are uniquely qualified to contribute to an understanding of these mechanisms and their resultant implications for work organization, rehabilitation, and health promotion. Statement of Recommendations: Physical therapists engaged in ergonomic job analysis should consider work related metabolic demands, worker control, and fatigue in their assessment of risk for injury and illness, in recommendations for return to work, and in the prescription of health promotion leisure time physical activity PMID:20467535

Narrative review of yoga intervention clinical trials including weight-related outcomes.

PubMed

Rioux, Jennifer Grace; Ritenbaugh, Cheryl

2013-01-01

Medical authorities have identified obesity as a causal factor in the development of diabetes, hypertension, and cardiovascular disease (CVD), and more broadly, of metabolic syndrome/insulin resistance syndrome. To provide solutions that can modify this risk factor, researchers need to identify methods of effective risk reduction and primary prevention of obesity. Research on the effectiveness of yoga as a treatment for obesity is limited, and studies vary in overall quality and methodological rigor. This narrative review assessed the quantity and quality of clinical trials of yoga as an intervention for weight loss or as a means of risk reduction or treatment for obesity and diseases in which obesity is a causal factor. This review summarized the studies' research designs and evaluated the efficacy of yoga for weight loss via the current evidence base. The research team evaluated published studies to determine the appropriateness of research designs, comparability of programs' intervention elements, and standardization of outcome measures. The research team's literature search used the key terms yoga and obesity or yoga and weight loss in three primary medical-literature databases (PubMed, PsychInfo, and Web of Science). The study excluded clinical trials with no quantitative obesity related measure. Extracted data included each study's (1) design; (2) setting and population; (3) nature, duration, and frequency of interventions; (4) comparison groups; (5) recruitment strategies; (6) outcome measures; (7) data analysis and presentation; and (8) results and conclusions. The research team developed an overall evaluation parameter to compare disparate trials. The research team reviewed each study to determine its key features, each worth a specified number of points, with a maximum total of 20 points. The features included a study's (1) duration, (2) frequency of yoga practice, (3) intensity of (length of) each practice, (4) number of yogic elements, (5) inclusion of dietary modification, (6) inclusion of a residential component, (7) the number of weight-related outcome measures, and (8) a discussion of the details of the yogic elements. Overall, therapeutic yoga programs are frequently effective in promoting weight loss and/or improvements in body composition. The effectiveness of yoga for weight loss is related to the following key features: (1) an increased frequency of practice; (2) a longer intervention duration (3) a yogic dietary component; (4) a residential component; (5) the comprehensive inclusion of yogic components; (5) and a home-practice component. Yoga appears to be an appropriate and potentially successful intervention for weight maintenance, prevention of obesity, and risk reduction for diseases in which obesity plays a significant causal role.

The making of the modern airport executive: Causal connections among key attributes in career development, compromise, and satisfaction in airport management

NASA Astrophysics Data System (ADS)

Byers, David Alan

The purpose of this study was to identify specific career development attributes of contemporary senior-level airport executives and to evaluate the relationship of these attributes to the level of satisfaction airport executives have in their career choice. Attribute sets that were examined included early aviation interests, health factors, psychological factors, demographic factors, formal education, and other aviation-related experiences. A hypothesized causal model that expressed direct and indirect effects among these attributes relative to airport executives' career satisfaction was tested using sample data collected from 708 airport executives from general aviation and commercial service airport throughout the United States. Applying a multiple regression analysis strategy to the model, the overall results revealed that 16% of the variability in airport executives' career satisfaction scores was due to the collective influence of the six research attribute sets, this was significant. The results of the path analysis also indicated that four attribute sets (early aviation interests, health factors, formal education, and other aviation-related experiences) had respective direct significant effects on participants' career satisfaction. Early aviation interests, health factors, and demographic factors had additional indirect effects on career satisfaction; all were mediated by formal education attitude. These results were inconsistent with the hypothesized path model and a revised model was developed to reflect the sample data. The findings suggest that airport executives, as a group, are satisfied with their career choice. Early aviation interests appear to play an important role for influencing the career field selection phase of career development. The study also suggests health factors, formal education, and other aviation-related experiences such as flight training or military experience influence the compromise phase of career development. Each of these four factors had significant effects on career satisfaction. In addition to its applicability to airport executives, the study provides a generalized path model for investigating factors influencing the career development, compromise, and satisfaction process in other vocations.

Could Plasmodium vivax malaria trigger malnutrition? Revisiting the Bradford Hill criteria to assess a causal relationship between two neglected problems.

PubMed

Monteiro, Wuelton Marcelo; Alexandre, Márcia Araújo; Siqueira, André; Melo, Gisely; Romero, Gustavo Adolfo Sierra; d'Ávila, Efrem; Benzecry, Silvana Gomes; Leite, Heitor Pons; Lacerda, Marcus Vinícius Guimarães

2016-01-01

The benign characteristics formerly attributed to Plasmodium vivax infections have recently changed owing to the increasing number of reports of severe vivax malaria resulting in a broad spectrum of clinical complications, probably including undernutrition. Causal inference is a complex process, and arriving at a tentative inference of the causal or non-causal nature of an association is a subjective process limited by the existing evidence. Applying classical epidemiology principles, such as the Bradford Hill criteria, may help foster an understanding of causality and lead to appropriate interventions being proposed that may improve quality of life and decrease morbidity in neglected populations. Here, we examined these criteria in the context of the available data suggesting that vivax malaria may substantially contribute to childhood malnutrition. We found the data supported a role for P. vivax in the etiology of undernutrition in endemic areas. Thus, the application of modern causal inference tools, in future studies, may be useful in determining causation.

Associations between Potentially Modifiable Risk Factors and Alzheimer Disease: A Mendelian Randomization Study.

PubMed

Østergaard, Søren D; Mukherjee, Shubhabrata; Sharp, Stephen J; Proitsi, Petroula; Lotta, Luca A; Day, Felix; Perry, John R B; Boehme, Kevin L; Walter, Stefan; Kauwe, John S; Gibbons, Laura E; Larson, Eric B; Powell, John F; Langenberg, Claudia; Crane, Paul K; Wareham, Nicholas J; Scott, Robert A

2015-06-01

Potentially modifiable risk factors including obesity, diabetes, hypertension, and smoking are associated with Alzheimer disease (AD) and represent promising targets for intervention. However, the causality of these associations is unclear. We sought to assess the causal nature of these associations using Mendelian randomization (MR). We used SNPs associated with each risk factor as instrumental variables in MR analyses. We considered type 2 diabetes (T2D, NSNPs = 49), fasting glucose (NSNPs = 36), insulin resistance (NSNPs = 10), body mass index (BMI, NSNPs = 32), total cholesterol (NSNPs = 73), HDL-cholesterol (NSNPs = 71), LDL-cholesterol (NSNPs = 57), triglycerides (NSNPs = 39), systolic blood pressure (SBP, NSNPs = 24), smoking initiation (NSNPs = 1), smoking quantity (NSNPs = 3), university completion (NSNPs = 2), and years of education (NSNPs = 1). We calculated MR estimates of associations between each exposure and AD risk using an inverse-variance weighted approach, with summary statistics of SNP-AD associations from the International Genomics of Alzheimer's Project, comprising a total of 17,008 individuals with AD and 37,154 cognitively normal elderly controls. We found that genetically predicted higher SBP was associated with lower AD risk (odds ratio [OR] per standard deviation [15.4 mm Hg] of SBP [95% CI]: 0.75 [0.62-0.91]; p = 3.4 × 10(-3)). Genetically predicted higher SBP was also associated with a higher probability of taking antihypertensive medication (p = 6.7 × 10(-8)). Genetically predicted smoking quantity was associated with lower AD risk (OR per ten cigarettes per day [95% CI]: 0.67 [0.51-0.89]; p = 6.5 × 10(-3)), although we were unable to stratify by smoking history; genetically predicted smoking initiation was not associated with AD risk (OR = 0.70 [0.37, 1.33]; p = 0.28). We saw no evidence of causal associations between glycemic traits, T2D, BMI, or educational attainment and risk of AD (all p > 0.1). Potential limitations of this study include the small proportion of intermediate trait variance explained by genetic variants and other implicit limitations of MR analyses. Inherited lifetime exposure to higher SBP is associated with lower AD risk. These findings suggest that higher blood pressure--or some environmental exposure associated with higher blood pressure, such as use of antihypertensive medications--may reduce AD risk.

Investigating genetic correlations and causal effects between caffeine consumption and sleep behaviours.

PubMed

Treur, Jorien L; Gibson, Mark; Taylor, Amy E; Rogers, Peter J; Munafò, Marcus R

2018-04-22

Observationally, higher caffeine consumption is associated with poorer sleep and insomnia. We investigated whether these associations are a result of shared genetic risk factors and/or (possibly bidirectional) causal effects. Summary-level data were available from genome-wide association studies on caffeine intake (n = 91 462), plasma caffeine and caffeine metabolic rate (n = 9876), sleep duration and chronotype (being a "morning" versus an "evening" person) (n = 128 266), and insomnia complaints (n = 113 006). First, genetic correlations were calculated, reflecting the extent to which genetic variants influencing caffeine consumption and those influencing sleep overlap. Next, causal effects were estimated with bidirectional, two-sample Mendelian randomization. This approach utilizes the genetic variants most robustly associated with an exposure variable as an "instrument" to test causal effects. Estimates from individual variants were combined using inverse-variance weighted meta-analysis, weighted median regression and MR-Egger regression. We found no clear evidence for a genetic correlation between caffeine intake and sleep duration (rg = 0.000, p = .998), chronotype (rg = 0.086, p = .192) or insomnia complaints (rg = -0.034, p = .700). For plasma caffeine and caffeine metabolic rate, genetic correlations could not be calculated because of the small sample size. Mendelian randomization did not support causal effects of caffeine intake on sleep, or vice versa. There was weak evidence that higher plasma caffeine levels causally decrease the odds of being a morning person. Although caffeine may acutely affect sleep when taken shortly before bedtime, our findings suggest that a sustained pattern of high caffeine consumption is more likely to be associated with poorer sleep through shared environmental factors. Future research should identify such environments, which could aid the development of interventions to improve sleep. © 2018 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.

Unified framework for information integration based on information geometry

PubMed Central

Oizumi, Masafumi; Amari, Shun-ichi

2016-01-01

Assessment of causal influences is a ubiquitous and important subject across diverse research fields. Drawn from consciousness studies, integrated information is a measure that defines integration as the degree of causal influences among elements. Whereas pairwise causal influences between elements can be quantified with existing methods, quantifying multiple influences among many elements poses two major mathematical difficulties. First, overestimation occurs due to interdependence among influences if each influence is separately quantified in a part-based manner and then simply summed over. Second, it is difficult to isolate causal influences while avoiding noncausal confounding influences. To resolve these difficulties, we propose a theoretical framework based on information geometry for the quantification of multiple causal influences with a holistic approach. We derive a measure of integrated information, which is geometrically interpreted as the divergence between the actual probability distribution of a system and an approximated probability distribution where causal influences among elements are statistically disconnected. This framework provides intuitive geometric interpretations harmonizing various information theoretic measures in a unified manner, including mutual information, transfer entropy, stochastic interaction, and integrated information, each of which is characterized by how causal influences are disconnected. In addition to the mathematical assessment of consciousness, our framework should help to analyze causal relationships in complex systems in a complete and hierarchical manner. PMID:27930289

Adapting to an Uncertain World: Cognitive Capacity and Causal Reasoning with Ambiguous Observations

PubMed Central

Shou, Yiyun; Smithson, Michael

2015-01-01

Ambiguous causal evidence in which the covariance of the cause and effect is partially known is pervasive in real life situations. Little is known about how people reason about causal associations with ambiguous information and the underlying cognitive mechanisms. This paper presents three experiments exploring the cognitive mechanisms of causal reasoning with ambiguous observations. Results revealed that the influence of ambiguous observations manifested by missing information on causal reasoning depended on the availability of cognitive resources, suggesting that processing ambiguous information may involve deliberative cognitive processes. Experiment 1 demonstrated that subjects did not ignore the ambiguous observations in causal reasoning. They also had a general tendency to treat the ambiguous observations as negative evidence against the causal association. Experiment 2 and Experiment 3 included a causal learning task requiring a high cognitive demand in which paired stimuli were presented to subjects sequentially. Both experiments revealed that processing ambiguous or missing observations can depend on the availability of cognitive resources. Experiment 2 suggested that the contribution of working memory capacity to the comprehensiveness of evidence retention was reduced when there were ambiguous or missing observations. Experiment 3 demonstrated that an increase in cognitive demand due to a change in the task format reduced subjects’ tendency to treat ambiguous-missing observations as negative cues. PMID:26468653

Spot the difference: Causal contrasts in scientific diagrams.

PubMed

Scholl, Raphael

2016-12-01

An important function of scientific diagrams is to identify causal relationships. This commonly relies on contrasts that highlight the effects of specific difference-makers. However, causal contrast diagrams are not an obvious and easy to recognize category because they appear in many guises. In this paper, four case studies are presented to examine how causal contrast diagrams appear in a wide range of scientific reports, from experimental to observational and even purely theoretical studies. It is shown that causal contrasts can be expressed in starkly different formats, including photographs of complexly visualized macromolecules as well as line graphs, bar graphs, or plots of state spaces. Despite surface differences, however, there is a measure of conceptual unity among such diagrams. In empirical studies they often serve not only to infer and communicate specific causal claims, but also as evidence for them. The key data of some studies is given nowhere except in the diagrams. Many diagrams show multiple causal contrasts in order to demonstrate both that an effect exists and that the effect is specific - that is, to narrowly circumscribe the phenomenon to be explained. In a large range of scientific reports, causal contrast diagrams reflect the core epistemic claims of the researchers. Copyright © 2016. Published by Elsevier Ltd.

An Explanation of the Distinction between Developmental Factors and Mechanisms

ERIC Educational Resources Information Center

Laski, Elida V.

2017-01-01

This paper provides five clear, relatable examples that can help students understand the distinction between the term "factors" and "mechanisms" in Developmental Psychology. The examples emphasize the idea that factors are related to changes in ways that moderate development, but are not causal. On the other hand, the term…

Applying Medical Anthropology: Developing Diabetes Education and Prevention Programs in American Indian Cultures.

ERIC Educational Resources Information Center

Olson, Brooke

1999-01-01

Medical anthropology provides a broader contextual framework for understanding complex causal factors associated with diabetes among American Indians and how to minimize these factors in education/treatment programs. Discusses historical, epidemiological, and genetic considerations in American Indian diabetes; cultural factors related to foods,…

Maternal BMI at the start of pregnancy and offspring epigenome-wide DNA methylation: findings from the pregnancy and childhood epigenetics (PACE) consortium

PubMed Central

Sharp, Gemma C.; Salas, Lucas A.; Monnereau, Claire; Allard, Catherine; Yousefi, Paul; Everson, Todd M.; Bohlin, Jon; Xu, Zongli; Huang, Rae-Chi; Reese, Sarah E.; Xu, Cheng-Jian; Baïz, Nour; Hoyo, Cathrine; Agha, Golareh; Roy, Ritu; Holloway, John W.; Ghantous, Akram; Merid, Simon K.; Bakulski, Kelly M.; Küpers, Leanne K.; Zhang, Hongmei; Richmond, Rebecca C.; Page, Christian M.; Duijts, Liesbeth; Lie, Rolv T.; Melton, Phillip E.; Vonk, Judith M.; Nohr, Ellen A.; Williams-DeVane, ClarLynda; Huen, Karen; Rifas-Shiman, Sheryl L.; Ruiz-Arenas, Carlos; Gonseth, Semira; Rezwan, Faisal I.; Herceg, Zdenko; Ekström, Sandra; Croen, Lisa; Falahi, Fahimeh; Perron, Patrice; Karagas, Margaret R.; Quraishi, Bilal M.; Suderman, Matthew; Magnus, Maria C.; Jaddoe, Vincent W.V.; Taylor, Jack A.; Anderson, Denise; Zhao, Shanshan; Smit, Henriette A.; Josey, Michele J.; Bradman, Asa; Baccarelli, Andrea A.; Bustamante, Mariona; Håberg, Siri E.; Pershagen, Göran; Hertz-Picciotto, Irva; Newschaffer, Craig; Corpeleijn, Eva; Bouchard, Luigi; Lawlor, Debbie A.; Maguire, Rachel L.; Barcellos, Lisa F.; Smith, George Davey; Eskenazi, Brenda; Karmaus, Wilfried; Marsit, Carmen J.; Hivert, Marie-France; Snieder, Harold; Fallin, M. Daniele; Melén, Erik; Munthe-Kaas, Monica C.; Arshad, Hasan; Wiemels, Joseph L.; Annesi-Maesano, Isabella; Vrijheid, Martine; Oken, Emily; Holland, Nina; Murphy, Susan K.; Sørensen, Thorkild I.A.; Koppelman, Gerard H.; Newnham, John P.; Wilcox, Allen J.; Nystad, Wenche; London, Stephanie J.; Felix, Janine F.; Relton, Caroline L.

2017-01-01

Pre-pregnancy maternal obesity is associated with adverse offspring outcomes at birth and later in life. Individual studies have shown that epigenetic modifications such as DNA methylation could contribute. Within the Pregnancy and Childhood Epigenetics (PACE) Consortium, we meta-analysed the association between pre-pregnancy maternal BMI and methylation at over 450,000 sites in newborn blood DNA, across 19 cohorts (9,340 mother-newborn pairs). We attempted to infer causality by comparing the effects of maternal versus paternal BMI and incorporating genetic variation. In four additional cohorts (1,817 mother-child pairs), we meta-analysed the association between maternal BMI at the start of pregnancy and blood methylation in adolescents. In newborns, maternal BMI was associated with small (<0.2% per BMI unit (1 kg/m2), P < 1.06 × 10−7) methylation variation at 9,044 sites throughout the genome. Adjustment for estimated cell proportions greatly attenuated the number of significant CpGs to 104, including 86 sites common to the unadjusted model. At 72/86 sites, the direction of the association was the same in newborns and adolescents, suggesting persistence of signals. However, we found evidence for a6causal intrauterine effect of maternal BMI on newborn methylation at just 8/86 sites. In conclusion, this well-powered analysis identified robust associations between maternal adiposity and variations in newborn blood DNA methylation, but these small effects may be better explained by genetic or lifestyle factors than a causal intrauterine mechanism. This highlights the need for large-scale collaborative approaches and the application of causal inference techniques in epigenetic epidemiology. PMID:29016858

Aspects of Synthetic Vision Display Systems and the Best Practices of the NASA's SVS Project

NASA Technical Reports Server (NTRS)

Bailey, Randall E.; Kramer, Lynda J.; Jones, Denise R.; Young, Steven D.; Arthur, Jarvis J.; Prinzel, Lawrence J.; Glaab, Louis J.; Harrah, Steven D.; Parrish, Russell V.

2008-01-01

NASA s Synthetic Vision Systems (SVS) Project conducted research aimed at eliminating visibility-induced errors and low visibility conditions as causal factors in civil aircraft accidents while enabling the operational benefits of clear day flight operations regardless of actual outside visibility. SVS takes advantage of many enabling technologies to achieve this capability including, for example, the Global Positioning System (GPS), data links, radar, imaging sensors, geospatial databases, advanced display media and three dimensional video graphics processors. Integration of these technologies to achieve the SVS concept provides pilots with high-integrity information that improves situational awareness with respect to terrain, obstacles, traffic, and flight path. This paper attempts to emphasize the system aspects of SVS - true systems, rather than just terrain on a flight display - and to document from an historical viewpoint many of the best practices that evolved during the SVS Project from the perspective of some of the NASA researchers most heavily involved in its execution. The Integrated SVS Concepts are envisagements of what production-grade Synthetic Vision systems might, or perhaps should, be in order to provide the desired functional capabilities that eliminate low visibility as a causal factor to accidents and enable clear-day operational benefits regardless of visibility conditions.

An alternative medicine, Agaricus blazei, may have induced severe hepatic dysfunction in cancer patients.

PubMed

Mukai, Hirofumi; Watanabe, Toru; Ando, Masashi; Katsumata, Noriyuki

2006-12-01

We report three cases of patients with advanced cancer who showed severe hepatic damage, and two of whom died of fulminant hepatitis. All the patients were taking Agaricus blazei (Himematsutake) extract, one of the most popular complementary and alternative medicines among Japanese cancer patients. In one patient, liver functions recovered gradually after she stopped taking the Agaricus blazei, but she restarted taking it, which resulted in deterioration of the liver function again. The other patients who were admitted for severe liver damage had started taking the Agaricus blazei several days before admission. Although several other factors cannot be completely ruled out as the causes of liver damage, a strong causal relationship between the Agaricus blazei extract and liver damage was suggested and, at least, taking the Agaricus blazei extract made the clinical decision-making process much more complicated. Doctors who are aware of their patients taking the extract may accept it probably because they believe there is no harm in a complementary and alternative medicine. When unexpected liver damage is documented, however, doctors should consider the use of the Agaricus blazei extract as one of its causal factors. It is necessary to evaluate many modes of complementary and alternative medicines, including the Agaricus blazei extract, in rigorous, scientifically designed and peer-reviewed clinical trials.

Synthetic Vision Enhanced Surface Operations and Flight Procedures Rehearsal Tool

NASA Technical Reports Server (NTRS)

Arthur, Jarvis J., III; Prinzel, Lawrence J., III; Williams, Steven P.; Kramer, Lynda J.

2006-01-01

Limited visibility has been cited as predominant causal factor for both Controlled-Flight-Into-Terrain (CFIT) and runway incursion accidents. NASA is conducting research and development of Synthetic Vision Systems (SVS) technologies which may potentially mitigate low visibility conditions as a causal factor to these accidents while replicating the operational benefits of clear day flight operations, regardless of the actual outside visibility condition. Two experimental evaluation studies were performed to determine the efficacy of two concepts: 1) head-worn display application of SVS technology to enhance transport aircraft surface operations, and 2) three-dimensional SVS electronic flight bag display concept for flight plan preview, mission rehearsal and controller-pilot data link communications interface of flight procedures. In the surface operation study, pilots evaluated two display devices and four display modes during taxi under unlimited and CAT II visibility conditions. In the mission rehearsal study, pilots flew approaches and departures in an operationally-challenged airport environment, including CFIT scenarios. Performance using the SVS concepts was compared to traditional baseline displays with paper charts only or EFB information. In general, the studies evince the significant situation awareness and enhanced operational capabilities afforded from these advanced SVS display concepts. The experimental results and conclusions from these studies are discussed along with future directions.

Frequency distribution of causal connectivity in rat sensorimotor network: resting-state fMRI analyses.

PubMed

Shim, Woo H; Baek, Kwangyeol; Kim, Jeong Kon; Chae, Yongwook; Suh, Ji-Yeon; Rosen, Bruce R; Jeong, Jaeseung; Kim, Young R

2013-01-01

Resting-state functional MRI (fMRI) has emerged as an important method for assessing neural networks, enabling extensive connectivity analyses between multiple brain regions. Among the analysis techniques proposed, partial directed coherence (PDC) provides a promising tool to unveil causal connectivity networks in the frequency domain. Using the MRI time series obtained from the rat sensorimotor system, we applied PDC analysis to determine the frequency-dependent causality networks. In particular, we compared in vivo and postmortem conditions to establish the statistical significance of directional PDC values. Our results demonstrate that two distinctive frequency populations drive the causality networks in rat; significant, high-frequency causal connections clustered in the range of 0.2-0.4 Hz, and the frequently documented low-frequency connections <0.15 Hz. Frequency-dependence and directionality of the causal connection are characteristic between sensorimotor regions, implying the functional role of frequency bands to transport specific resting-state signals. In particular, whereas both intra- and interhemispheric causal connections between heterologous sensorimotor regions are robust over all frequency levels, the bilaterally homologous regions are interhemispherically linked mostly via low-frequency components. We also discovered a significant, frequency-independent, unidirectional connection from motor cortex to thalamus, indicating dominant cortical inputs to the thalamus in the absence of external stimuli. Additionally, to address factors underlying the measurement error, we performed signal simulations and revealed that the interactive MRI system noise alone is a likely source of the inaccurate PDC values. This work demonstrates technical basis for the PDC analysis of resting-state fMRI time series and the presence of frequency-dependent causality networks in the sensorimotor system.

Causal attributions in parents of babies with a cleft lip and/or palate and their association with psychological well-being.

PubMed

Nelson, Jonathan; O'Leary, Catherine; Weinman, John

2009-07-01

This study aimed to assess causal attributions of parents of babies with a cleft lip and/or palate. Evidence from causal attribution theory and attribution studies in other medical conditions led to the hypothesis that parents who make internal attributions (self-blame) will have poorer psychological well-being. A cross-sectional survey. Postal questionnaires were sent to parents of children under the care of the South Thames Cleft Service at Guy's Hospital. PARTICIPANTS were recruited if they had a baby between 12 and 24 months old with a cleft lip and/or palate. Of 204 parents, 42 responded. A semistructured questionnaire about causal beliefs was completed alongside validated questionnaires measuring anxiety, depression (Hospital Anxiety and Depression Scale), and perceived stress (Perceived Stress Scale). Causal attributions were grouped according to type (environmental, chance, self-blame, and no belief) and loci (external or internal). The most common attribution made was to external factors (54.4%), followed by no causal attribution (38.1%). Parents making an internal (self-blaming) attribution (16.7%) had significantly (p < .05) higher scores on the Hospital Anxiety and Depression Scale anxiety measure (r = .32) and Perceived Stress Scale (r = .33), but not on the Hospital Anxiety and Depression Scale depression measure (p = .283). The high number of parents making an external attribution can be explained by causal attribution theory. However, the percentage of parents making no causal attribution was higher than seen in previous research. Surprisingly, no parents blamed others. The main hypothesis was tentatively accepted because there were significantly higher anxiety and stress scores in parents who self-blamed; although, depression scores were not significantly higher.

Leveraging lung tissue transcriptome to uncover candidate causal genes in COPD genetic associations.

PubMed

Lamontagne, Maxime; Bérubé, Jean-Christophe; Obeidat, Ma'en; Cho, Michael H; Hobbs, Brian D; Sakornsakolpat, Phuwanat; de Jong, Kim; Boezen, H Marike; Nickle, David; Hao, Ke; Timens, Wim; van den Berge, Maarten; Joubert, Philippe; Laviolette, Michel; Sin, Don D; Paré, Peter D; Bossé, Yohan

2018-05-15

Causal genes of chronic obstructive pulmonary disease (COPD) remain elusive. The current study aims at integrating genome-wide association studies (GWAS) and lung expression quantitative trait loci (eQTL) data to map COPD candidate causal genes and gain biological insights into the recently discovered COPD susceptibility loci. Two complementary genomic datasets on COPD were studied. First, the lung eQTL dataset which included whole-genome gene expression and genotyping data from 1038 individuals. Second, the largest COPD GWAS to date from the International COPD Genetics Consortium (ICGC) with 13 710 cases and 38 062 controls. Methods that integrated GWAS with eQTL signals including transcriptome-wide association study (TWAS), colocalization and Mendelian randomization-based (SMR) approaches were used to map causality genes, i.e. genes with the strongest evidence of being the functional effector at specific loci. These methods were applied at the genome-wide level and at COPD risk loci derived from the GWAS literature. Replication was performed using lung data from GTEx. We collated 129 non-overlapping risk loci for COPD from the GWAS literature. At the genome-wide scale, 12 new COPD candidate genes/loci were revealed and six replicated in GTEx including CAMK2A, DMPK, MYO15A, TNFRSF10A, BTN3A2 and TRBV30. In addition, we mapped candidate causal genes for 60 out of the 129 GWAS-nominated loci and 23 of them were replicated in GTEx. Mapping candidate causal genes in lung tissue represents an important contribution to the genetics of COPD, enriches our biological interpretation of GWAS findings, and brings us closer to clinical translation of genetic associations.

Interaction Between Allergy and Middle Ear Infection.

PubMed

Oh, Jeong-Hoon; Kim, Woo Jin

2016-09-01

Recent studies have attempted to identify interactions among the causes of otitis media with effusion (OME). This review discusses the interaction between allergy and infection with regard to host and environmental factors in terms of the development of OME. Protection of the upper airway against microbial invasion requires active interaction between the defense mechanisms of the respiratory epithelium, including innate and adaptive immunity, and mechanical factors. The impairment of these defenses due to allergy and/or increased bacterial resistance may lead to increased susceptibility to infectious organisms in the respiratory tract and middle ear mucosa. Recent genetic studies have provided valuable information about the association of Toll-like receptor signaling variations with clinical phenotypes and the risk of infection in the middle ear. Among the causal factors of OME, allergy not only induces an inflammatory reaction in the middle ear cavity but also facilitates the invasion of infectious pathogens. There is also evidence that allergy can affect the susceptibility of patients to infection of the upper respiratory tract, including the middle ear cavity.

Genomic selection in domestic animals: Principles, applications and perspectives.

PubMed

Boichard, Didier; Ducrocq, Vincent; Croiseau, Pascal; Fritz, Sébastien

2016-01-01

The principles of genomic selection are described, with the main factors affecting its efficiency and the assumptions underlying the different models proposed. The reasons of its fast adoption in dairy cattle are explained and the conditions of its application to other species are discussed. Perspectives of development include: selection for new traits and new breeding objectives; adoption of more robust approaches based on information on causal variants; predictions of genotype×environment interactions. Copyright © 2016 Académie des sciences. Published by Elsevier SAS. All rights reserved.

CONCEPT ANALYSIS: AGGRESSION

PubMed Central

Liu, Jianghong

2006-01-01

The concept of aggression is important to nursing because further knowledge of aggression can help generate a better theoretical model to drive more effective intervention and prevention approaches. This paper outlines a conceptual analysis of aggression. First, the different forms of aggression are reviewed, including the clinical classification and the stimulus-based classification. Then the manifestations and measurement of aggression are described. Finally, the causes and consequences of aggression are outlined. It is argued that a better understanding of aggression and the causal factors underlying it are essential for learning how to prevent negative aggression in the future. PMID:15371137

Causal hydrodynamics of gauge theory plasmas from AdS/CFT duality

DOE Office of Scientific and Technical Information (OSTI.GOV)

Natsuume, Makoto; Okamura, Takashi; Department of Physics, Kwansei Gakuin University, Sanda, Hyogo, 669-1337

2008-03-15

We study causal hydrodynamics (Israel-Stewart theory) of gauge theory plasmas from the AdS/CFT duality. Causal hydrodynamics requires new transport coefficients (relaxation times) and we compute them for a number of supersymmetric gauge theories including the N=4 super Yang-Mills theory. However, the relaxation times obtained from the 'shear mode' do not agree with the ones from the 'sound mode', which implies that the Israel-Stewart theory is not a sufficient framework to describe the gauge theory plasmas.

Wormholes, baby universes, and causality

NASA Astrophysics Data System (ADS)

Visser, Matt

1990-02-01

In this paper wormholes defined on a Minkowski signature manifold are considered, both at the classical and quantum levels. It is argued that causality in quantum gravity may best be imposed by restricting the functional integral to include only causal Lorentzian spacetimes. Subject to this assumption, one can put very tight constraints on the quantum behavior of wormholes, their cousins the baby universes, and topology-changing processes in general. Even though topology-changing processes are tightly constrained, this still allows very interesting geometrical (rather than topological) effects. In particular, the laboratory construction of baby universes is not prohibited provided that the ``umbilical cord'' is never cut. Methods for relaxing these causality constraints are also discussed.

Risk Factors for Neck and Upper Extremity Disorders among Computers Users and the Effect of Interventions: An Overview of Systematic Reviews

PubMed Central

Andersen, Johan H.; Fallentin, Nils; Thomsen, Jane F.; Mikkelsen, Sigurd

2011-01-01

Background To summarize systematic reviews that 1) assessed the evidence for causal relationships between computer work and the occurrence of carpal tunnel syndrome (CTS) or upper extremity musculoskeletal disorders (UEMSDs), or 2) reported on intervention studies among computer users/or office workers. Methodology/Principal Findings PubMed, Embase, CINAHL and Web of Science were searched for reviews published between 1999 and 2010. Additional publications were provided by content area experts. The primary author extracted all data using a purpose-built form, while two of the authors evaluated the quality of the reviews using recommended standard criteria from AMSTAR; disagreements were resolved by discussion. The quality of evidence syntheses in the included reviews was assessed qualitatively for each outcome and for the interventions. Altogether, 1,349 review titles were identified, 47 reviews were retrieved for full text relevance assessment, and 17 reviews were finally included as being relevant and of sufficient quality. The degrees of focus and rigorousness of these 17 reviews were highly variable. Three reviews on risk factors for carpal tunnel syndrome were rated moderate to high quality, 8 reviews on risk factors for UEMSDs ranged from low to moderate/high quality, and 6 reviews on intervention studies were of moderate to high quality. The quality of the evidence for computer use as a risk factor for CTS was insufficient, while the evidence for computer use and UEMSDs was moderate regarding pain complaints and limited for specific musculoskeletal disorders. From the reviews on intervention studies no strong evidence based recommendations could be given. Conclusions/Significance Computer use is associated with pain complaints, but it is still not very clear if this association is causal. The evidence for specific disorders or diseases is limited. No effective interventions have yet been documented. PMID:21589875

Prenatal, Perinatal, and Neonatal Risk Factors for Specific Language Impairment: A Prospective Pregnancy Cohort Study

ERIC Educational Resources Information Center

Whitehouse, Andrew J. O.; Shelton, W. M. R.; Ing, Caleb; Newnham, John P.

2014-01-01

Purpose: Although genetic factors are known to play a causal role in specific language impairment (SLI), environmental factors may also be important. This study examined whether there are prenatal, perinatal, and neonatal factors that are associated with childhood SLI. Method: Participants were members of the Raine Study, a prospective cohort…

Imputation of adverse drug reactions: Causality assessment in hospitals

PubMed Central

Mastroianni, Patricia de Carvalho

2017-01-01

Background & objectives Different algorithms have been developed to standardize the causality assessment of adverse drug reactions (ADR). Although most share common characteristics, the results of the causality assessment are variable depending on the algorithm used. Therefore, using 10 different algorithms, the study aimed to compare inter-rater and multi-rater agreement for ADR causality assessment and identify the most consistent to hospitals. Methods Using ten causality algorithms, four judges independently assessed the first 44 cases of ADRs reported during the first year of implementation of a risk management service in a medium complexity hospital in the state of Sao Paulo (Brazil). Owing to variations in the terminology used for causality, the equivalent imputation terms were grouped into four categories: definite, probable, possible and unlikely. Inter-rater and multi-rater agreement analysis was performed by calculating the Cohen´s and Light´s kappa coefficients, respectively. Results None of the algorithms showed 100% reproducibility in the causal imputation. Fair inter-rater and multi-rater agreement was found. Emanuele (1984) and WHO-UMC (2010) algorithms showed a fair rate of agreement between the judges (k = 0.36). Interpretation & conclusions Although the ADR causality assessment algorithms were poorly reproducible, our data suggest that WHO-UMC algorithm is the most consistent for imputation in hospitals, since it allows evaluating the quality of the report. However, to improve the ability of assessing the causality using algorithms, it is necessary to include criteria for the evaluation of drug-related problems, which may be related to confounding variables that underestimate the causal association. PMID:28166274

Anxiety Disorders and Sensory Over-Responsivity in Children with Autism Spectrum Disorders: Is There a Causal Relationship?

PubMed Central

Ben-Sasson, Ayelet

2010-01-01

Anxiety disorders and sensory over-responsivity (SOR) are common in children with autism spectrum disorders (ASD), and there is evidence for an association between these two conditions. Currently, it is unclear what causal mechanisms may exist between SOR and anxiety. We propose three possible theories to explain the association between anxiety and SOR: (a) SOR is caused by anxiety; (b) Anxiety is caused by SOR; or (c) SOR and anxiety are causally unrelated but are associated through a common risk factor or diagnostic overlap. In this paper, we examine support for each theory in the existing anxiety, autism, and neuroscience literature, and discuss how each theory informs choice of interventions and implications for future studies. PMID:20383658

Attributional "Tunnel Vision" in Patients With Borderline Personality Disorder.

PubMed

Schilling, Lisa; Moritz, Steffen; Schneider, Brooke; Bierbrodt, Julia; Nagel, Matthias

2015-12-01

We aimed to examine the profile of interpersonal attributions in BPD. We hypothesized that patients show more mono-causal and internal attributions than healthy controls. A revised version of the Internal, Personal, Situational and Attributions Questionnaire was assessed in 30 BPD patients and 30 healthy controls. BPD patients and controls differed significantly in their attributional pattern. Patients displayed more mono-causal inferences, that is, they had difficulties considering alternative explanatory factors. For negative events, patients made more internal attributions compared to healthy controls. We concluded that mono-causal "trapped" thinking might contribute to (interpersonal) problems in BPD patients by fostering impulsive consequential behaviors, for example, harming one's self or others. A self-blaming tendency likely promotes depressive symptoms and low self-esteem.

Two heads are better than one, but how much? Evidence that people's use of causal integration rules does not always conform to normative standards.

PubMed

Vadillo, Miguel A; Ortega-Castro, Nerea; Barberia, Itxaso; Baker, A G

2014-01-01

Many theories of causal learning and causal induction differ in their assumptions about how people combine the causal impact of several causes presented in compound. Some theories propose that when several causes are present, their joint causal impact is equal to the linear sum of the individual impact of each cause. However, some recent theories propose that the causal impact of several causes needs to be combined by means of a noisy-OR integration rule. In other words, the probability of the effect given several causes would be equal to the sum of the probability of the effect given each cause in isolation minus the overlap between those probabilities. In the present series of experiments, participants were given information about the causal impact of several causes and then they were asked what compounds of those causes they would prefer to use if they wanted to produce the effect. The results of these experiments suggest that participants actually use a variety of strategies, including not only the linear and the noisy-OR integration rules, but also averaging the impact of several causes.

Causal-explanatory pluralism: How intentions, functions, and mechanisms influence causal ascriptions.

PubMed

Lombrozo, Tania

2010-12-01

Both philosophers and psychologists have argued for the existence of distinct kinds of explanations, including teleological explanations that cite functions or goals, and mechanistic explanations that cite causal mechanisms. Theories of causation, in contrast, have generally been unitary, with dominant theories focusing either on counterfactual dependence or on physical connections. This paper argues that both approaches to causation are psychologically real, with different modes of explanation promoting judgments more or less consistent with each approach. Two sets of experiments isolate the contributions of counterfactual dependence and physical connections in causal ascriptions involving events with people, artifacts, or biological traits, and manipulate whether the events are construed teleologically or mechanistically. The findings suggest that when events are construed teleologically, causal ascriptions are sensitive to counterfactual dependence and relatively insensitive to the presence of physical connections, but when events are construed mechanistically, causal ascriptions are sensitive to both counterfactual dependence and physical connections. The conclusion introduces an account of causation, an "exportable dependence theory," that provides a way to understand the contributions of physical connections and teleology in terms of the functions of causal ascriptions. Copyright © 2010 Elsevier Inc. All rights reserved.

"It Can Bust at Any Seam": Lessons for Deep Space Flight from Mawson's 1911-1914 Australasian Antarctic Expedition

NASA Astrophysics Data System (ADS)

Wallace, Phillip Scott

2010-09-01

Lessons useful for manned space flight can be gained by looking at exploring expeditions of the past. An aviation-accident style investigation was conducted on two fatalities that occurred on an Antarctic expedition in 1912-13. The causal factors of the accidents were determined; and lessons for future missions beyond LEO gleaned from both the causal factors and from looking at the expedition as a whole. The investigation highlighted, among other things, that probabilistic hazards can eventually take a life and that factors of terrain can and will damage equipment and kill men; that consumables should be segregated such that one mishap does not reduce margins to below those needed for survival, and that manned missions need to be able to jury-rig equipment in the field.

Searching for the Final Answer: Factors Contributing to Medication Administration Errors.

ERIC Educational Resources Information Center

Pape, Tess M.

2001-01-01

Causal factors contributing to errors in medication administration should be thoroughly investigated, focusing on systems rather than individual nurses. Unless systemic causes are addressed, many errors will go unreported for fear of reprisal. (Contains 42 references.) (SK)

Development of a methodology for accident causation research

DOT National Transportation Integrated Search

1983-06-01

The obj ective of this study was to fully develop and apply a me thodology to : study accident causation, uhich was outlined in a previous study . " Causal" factors : are those pre-crash factors, which are statistically related to the accident rate :...

Summary of 1968-1970 multidisciplinary accident investigation reports. Volume 2

DOT National Transportation Integrated Search

1972-08-01

In June 1971, Volume 1 of a two-volume series summarizing the causal factors, conclusions and recommendations which emanated from various in-depth accident reports was published. This first volume contained a listing of these factors according to tea...

Belief beyond the evidence: using the proposed effect of breakfast on obesity to show 2 practices that distort scientific evidence1234

PubMed Central

Brown, Andrew W; Bohan Brown, Michelle M

2013-01-01

Background: Various intentional and unintentional factors influence beliefs beyond what scientific evidence justifies. Two such factors are research lacking probative value (RLPV) and biased research reporting (BRR). Objective: We investigated the prevalence of RLPV and BRR in research about the proposition that skipping breakfast causes weight gain, which is called the proposed effect of breakfast on obesity (PEBO) in this article. Design: Studies related to the PEBO were synthesized by using a cumulative meta-analysis. Abstracts from these studies were also rated for the improper use of causal language and biased interpretations. In separate analyses, articles that cited an observational study about the PEBO were rated for the inappropriate use of causal language, and articles that cited a randomized controlled trial (RCT) about the PEBO were rated for misleadingly citing the RCT. Results: The current body of scientific knowledge indicates that the PEBO is only presumed true. The observational literature on the PEBO has gratuitously established the association, but not the causal relation, between skipping breakfast and obesity (final cumulative meta-analysis P value <10−42), which is evidence of RLPV. Four examples of BRR are evident in the PEBO literature as follows: 1) biased interpretation of one's own results, 2) improper use of causal language in describing one's own results, 3) misleadingly citing others’ results, and 4) improper use of causal language in citing others’ work. Conclusions: The belief in the PEBO exceeds the strength of scientific evidence. The scientific record is distorted by RLPV and BRR. RLPV is a suboptimal use of collective scientific resources. PMID:24004890

No association between hyponatremia and rhabdomyolysis in rats.

PubMed

Peled, Michael; Dolkart, Oleg; Finn, Talya; Amar, Eyal; Zeltser, David

2014-10-01

Rhabdomyolysis is an uncommon complication of hyponatremia, reported previously only in case reports and small retrospective studies, and its underlying mechanism is controversial. Some studies support the hypothesis that the rapid correction of hyponatremia is responsible for rhabdomyolysis, whereas others emphasize the severity of the hyponatremia as a predisposing factor for rhabdomyolysis. To test the association between hyponatremia and rhabdomyolysis and to demonstrate a causal association. Hyponatremia was induced by administration of water and desmopressin acetate in rats during 3 days, followed by its rapid correction, using animal models established for the evaluation of central pontine myelinolysis. The plasma creatine phosphokinase levels, a marker for rhabdomyolysis, were monitored, and hematoxylin and eosin sections of the quadriceps and gastrocnemius muscles were evaluated for signs of rhabdomyolysis. The induction of hyponatremia and its correction were accompanied by the previously reported neurological sequelae, including signs of central pontine myelinolysis. However, no increase in plasma creatine phosphokinase levels was found, and histopathological examination of the quadriceps and gastrocnemius muscles revealed no sign of rhabdomyolysis. The present study, which is the first to test the association between hyponatremia and rhabdomyolysis in an animal model, does not support any causal association between hyponatremia and rhabdomyolysis. Thus, other factors might be necessary for an association between hyponatremia and rhabdomyolysis, such as genetic factors or convulsions that are known to be associated with both hyponatremia and rhabdomyolysis. Further research in this important physiologic and clinical question is needed. Copyright © 2014 Elsevier Inc. All rights reserved.

Self-organizing map analysis using multivariate data from theophylline powders predicted by a thin-plate spline interpolation.

PubMed

Yasuda, Akihito; Onuki, Yoshinori; Kikuchi, Shingo; Takayama, Kozo

2010-11-01

The quality by design concept in pharmaceutical formulation development requires establishment of a science-based rationale and a design space. We integrated thin-plate spline (TPS) interpolation and Kohonen's self-organizing map (SOM) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline powders were prepared based on the standard formulation. The angle of repose, compressibility, cohesion, and dispersibility were measured as the response variables. These responses were predicted quantitatively on the basis of a nonlinear TPS. A large amount of data on these powders was generated and classified into several clusters using an SOM. The experimental values of the responses were predicted with high accuracy, and the data generated for the powders could be classified into several distinctive clusters. The SOM feature map allowed us to analyze the global and local correlations between causal factors and powder characteristics. For instance, the quantities of microcrystalline cellulose (MCC) and magnesium stearate (Mg-St) were classified distinctly into each cluster, indicating that the quantities of MCC and Mg-St were crucial for determining the powder characteristics. This technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline powder formulations. © 2010 Wiley-Liss, Inc. and the American Pharmacists Association

On the factorial and construct validity of the Intrinsic Motivation Inventory: conceptual and operational concerns.

PubMed

Markland, D; Hardy, L

1997-03-01

The Intrinsic Motivation Inventory (IMI) has been gaining acceptance in the sport and exercise domain since the publication of research by McAuley, Duncan, and Tammen (1989) and McAuley, Wraith, and Duncan (1991), which reported confirmatory support for the factorial validity of a hierarchical model of intrinsic motivation. Authors of the present study argue that the results of these studies did not conclusively support the hierarchical model and that the model did not accurately reflect the tenets of cognitive evaluation theory (Deci & Ryan, 1985) from which the IMI is drawn. It is also argued that a measure of perceived locus of causality is required to model intrinsic motivation properly. The development of a perceived locus of causality for exercise scale is described, and alternative models, in which perceived competence and perceived locus of causality are held to have causal influences on intrinsic motivation, are compared with an oblique confirmatory factor analytic model in which the constructs are held at the same conceptual level. Structural equation modeling showed support for a causal model in which perceived locus of causality mediates the effects of perceived competence on pressure-tension, interest-enjoyment, and effort-importance. It is argued that conceptual and operational problems with the IMI, as currently used, should be addressed before it becomes established as the instrument of choice for assessing levels of intrinsic motivation.

Update on Multiple Ovulations in Dairy Cattle.

PubMed

Macmillan, Kira; Kastelic, John P; Colazo, Marcos G

2018-04-24

This review updates the causal mechanisms and risk factors for multiple ovulations (MOV) in cattle. Clearly, MOV can lead to twin pregnancies, which negatively affects the health, production, and reproduction of cows. Therefore, a better understanding of the factors causing MOV may help to reduce twinning. Multiple ovulations occur after two or more follicles deviate and achieve codominance. The MOV rate is influenced by a complex network of hormones. For example, MOV is more common during periods of low progesterone (P4), that is, in anovulatory cattle or when luteolysis coincides with the selection of the future ovulatory follicle. There is also strong evidence for the luteinizing hormone (LH) being the primary factor leading to codominance, as high P4 concentrations suppress the transient LH surges and can reduce the ovulation rate in cattle or even inhibit deviation. Rates of MOV are increased in older and higher-producing dairy cows. Increased milk production and dry matter intake (DMI) increases hormone clearance, including P4; however, the association between milk yield and MOV has not been consistent. Additional risk factors for MOV include ovarian cysts, diet, season, and genetics.

Three Cs in measurement models: causal indicators, composite indicators, and covariates.

PubMed

Bollen, Kenneth A; Bauldry, Shawn

2011-09-01

In the last 2 decades attention to causal (and formative) indicators has grown. Accompanying this growth has been the belief that one can classify indicators into 2 categories: effect (reflective) indicators and causal (formative) indicators. We argue that the dichotomous view is too simple. Instead, there are effect indicators and 3 types of variables on which a latent variable depends: causal indicators, composite (formative) indicators, and covariates (the "Three Cs"). Causal indicators have conceptual unity, and their effects on latent variables are structural. Covariates are not concept measures, but are variables to control to avoid bias in estimating the relations between measures and latent variables. Composite (formative) indicators form exact linear combinations of variables that need not share a concept. Their coefficients are weights rather than structural effects, and composites are a matter of convenience. The failure to distinguish the Three Cs has led to confusion and questions, such as, Are causal and formative indicators different names for the same indicator type? Should an equation with causal or formative indicators have an error term? Are the coefficients of causal indicators less stable than effect indicators? Distinguishing between causal and composite indicators and covariates goes a long way toward eliminating this confusion. We emphasize the key role that subject matter expertise plays in making these distinctions. We provide new guidelines for working with these variable types, including identification of models, scaling latent variables, parameter estimation, and validity assessment. A running empirical example on self-perceived health illustrates our major points.

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

PubMed

Yang, Lawrence H; Wonpat-Borja, Ahtoy J

2012-08-01

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-specific epistemologies of illness) might have on mental illness identification. Forty-nine relatives of Chinese-immigrant consumers with psychosis were sampled. Higher endorsement of 'physical causes' was associated with mental illness labeling. However among the non-biomedical causal beliefs, 'general social causes' demonstrated no relationship with mental illness identification, while endorsement of 'indigenous Chinese beliefs' showed a negative relationship. Effective treatment- and community-based psychoeducation, in addition to emphasizing biomedical models, might integrate indigenous Chinese epistemologies of illness to facilitate rapid identification of psychotic disorders and promote treatment use.

Underweight as a risk factor for respiratory death in the Whitehall cohort study: exploring reverse causality using a 45-year follow-up.

PubMed

Kivimäki, Mika; Shipley, Martin J; Bell, Joshua A; Brunner, Eric J; Batty, G David; Singh-Manoux, Archana

2016-01-01

Underweight adults have higher rates of respiratory death than the normal weight but it is unclear whether this association is causal or reflects illness-induced weight loss (reverse causality). Evidence from a 45-year follow-up of underweight participants for respiratory mortality in the Whitehall study (N=18 823; 2139 respiratory deaths) suggests that excess risk among the underweight is attributable to reverse causality. The age-adjusted and smoking-adjusted risk was 1.55-fold (95% CI 1.32 to 1.83) higher among underweight compared with normal weight participants, but attenuated in a stepwise manner to 1.14 (95% CI 0.76 to 1.71) after serial exclusions of deaths during the first 5-35 years of follow-up (P(trend)<0.001). Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

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

PubMed Central

Wonpat-Borja, Ahtoy J.

2013-01-01

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-specific epistemologies of illness) might have on mental illness identification. Forty-nine relatives of Chinese-immigrant consumers with psychosis were sampled. Higher endorsement of ‘physical causes’ was associated with mental illness labeling. However among the non-biomedical causal beliefs, ‘general social causes’ demonstrated no relationship with mental illness identification, while endorsement of ‘indigenous Chinese beliefs’ showed a negative relationship. Effective treatment- and community-based psychoeducation, in addition to emphasizing biomedical models, might integrate indigenous Chinese epistemologies of illness to facilitate rapid identification of psychotic disorders and promote treatment use. PMID:22075770

Shared Predisposition in the Association Between Cannabis Use and Subcortical Brain Structure.

PubMed

Pagliaccio, David; Barch, Deanna M; Bogdan, Ryan; Wood, Phillip K; Lynskey, Michael T; Heath, Andrew C; Agrawal, Arpana

2015-10-01

Prior neuroimaging studies have suggested that alterations in brain structure may be a consequence of cannabis use. Siblings discordant for cannabis use offer an opportunity to use cross-sectional data to disentangle such causal hypotheses from shared effects of genetics and familial environment on brain structure and cannabis use. To determine whether cannabis use is associated with differences in brain structure in a large sample of twins/siblings and to examine sibling pairs discordant for cannabis use to separate potential causal and predispositional factors linking lifetime cannabis exposure to volumetric alterations. Cross-sectional diagnostic interview, behavioral, and neuroimaging data were collected from community sampling and established family registries from August 2012 to September 2014. This study included data from 483 participants (22-35 years old) enrolled in the ongoing Human Connectome Project, with 262 participants reporting cannabis exposure (ie, ever used cannabis in their lifetime). Cannabis exposure was measured with the Semi-Structured Assessment for the Genetics of Alcoholism. Whole-brain, hippocampus, amygdala, ventral striatum, and orbitofrontal cortex volumes were related to lifetime cannabis use (ever used, age at onset, and frequency of use) using linear regressions. Genetic (ρg) and environmental (ρe) correlations between cannabis use and brain volumes were estimated. Linear mixed models were used to examine volume differences in sex-matched concordant unexposed (n = 71 pairs), exposed (n = 81 pairs), or exposure discordant (n = 89 pairs) sibling pairs. Among 483 study participants, cannabis exposure was related to smaller left amygdala (approximately 2.3%; P = .007) and right ventral striatum (approximately 3.5%; P < .005) volumes. These volumetric differences were within the range of normal variation. The association between left amygdala volume and cannabis use was largely owing to shared genetic factors (ρg = -0.43; P = .004), while the origin of the association with right ventral striatum volumes was unclear. Importantly, brain volumes did not differ between sex-matched siblings discordant for use (fixed effect = -7.43; t = -0.93, P = .35). Both the exposed and unexposed siblings in pairs discordant for cannabis exposure showed reduced amygdala volumes relative to members of concordant unexposed pairs (fixed effect = 12.56; t = 2.97; P = .003). In this study, differences in amygdala volume in cannabis users were attributable to common predispositional factors, genetic or environmental in origin, with little support for causal influences. Causal influences, in isolation or in conjunction with predispositional factors, may exist for other brain regions (eg, ventral striatum) or at more severe levels of cannabis involvement and deserve further study.

Obesity, metabolic factors and risk of different histological types of lung cancer: A Mendelian randomization study

PubMed Central

Carreras-Torres, Robert; Johansson, Mattias; Haycock, Philip C.; Wade, Kaitlin H.; Relton, Caroline L.; Martin, Richard M.; Davey Smith, George; Albanes, Demetrius; Aldrich, Melinda C.; Andrew, Angeline; Bickeböller, Heike; Bojesen, Stig E.; Brunnström, Hans; Manjer, Jonas; Brüske, Irene; Caporaso, Neil E.; Chen, Chu; Christiani, David C.; Christian, W. Jay; Doherty, Jennifer A.; Duell, Eric J.; Goodman, Gary E.; Grankvist, Kjell; Haugen, Aage; Hong, Yun-Chul; Johansson, Mikael B.; Lam, Stephen; Landi, Maria Teresa; Lazarus, Philip; Le Marchand, Loïc; Liu, Geoffrey; Melander, Olle; Rennert, Gad; Risch, Angela; Haura, Eric B.; Scelo, Ghislaine; Zaridze, David; Mukeriya, Anush; Savić, Milan; Lissowska, Jolanta; Swiatkowska, Beata; Janout, Vladimir; Holcatova, Ivana; Mates, Dana; Shen, Hongbing; Tardon, Adonina; Woll, Penella; Tsao, Ming-Sound; Wu, Xifeng; Yuan, Jian-Min; Hung, Rayjean J.; Amos, Christopher I.; Brennan, Paul

2017-01-01

Background Assessing the relationship between lung cancer and metabolic conditions is challenging because of the confounding effect of tobacco. Mendelian randomization (MR), or the use of genetic instrumental variables to assess causality, may help to identify the metabolic drivers of lung cancer. Methods and findings We identified genetic instruments for potential metabolic risk factors and evaluated these in relation to risk using 29,266 lung cancer cases (including 11,273 adenocarcinomas, 7,426 squamous cell and 2,664 small cell cases) and 56,450 controls. The MR risk analysis suggested a causal effect of body mass index (BMI) on lung cancer risk for two of the three major histological subtypes, with evidence of a risk increase for squamous cell carcinoma (odds ratio (OR) [95% confidence interval (CI)] = 1.20 [1.01–1.43] and for small cell lung cancer (OR [95%CI] = 1.52 [1.15–2.00]) for each standard deviation (SD) increase in BMI [4.6 kg/m2]), but not for adenocarcinoma (OR [95%CI] = 0.93 [0.79–1.08]) (Pheterogeneity = 4.3x10-3). Additional analysis using a genetic instrument for BMI showed that each SD increase in BMI increased cigarette consumption by 1.27 cigarettes per day (P = 2.1x10-3), providing novel evidence that a genetic susceptibility to obesity influences smoking patterns. There was also evidence that low-density lipoprotein cholesterol was inversely associated with lung cancer overall risk (OR [95%CI] = 0.90 [0.84–0.97] per SD of 38 mg/dl), while fasting insulin was positively associated (OR [95%CI] = 1.63 [1.25–2.13] per SD of 44.4 pmol/l). Sensitivity analyses including a weighted-median approach and MR-Egger test did not detect other pleiotropic effects biasing the main results. Conclusions Our results are consistent with a causal role of fasting insulin and low-density lipoprotein cholesterol in lung cancer etiology, as well as for BMI in squamous cell and small cell carcinoma. The latter relation may be mediated by a previously unrecognized effect of obesity on smoking behavior. PMID:28594918

An exploration of the factor structure and development of potentially useful subscales of etiological beliefs about schizophrenia in a general population sample.

PubMed

Goulding, Sandra M; Broussard, Beth; Demir, Berivan; Compton, Michael T

2009-11-01

Given that accessing care, treatment engagement, and course and outcomes among people with schizophrenia may be influenced by beliefs about causes in the larger community, causal beliefs about schizophrenia have been studied in numerous communities around the world. In particular, the 30-item list of etiological attributions developed by Angermeyer and colleagues has been used to describe causal beliefs in patients, family members, and lay community members within such communities. The current study, the first examination of the latent or factorial structure of these 30 causal beliefs, seeks to provide informative subscales that may enhance reliability and validity of groupings of causes for future analyses involving community members. Data were gathered from six separate surveys involving three distinct groups of individuals from the same community within the southeastern United States: lay community members, relatives of individuals with schizophrenia-spectrum disorders, and police officers at the start of a 1-week mental health training program. Exploratory factor analysis in the overall sample (n=577) revealed four factors that were used to define four subscales, termed: personal/family/social stressors (14 items), inconsistent with modern conceptions of risk (8 items), external/environmental insults to the brain (6 items), and consistent with modern biological conceptions (2 items). Cronbach's internal consistency reliability coefficients for these subscales were 0.91, 0.83, 0.71, and 0.65, respectively. These findings suggest that subscales could be derived to provide continuous measures for assessing causal beliefs in order to study how this concept relates to attitudes toward schizophrenia, the people affected by the disorder, and treatments that are recommended by mental health professionals. Replication within similar and dissimilar groups is warranted.

Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression.

PubMed

Fairfax, Benjamin P; Humburg, Peter; Makino, Seiko; Naranbhai, Vivek; Wong, Daniel; Lau, Evelyn; Jostins, Luke; Plant, Katharine; Andrews, Robert; McGee, Chris; Knight, Julian C

2014-03-07

To systematically investigate the impact of immune stimulation upon regulatory variant activity, we exposed primary monocytes from 432 healthy Europeans to interferon-γ (IFN-γ) or differing durations of lipopolysaccharide and mapped expression quantitative trait loci (eQTLs). More than half of cis-eQTLs identified, involving hundreds of genes and associated pathways, are detected specifically in stimulated monocytes. Induced innate immune activity reveals multiple master regulatory trans-eQTLs including the major histocompatibility complex (MHC), coding variants altering enzyme and receptor function, an IFN-β cytokine network showing temporal specificity, and an interferon regulatory factor 2 (IRF2) transcription factor-modulated network. Induced eQTL are significantly enriched for genome-wide association study loci, identifying context-specific associations to putative causal genes including CARD9, ATM, and IRF8. Thus, applying pathophysiologically relevant immune stimuli assists resolution of functional genetic variants.

Hearing loss among older construction workers: Updated analyses.

PubMed

Dement, John; Welch, Laura S; Ringen, Knut; Cranford, Kim; Quinn, Patricia

2018-04-01

A prior study of this construction worker population found significant noise-associated hearing loss. This follow-up study included a much larger study population and consideration of additional risk factors. Data included audiometry, clinical chemistry, personal history, and work history. Qualitative exposure metrics for noise and solvents were developed. Analyses compared construction workers to an internal reference group with lower exposures and an external worker population with low noise exposure. Among participants (n = 19 127) an overall prevalence of hearing loss of 58% was observed, with significantly increased prevalence across all construction trades. Construction workers had significantly increased risk of hearing loss compared to reference populations, with increasing risk by work duration. Noise exposure, solvent exposure, hypertension, and smoking were significant risk factors in multivariate models. Results support a causal relationship between construction trades work and hearing loss. Prevention should focus on reducing exposure to noise, solvents, and cigarette smoke. © 2018 Wiley Periodicals, Inc.

Novel Adaptive and Innate Immunity Targets in Hypertension

PubMed Central

Abais-Battad, Justine M.; Dasinger, John Henry; Fehrenbach, Daniel J.; Mattson, David L.

2017-01-01

Hypertension is a worldwide epidemic and global health concern as it is a major risk factor for the development of cardiovascular diseases. A relationship between the immune system and its contributing role to the pathogenesis of hypertension has been long established, but substantial advancements within the last few years have dissected specific causal molecular mechanisms. This review will briefly examine these recent studies exploring the involvement of either innate or adaptive immunity pathways. Such pathways to be discussed include innate immunity factors such as antigen presenting cells and pattern recognition receptors, adaptive immune elements including T and B lymphocytes, and more specifically, the emerging role of T regulatory cells, as well as the potential of cytokines and chemokines to serve as signaling messengers connecting innate and adaptive immunity. Together, we summarize these studies to provide new perspective for what will hopefully lead to more targeted approaches to manipulate the immune system as hypertensive therapy. PMID:28336371

Inefficiencies in water project design and operation in the third world: An economic perspective

NASA Astrophysics Data System (ADS)

Howe, Charles W.; Dixon, John A.

1993-07-01

Water projects in less developed countries (LDCs) frequently are poorly operated and maintained. As a result, project benefits and development impacts fall short of plans. The problems begin in the project identification, design, and construction stages: donor and host country biases lead to inappropriate projects, unsustainable technologies, and shoddy construction. Later operation and maintenance are then difficult or impossible. Causal factors include donor desire to build monuments and sell technology, provision of excessive capital to favored sectors or institutions, and an unwillingness to require a reasonable quid pro quo from the host country. Host country factors include excessive administrative centralization, lack of rewards for good operation and maintenance, and widespread corruption in forms that seriously distort allocative efficiency. Until individual actors on both sides can be motivated to pursue the long-run good of the LDC, Third World water projects will continue to have low or negative net payoffs.

From cognition to the system: developing a multilevel taxonomy of patient safety in general practice.

PubMed

Kostopoulou, O

The paper describes the process of developing a taxonomy of patient safety in general practice. The methodologies employed included fieldwork, task analysis and confidential reporting of patient-safety events in five West Midlands practices. Reported events were traced back to their root causes and contributing factors. The resulting taxonomy is based on a theoretical model of human cognition, includes multiple levels of classification to reflect the chain of causation and considers affective and physiological influences on performance. Events are classified at three levels. At level one, the information-processing model of cognition is used to classify errors. At level two, immediate causes are identified, internal and external to the individual. At level three, more remote causal factors are classified as either 'work organization' or 'technical' with subcategories. The properties of the taxonomy (validity, reliability, comprehensiveness) as well as its usability and acceptability remain to be tested with potential users.

Possible risk factors for increased suicide following bariatric surgery.

PubMed

Mitchell, James E; Crosby, Ross; de Zwaan, Martina; Engel, Scott; Roerig, James; Steffen, Kristine; Gordon, Kathryn H; Karr, Trisha; Lavender, Jason; Wonderlich, Steve

2013-04-01

There is a growing research literature suggesting that there may be elevated risk of suicide following bariatric surgery. Most of the data reported thus far has been cross-sectional and observational, and very little is known about the possible specific causal variables involved. The purpose of this report is to review this literature and to review possible risk factors for increased suicidal risk following bariatric surgery, to delineate future research directions. First a variety of medical, biological, and genetic factors, including the persistence or recurrence of medical comorbidities after bariatric surgery, the disinhibition and impulsivity secondary to changes in the absorption of alcohol, hypoglycemia, as well as pharmacokinetic changes that may affect the absorption of various medications including antidepressant medications are reviewed. Also reviewed are possible mediating factors involving changes in various peptidergic systems such as GLP-1 and Ghrelin. A number of psychosocial issues that might be involved are discussed, including lack of improvement in quality of life after surgery, continued or recurrent physical mobility restrictions, persistence or recurrence of sexual dysfunction and relationship problems, low self-esteem, and a history of child maltreatment. Inadequate weight loss or weight regain are also discussed. A number of possible contributing factors have been identified. Possible theoretical models involved and directions for research are suggested. Copyright © 2012 The Obesity Society.

Environmental Factors and Zoonotic Pathogen Ecology in Urban Exploiter Species.

PubMed

Rothenburger, Jamie L; Himsworth, Chelsea H; Nemeth, Nicole M; Pearl, David L; Jardine, Claire M

2017-09-01

Knowledge of pathogen ecology, including the impacts of environmental factors on pathogen and host dynamics, is essential for determining the risk that zoonotic pathogens pose to people. This review synthesizes the scientific literature on environmental factors that influence the ecology and epidemiology of zoonotic microparasites (bacteria, viruses and protozoa) in globally invasive urban exploiter wildlife species (i.e., rock doves [Columba livia domestica], European starlings [Sturnus vulgaris], house sparrows [Passer domesticus], Norway rats [Rattus norvegicus], black rats [R. rattus] and house mice [Mus musculus]). Pathogen ecology, including prevalence and pathogen characteristics, is influenced by geographical location, habitat, season and weather. The prevalence of zoonotic pathogens in mice and rats varies markedly over short geographical distances, but tends to be highest in ports, disadvantaged (e.g., low income) and residential areas. Future research should use epidemiological approaches, including random sampling and robust statistical analyses, to evaluate a range of biotic and abiotic environmental factors at spatial scales suitable for host home range sizes. Moving beyond descriptive studies to uncover the causal factors contributing to uneven pathogen distribution among wildlife hosts in urban environments may lead to targeted surveillance and intervention strategies. Application of this knowledge to urban maintenance and planning may reduce the potential impacts of urban wildlife-associated zoonotic diseases on people.

Confirmatory Factor Analytic Structure and Measurement Invariance of Quantitative Autistic Traits Measured by the Social Responsiveness Scale-2

ERIC Educational Resources Information Center

Frazier, Thomas W.; Ratliff, Kristin R.; Gruber, Chris; Zhang, Yi; Law, Paul A.; Constantino, John N.

2014-01-01

Understanding the factor structure of autistic symptomatology is critical to the discovery and interpretation of causal mechanisms in autism spectrum disorder. We applied confirmatory factor analysis and assessment of measurement invariance to a large ("N" = 9635) accumulated collection of reports on quantitative autistic traits using…

Exclusion of MYF5, GSC, RUNX2, and TCOF1 mutation in a case of cerebro-costo-mandibular syndrome.

PubMed

Su, Pen-Hua; Chen, Jia-Yuh; Chiang, Chin-Lung; Ng, Yan-Yan; Chen, Suh-Jen

2010-04-01

Cerebro-costo-mandibular syndrome (CCMS) is an uncommon multiple congenital anomaly syndrome characterized by severe micrognathia, posterior rib-gap defects, and developmental delay. The cause of CCMS is unknown. Genes hypothesized to have a causal role in CCMS, include myogenic factor 5 (MYF5), goosecoid homeobox (GSC) and runt-related transcription factor 2 (RUNX2) [formerly known as core-binding factor (CBFA1)]. We report an infant with typical features of CCMS who, on prenatal ultrasound, was found to have severe micrognathia. We present the first image by three-dimensional computed tomography of posterior rib-defect, and we exclude mutations of the MYF5, GSC, RUNX2, and TCOF1 genes in our patient. Further molecular studies are needed to evaluate the cause of CCMS.

Formalizing the Role of Agent-Based Modeling in Causal Inference and Epidemiology

PubMed Central

Marshall, Brandon D. L.; Galea, Sandro

2015-01-01

Calls for the adoption of complex systems approaches, including agent-based modeling, in the field of epidemiology have largely centered on the potential for such methods to examine complex disease etiologies, which are characterized by feedback behavior, interference, threshold dynamics, and multiple interacting causal effects. However, considerable theoretical and practical issues impede the capacity of agent-based methods to examine and evaluate causal effects and thus illuminate new areas for intervention. We build on this work by describing how agent-based models can be used to simulate counterfactual outcomes in the presence of complexity. We show that these models are of particular utility when the hypothesized causal mechanisms exhibit a high degree of interdependence between multiple causal effects and when interference (i.e., one person's exposure affects the outcome of others) is present and of intrinsic scientific interest. Although not without challenges, agent-based modeling (and complex systems methods broadly) represent a promising novel approach to identify and evaluate complex causal effects, and they are thus well suited to complement other modern epidemiologic methods of etiologic inquiry. PMID:25480821

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

PubMed

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.

Relativistic causality

NASA Astrophysics Data System (ADS)

Valente, Giovanni; Owen Weatherall, James

2014-11-01

Relativity theory is often taken to include, or to imply, a prohibition on superluminal propagation of causal processes. Yet, what exactly the prohibition on superluminal propagation amounts to and how one should deal with its possible violation have remained open philosophical problems, both in the context of the metaphysics of causation and the foundations of physics. In particular, recent work in philosophy of physics has focused on the causal structure of spacetime in relativity theory and on how this causal structure manifests itself in our most fundamental theories of matter. These topics were the subject of a workshop on "Relativistic Causality in Quantum Field Theory and General Relativity" that we organized (along with John Earman) at the Center for Philosophy of Science in Pittsburgh on April 5-7, 2013. The present Special Issue comprises contributions by speakers in that workshop as well as several other experts exploring different aspects of relativistic causality. We are grateful to the journal for hosting this Special Issue, to the journal's managing editor, Femke Kuiling, for her help and support in putting the issue together, and to the authors and the referees for their excellent work.

History, politics and vulnerability: explaining excess mortality in Scotland and Glasgow.

PubMed

Walsh, D; McCartney, G; Collins, C; Taulbut, M; Batty, G D

2017-10-01

High levels of excess mortality (i.e. that not explained by deprivation) have been observed for Scotland compared with England & Wales, and especially for Glasgow in comparison with similar post-industrial cities such as Liverpool and Manchester. Many potential explanations have been suggested. Based on an assessment of these, the aim was to develop an understanding of the most likely underlying causes. Note that this paper distils a larger research report, with the aim of reaching wider audiences beyond Scotland, as the important lessons learnt are relevant to other populations. Review and dialectical synthesis of evidence. Forty hypotheses were examined, including those identified from a systematic review. The relevance of each was assessed by means of Bradford Hill's criteria for causality alongside-for hypotheses deemed causally linked to mortality-comparisons of exposures between Glasgow and Liverpool/Manchester, and between Scotland and the rest of Great Britain. Where gaps in the evidence base were identified, new research was undertaken. Causal chains of relevant hypotheses were created, each tested in terms of its ability to explain the many different aspects of excess mortality. The models were further tested with key informants from public health and other disciplines. In Glasgow's case, the city was made more vulnerable to important socioeconomic (deprivation, deindustrialisation) and political (detrimental economic and social policies) exposures, resulting in worse outcomes. This vulnerability was generated by a series of historical factors, processes and decisions: the lagged effects of historical overcrowding; post-war regional policy including the socially selective relocation of population to outside the city; more detrimental processes of urban change which impacted on living conditions; and differences in local government responses to UK government policy in the 1980s which both impacted in negative terms in Glasgow and also conferred protective effects on comparator cities. Further resulting protective factors were identified (e.g. greater 'social capital' in Liverpool) which placed Glasgow at a further relative disadvantage. Other contributory factors were highlighted, including the inadequate measurement of deprivation. A similar 'explanatory model' resulted for Scotland as a whole. This included: the components of the Glasgow model, given their impact on nationally measured outcomes; inadequate measurement of deprivation; the lagged effects of deprivation (in particular higher levels of overcrowding historically); and additional key vulnerabilities. The work has helped to further understanding of the underlying causes of Glasgow's and Scotland's high levels of excess mortality. The implications for policy include the need to address three issues simultaneously: to protect against key exposures (e.g. poverty) which impact detrimentally across all parts of the UK; to address the existing consequences of Glasgow's and Scotland's vulnerability; and to mitigate against the effects of future vulnerabilities which are likely to emerge from policy responses to contemporary problems which fail sufficiently to consider and to prevent long-term, unintended social consequences. Copyright © 2017 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Should visceral fat be reduced to increase longevity?

PubMed

Finelli, Carmine; Sommella, Luigi; Gioia, Saverio; La Sala, Nicolina; Tarantino, Giovanni

2013-09-01

Several epidemiologic studies have implicated visceral fat as a major risk factor for insulin resistance, type 2 diabetes mellitus, cardiovascular disease, stroke, metabolic syndrome and death. Utilizing novel models of visceral obesity, numerous studies have demonstrated that the relationship between visceral fat and longevity is causal while the accrual of subcutaneous fat does not appear to play an important role in the etiology of disease risk. Specific recommended intake levels vary based on a number of factors, including current weight, activity levels, and weight loss goals. It is discussed the need of reducing the visceral fat as a potential treatment strategy to prevent or delay age-related diseases and to increase longevity. Copyright © 2013 Elsevier B.V. All rights reserved.

Maternal smoking during pregnancy and child outcomes: Real or spurious effect?

PubMed Central

Knopik, Valerie S.

2013-01-01

Maternal smoking during pregnancy (MSDP) is a major public health concern with clearly established consequences to both mother and newborn (e.g., low birth weight, altered cardiorespiratory responses). MSDP has also been associated with higher rates of a variety of poor cognitive and behavioral outcomes in children, including ADHD, conduct disorder, impaired learning and memory, and cognitive dysfunction. However, the evidence suggesting causal effects of MSDP for these outcomes is muddied in the existing literature due to the frequent inability to separate prenatal exposure effects from other confounding environmental and genetic factors. Carefully designed studies using genetically sensitive strategies can build upon current evidence and begin to elucidate the likely complex factors contributing to associations between MSDP and child outcomes. PMID:19142764

Genetic Instrumental Variable Studies of Effects of Prenatal Risk Factors

PubMed Central

von Hinke Kessler Scholder, Stephanie

2013-01-01

Identifying the effects of maternal risk factors during pregnancy on infant and child health is an area of tremendous research interest. However, of interest to policy makers is unraveling the causal effects of prenatal risk factors, not their associations with child health, which may be confounded by several unobserved factors. In this paper, we evaluate the utility of genetic variants in three genes that have unequivocal evidence of being related to three major risk factors – CHRNA3 for smoking, ADH1B for alcohol use, and FTO for obesity – as instrumental variables for identifying the causal effects of such factors during pregnancy. Using two independent datasets, we find that these variants are overall predictive of the risk factors and are not systematically related to observed confounders, suggesting that they may be useful instruments. We also find some suggestive evidence that genetic effects are stronger during than before pregnancy. We provide an empirical example illustrating the use of these genetic variants as instruments to evaluate the effects of risk factors on birth weight. Finally, we offer suggestions for researchers contemplating the use of these variants as instruments. PMID:23701534

Mathematical Intelligence and Mathematical Creativity: A Causal Relationship

ERIC Educational Resources Information Center

Tyagi, Tarun Kumar

2017-01-01

This study investigated the causal relationship between mathematical creativity and mathematical intelligence. Four hundred thirty-nine 8th-grade students, age ranged from 11 to 14 years, were included in the sample of this study by random cluster technique on which mathematical creativity and Hindi adaptation of mathematical intelligence test…

Structural Equations and Path Analysis for Discrete Data.

ERIC Educational Resources Information Center

Winship, Christopher; Mare, Robert D.

1983-01-01

Presented is an approach to causal models in which some or all variables are discretely measured, showing that path analytic methods permit quantification of causal relationships among variables with the same flexibility and power of interpretation as is feasible in models including only continuous variables. Examples are provided. (Author/IS)

The representation of inherent properties.

PubMed

Prasada, Sandeep

2014-10-01

Research on the representation of generic knowledge suggests that inherent properties can have either a principled or a causal connection to a kind. The type of connection determines whether the outcome of the storytelling process will include intuitions of inevitability and a normative dimension and whether it will ground causal explanations.

Statins and tendinopathy: a systematic review.

PubMed

Teichtahl, Andrew J; Brady, Sharmayne R E; Urquhart, Donna M; Wluka, Anita E; Wang, Yuanyuan; Shaw, Jonathan E; Cicuttini, Flavia M

2016-02-15

To systematically review the evidence on whether statin therapy, commonly used in clinical practice to treat hypercholesterolaemia for primary and secondary prevention of cardiovascular disease, contributes to tendinopathy; and to examine causality according to the Bradford Hill criteria. A systematic review of studies examining the relationship between statin therapy and tendinopathy. Included studies were rated based on their methodological quality. A best evidence synthesis was used to summarise the results, and Bradford Hill criteria were used to assess causation. Ovid MEDLINE, CINAHL Plus, PubMed and Embase databases. We included adult human studies published in the English language between January 1966 and October 2015. Study designs eligible for inclusion were randomised controlled trials and cross-sectional, cohort or case-control studies. Four studies (three cohort studies and one case-control study) were included, with a mean methodological quality score of 67%. Three studies were deemed high quality. Tendon rupture was the primary outcome in three studies, and rotator cuff disease in the other. All studies found no positive association between statin therapy and tendon rupture for the total study population. There was evidence that simvastatin reduces the risk of tendinopathy. To date, there is a paucity of evidence to implicate statin therapy as a well established risk factor or causal mechanism for tendon rupture in the general population. There is strong evidence that simvastatin reduces the risk of tendinopathy.

Italian regional health system structure and expected cancer survival.

PubMed

Vercelli, Marina; Lillini, Roberto; Quaglia, Alberto; Capocaccia, Riccardo

2014-01-01

Few studies deal with the association of socioeconomic and health system resource variables with cancer survival at the Italian regional level, where the greatest number of decisions about social and health policies and resource allocations are taken. The present study aimed to describe the causal relationships between socioeconomic and health system resource factors and regional cancer survival and to compute the expected cancer survival at provincial, regional and area levels. Age-standardized relative survival at 5 years from diagnosis of cases incident in 1995-1998 and followed up to 2004 were derived by gender for 11 sites from the Italian Association of Cancer Registries data bank. The socioeconomic and health system resource variables, describing at a regional level the macro-economy, demography, labor market, and health resources for 1995-2005, came from the Health for All database. A principal components factor analysis was applied to the socioeconomic and health system resource variables. For every site, linear regression models were computed considering the relative survival at 5 years as a dependent variable and the principal components factor analysis factors as independent variables. The factors described the socioeconomic and health-related features of the regional systems and were causally related to the characteristics of the patient taken in charge. The models built by the factors allowed computation of the expected relative survival at 5 years with very good concordance with those observed at regional, macro-regional and national levels. In the regions without any cancer registry, survival was coherent with that of neighboring regions with similar socioeconomic and health system resources characteristics. The models highlighted the causal correlations between socioeconomic and health system resources and cancer survival, suggesting that they could be good evaluation tools for the efficiency of the resources allocation and use.

Causal assessment of dietary acid load and bone disease: a systematic review & meta-analysis applying Hill's epidemiologic criteria for causality

PubMed Central

2011-01-01

Background Modern diets have been suggested to increase systemic acid load and net acid excretion. In response, alkaline diets and products are marketed to avoid or counteract this acid, help the body regulate its pH to prevent and cure disease. The objective of this systematic review was to evaluate causal relationships between dietary acid load and osteoporosis using Hill's criteria. Methods Systematic review and meta-analysis. We systematically searched published literature for randomized intervention trials, prospective cohort studies, and meta-analyses of the acid-ash or acid-base diet hypothesis with bone-related outcomes, in which the diet acid load was altered, or an alkaline diet or alkaline salts were provided, to healthy human adults. Cellular mechanism studies were also systematically examined. Results Fifty-five of 238 studies met the inclusion criteria: 22 randomized interventions, 2 meta-analyses, and 11 prospective observational studies of bone health outcomes including: urine calcium excretion, calcium balance or retention, changes of bone mineral density, or fractures, among healthy adults in which acid and/or alkaline intakes were manipulated or observed through foods or supplements; and 19 in vitro cell studies which examined the hypothesized mechanism. Urine calcium excretion rates were consistent with osteoporosis development; however calcium balance studies did not demonstrate loss of whole body calcium with higher net acid excretion. Several weaknesses regarding the acid-ash hypothesis were uncovered: No intervention studies provided direct evidence of osteoporosis progression (fragility fractures, or bone strength as measured using biopsy). The supporting prospective cohort studies were not controlled regarding important osteoporosis risk factors including: weight loss during follow-up, family history of osteoporosis, baseline bone mineral density, and estrogen status. No study revealed a biologic mechanism functioning at physiological pH. Finally, randomized studies did not provide evidence for an adverse role of phosphate, milk, and grain foods in osteoporosis. Conclusions A causal association between dietary acid load and osteoporotic bone disease is not supported by evidence and there is no evidence that an alkaline diet is protective of bone health. PMID:21529374

Causal assessment of dietary acid load and bone disease: a systematic review & meta-analysis applying Hill's epidemiologic criteria for causality.

PubMed

Fenton, Tanis R; Tough, Suzanne C; Lyon, Andrew W; Eliasziw, Misha; Hanley, David A

2011-04-30

Modern diets have been suggested to increase systemic acid load and net acid excretion. In response, alkaline diets and products are marketed to avoid or counteract this acid, help the body regulate its pH to prevent and cure disease. The objective of this systematic review was to evaluate causal relationships between dietary acid load and osteoporosis using Hill's criteria. Systematic review and meta-analysis. We systematically searched published literature for randomized intervention trials, prospective cohort studies, and meta-analyses of the acid-ash or acid-base diet hypothesis with bone-related outcomes, in which the diet acid load was altered, or an alkaline diet or alkaline salts were provided, to healthy human adults. Cellular mechanism studies were also systematically examined. Fifty-five of 238 studies met the inclusion criteria: 22 randomized interventions, 2 meta-analyses, and 11 prospective observational studies of bone health outcomes including: urine calcium excretion, calcium balance or retention, changes of bone mineral density, or fractures, among healthy adults in which acid and/or alkaline intakes were manipulated or observed through foods or supplements; and 19 in vitro cell studies which examined the hypothesized mechanism. Urine calcium excretion rates were consistent with osteoporosis development; however calcium balance studies did not demonstrate loss of whole body calcium with higher net acid excretion. Several weaknesses regarding the acid-ash hypothesis were uncovered: No intervention studies provided direct evidence of osteoporosis progression (fragility fractures, or bone strength as measured using biopsy). The supporting prospective cohort studies were not controlled regarding important osteoporosis risk factors including: weight loss during follow-up, family history of osteoporosis, baseline bone mineral density, and estrogen status. No study revealed a biologic mechanism functioning at physiological pH. Finally, randomized studies did not provide evidence for an adverse role of phosphate, milk, and grain foods in osteoporosis. A causal association between dietary acid load and osteoporotic bone disease is not supported by evidence and there is no evidence that an alkaline diet is protective of bone health.

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

PubMed Central

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 by studying CD in the context of its causal and phenotypic associations with other disorders over time. Advancing and refining formal causal models that specify the common and unique causes and biological mechanisms underlying each correlated dimension of psychopathology should facilitate research on the fundamental nature and nosology of CD. PMID:22211395

Causal modeling of self-concept, job satisfaction, and retention of nurses.

PubMed

Cowin, Leanne S; Johnson, Maree; Craven, Rhonda G; Marsh, Herbert W

2008-10-01

The critical shortage of nurses experienced throughout the western world has prompted researchers to examine one major component of this complex problem - the impact of nurses' professional identity and job satisfaction on retention. A descriptive correlational design with a longitudinal element was used to examine a causal model of nurses' self-concept, job satisfaction, and retention plans in 2002. A random sample of 2000 registered nurses was selected from the state registering authority listing. A postal survey assessing multiple dimensions of nurses' self-concept (measured by the nurse self-concept questionnaire), job satisfaction (measured by the index of work satisfaction) was undertaken at Time 1 (n=528) and 8 months later at Time 2 (n=332) (including retention plans (measured by the Nurse Retention Index). Using confirmatory factor analysis, correlation matrices and path analysis, measurement and structural models were examined on matching pairs of data from T1 and T2 (total sample N=332). Nurses' self-concept was found to have a stronger association with nurses' retention plans (B=.45) than job satisfaction (B=.28). Aspects of pay and task were not significantly related to retention plans, however, professional status (r=.51), and to a lesser extent, organizational policies (r=.27) were significant factors. Nurses' general self-concept was strongly related (r=.57) to retention plans. Strategies or interventions requiring implementation and evaluation include: counseling to improve nurse general self-concept, education programs and competencies in health communication between health professionals, reporting of nurse-initiated programs with substantial patient benefit, nurse-friendly organizational policies, common health team learning opportunities, and autonomous practice models.

Generalized group field theories and quantum gravity transition amplitudes

NASA Astrophysics Data System (ADS)

Oriti, Daniele

2006-03-01

We construct a generalized formalism for group field theories, in which the domain of the field is extended to include additional proper time variables, as well as their conjugate mass variables. This formalism allows for different types of quantum gravity transition amplitudes in perturbative expansion, and we show how both causal spin foam models and the usual a-causal ones can be derived from it, within a sum over triangulations of all topologies. We also highlight the relation of the so-derived causal transition amplitudes with simplicial gravity actions.

Disentangling the Correlated Evolution of Monogamy and Cooperation.

PubMed

Dillard, Jacqueline R; Westneat, David F

2016-07-01

Lifetime genetic monogamy, by increasing sibling relatedness, has been proposed as an important causal factor in the evolution of altruism. Monogamy, however, could influence the subsequent evolution of cooperation in other ways. We present several alternative, non-mutually exclusive, evolutionary processes that could explain the correlated evolution of monogamy and cooperation. Our analysis of these possibilities reveals that many ecological or social factors can affect all three variables of Hamilton's Rule simultaneously, thus calling for a more holistic, systems-level approach to studying the evolution of social traits. This perspective reveals novel dimensions to coevolutionary relationships and provides solutions for assigning causality in complex cases of correlated social trait evolution, such as the sequential evolution of monogamy and cooperation. Copyright © 2016 Elsevier Ltd. All rights reserved.

New insights in the pathogenesis of atopic disease.

PubMed

Ionescu, John G

2009-01-01

A causal link between the increasing environmental pollution and the fast spreading of allergic diseases is currently discussed. The exogenic and endogenic noxious agents contributing to the total environmental load are primarily acting through immunotoxic, sensitizing and neurotoxic mechanisms in animal experiments and in humans. Beside classic allergic-triggering factors (allergen potency, intermittent exposure to different allergen concentrations, presence of microbial bodies and sensitizing phenols), the adjuvant role of environmental pollutants gains increasing importance in allergy induction. Our therapy experience with more than 18.000 atopic eczema patients shows that beside allergic reactions pseudoallergic mechanisms through toxic environmental agents (formaldehyde, industrial and traffic smog, wood preservatives, microbial toxins, additive-rich food, nicotine, alcohol, pesticides, solvents, amalgam-heavy metals) are increasingly incriminated as causal factors for the complex symptomatology. The avoidance and elimination of such triggering factors before and during pregnancy and in early childhood may result in a significant decrease of the incidence of atopic diseases.

New Insights in the Pathogenesis of Atopic Disease

PubMed Central

Ionescu, GJ

2009-01-01

A causal link between the increasing environmental pollution and the fast spreading of allergic diseases is currently discussed. The exogenic and endogenic noxious agents contributing to the total environmental load are primarily acting through immunotoxic, sensitizing and neurotoxic mechanisms in animal experiments and in humans. Beside classic allergic–triggering factors (allergen potency, intermittent exposure to different allergen concentrations, presence of microbial bodies and sensitizing phenols), the adjuvant role of environmental pollutants gains increasing importance in allergy induction. Our therapy experience with more than 18.000 atopic eczema patients shows that beside allergic reactions pseudoallergic mechanisms through toxic environmental agents (formaldehyde, industrial and traffic smog, wood preservatives, microbial toxins, additive–rich food, nicotine, alcohol, pesticides, solvents, amalgam–heavy metals) are increasingly incriminated as causal factors for the complex symptomatology. The avoidance and elimination of such triggering factors before and during pregnancy and in early childhood may result in a significant decrease of the incidence of atopic diseases.

New Insights in the Pathogenesis of Atopic Disease

PubMed Central

John G., Ionescu

2009-01-01

A causal link between the increasing environmental pollution and the fast spreading of allergic diseases is currently discussed. The exogenic and endogenic noxious agents contributing to the total environmental load are primarily acting through immunotoxic, sensitizing and neurotoxic mechanisms in animal experiments and in humans. Beside classic allergic-triggering factors (allergen potency, intermittent exposure to different allergen concentrations, presence of microbial bodies and sensitizing phenols), the adjuvant role of environmental pollutants gains increasing importance in allergy induction. Our therapy experience with more than 18.000 atopic eczema patients shows that beside allergic reactions pseudoallergic mechanisms through toxic environmental agents (formaldehyde, industrial and traffic smog, wood preservatives, microbial toxins, additive-rich food, nicotine, alcohol, pesticides, solvents, amalgam-heavy metals) are increasingly incriminated as causal factors for the complex symptomatology. The avoidance and elimination of such triggering factors before and during pregnancy and in early childhood may result in a significant decrease of the incidence of atopic diseases. PMID:20108533

Maternal obesity and childhood wheezing and asthma.

PubMed

Rusconi, Franca; Popovic, Maja

2017-03-01

Obesity represents one of the major public health problems worldwide, with an increased prevalence also among women of reproductive age. Maternal pre-pregnancy overweight and obesity are important risk factors for a number of maternal and foetal/neonatal complications. The objective of this review is to provide an overview of the most recent evidence regarding the associations between pre-pregnancy overweight/obesity and wheezing and asthma in childhood. Potential mechanisms, mediators and confounding factors involved in these associations are also discussed. Despite the relatively large body of studies examining these associations and taking into account main confounders and potential mediators, the causal relationship between maternal obesity and wheezing and asthma in childhood is still uncertain. This uncertainty is not trivial, as any prevention strategy aimed at reducing the burden of these conditions would necessarily imply better understanding of the factors that are in the causal chain. Copyright © 2016. Published by Elsevier Ltd.

The impact of airport characteristics on airport surface accidents and incidents.

PubMed

Wilke, Sabine; Majumdar, Arnab; Ochieng, Washington Y

2015-06-01

Airport surface safety and in particular runway and taxiway safety is acknowledged globally as one of aviation's greatest challenges. To improve this key area of aviation safety, it is necessary to identify and understand the causal and contributing factors on safety occurrences. While the contribution of human factors, operations, and procedures has been researched extensively, the impact of the airport and its associated characteristics itself has received little or no attention. This paper introduces a novel methodology for risk and hazard assessment of airport surface operations, and models the relationships between airport characteristics, and (a) the rate of occurrences, (b) the severity of occurrences, and (c) the causal factors underlying occurrences. The results show for the first time how the characteristics of airports, and in particular its infrastructure and operations, influence the safety of surface operations. Copyright © 2015 Elsevier Ltd. and National Safety Council. Published by Elsevier Ltd. All rights reserved.

Agents and Patients in Physical Settings: Linguistic Cues Affect the Assignment of Causality in German and Tongan

PubMed Central

Bender, Andrea; Beller, Sieghard

2017-01-01

Linguistic cues may be considered a potent tool for focusing attention on causes or effects. In this paper, we explore how different cues affect causal assignments in German and Tongan. From a larger screening study, two parts are reported here: Part 1 dealt with syntactic variations, including word order (agent vs. patient in first/subject position) and case marking (e.g., as ergative vs. non-ergative in Tongan) depending on verb type (transitive vs. intransitive). For two physical settings (wood floating on water and a man breaking a glass), participants assigned causality to the two entities involved. In the floating setting, speakers of the two languages were sensitive to syntactic variations, but differed in the entity regarded as causative. In the breaking setting, the human agent was uniformly regarded as causative. Part 2 dealt with implicit verb causality. Participants assigned causality to subject or object of 16 verbs presented in minimal social scenarios. In German, all verbs showed a subject (agent) focus; in Tongan, the focus depended on the verb; and for nine verbs, the focus differed across languages. In conclusion, we discuss the question of domain-specificity of causal cognition, the role of the ergative as causal marker, and more general differences between languages. PMID:28736538

Model Selection Approach Suggests Causal Association between 25-Hydroxyvitamin D and Colorectal Cancer

PubMed Central

Theodoratou, Evropi; Farrington, Susan M.; Tenesa, Albert; Dunlop, Malcolm G.; McKeigue, Paul; Campbell, Harry

2013-01-01

Introduction 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. Methods 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. Results 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. Conclusion Results suggest causal association between 25-OHD and colorectal cancer, and support the need for randomised clinical trials for further confirmations. PMID:23717431

Three Cs in Measurement Models: Causal Indicators, Composite Indicators, and Covariates

PubMed Central

Bollen, Kenneth A.; Bauldry, Shawn

2013-01-01

In the last two decades attention to causal (and formative) indicators has grown. Accompanying this growth has been the belief that we can classify indicators into two categories, effect (reflective) indicators and causal (formative) indicators. This paper argues that the dichotomous view is too simple. Instead, there are effect indicators and three types of variables on which a latent variable depends: causal indicators, composite (formative) indicators, and covariates (the “three Cs”). Causal indicators have conceptual unity and their effects on latent variables are structural. Covariates are not concept measures, but are variables to control to avoid bias in estimating the relations between measures and latent variable(s). Composite (formative) indicators form exact linear combinations of variables that need not share a concept. Their coefficients are weights rather than structural effects and composites are a matter of convenience. The failure to distinguish the “three Cs” has led to confusion and questions such as: are causal and formative indicators different names for the same indicator type? Should an equation with causal or formative indicators have an error term? Are the coefficients of causal indicators less stable than effect indicators? Distinguishing between causal and composite indicators and covariates goes a long way toward eliminating this confusion. We emphasize the key role that subject matter expertise plays in making these distinctions. We provide new guidelines for working with these variable types, including identification of models, scaling latent variables, parameter estimation, and validity assessment. A running empirical example on self-perceived health illustrates our major points. PMID:21767021

Jordanian Pre-Service Teachers' and Technology Integration: A Human Resource Development Approach

ERIC Educational Resources Information Center

Al-Ruz, Jamal Abu; Khasawneh, Samer

2011-01-01

The purpose of this study was to test a model in which technology integration of pre-service teachers was predicted by a number of university-based and school-based factors. Initially, factors affecting technology integration were identified, and a research-based path model was developed to explain causal relationships between these factors. The…

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

PubMed Central

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 confidence intervals. PMID:26050256

Beyond Markov: Accounting for independence violations in causal reasoning.

PubMed

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.

Environmental influences on energy balance-related behaviors: A dual-process view

PubMed Central

Kremers, Stef PJ; de Bruijn, Gert-Jan; Visscher, Tommy LS; van Mechelen, Willem; de Vries, Nanne K; Brug, Johannes

2006-01-01

Background Studies on the impact of the 'obesogenic' environment have often used non-theoretical approaches. In this journal's debate and in other papers authors have argued the necessity of formulating conceptual models for differentiating the causal role of environmental influences on behavior. Discussion The present paper aims to contribute to the debate by presenting a dual-process view on the environment – behavior relationship. This view is conceptualized in the EnRG framework (Environmental Research framework for weight Gain prevention). In the framework, behavior is postulated to be the result of a simultaneous influence of conscious and unconscious processes. Environmental influences are hypothesized to influence behavior both indirectly and directly. The indirect causal mechanism reflects the mediating role of behavior-specific cognitions in the influence of the environment on behavior. A direct influence reflects the automatic, unconscious, influence of the environment on behavior. Specific personal and behavioral factors are postulated to moderate the causal path (i.e., inducing either the automatic or the cognitively mediated environment – behavior relation). In addition, the EnRG framework applies an energy balance-approach, stimulating the integrated study of determinants of diet and physical activity. Conclusion The application of a dual-process view may guide research towards causal mechanisms linking specific environmental features with energy balance-related behaviors in distinct populations. The present paper is hoped to contribute to the evolution of a paradigm that may help to disentangle the role of 'obesogenic' environmental factors. PMID:16700907

Age at Menarche and Time Spent in Education: A Mendelian Randomization Study.

PubMed

Gill, D; Del Greco M, F; Rawson, T M; Sivakumaran, P; Brown, A; Sheehan, N A; Minelli, C

2017-09-01

Menarche signifies the primary event in female puberty and is associated with changes in self-identity. It is not clear whether earlier puberty causes girls to spend less time in education. Observational studies on this topic are likely to be affected by confounding environmental factors. The Mendelian randomization (MR) approach addresses these issues by using genetic variants (such as single nucleotide polymorphisms, SNPs) as proxies for the risk factor of interest. We use this technique to explore whether there is a causal effect of age at menarche on time spent in education. Instruments and SNP-age at menarche estimates are identified from a Genome Wide Association Study (GWAS) meta-analysis of 182,416 women of European descent. The effects of instruments on time spent in education are estimated using a GWAS meta-analysis of 118,443 women performed by the Social Science Genetic Association Consortium (SSGAC). In our main analysis, we demonstrate a small but statistically significant causal effect of age at menarche on time spent in education: a 1 year increase in age at menarche is associated with 0.14 years (53 days) increase in time spent in education (95% CI 0.10-0.21 years, p = 3.5 × 10 -8 ). The causal effect is confirmed in sensitivity analyses. In identifying this positive causal effect of age at menarche on time spent in education, we offer further insight into the social effects of puberty in girls.

Drug Induced Liver Injury: Can Biomarkers Assist RUCAM in Causality Assessment?

PubMed Central

Teschke, Rolf; Schulze, Johannes; Eickhoff, Axel; Danan, Gaby

2017-01-01

Drug induced liver injury (DILI) is a potentially serious adverse reaction in a few susceptible individuals under therapy by various drugs. Health care professionals facing DILI are confronted with a wealth of drug-unrelated liver diseases with high incidence and prevalence rates, which can confound the DILI diagnosis. Searching for alternative causes is a key element of RUCAM (Roussel Uclaf Causality Assessment Method) to assess rigorously causality in suspected DILI cases. Diagnostic biomarkers as blood tests would be a great help to clinicians, regulators, and pharmaceutical industry would be more comfortable if, in addition to RUCAM, causality of DILI can be confirmed. High specificity and sensitivity are required for any diagnostic biomarker. Although some risk factors are available to evaluate liver safety of drugs in patients, no valid diagnostic or prognostic biomarker exists currently for idiosyncratic DILI when a liver injury occurred. Identifying a biomarker in idiosyncratic DILI requires detailed knowledge of cellular and biochemical disturbances leading to apoptosis or cell necrosis and causing leakage of specific products in blood. As idiosyncratic DILI is typically a human disease and hardly reproducible in animals, pathogenetic events and resulting possible biomarkers remain largely undisclosed. Potential new diagnostic biomarkers should be evaluated in patients with DILI and RUCAM-based established causality. In conclusion, causality assessment in cases of suspected idiosyncratic DILI is still best achieved using RUCAM since specific biomarkers as diagnostic blood tests that could enhance RUCAM results are not yet available. PMID:28398242

Preeminence of Staphylococcus aureus in infective endocarditis: a 1-year population-based survey.

PubMed

Selton-Suty, Christine; Célard, Marie; Le Moing, Vincent; Doco-Lecompte, Thanh; Chirouze, Catherine; Iung, Bernard; Strady, Christophe; Revest, Matthieu; Vandenesch, François; Bouvet, Anne; Delahaye, François; Alla, François; Duval, Xavier; Hoen, Bruno

2012-05-01

Observational studies showed that the profile of infective endocarditis (IE) significantly changed over the past decades. However, most studies involved referral centers. We conducted a population-based study to control for this referral bias. The objective was to update the description of characteristics of IE in France and to compare the profile of community-acquired versus healthcare-associated IE. A prospective population-based observational study conducted in all medical facilities from 7 French regions (32% of French individuals aged ≥18 years) identified 497 adults with Duke-Li-definite IE who were first admitted to the hospital in 2008. Main measures included age-standardized and sex-standardized incidence of IE and multivariate Cox regression analysis for risk factors of in-hospital death. The age-standardized and sex-standardized annual incidence of IE was 33.8 (95% confidence interval [CI], 30.8-36.9) cases per million inhabitants. The incidence was highest in men aged 75-79 years. A majority of patients had no previously known heart disease. Staphylococci were the most common causal agents, accounting for 36.2% of cases (Staphylococcus aureus, 26.6%; coagulase-negative staphylococci, 9.7%). Healthcare-associated IE represented 26.7% of all cases and exhibited a clinical pattern significantly different from that of community-acquired IE. S. aureus as the causal agent of IE was the most important factor associated with in-hospital death in community-acquired IE (hazard ratio [HR], 2.82 [95% CI, 1.72-4.61]) and the single factor in healthcare-associated IE (HR, 2.54 [95% CI, 1.33-4.85]). S. aureus became both the leading cause and the most important prognostic factor of IE, and healthcare-associated IE appeared as a major subgroup of the disease.

Does injury compensation lead to worse health after whiplash? A systematic review.

PubMed

Spearing, Natalie M; Connelly, Luke B; Gargett, Susan; Sterling, Michele

2012-06-01

One might expect that injury compensation would leave injured parties better off than they would otherwise have been, yet many believe that compensation does more harm than good. This study systematically reviews the evidence on this "compensation hypothesis" in relation to compensable whiplash injuries. PubMed, CINAHL, EMBASE, PEDro, PsycInfo, CCTR, Lexis, and EconLit were searched from the date of their inception to April 2010 to locate longitudinal studies, published in English, comparing the health outcomes of adults exposed/not exposed to compensation-related factors. Studies concerning serious neck injuries, using claimants only, or using proxy measures of health outcomes were excluded. Eleven studies were included. These examined the effect of lawyer involvement, litigation, claim submission, or previous claims on pain and other health outcomes. Among the 16 results reported were 9 statistically significant negative associations between compensation-related factors and health outcomes. Irrespective of the compensation-related factor involved and the health outcome measured, the quality of these studies was similar to studies that did not find a significant negative association: most took some measures to address selection bias, confounding, and measurement bias, and none resolved the potential for reverse causality bias that arises in the relationship between compensation-related factors and health. Unless ambiguous causal pathways are addressed, one cannot draw conclusions from statistical associations, regardless of their statistical significance and the extent of measures to address other sources of bias. Consequently, there is no clear evidence to support the idea that compensation and its related processes lead to worse health. Copyright © 2012 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

A causal analysis framework for land-use change and the potential role of bioenergy policy

DOE PAGES

Efroymson, Rebecca A.; Kline, Keith L.; Angelsen, Arild; ...

2016-10-05

Here we propose a causal analysis framework to increase the reliability of land-use change (LUC) models and the accuracy of net greenhouse gas (GHG) emissions calculations for biofuels. The health-sciences-inspired framework is used here to determine probable causes of LUC, with an emphasis on bioenergy and deforestation. Calculations of net GHG emissions for LUC are critical in determining whether a fuel qualifies as a biofuel or advanced biofuel category under national (U.S., U.K.), state (California), and European Union regulations. Biofuel policymakers and scientists continue to discuss whether presumed indirect land-use change (ILUC) estimates, which often involve deforestation, should be includedmore » in GHG accounting for biofuel pathways. Current estimates of ILUC for bioenergy rely largely on economic simulation models that focus on causal pathways involving global commodity trade and use coarse land cover data with simple land classification systems. ILUC estimates are highly uncertain, partly because changes are not clearly defined and key causal links are not sufficiently included in the models. The proposed causal analysis framework begins with a definition of the change that has occurred and proceeds to a strength-of-evidence approach based on types of epidemiological evidence including plausibility of the relationship, completeness of the causal pathway, spatial co-occurrence, time order, analogous agents, simulation model results, and quantitative agent response relationships.Lastly, we discuss how LUC may be allocated among probable causes for policy purposes and how the application of the framework has the potential to increase the validity of LUC models and resolve ILUC and biofuel controversies.« less

A causal analysis framework for land-use change and the potential role of bioenergy policy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Efroymson, Rebecca A.; Kline, Keith L.; Angelsen, Arild

Here we propose a causal analysis framework to increase the reliability of land-use change (LUC) models and the accuracy of net greenhouse gas (GHG) emissions calculations for biofuels. The health-sciences-inspired framework is used here to determine probable causes of LUC, with an emphasis on bioenergy and deforestation. Calculations of net GHG emissions for LUC are critical in determining whether a fuel qualifies as a biofuel or advanced biofuel category under national (U.S., U.K.), state (California), and European Union regulations. Biofuel policymakers and scientists continue to discuss whether presumed indirect land-use change (ILUC) estimates, which often involve deforestation, should be includedmore » in GHG accounting for biofuel pathways. Current estimates of ILUC for bioenergy rely largely on economic simulation models that focus on causal pathways involving global commodity trade and use coarse land cover data with simple land classification systems. ILUC estimates are highly uncertain, partly because changes are not clearly defined and key causal links are not sufficiently included in the models. The proposed causal analysis framework begins with a definition of the change that has occurred and proceeds to a strength-of-evidence approach based on types of epidemiological evidence including plausibility of the relationship, completeness of the causal pathway, spatial co-occurrence, time order, analogous agents, simulation model results, and quantitative agent response relationships.Lastly, we discuss how LUC may be allocated among probable causes for policy purposes and how the application of the framework has the potential to increase the validity of LUC models and resolve ILUC and biofuel controversies.« less

What Can Causal Networks Tell Us about Metabolic Pathways?

PubMed Central

Blair, Rachael Hageman; Kliebenstein, Daniel J.; Churchill, Gary A.

2012-01-01

Graphical models describe the linear correlation structure of data and have been used to establish causal relationships among phenotypes in genetic mapping populations. Data are typically collected at a single point in time. Biological processes on the other hand are often non-linear and display time varying dynamics. The extent to which graphical models can recapitulate the architecture of an underlying biological processes is not well understood. We consider metabolic networks with known stoichiometry to address the fundamental question: “What can causal networks tell us about metabolic pathways?”. Using data from an Arabidopsis BaySha population and simulated data from dynamic models of pathway motifs, we assess our ability to reconstruct metabolic pathways using graphical models. Our results highlight the necessity of non-genetic residual biological variation for reliable inference. Recovery of the ordering within a pathway is possible, but should not be expected. Causal inference is sensitive to subtle patterns in the correlation structure that may be driven by a variety of factors, which may not emphasize the substrate-product relationship. We illustrate the effects of metabolic pathway architecture, epistasis and stochastic variation on correlation structure and graphical model-derived networks. We conclude that graphical models should be interpreted cautiously, especially if the implied causal relationships are to be used in the design of intervention strategies. PMID:22496633

The psychophysics of comic: Effects of incongruity in causality and animacy.

PubMed

Parovel, Giulia; Guidi, Stefano

2015-07-01

According to several theories of humour (see Berger, 2012; Martin, 2007), incongruity - i.e., the presence of two incompatible meanings in the same situation - is a crucial condition for an event being evaluated as comical. The aim of this research was to test with psychophysical methods the role of incongruity in visual perception by manipulating the causal paradigm (Michotte, 1946/1963) to get a comic effect. We ran three experiments. In Experiment 1, we tested the role of speed ratio between the first and the second movement, and the effect of animacy cues (i.e. frog-like and jumping-like trajectories) in the second movement; in Experiment 2, we manipulated the temporal delay between the movements to explore the relationship between perceptual causal contingencies and comic impressions; in Experiment 3, we compared the strength of the comic impressions arising from incongruent trajectories based on animacy cues with those arising from incongruent trajectories not based on animacy cues (bouncing and rotating) in the second part of the causal event. General findings showed that the paradoxical juxtaposition of a living behaviour in the perceptual causal paradigm is a powerful factor in eliciting comic appreciations, coherently with the Bergsonian perspective in particular (Bergson, 2003), and with incongruity theories in general. Copyright © 2015 Elsevier B.V. All rights reserved.

Cope's Rule and Romer's theory: patterns of diversity and gigantism in eurypterids and Palaeozoic vertebrates

PubMed Central

Lamsdell, James C.; Braddy, Simon J.

2010-01-01

Gigantism is widespread among Palaeozoic arthropods, yet causal mechanisms, particularly the role of (abiotic) environmental factors versus (biotic) competition, remain unknown. The eurypterids (Arthropoda: Chelicerata) include the largest arthropods; gigantic predatory pterygotids (Eurypterina) during the Siluro-Devonian and bizarre sweep-feeding hibbertopterids (Stylonurina) from the Carboniferous to end-Permian. Analysis of family-level originations and extinctions among eurypterids and Palaeozoic vertebrates show that the diversity of Eurypterina waned during the Devonian, while the Placodermi radiated, yet Stylonurina remained relatively unaffected; adopting a sweep-feeding strategy they maintained their large body size by avoiding competition, and persisted throughout the Late Palaeozoic while the predatory nektonic Eurypterina (including the giant pterygotids) declined during the Devonian, possibly out-competed by other predators including jawed vertebrates. PMID:19828493

DES daughters in France: experts' points of view on the various genital, uterine and obstetric pathologies, and in utero DES exposure.

PubMed

Clement, R; Guilbaud, E; Barrios, L; Rougé-Maillart, C; Jousset, N; Rodat, O

2014-10-01

Compensation of diethylstilbestrol exposure depends on the judicial system. In France, girls having been exposed to diethylstilbestrol are currently being compensated, and each exposure victim is being evaluated. Fifty-nine expert evaluations were studied to determine the causal relation between exposure to diethylstilbestrol and the pathologies attributable to diethylstilbestrol. The following were taken into consideration: age at the first signs of the pathology; age of the sufferer at the time of evaluation; the pathologies grouped into five categories: fertility disorders - cancers - mishaps during pregnancy - psychosomatic complaints - pathologies of "3rd generation DES victims"; submission of proof of DES exposure; the degree of causality determined (direct, indirect, ruled out). 61% of the cases related to fertility disorders, 28.8% to cancer pathologies (clear-cell adenocarcinoma), 18.6% to mishaps during pregnancy, 8.5% to disorders resulting from preterm delivery, and 3.4% to psychosomatic disorders. Some cases involved a combination of two types of complaints. Indirect causality was determined in 47.1% of the cases involving primary sterility, in 66.7% involving secondary sterility, and in 5 out of 6 cases of total sterility. There is direct causality between in utero diethylstilbestrol exposure and vaginal or cervical clear cell adenocarcinoma. Causality is indirect in the case of disorders linked to prematurity in third generation victims. Causality was determined by the experts on the basis of scientific criteria which attribute the presenting pathologies to diethylstilbestrol exposure. When other risk factors come into play, or when exposure is indirect (third generation), this causality is diminished. © IMechE 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Identification of causal genes for complex traits

PubMed Central

Hormozdiari, Farhad; Kichaev, Gleb; Yang, Wen-Yun; Pasaniuc, Bogdan; Eskin, Eleazar

2015-01-01

Motivation: Although genome-wide association studies (GWAS) have identified thousands of variants associated with common diseases and complex traits, only a handful of these variants are validated to be causal. We consider ‘causal variants’ as variants which are responsible for the association signal at a locus. As opposed to association studies that benefit from linkage disequilibrium (LD), the main challenge in identifying causal variants at associated loci lies in distinguishing among the many closely correlated variants due to LD. This is particularly important for model organisms such as inbred mice, where LD extends much further than in human populations, resulting in large stretches of the genome with significantly associated variants. Furthermore, these model organisms are highly structured and require correction for population structure to remove potential spurious associations. Results: In this work, we propose CAVIAR-Gene (CAusal Variants Identification in Associated Regions), a novel method that is able to operate across large LD regions of the genome while also correcting for population structure. A key feature of our approach is that it provides as output a minimally sized set of genes that captures the genes which harbor causal variants with probability ρ. Through extensive simulations, we demonstrate that our method not only speeds up computation, but also have an average of 10% higher recall rate compared with the existing approaches. We validate our method using a real mouse high-density lipoprotein data (HDL) and show that CAVIAR-Gene is able to identify Apoa2 (a gene known to harbor causal variants for HDL), while reducing the number of genes that need to be tested for functionality by a factor of 2. Availability and implementation: Software is freely available for download at genetics.cs.ucla.edu/caviar. Contact: eeskin@cs.ucla.edu PMID:26072484

Identification of causal genes for complex traits.

PubMed

Hormozdiari, Farhad; Kichaev, Gleb; Yang, Wen-Yun; Pasaniuc, Bogdan; Eskin, Eleazar

2015-06-15

Although genome-wide association studies (GWAS) have identified thousands of variants associated with common diseases and complex traits, only a handful of these variants are validated to be causal. We consider 'causal variants' as variants which are responsible for the association signal at a locus. As opposed to association studies that benefit from linkage disequilibrium (LD), the main challenge in identifying causal variants at associated loci lies in distinguishing among the many closely correlated variants due to LD. This is particularly important for model organisms such as inbred mice, where LD extends much further than in human populations, resulting in large stretches of the genome with significantly associated variants. Furthermore, these model organisms are highly structured and require correction for population structure to remove potential spurious associations. In this work, we propose CAVIAR-Gene (CAusal Variants Identification in Associated Regions), a novel method that is able to operate across large LD regions of the genome while also correcting for population structure. A key feature of our approach is that it provides as output a minimally sized set of genes that captures the genes which harbor causal variants with probability ρ. Through extensive simulations, we demonstrate that our method not only speeds up computation, but also have an average of 10% higher recall rate compared with the existing approaches. We validate our method using a real mouse high-density lipoprotein data (HDL) and show that CAVIAR-Gene is able to identify Apoa2 (a gene known to harbor causal variants for HDL), while reducing the number of genes that need to be tested for functionality by a factor of 2. Software is freely available for download at genetics.cs.ucla.edu/caviar. © The Author 2015. Published by Oxford University Press.

Pairwise measures of causal direction in the epidemiology of sleep problems and depression.

PubMed

Rosenström, Tom; Jokela, Markus; Puttonen, Sampsa; Hintsanen, Mirka; Pulkki-Råback, Laura; Viikari, Jorma S; Raitakari, Olli T; Keltikangas-Järvinen, Liisa

2012-01-01

Depressive mood is often preceded by sleep problems, suggesting that they increase the risk of depression. Sleep problems can also reflect prodromal symptom of depression, thus temporal precedence alone is insufficient to confirm causality. The authors applied recently introduced statistical causal-discovery algorithms that can estimate causality from cross-sectional samples in order to infer the direction of causality between the two sets of symptoms from a novel perspective. Two common-population samples were used; one from the Young Finns study (690 men and 997 women, average age 37.7 years, range 30-45), and another from the Wisconsin Longitudinal study (3101 men and 3539 women, average age 53.1 years, range 52-55). These included three depression questionnaires (two in Young Finns data) and two sleep problem questionnaires. Three different causality estimates were constructed for each data set, tested in a benchmark data with a (practically) known causality, and tested for assumption violations using simulated data. Causality algorithms performed well in the benchmark data and simulations, and a prediction was drawn for future empirical studies to confirm: for minor depression/dysphoria, sleep problems cause significantly more dysphoria than dysphoria causes sleep problems. The situation may change as depression becomes more severe, or more severe levels of symptoms are evaluated; also, artefacts due to severe depression being less well presented in the population data than minor depression may intervene the estimation for depression scales that emphasize severe symptoms. The findings are consistent with other emerging epidemiological and biological evidence.

Causal structures in Gauss-Bonnet gravity

NASA Astrophysics Data System (ADS)

Izumi, Keisuke

2014-08-01

We analyze causal structures in Gauss-Bonnet gravity. It is known that Gauss-Bonnet gravity potentially has superluminal propagation of gravitons due to its noncanonical kinetic terms. In a theory with superluminal modes, an analysis of causality based on null curves makes no sense, and thus, we need to analyze them in a different way. In this paper, using the method of the characteristics, we analyze the causal structure in Gauss-Bonnet gravity. We have the result that, on a Killing horizon, gravitons can propagate in the null direction tangent to the Killing horizon. Therefore, a Killing horizon can be a causal edge as in the case of general relativity; i.e. a Killing horizon is the "event horizon" in the sense of causality. We also analyze causal structures on nonstationary solutions with (D-2)-dimensional maximal symmetry, including spherically symmetric and flat spaces. If the geometrical null energy condition, RABNANB≥0 for any null vector NA, is satisfied, the radial velocity of gravitons must be less than or equal to that of light. However, if the geometrical null energy condition is violated, gravitons can propagate faster than light. Hence, on an evaporating black hole where the geometrical null energy condition is expected not to hold, classical gravitons can escape from the "black hole" defined with null curves. That is, the causal structures become nontrivial. It may be one of the possible solutions for the information loss paradox of evaporating black holes.

Mapping historical information for better understanding the causality factors of past disasters

NASA Astrophysics Data System (ADS)

Boudou, Martin; Lang, Michel; Vinet, Freddy; Coeur, Denis

2015-04-01

The Flood Directive of 2007 promotes the use of historical information in order to mitigate the impact of future extreme events. According to this text, the study of past events offers new insights for better understanding the causality factors of a disaster, from hydrometeorological keys to socio-political repercussions of the flood. In this presentation we decided to focus on the study of factors leading to the exceptionality of a hydrological flood event. This aspect is regularly pointed out by the feedbacks carried out after a catastrophic event and remains a subject of debate for risk managers. The role of antecedent meteorological conditions is especially underestimated by local authorities. These factors can however be considered as a key issue to appreciate the exceptional character of a hydrological disaster. For example the 2013 June floods in France that affected the region of Pyrenees revealed the significant contribution of snow melting to the discharges recorded. In an article of 2014, Schröter et al. showed that the soil moisture can be considered as a key driver of the generalised flood hazard intensity that affected Germany over the same month of June 2013. With regard to these assessments, some considerations emerge. Does a diachronic appraisal of past disasters point out the main issues responsible for an exceptional flood hazard level? Is there common causality issues involved into these extreme hydrological events? In order to answer these questions this presentation proposes a comparative analysis of nine major floods that impacted the French territory during the XXth century (from 1910 to 2010). The set is composed by different flood typologies (from torrential events to floods resulting from groundwater level rising) so as to get a complete view of flood risk in France. The methodology proposed relies on a cartographic approach to highlight the causality factors of these past hydrological disasters. For instance, mapping the rainfall data over the representation of the maximum discharges recorded can help to understand the significance of the rainfall event. In some cases, the use of textual historical information allows to emphasize the significance of other factors such as snow melting or the influence of anthropogenic infrastructures. Indeed, mapping historical information seems to be an original approach to represent the various spatial and temporal scales of historical disasters and an interesting tool to explore the exceptionality of the hazard level.

Does bilirubin protect against developing diabetes mellitus?

PubMed

Breimer, Lars H; Mikhailidis, Dimitri P

2016-01-01

After 25 years of evaluating bilirubin as a possible protective agent in neonatal and cardiovascular disease, interest has moved on to a exploring a possible protective role in diabetes mellitus (DM). This review finds conflicting prospective data for a protective relationship though there are retrospective, case-controlled data, that can only show association, which is not causality. Only prospective studies can show causality. Also, it would appear that the underlying biochemical assumptions do not readily translate from the animal to the human setting. Given that many factors impact on circulating bilirubin levels, it is not surprising that a clear-cut answer is not available; the jury is still out. Any relationship between DM and bilirubin might relate to intermediates in bilirubin metabolism, including relationships involving the genes for the enzymes participating in those steps. Nevertheless, the pursuit of bilirubin in disease causation is opening new avenues for research and if it is established that serum bilirubin can predict risks, much will have been achieved. The answer may have to come from molecular genetic analyses. Copyright © 2016 Elsevier Inc. All rights reserved.

Psychosocial work factors, major depressive and generalised anxiety disorders: results from the French national SIP study.

PubMed

Murcia, Marie; Chastang, Jean-François; Niedhammer, Isabelle

2013-04-25

Anxiety and depression are prevalent mental disorders in working populations. The risk factors of these disorders are not completely well known. Developing knowledge on occupational risk factors for mental disorders appears crucial. This study investigates the association between various classical and emergent psychosocial work factors and major depressive and generalised anxiety disorders in the French working population. The study was based on a national random sample of 3765 men and 3944 women of the French working population (SIP 2006 survey). Major Depressive Disorder (MDD) and Generalised Anxiety Disorder (GAD) were measured using a standardised diagnostic interview (MINI). Occupational factors included psychosocial work factors as well as biomechanical, physical, and chemical exposures. Adjustment variables included age, occupation, marital status, social support, and life events. Multivariate analysis was performed using logistic regression analysis. Low decision latitude, overcommitment, and emotional demands were found to be risk factors for both MDD-GAD among both genders. Other risk factors were observed: high psychological demands, low reward, ethical conflict, and job insecurity, but differences were found according to gender and outcome. Significant interaction terms were observed suggesting that low decision latitude, high psychological demands, and job insecurity had stronger effects on mental disorders for men than for women. Given the cross-sectional study design, no causal conclusion could be drawn. This study showed significant associations between classical and emergent psychosocial work factors and MDD-GAD. Preventive actions targeting various psychosocial work factors, including emergent factors, may help to reduce mental disorders at the workplace. Copyright © 2012 Elsevier B.V. All rights reserved.

Causality Assessment of Olfactory and Gustatory Dysfunction Associated with Intranasal Fluticasone Propionate: Application of the Bradford Hill Criteria.

PubMed

Muganurmath, Chandrashekhar S; Curry, Amy L; Schindzielorz, Andrew H

2018-02-01

Causality assessment is crucial to post-marketing pharmacovigilance and helps optimize safe and appropriate use of medicines by patients in the real world. Self-reported olfactory and gustatory dysfunction are common in the general population as well as in patients with allergic rhinitis and nasal polyposis. Intranasal corticosteroids, including intranasal fluticasone propionate (INFP), are amongst the most effective drugs indicated in the treatment of allergic rhinitis and nasal polyposis. While intranasal corticosteroids are associated with olfactory and gustatory dysfunction and are currently labeled for these adverse events, causality assessment has not been performed to date. Although there is no single widely accepted method to assess causality in pharmacovigilance, the Bradford Hill criteria offer a robust and comprehensive approach because nine distinct aspects of an observed potential drug-event association are assessed. In this literature-based narrative review, Hill's criteria were applied to determine causal inference between INFP and olfactory and gustatory dysfunction.

Estimating Causal Effects with Ancestral Graph Markov Models

PubMed Central

Malinsky, Daniel; Spirtes, Peter

2017-01-01

We present an algorithm for estimating bounds on causal effects from observational data which combines graphical model search with simple linear regression. We assume that the underlying system can be represented by a linear structural equation model with no feedback, and we allow for the possibility of latent variables. Under assumptions standard in the causal search literature, we use conditional independence constraints to search for an equivalence class of ancestral graphs. Then, for each model in the equivalence class, we perform the appropriate regression (using causal structure information to determine which covariates to include in the regression) to estimate a set of possible causal effects. Our approach is based on the “IDA” procedure of Maathuis et al. (2009), which assumes that all relevant variables have been measured (i.e., no unmeasured confounders). We generalize their work by relaxing this assumption, which is often violated in applied contexts. We validate the performance of our algorithm on simulated data and demonstrate improved precision over IDA when latent variables are present. PMID:28217244

Verification of causal influences of reasoning skills and epistemology on physics conceptual learning

NASA Astrophysics Data System (ADS)

Ding, Lin

2014-12-01

This study seeks to test the causal influences of reasoning skills and epistemologies on student conceptual learning in physics. A causal model, integrating multiple variables that were investigated separately in the prior literature, is proposed and tested through path analysis. These variables include student preinstructional reasoning skills measured by the Classroom Test of Scientific Reasoning, pre- and postepistemological views measured by the Colorado Learning Attitudes about Science Survey, and pre- and postperformance on Newtonian concepts measured by the Force Concept Inventory. Students from a traditionally taught calculus-based introductory mechanics course at a research university participated in the study. Results largely support the postulated causal model and reveal strong influences of reasoning skills and preinstructional epistemology on student conceptual learning gains. Interestingly enough, postinstructional epistemology does not appear to have a significant influence on student learning gains. Moreover, pre- and postinstructional epistemology, although barely different from each other on average, have little causal connection between them.

Causal essentialism in kinds.

PubMed

Ahn, Woo-kyoung; Taylor, Eric G; Kato, Daniel; Marsh, Jessecae K; Bloom, Paul

2013-06-01

The current study examines causal essentialism, derived from psychological essentialism of concepts. We examine whether people believe that members of a category share some underlying essence that is both necessary and sufficient for category membership and that also causes surface features. The main claim is that causal essentialism is restricted to categories that correspond to our intuitive notions of existing kinds and hence is more attenuated for categories that are based on arbitrary criteria. Experiments 1 and 3 found that people overtly endorse causal essences in nonarbitrary kinds but are less likely to do so for arbitrary categories. Experiments 2 and 4 found that people were more willing to generalize a member's known causal relations (or lack thereof) when dealing with a kind than when dealing with an arbitrary category. These differences between kinds and arbitrary categories were found across various domains-not only for categories of living things, but also for artefacts. These findings have certain real-world implications, including how people make sense of mental disorders that are treated as real kinds.

Self-organizing map analysis using multivariate data from theophylline tablets predicted by a thin-plate spline interpolation.

PubMed

Yasuda, Akihito; Onuki, Yoshinori; Obata, Yasuko; Yamamoto, Rie; Takayama, Kozo

2013-01-01

The "quality by design" concept in pharmaceutical formulation development requires the establishment of a science-based rationale and a design space. We integrated thin-plate spline (TPS) interpolation and Kohonen's self-organizing map (SOM) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline tablets were prepared based on a standard formulation. The tensile strength, disintegration time, and stability of these variables were measured as response variables. These responses were predicted quantitatively based on nonlinear TPS. A large amount of data on these tablets was generated and classified into several clusters using an SOM. The experimental values of the responses were predicted with high accuracy, and the data generated for the tablets were classified into several distinct clusters. The SOM feature map allowed us to analyze the global and local correlations between causal factors and tablet characteristics. The results of this study suggest that increasing the proportion of microcrystalline cellulose (MCC) improved the tensile strength and the stability of tensile strength of these theophylline tablets. In addition, the proportion of MCC has an optimum value for disintegration time and stability of disintegration. Increasing the proportion of magnesium stearate extended disintegration time. Increasing the compression force improved tensile strength, but degraded the stability of disintegration. This technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline tablet formulations.

A Children of Twins Study of parental divorce and offspring psychopathology.

PubMed

D'Onofrio, Brian M; Turkheimer, Eric; Emery, Robert E; Maes, Hermine H; Silberg, Judy; Eaves, Lindon J

2007-07-01

Although parental divorce is associated with increased substance use and internalizing problems, experiencing the separation of one's parents may not cause these outcomes. The relations may be due to genetic or environmental selection factors, characteristics that lead to both marital separation and offspring functioning. We used the Children of Twins (CoT) Design to explore whether unmeasured genetic or environmental factors related to the twin parent, and measured characteristics of both parents, account for the association between parental divorce and offspring substance use and internalizing problems. The association between parental divorce and offspring substance use problems remained robust when controlling for genetic and environmental risk from the twin parent associated with parental divorce, and measured characteristics of both parents. The results do not prove, but are consistent with, a causal connection. In contrast, the analyses suggest that shared genetic liability in parents and their offspring accounts for the increased risk of internalizing problems in adult offspring from divorced families. The study illustrates that unmeasured genetic and environmental selection factors must be considered when studying parental divorce. In explaining associations between parental divorce and young-adult adjustment, our evidence suggests that selection versus causal mechanisms may operate differently for substance abuse (a causal relation) and internalizing problems (an artifact of selection). The CoT design only controls for the genetic and environmental characteristics of one parent; thus, additional genetically informed analyses are needed.

The Global Drivers of Photosynthesis and Light Use Efficiency Seasonality: A Granger Frequency Causality Analysis

NASA Astrophysics Data System (ADS)

Green, J.; Lee, J. E.; Gentine, P.; Berry, J. A.; Konings, A. G.

2015-12-01

hotosynthesis and light use efficiency (LUE) are major factors in the evolution of the continental carbon cycle due to their contribution to gross primary production (GPP). However, while the drivers of photosynthesis and LUE on a plant or canopy scale can often be identified, significant uncertainties exist when modeling these on a global scale. This is due to sparse observations in regions such as the tropics and the lack of a direct global observation dataset. Although others have attempted to address this issue using correlations (Beer, 2010) or calculating GPP from vegetation indices (Running, 2004), in this study we take a new approach. We combine the statistical method of Granger frequency causality and partial Granger frequency causality with remote sensing data products (including sun-induced fluorescence used as a proxy for GPP) to determine the main environmental drivers of GPP across the globe. References:Beer, C., M. Reichstein, E. Tomelleri, P. Ciais, M. Jung, N. Carvalhais, C. Ro¨denbeck, M. Altaf Arain, D. Baldocchi, G. B. Bonan, A. Bondeau, A. Cescatti, G. Lasslop, A. Lindroth, M. Lomas, S. Luyssaert, H. Margolis, K. W. Oleson, O. Roupsard, E. Veenendaal, N. Viovy, C. Williams, I. Woodward, and D. Papale, 2010: Terrestrial Gross Carbon Dioxide Uptake: Global Distribution and Covariation with Climate. doi: 10.1126/science.1184984. Running, S.W., Nemani, R. R., Heinsch, F. A., Zhao, M., Reeves, M., Hashimoto, H., 2004. A Continuous Satellite Derived Measure of Global Terrestrial Primary Production. BioScience 54(6), 547-560.

Applying a Multiple Group Causal Indicator Modeling Framework to the Reading Comprehension Skills of Third, Seventh, and Tenth Grade Students

PubMed Central

Tighe, Elizabeth L.; Wagner, Richard K.; Schatschneider, Christopher

2015-01-01

This study demonstrates the utility of applying a causal indicator modeling framework to investigate important predictors of reading comprehension in third, seventh, and tenth grade students. The results indicated that a 4-factor multiple indicator multiple indicator cause (MIMIC) model of reading comprehension provided adequate fit at each grade level. This model included latent predictor constructs of decoding, verbal reasoning, nonverbal reasoning, and working memory and accounted for a large portion of the reading comprehension variance (73% to 87%) across grade levels. Verbal reasoning contributed the most unique variance to reading comprehension at all grade levels. In addition, we fit a multiple group 4-factor MIMIC model to investigate the relative stability (or variability) of the predictor contributions to reading comprehension across development (i.e., grade levels). The results revealed that the contributions of verbal reasoning, nonverbal reasoning, and working memory to reading comprehension were stable across the three grade levels. Decoding was the only predictor that could not be constrained to be equal across grade levels. The contribution of decoding skills to reading comprehension was higher in third grade and then remained relatively stable between seventh and tenth grade. These findings illustrate the feasibility of using MIMIC models to explain individual differences in reading comprehension across the development of reading skills. PMID:25821346

Flood regimes in a changing world: What do we know?

NASA Astrophysics Data System (ADS)

Bloeschl, G.

2015-12-01

There has been a surprisingly large number of major floods in the last years around the world which suggests that floods may have increased and will continue to increase in the next decades. However, the realism of such changes is still hotly discussed in the literature. In this presentation I will argue that a fresh look is needed at the flood change problem in terms of the causal factors including river training, land use changes and climate variability. Analysing spatial patterns of dynamic flood characteristics helps learn form the rich diversity of flood processes across the landscape. I will present a number of examples across Europe to illustrate the range of flood generation processes and the causal factors of changes in the flood regime. On the basis of these examples, I will demonstrate how comparative hydrology can assist in learning from the differences of flood characteristics between catchments both for present and future conditions. Focus on the interactions of the natural and human water system will be instrumental in making meaningful statements about future floods in a changing world. References Hall et al. (2014) Understanding Flood Regime Changes in Europe: A state of the art assessment. Hydrol. Earth Sys. Sc., 18, 2735-2772. Blöschl et al. (2015) Increasing river floods: fiction or reality? Wiley Interdisciplinary Reviews: Water. doi: 10.1002/wat2.1079

Reflecting on explanatory ability: A mechanism for detecting gaps in causal knowledge.

PubMed

Johnson, Dan R; Murphy, Meredith P; Messer, Riley M

2016-05-01

People frequently overestimate their understanding-with a particularly large blind-spot for gaps in their causal knowledge. We introduce a metacognitive approach to reducing overestimation, termed reflecting on explanatory ability (REA), which is briefly thinking about how well one could explain something in a mechanistic, step-by-step, causally connected manner. Nine experiments demonstrated that engaging in REA just before estimating one's understanding substantially reduced overestimation. Moreover, REA reduced overestimation with nearly the same potency as generating full explanations, but did so 20 times faster (although only for high complexity objects). REA substantially reduced overestimation by inducing participants to quickly evaluate an object's inherent causal complexity (Experiments 4-7). REA reduced overestimation by also fostering step-by-step, causally connected processing (Experiments 2 and 3). Alternative explanations for REA's effects were ruled out including a general conservatism account (Experiments 4 and 5) and a covert explanation account (Experiment 8). REA's overestimation-reduction effect generalized beyond objects (Experiments 1-8) to sociopolitical policies (Experiment 9). REA efficiently detects gaps in our causal knowledge with implications for improving self-directed learning, enhancing self-insight into vocational and academic abilities, and even reducing extremist attitudes. (c) 2016 APA, all rights reserved).

Inability of the entropy vector method to certify nonclassicality in linelike causal structures

NASA Astrophysics Data System (ADS)

Weilenmann, Mirjam; Colbeck, Roger

2016-10-01

Bell's theorem shows that our intuitive understanding of causation must be overturned in light of quantum correlations. Nevertheless, quantum mechanics does not permit signaling and hence a notion of cause remains. Understanding this notion is not only important at a fundamental level, but also for technological applications such as key distribution and randomness expansion. It has recently been shown that a useful way to decide which classical causal structures could give rise to a given set of correlations is to use entropy vectors. These are vectors whose components are the entropies of all subsets of the observed variables in the causal structure. The entropy vector method employs causal relationships among the variables to restrict the set of possible entropy vectors. Here, we consider whether the same approach can lead to useful certificates of nonclassicality within a given causal structure. Surprisingly, we find that for a family of causal structures that includes the usual bipartite Bell structure they do not. For all members of this family, no function of the entropies of the observed variables gives such a certificate, in spite of the existence of nonclassical correlations. It is therefore necessary to look beyond entropy vectors to understand cause from a quantum perspective.

Bayesian networks improve causal environmental ...

EPA Pesticide Factsheets

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

Social determinants of common metabolic risk factors (high blood pressure, high blood sugar, high body mass index and high waist-hip ratio) of major non-communicable diseases in South Asia region: a systematic review protocol.

PubMed

Sharma, Sudesh Raj; Mishra, Shiva Raj; Wagle, Kusum; Page, Rachel; Matheson, Anna; Lambrick, Danielle; Faulkner, James; Lounsbury, David; Vaidya, Abhinav

2017-09-07

Prevalence of non-communicable diseases has been increasing at a greater pace in developing countries and, in particular, the South Asia region. Various behavioral, social and environmental factors present in this region perpetuate common metabolic risk factors of non-communicable diseases. This study will identify social determinants of common metabolic risk factors of major non-communicable diseases in the context of the South Asian region and map their causal pathway. A systematic review of selected articles will be carried out following Cochrane guidelines. Review will be guided by Social Determinants of Health Framework developed by the World Health Organization to extract social determinants of metabolic risk factors of non-communicable diseases from studies. A distinct search strategy will be applied using key words to screen relevant studies from online databases. Primary and grey literature published from the year 2000 to 2016 and studies with discussion on proximal and distal determinants of non-communicable risk factors among adults of the South Asia region will be selected. They will be further checked for quality, and a matrix illustrating contents of selected articles will be developed. Thematic content analysis will be done to trace social determinants and their interaction with metabolic risk factors. Findings will be illustrated in causal loop diagrams with social determinants of risk factors along with their interaction (feedback mechanism). The review will describe the interplay of social determinants of common NCD metabolic risk factors in the form of causal loop diagram. Findings will be structured in two parts: the first part will explain the linkage between proximal determinants with the metabolic risk factors and the second part will describe the linkage among the risk factors, proximal determinants and distal determinants. Evidences across different regions will be discussed to compare and validate and/or contrast the findings. Possible bias and limitations of this study will also be discussed. PROSPERO CRD42017067212.

Judgments of cause and blame: the effects of intentionality and foreseeability.

PubMed

Lagnado, David A; Channon, Shelley

2008-09-01

What are the factors that influence everyday attributions of cause and blame? The current studies focus on sequences of events that lead to adverse outcomes, and examine people's cause and blame ratings for key events in these sequences. Experiment 1 manipulated the intentional status of candidate causes and their location in a causal chain. Participants rated intentional actions as more causal, and more blameworthy, than unintentional actions or physical events. There was also an overall effect of location, with later events assigned higher ratings than earlier events. Experiment 2 manipulated both intentionality and foreseeability. The preference for intentional actions was replicated, and there was a strong influence of foreseeability: actions were rated as more causal and more blameworthy when they were highly foreseeable. These findings are interpreted within two prominent theories of blame, [Shaver, K. G. (1985). The attribution of blame: Causality, responsibility, and blameworthiness. New York: Springer-Verlag] and [Alicke, M. D. (2000). Culpable control and the psychology of blame. Psychological Bulletin, 126, 556-574]. Overall, it is argued that the data are more consistent with Alicke's model of culpable control.

Black Women's Achievement Orientation: Motivational and Cognitive Factors

ERIC Educational Resources Information Center

Murray, Saundra Rice; Mednick, Martha Tamara Shuch

1977-01-01

The literature on motivational and cognitive factors related to the achievement orientation of black women is reviewed. Achievement motivation and fear of success are discussed, and the inconclusiveness of the findings for black women is noted. Limited data concerning black women's expectations for and causal attributions about achievement…

Sustainability Reporting Experience by Universities: A Causal Configuration Approach

ERIC Educational Resources Information Center

Zorio-Grima, Ana; Sierra-García, Laura; Garcia-Benau, Maria A.

2018-01-01

Purpose: The purpose of this research is to identify the combinations of factors leading to experience in sustainability reporting by Spanish public universities. Design/methodology/approach: Using a sample of 49 public universities in Spain, this paper identifies the combinations of factors on innovation profile, political and internal factors…

The multidimensional causal factors of 'wet litter' in chicken-meat production.

PubMed

Dunlop, Mark W; Moss, Amy F; Groves, Peter J; Wilkinson, Stuart J; Stuetz, Richard M; Selle, Peter H

2016-08-15

The problem of 'wet litter', which occurs primarily in grow-out sheds for meat chickens (broilers), has been recognised for nearly a century. Nevertheless, it is an increasingly important problem in contemporary chicken-meat production as wet litter and associated conditions, especially footpad dermatitis, have developed into tangible welfare issues. This is only compounded by the market demand for chicken paws and compromised bird performance. This review considers the multidimensional causal factors of wet litter. While many causal factors can be listed it is evident that the critical ones could be described as micro-environmental factors and chief amongst them is proper management of drinking systems and adequate shed ventilation. Thus, this review focuses on these environmental factors and pays less attention to issues stemming from health and nutrition. Clearly, there are times when related avian health issues of coccidiosis and necrotic enteritis cannot be overlooked and the development of efficacious vaccines for the latter disease would be advantageous. Presently, the inclusion of phytate-degrading enzymes in meat chicken diets is routine and, therefore, the implication that exogenous phytases may contribute to wet litter is given consideration. Opinion is somewhat divided as how best to counter the problem of wet litter as some see education and extension as being more beneficial than furthering research efforts. However, it may prove instructive to assess the practice of whole grain feeding in relation to litter quality and the incidence of footpad dermatitis. Additional research could investigate the relationships between dietary concentrations of key minerals and the application of exogenous enzymes with litter quality. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

Application of the revised WHO causality assessment protocol for adverse events following immunization in India.

PubMed

Singh, Awnish Kumar; Wagner, Abram L; Joshi, Jyoti; Carlson, Bradley F; Aneja, Satinder; Boulton, Matthew L

2017-07-24

In 2013, the World Health Organization (WHO) and CIOMS introduced a revised Causality Assessment Protocol (CAP) for Adverse Events following Immunization (AEFI). India is one of the first countries to adopt the revised CAP. This study describes the application of the revised CAP in India. We describe use of CAP by India's AEFI surveillance program to assess reported AEFIs. Using publicly available results of causality assessment for reported AEFIs, we describe the results by demographic characteristics and review the trends for the results of the causality assessment. A total of 771 reports of AEFI between January 2012 and January 2015, completed causality review by August 2016. The cases were reported as belonging to a cluster (54%; n=302), hospitalized or requiring hospitalization (41%; n=270), death (25%; n=195), or resulting in disability (0.4%; n=3). The most common combinations of vaccines leading to report of an AEFI were DTwP, Hepatitis B, and OPV (14%; n=106), followed by Pentavalent and OPV (13%; n=103), and JE vaccine (13%; n=101). Using the WHO Algorithm, most AEFI reports (89%, n=683) were classifiable. Classifiable AEFI reports included those with a consistent causal association (53%; n=407), an inconsistent causal association (29%; n=226) or were indeterminate causal association with implicated vaccine(s) or vaccination process (6.5%; n=50) (Fig. 1); 88 reports remained unclassifiable. The revised CAP was informative and useful in classifying most of the reviewed AEFIs in India. Unclassifiable reports could be minimized with more complete information from health records. Improvements in causality assessment, and standardization in reporting between countries, can improve public confidence in vaccine system performance and identify important vaccine safety signals. Copyright © 2017 Elsevier Ltd. All rights reserved.

The neurophysiology of sexual arousal.

PubMed

Schober, Justine M; Pfaff, Donald

2007-09-01

Our understanding of the process and initiation of sexual arousal is being enhanced by both animal and human studies, inclusive of basic science principles and research on clinical outcomes. Sexual arousal is dependent on neural (sensory and cognitive) factors, hormonal factors, genetic factors and, in the human case, the complex influences of culture and context. Sexual arousal activates the cognitive and physiologic processes that can eventually lead to sexual behavior. Sexual arousal comprises a particular subset of central nervous system arousal functions which depend on primitive, fundamental arousal mechanisms that cause generalized brain activity, but are manifest in a sociosexual context. The neurophysiology of sexual arousal is seen as a bidirectional system universal to all vertebrates. The following review includes known neural and genomic mechanisms of a hormone-dependent circuit for simple sex behavior. New information about hormone effects on causal steps related to sex hormones' nuclear receptor isoforms expressed by hypothalamic neurons continues to enrich our understanding of this neurophysiology.

Interrupting Intergenerational Cycles of Maternal Obesity

PubMed Central

Gillman, Matthew W.

2016-01-01

Factors operating in the preconception and prenatal periods, such as maternal obesity, excessive gestational weight gain, and gestational diabetes, predict a substantial fraction of childhood obesity as well as lifelong adverse health consequences in the mother. These periods may lend themselves to successful intervention to reduce such risk factors because parents may be especially willing to change behavior if it confers health advantages to their children. If effective interventions started before or during pregnancy can be maintained after birth, they have the potential to lower the risk of both maternal obesity in the next pregnancy and obesity in the growing child, thus helping to interrupt maternal and child inter-generational vicious cycles of obesity, diabetes, and related cardiometabolic health consequences. While this paradigm is appealing, challenges include determining the magnitude, causality, and modifiability of these risk factors, and quantifying any adverse consequences of intervention. PMID:27088333

Social-relational risk factors for predicting elder physical abuse: an ecological bi-focal model.

PubMed

von Heydrich, Levente; Schiamberg, Lawrence B; Chee, Grace

2012-01-01

Annually in the United States, 1 to 5 million older adults, 65 and above, are physically or sexually injured or mistreated by their caregivers in family settings. This study examined the prevalence and risk factors involved in elder physical abuse by adult child caregivers, moving from the immediate elderly parent/adult child relationship context to more distal social support contexts, utilizing a subsample of 203 elderly participants from the Midlife Development in the United States study (MIDUS II, 2004-2006). LISREL modeling examined causal pathways between elderly demographic characteristics, physical/emotional health, and behavioral and contextual characteristics from an ecological perspective. Data modeling was accomplished using Mplus, PAXW, and SYSTAT statistical software packages. Results indicate that latent factors including older adult health, social isolation of the older adult, and adult child characteristics were significantly associated with elder physical abuse, as mediated by the quality of the elderly parent/adult child relationship.

Characteristics and causal factors of hysteresis in the hydrodynamics of a large floodplain system: Poyang Lake (China)

NASA Astrophysics Data System (ADS)

Zhang, X. L.; Zhang, Q.; Werner, A. D.; Tan, Z. Q.

2017-10-01

A previous modeling study of the lake-floodplain system of Poyang Lake (China) revealed complex hysteretic relationships between stage, storage volume and surface area. However, only hypothetical causal factors were presented, and the reasons for the occurrence of both clockwise and counterclockwise hysteretic functions were unclear. The current study aims to address this by exploring further Poyang Lake's hysteretic behavior, including consideration of stage-flow relationships. Remotely sensed imagery is used to validate the water surface areas produced by hydrodynamic modeling. Stage-area relationships obtained using the two methods are in strong agreement. The new results reveal a three-phase hydrological regime in stage-flow relationships, which assists in developing improved physical interpretation of hysteretic stage-area relationships for the lake-floodplain system. For stage-area relationships, clockwise hysteresis is the result of classic floodplain hysteretic processes (e.g., restricted drainage of the floodplain during recession), whereas counterclockwise hysteresis derives from the river hysteresis effect (i.e., caused by backwater effects). The river hysteresis effect is enhanced by the time lag between the peaks of catchment inflow and Yangtze discharge (i.e., the so-called Yangtze River blocking effect). The time lag also leads to clockwise hysteresis in the relationship between Yangtze River discharge and lake stage. Thus, factors leading to hysteresis in other rivers, lakes and floodplains act in combination within Poyang Lake to create spatial variability in hydrological hysteresis. These effects dominate at different times, in different parts of the lake, and during different phases of the lake's water level fluctuations, creating the unique hysteretic hydrological behavior of Poyang Lake.

Cyclic Stretching of Mesangial Cells Up-Regulates Intercellular Adhesion Molecule-1 and Leukocyte Adherence

PubMed Central

Riser, Bruce L.; Varani, James; Cortes, Pedro; Yee, Jerry; Dame, Michael; Sharba, Abdul K.

2001-01-01

Intraglomerular hypertension is a primary causal factor in the progressive glomerulosclerosis that characterizes diabetic nephropathy or severe renal ablation. However, inflammation of the glomerular mesangium also participates in at least the early phase of these diseases. In glomerulonephritis, where inflammation is thought to be the predominant causal factor, intraglomerular hypertension is also often present. Mesangial cells (MCs) are critical in orchestrating key functions of the glomerulus including extracellular matrix metabolism, cytokine production, and interaction with leukocytes. Because MCs are subject to increased stretching when intraglomerular hypertension is present, and in glomerulonephritis MC/leukocyte interactions seem to be mediated primarily via the up-regulation of intercellular adhesion molecule-1 (ICAM-1), we examine the possibility that cyclic stretching is a stimulus for increased MC ICAM-1 activity. We demonstrate that the normal low levels of MC ICAM-1 mRNA and protein are dramatically up-regulated by even short intervals of cyclic stretch. This effect is dose- and time-dependent, and requires little amplitude and a brief period of elongation for significant induction. Stretch-induced MC ICAM-1 also leads to a marked elevation in phagocytic leukocyte adherence. This stimulated adherence is equal or greater than that induced by the inflammatory cytokine tumor necrosis factor-α, whereas an additive effect occurs when both are applied in combination. Our results indicate that stretch-induced ICAM-1 may provide a direct link between hypertension and inflammation in the progression of injury and glomerulosclerosis in diabetes, renal ablation, and other forms of glomerulonephritis. PMID:11141473

Cyclic stretching of mesangial cells up-regulates intercellular adhesion molecule-1 and leukocyte adherence: a possible new mechanism for glomerulosclerosis.

PubMed

Riser, B L; Varani, J; Cortes, P; Yee, J; Dame, M; Sharba, A K

2001-01-01

Intraglomerular hypertension is a primary causal factor in the progressive glomerulosclerosis that characterizes diabetic nephropathy or severe renal ablation. However, inflammation of the glomerular mesangium also participates in at least the early phase of these diseases. In glomerulonephritis, where inflammation is thought to be the predominant causal factor, intraglomerular hypertension is also often present. Mesangial cells (MCs) are critical in orchestrating key functions of the glomerulus including extracellular matrix metabolism, cytokine production, and interaction with leukocytes. Because MCs are subject to increased stretching when intraglomerular hypertension is present, and in glomerulonephritis MC/leukocyte interactions seem to be mediated primarily via the up-regulation of intercellular adhesion molecule-1 (ICAM-1), we examine the possibility that cyclic stretching is a stimulus for increased MC ICAM-1 activity. We demonstrate that the normal low levels of MC ICAM-1 mRNA and protein are dramatically up-regulated by even short intervals of cyclic stretch. This effect is dose- and time-dependent, and requires little amplitude and a brief period of elongation for significant induction. Stretch-induced MC ICAM-1 also leads to a marked elevation in phagocytic leukocyte adherence. This stimulated adherence is equal or greater than that induced by the inflammatory cytokine tumor necrosis factor-alpha, whereas an additive effect occurs when both are applied in combination. Our results indicate that stretch-induced ICAM-1 may provide a direct link between hypertension and inflammation in the progression of injury and glomerulosclerosis in diabetes, renal ablation, and other forms of glomerulonephritis.

Inferring causes during speech perception.

PubMed

Liu, Linda; Jaeger, T Florian

2018-05-01

One of the central challenges in speech perception is the lack of invariance: talkers differ in how they map words onto the speech signal. Previous work has shown that one mechanism by which listeners overcome this variability is adaptation. However, talkers differ in how they pronounce words for a number of reasons, ranging from more permanent, characteristic factors such as having a foreign accent, to more temporary, incidental factors, such as speaking with a pen in the mouth. One challenge for listeners is that the true cause underlying atypical pronunciations is never directly known, and instead must be inferred from (often causally ambiguous) evidence. In three experiments, we investigate whether these inferences underlie speech perception, and how the speech perception system deals with uncertainty about competing causes for atypical pronunciations. We find that adaptation to atypical pronunciations is affected by whether the atypical pronunciations are seen as characteristic or incidental. Furthermore, we find that listeners are able to maintain information about previous causally ambiguous pronunciations that they experience, and use this previously experienced evidence to drive their adaptation after additional evidence has disambiguated the cause. Our findings revise previous proposals that causally ambiguous evidence is ignored during speech adaptation. Copyright © 2018 Elsevier B.V. All rights reserved.

The Social Modulation of Imitation Fidelity in School-Age Children

PubMed Central

Marsh, Lauren E.; Ropar, Danielle; Hamilton, Antonia F. de C.

2014-01-01

Children copy the actions of others with high fidelity, even when they are not causally relevant. This copying of visibly unnecessary actions is termed overimitation. Many competing theories propose mechanisms for overimitation behaviour. The present study examines these theories by studying the social factors that lead children to overimitate actions. Ninety-four children aged 5- to 8-years each completed five trials of an overimitation task. Each trial provided the opportunity to overimitate an action on familiar objects with minimal causal reasoning demands. Social cues (live or video demonstration) and eye contact from the demonstrator were manipulated. After the imitation, children's ratings of action rationality were collected. Substantial overimitation was seen which increased with age. In older children, overimitation was higher when watching a live demonstrator and when eye contact was absent. Actions rated as irrational were more likely to be imitated than those rated as rational. Children overimitated actions on familiar objects even when they rated those actions as irrational, suggesting that failure of causal reasoning cannot be driving overimitation. Our data support social explanations of overimitation and show that the influence of social factors increases with age over the 5- to 8-year-old age range. PMID:24465913

An Analysis on the Unemployment Rate in the Philippines: A Time Series Data Approach

NASA Astrophysics Data System (ADS)

Urrutia, J. D.; Tampis, R. L.; E Atienza, JB

2017-03-01

This study aims to formulate a mathematical model for forecasting and estimating unemployment rate in the Philippines. Also, factors which can predict the unemployment is to be determined among the considered variables namely Labor Force Rate, Population, Inflation Rate, Gross Domestic Product, and Gross National Income. Granger-causal relationship and integration among the dependent and independent variables are also examined using Pairwise Granger-causality test and Johansen Cointegration Test. The data used were acquired from the Philippine Statistics Authority, National Statistics Office, and Bangko Sentral ng Pilipinas. Following the Box-Jenkins method, the formulated model for forecasting the unemployment rate is SARIMA (6, 1, 5) × (0, 1, 1)4 with a coefficient of determination of 0.79. The actual values are 99 percent identical to the predicted values obtained through the model, and are 72 percent closely relative to the forecasted ones. According to the results of the regression analysis, Labor Force Rate and Population are the significant factors of unemployment rate. Among the independent variables, Population, GDP, and GNI showed to have a granger-causal relationship with unemployment. It is also found that there are at least four cointegrating relations between the dependent and independent variables.

Epidemiología genética sobre las teorías causales y la patogénesis de la diabetes mellitus tipo 2.

PubMed

Castro-Juárez, Carlos Jonnathan; Ramírez-García, Sergio Alberto; Villa-Ruano, Nemesio; García-Cruz, Diana

2017-01-01

Diabetes mellitus type 2 (DM2) is a worldwide public health problem. The etiology of the disease is multifactorial and is characterized by great heterogeneity of metabolic disorders. The most common are the insufficient production of insulin, insulin resistance and impaired incretin system. The specialist must understand the multi-causal nature of DM2 in the post-genomic era. This nature is determined by the additive effect of genes and environment, so there is no simple genetic epidemiological model to explain the inheritance pattern. Hence the need to establish the proportion of disease that is determined by genes and the contribution of environmental factors, the combination of which regulates the threshold or tolerance level for diabetes development. Given this complexity in DM2 in this work are discussed the various existing theories of causality of this disease, which will permit us to understand the interaction between the environment and the human genome, and also to know how risk factors or predisposition to this disease influence, laying the grounds that delimit environment interaction with the genome. Copyright: © 2017 SecretarÍa de Salud.

Causality in cancer epidemiology.

PubMed

Lagiou, Pagona; Adami, Hans-Olov; Trichopoulos, Dimitrios

2005-01-01

In this review, issues of causality in epidemiologic research with emphasis on the aetiology of human cancer are considered. Principles of assessing causation in epidemiological studies of cancer are distinguished into those concerning an individual study, several studies and a particular person. Strengths and weaknesses of various approaches of documenting carcinogenicity in humans are examined and lists of major established causes of human cancer are presented. The review concludes with estimates of mortality from cancer around the world that can be attributed to specific factors under the light of the current scientific knowledge.

"It Was My Fault": Bullied Students' Causal and Controllable Attributions in Bullying Blogs.

PubMed

Danielson, Carly M; Emmers-Sommer, Tara M

2016-01-01

Student bullying is a growing and damaging social problem. The devastating outcomes bullied individuals often experience due to such treatment make understanding this phenomenon imperative. Utilizing Heider's (1958) attribution theory, this study explores how bullied students (n = 100) attribute locus of causality and controllability for their victimization in 5 bullying blogs. Findings from this investigation reveal that (a) male and female bloggers' causal and controllable attributions do not differ; (b) bloggers most often attribute blame to bullies, although a noteworthy portion also attribute internal causation; and (c) bloggers often attribute bullying as uncontrollable for several reasons. This study also identifies factors that influence shifts in negative attributions about bullying. These findings inform bullying programs with the hope of reducing destructive attribution formations that potentially lead to prolonged victimization and detrimental consequences.

Using multiple cause-of-death data to investigate associations and causality between conditions listed on the death certificate.

PubMed

Redelings, Matthew D; Wise, Matthew; Sorvillo, Frank

2007-07-01

Death rarely results from only one cause, and it can be caused by a variety of factors. Multiple cause-of-death data files can list as many as 20 contributing causes of death in addition to the reported underlying cause of death. Analysis of multiple cause-of-death data can provide information on associations between causes of death, revealing common combinations of events or conditions which lead to death. Additionally, physicians report the causal train of events through which they believe that different conditions or events may have led to each other and ultimately caused death. In this paper, the authors discuss methods used in studying associations between reported causes of death and in investigating commonly reported causal pathways between events or conditions listed on the death certificate.

Triglyceride-rich lipoproteins as a causal factor for cardiovascular disease

PubMed Central

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 epidemiological, clinical, and genetic evidence relating to the atherogenicity of TRLs and their role in the progression of CVD. PMID:27226718

Associations between Potentially Modifiable Risk Factors and Alzheimer Disease: A Mendelian Randomization Study

PubMed Central

Østergaard, Søren D.; Mukherjee, Shubhabrata; Sharp, Stephen J.; Proitsi, Petroula; Lotta, Luca A.; Day, Felix; Perry, John R. B.; Boehme, Kevin L.; Walter, Stefan; Kauwe, John S.; Gibbons, Laura E.; Larson, Eric B.; Powell, John F.; Langenberg, Claudia; Crane, Paul K.; Wareham, Nicholas J.; Scott, Robert A.

2015-01-01

Background Potentially modifiable risk factors including obesity, diabetes, hypertension, and smoking are associated with Alzheimer disease (AD) and represent promising targets for intervention. However, the causality of these associations is unclear. We sought to assess the causal nature of these associations using Mendelian randomization (MR). Methods and Findings We used SNPs associated with each risk factor as instrumental variables in MR analyses. We considered type 2 diabetes (T2D, N SNPs = 49), fasting glucose (N SNPs = 36), insulin resistance (N SNPs = 10), body mass index (BMI, N SNPs = 32), total cholesterol (N SNPs = 73), HDL-cholesterol (N SNPs = 71), LDL-cholesterol (N SNPs = 57), triglycerides (N SNPs = 39), systolic blood pressure (SBP, N SNPs = 24), smoking initiation (N SNPs = 1), smoking quantity (N SNPs = 3), university completion (N SNPs = 2), and years of education (N SNPs = 1). We calculated MR estimates of associations between each exposure and AD risk using an inverse-variance weighted approach, with summary statistics of SNP–AD associations from the International Genomics of Alzheimer’s Project, comprising a total of 17,008 individuals with AD and 37,154 cognitively normal elderly controls. We found that genetically predicted higher SBP was associated with lower AD risk (odds ratio [OR] per standard deviation [15.4 mm Hg] of SBP [95% CI]: 0.75 [0.62–0.91]; p = 3.4 × 10−3). Genetically predicted higher SBP was also associated with a higher probability of taking antihypertensive medication (p = 6.7 × 10−8). Genetically predicted smoking quantity was associated with lower AD risk (OR per ten cigarettes per day [95% CI]: 0.67 [0.51–0.89]; p = 6.5 × 10−3), although we were unable to stratify by smoking history; genetically predicted smoking initiation was not associated with AD risk (OR = 0.70 [0.37, 1.33]; p = 0.28). We saw no evidence of causal associations between glycemic traits, T2D, BMI, or educational attainment and risk of AD (all p > 0.1). Potential limitations of this study include the small proportion of intermediate trait variance explained by genetic variants and other implicit limitations of MR analyses. Conclusions Inherited lifetime exposure to higher SBP is associated with lower AD risk. These findings suggest that higher blood pressure—or some environmental exposure associated with higher blood pressure, such as use of antihypertensive medications—may reduce AD risk. PMID:26079503