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PubMed2007

Knowing who dunnit: Infants identify the causal agent in an unseen causal interaction.

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 novel puppet (causal agents), but not a toy train (an inert object), to predict the subsequent motion of a beanbag. Conversely, in Experiment 3, 10- and 7-month-olds used the motion of the beanbag to infer the position of a hand but not of a toy block. These data suggest that preverbal infants expect a causal agent as the source of motion of an inert object.

Association Learning↗
PubMed2026

Multitarget interactions of bisphenol A in polycystic ovary syndrome: evidence from integrated network toxicology, mendelian randomization, and molecular docking.

OBJECTIVE: To study the potential pathogenic mechanisms of bisphenol A (BPA) in polycystic ovary syndrome (PCOS) using an integrative computational strategy. DESIGN: Integrative computational study combining network toxicology, Mendelian randomization (MR), and molecular docking. SUBJECTS: For MR analysis, genetic data were sourced from large European-ancestry cohorts, including plasma protein quantitative trait loci data and genome-wide association study summary statistics for PCOS (3,045 cases and 267,780 controls). EXPOSURE: In silico exposure to BPA for target prediction; genetically predicted plasma protein levels for causal inference. MAIN OUTCOME MEASURES: Identification of overlapping targets between BPA and PCOS; functional enrichment pathways; causal effects of prioritized proteins on PCOS risk (odds ratios with 95% confidence intervals); binding affinities between BPA and core targets (kcal/mol). RESULTS: Network toxicology identified 310 overlapping targets between BPA and PCOS. Enrichment analyses revealed significant involvement in endocrine signaling, inflammatory pathways (eg, IL-17), and cellular processes. MR demonstrated that genetically elevated levels of RET, CXCL8, HTR6, MMP1, MMP9, NTRK1, and TNNI2 were significantly associated with increased PCOS risk, whereas higher PSAP and SHBG levels were protective. Molecular docking confirmed stable binding between BPA and all nine key targets, with strongest affinity for SHBG (-8.4 kcal/mol), followed by NTRK1, TNNI2, and RET. CONCLUSION: This integrative investigation suggests that BPA may contribute to PCOS pathogenesis through multitarget interactions involving inflammatory mediators, endocrine regulators, and tissue remodeling proteins. The findings provide prioritized targets and mechanistic insights for future experimental validation and environmental risk assessment.

Female↗
PubMed2025

Exact model-free function inference using uniform marginal counts for null population.

MOTIVATION: Recognizing cause-effect relationships is a fundamental inquiry in science. However, current causal inference methods often focus on directionality but not statistical significance. A ramification is chance patterns of uneven marginal distributions achieving a perfect directionality score. RESULTS: To overcome such issues, we design the uniform exact function test with continuity correction (UEFTC) to detect functional dependency between two discrete random variables. The null hypothesis is two variables being statistically independent. Unique from related tests whose null populations use observed marginals, we define the null population by an embedded uniform square. We also present a fast algorithm to accomplish the test. On datasets with ground truth, the UEFTC exhibits accurate directionality, low biases, and robust statistical behavior over alternatives. We found nonmonotonic response by gene TCB2 to beta-estradiol dosage in engineered yeast strains. In the human duodenum with environmental enteric dysfunction, we discovered pathology-dependent anti-co-methylated CpG sites in the vicinity of genes POU2AF1 and LSP1; such activity represents orchestrated methylation and demethylation along the same gene, unreported previously. The UEFTC has much improved effectiveness in exact model-free function inference for data-driven knowledge discovery. AVAILABILITY AND IMPLEMENTATION: An open-source R package "UniExactFunTest" implementing the presented uniform exact function tests is available via CRAN at doi: 10.32614/CRAN.package.UniExactFunTest. Computer code to reproduce figures can be found in supplementary file "UEFTC-main.zip."

Algorithms↗
PubMed2002

Toward a better understanding of the influences on physical activity: the role of determinants, correlates, causal variables, mediators, moderators, and confounders.

BACKGROUND: For research on physical activity interventions to progress systematically, the mechanisms of action must be studied. In doing so, the research methods and their associated concepts and terminology become more complex. It is particularly important to clearly distinguish among determinants, correlates, mediators, moderators, and confounder variables used in physical activity research. This article examines the factors that are correlated with and that may have a causal relationship to physical activity. METHODS AND RESULTS: We propose that the term "correlate" be used, instead of "determinant," to describe statistical associations or correlations between measured variables and physical activity. Studies of the correlates of physical activity are reviewed. The findings of these studies can help to critique existing theories of health behavior change and can provide hypotheses to be tested in intervention studies from which it is possible to draw causal inferences. Mediator, moderator, and confounder variables can act to influence measured changes in physical activity. Intervening causal variables that are necessary to complete a cause-effect pathway between an intervention and physical activity are termed "mediators." The relationship between an intervention and physical activity behaviors may vary for different groups; the strata by which they vary are levels of "moderators" of the relationship. Other factors may distort or affect the observed relationships between program exposure and physical activity, and are known as "confounders." CONCLUSIONS: Consistent use of terms and additional research on mediators and moderators of intervention effects will improve our ability to understand and influence physical activity.

Behavioral Sciences↗
PubMed2026

Identifying causal genetic variants for high-altitude adaptation through blood eQTL analysis in plateau populations.

A substantial number of genetic variants have been associated with high-altitude adaptation (HAA), yet most of them are located in non-coding genomic regions, leaving their specific functions and underlying mechanisms largely unknown. In this study, we analyze whole-genome and transcriptome sequencing data from a self-established cohort comprising 61 native highlanders (NHs) and 164 acclimatized newcomers (ANs), identifying 6,586 cis- and 34,203 trans-expression quantitative trait loci (eQTLs), along with 130 cell type-specific eQTLs. By further combining these data with a large East Asia (~30% Tibetan) genome-wide association study (GWAS) cohort, we employ colocalization and causal inference analyses to prioritize 85 cis-eQTLs associated with HAA and identify several novel candidate causal genes, including EXOC8, which is experimentally confirmed to regulate erythroid differentiation. Additionally, network analysis of these causal genes uncovers multiple regulatory pathways, mainly involving energy metabolism, autophagy, ubiquitination and inflammation. Our study offers a comprehensive eQTL map and reveals causal chains of "variant-gene-phenotype" for HAA-related traits, which provides new insights into potential regulatory mechanisms and targets for prevention and treatment of altitude sickness.

Quantitative Trait Loci↗
PubMed2005

Evidence for dissociable neural mechanisms underlying inference generation in familiar and less-familiar scenarios.

In this study, we investigated whether the left and right hemispheres are differentially involved in causal inference generation. Participants read short inference-promoting texts that described either familiar or less-familiar scenarios. After each text, they performed a lexical decision on a letter string (which sometimes constituted an inference-related word) presented directly to the left or right hemisphere. Response-time results indicated that hemisphere of direct presentation interacted with type of inference scenario. When test stimuli were presented directly to the left hemisphere, lexical decisions were facilitated following familiar but not following less-familiar inference scenarios, whereas when test stimuli were presented directly to the right hemisphere, facilitation was observed in both familiar and less-familiar conditions. Thus, inferences may be generated in different ways depending on which of two dissociable neural subsystems underlies the activation of background information.

Adult↗
PubMed2002

A methodology for inferring the causes of observed impairments in aquatic ecosystems.

Biological surveys have become a common technique for determining whether aquatic communities have been injured. However, their results are not useful for identifying management options until the causes of apparent injuries have been identified. Techniques for determining causation have been largely informal and ad hoc. This paper presents a logical system for causal inference. It begins by analyzing the available information to generate causal evidence; available information may include spatial or temporal associations of potential cause and effect, field or laboratory experimental results, and diagnostic evidence from the affected organisms. It then uses a series of three alternative methods to infer the cause: Elimination of causes, diagnostic protocols, and analysis of the strength of evidence. If the cause cannot be identified with sufficient confidence, the reality of the effects is examined, and if the effects are determined to be real, more information is obtained to reiterate the process.

Animals↗
PubMed2004

Statistical and substantive inferences in public health: issues in the application of multilevel models.

Multilevel statistical models have become increasingly popular among public health researchers over the past decade. Yet the enthusiasm with which these models are being adopted may obscure rather than solve some problems of statistical and substantive inference. We discuss the three most common applications of multilevel models in public health: (a) cluster-randomized trials, (b) observational studies of the multilevel etiology of health and disease, and (c) assessments of health care provider performance. In each area of investigation, we describe how multilevel models are being applied, comment on the validity of the statistical and substantive inferences being drawn, and suggest ways in which the strengths of multilevel models might be more fully exploited. We conclude with a call for more careful thinking about multilevel causal inference.

Bayes Theorem↗
PubMedDate not supplied

Epidemiology in community psychiatric research: common uses and methodological issues.

OBJECTIVE: Epidemiological principles underpin much medical research particularly that concerned with the planning and evaluation of health services, including research in community and social psychiatry. The aim of this paper is to review some of the common uses of epidemiology in community psychiatric research and to discuss some methodological issues that arise frequently in epidemiological research in community settings. METHODS: This is a review of the relevant literature and of the work currently in progress in the department of psychological medicine of the university of Wales College of Medicine. RESULTS: Among the many uses of epidemiology in health care, four are especially relevant in community psychiatric settings: the assessment of the mental health needs of the population (four approaches are described: the collection of routine data, surveys of existing patients, surveys of the general population and statistical modelling), the identification of risk factors of disease, the contribution to prevention and the assessment of the clinical effectiveness of health care interventions. The most important methodological issues include causal inference which in epidemiology takes the form of explaining the association between an exposure and disease (chance, bias, confounding, reverse causality and causality), the issue of confounding and how to adjust for it and issues arising in the context of specific study designs. CONCLUSION: Epidemiology has become a set of methods used to investigate a wide range of clinical questions. Population based research is an essential part of clinical research but epidemiological knowledge is also needed by clinicians in order to critically appraise and interpret the scientific literature.

Bias↗
PubMed1980

Types of research: a synopsis of the major categories and data collection methods.

Different types of research are categorized by reviewing their characteristics and describing how they can be used. Controlled research is experimental in nature and, through a priori planning, allows manipulation of the independent variable so causality can be shown. In ex post facto research, the researcher does not have control of the independent variable and so must infer causality by measuring dependent variables within the framework of independent variables that are already established or whose changes have already taken place. Most applied research in pharmacy is of the ex post facto type. The research questions to be answered will help determine the timing of the measurement of dependent variable (i.e., measure past events or make plans to measure future events), the measuring of the dependent variable (primarily with surveys), and whether time can be used as an independent variable. The effect of time can be determined by repeated measurements over a span of time (longitudinal design) or by measurement of several groups at one point in time (cross-sectional design).

Data Collection↗
PubMed2003

Overview of clinical trials in medical rehabilitation: impetuses, challenges, and needed future directions.

The goal of clinical trials is to provide the strongest possible basis for inferring that the observed results of a health-oriented intervention are attributable to that intervention and not to other factors. Particularly strong causal inferences can be drawn from the randomized clinical trial in which participants are assigned on a random basis to either the intervention of interest or to a comparison condition. This article explains the reasons for that contention and explores its implications for medical rehabilitation research. Among the topics discussed are: the role of evidence-based practice in fostering interest in randomized clinical trials; a contextual view of randomized clinical trials that emphasizes strategies of investigation and the goals of particular studies; two key distinctions, efficacy-oriented vs. effectiveness-oriented clinical trials and pragmatic vs. explanatory clinical trials; the sequencing of different study designs, including randomized clinical trials; and needed advances in treatment theory, treatment fidelity, and adherence.

Evidence-Based Medicine↗
PubMed1982

Psychiatry and the elderly in the Middle East: a report from Iran.

One of the more firmly established generalizations in mental health concerns the positive correlation found between aging on the one hand and levels of psychiatric distress and utilization of mental health services on the other. It is also generally believed that the young, being more resilient and healthier, possess a greater capacity to cope with psychiatric stress than the elderly. The causal inferences are often unavoidable. Since cross-cultural studies can examine naturally occurring differences in exogenous factors, they may help clarify some of the causal connections. This paper presents utilization rates as well as the results of psychiatric tests on older and younger populations of psychiatric patients and addicts in Iran. The psychiatric population includes both inpatients and outpatients from hospitals and clinics in Tehran, and the provinces. The addicts' population includes a nationwide sample of registered addicts as well as illicit addicts from Tehran and other provinces. Psychiatric profiles are constructed from Symptom-Checklist-90 (SCL-90) questionnaire translated and adapted for use in Iran. For each individual, nine primary symptom distress levels together with three global indices are obtained. Primary comparison is made across age variable with fifty-five years and over age group versus those below fifty-five years of age. Secondary comparisons include psychiatric versus addicts, inpatients versus outpatients, male versus female, as well as comparisons across other socio-economic variables. Findings are discussed in the light of prevalent socio-cultural factors.

Aged↗
PubMed1994

Causal estimation of time-varying treatment effects in observational studies: application to depressive disorder.

Clinicians recognize three phases of the treatment of major depression: an acute phase to control disabling symptoms, a continuation phase to avoid relapses of a single episode, and a preventive phase to avoid recurrences of new episodes over time. With no directly measurable trace of the underlying pathological process, the distinction is based arbitrarily on the passage of time in remission. The clinician who has successfully treated a patient with antidepressant medications in the acute phase has a critical clinical decision to make for the continuation and preventive phases: whether to continue to prescribe the medication, for how long, and at what dose. This decision, like most clinical decisions in psychiatry, is not yet completely determined by the results of randomized clinical trials. Only a handful of such trials have been completed, covering just a fraction of the possible maintenance strategies (defined by treatment drop times). For many reasons, observational studies of the outcome of naturally occurring treatment choices play an important supporting role, helping to extend the reach of completed studies and to design new studies. Causal inference from observational studies has usually been considered in the context of a decision among a few fixed alternatives at a single time. The particular causal effect of interest in the maintenance of remission dictates that treatment be studied over remission time. This challenges the causal analysis of the observational study. We present issues arising from assessing temporal treatment effects due to nonrandomized treatment assignment over time. We use data from a large observational study of the course of affective illness, to illustrate an approach to this problem.

Bias↗
PubMed2003

The mind's best trick: how we experience conscious will.

We often consciously will our own actions. This experience is so profound that it tempts us to believe that our actions are caused by consciousness. It could also be a trick, however - the mind's way of estimating its own apparent authorship by drawing causal inferences about relationships between thoughts and actions. Cognitive, social, and neuropsychological studies of apparent mental causation suggest that experiences of conscious will frequently depart from actual causal processes and so might not reflect direct perceptions of conscious thought causing action.

Journal Article↗
PubMed2026

Causal Effects of Gut Microbiota on Morning Chronotype, Insomnia and Sleep Duration: A Two-Sample Mendelian Randomization Study.

BACKGROUND: The gut microbiota has been shown to be closely associated with brain function; however, whether it exerts a causal influence on sleep traits remains to be further explored. Mendelian randomization (MR) is an emerging epidemiological approach that uses whole-genome sequencing data to infer causal relationships. In this study, we conducted a two-sample MR analysis to investigate the causal effects of gut microbiota on three domains of sleep traits: morning chronotype, insomnia, and sleep duration. METHODS: Single nucleotide polymorphisms strongly associated with 196 gut microbiota taxa were selected as instrumental variables. Morning chronotype, insomnia, and sleep duration were used as outcomes. MR and sensitivity analyses were performed to assess the causal relationships between gut microbiota and sleep traits. RESULTS: Three taxa (Bifidobacteriales, Bifidobacteriaceae, and Bifidobacterium) were negatively associated with morning chronotype, while Tyzzerella 3 showed a positive causal effect on morning chronotype. Oscillibacter was negatively associated with insomnia, whereas four taxa (Negativicutes, Selenomonadales, the Clostridium innocuum group, and Lachnoclostridium) were identified as risk-increasing factors for insomnia. Lentisphaerae and Victivallaceae were positively associated with sleep duration. Actinobacteria and Alistipes had negative effects on long sleep duration, whereas Ruminiclostridium 6 was positively associated with long sleep duration. Four taxa (Victivallales, Anaerofilum, Lentisphaerae, and Lentisphaeria) were negatively associated with short sleep duration. CONCLUSIONS: Our findings suggest that specific gut microbiota taxa may be positively or negatively associated with sleep traits. These results offer new insights into the potential role of gut microbiota in sleep regulation and provide a basis for future studies aimed at understanding whether modulating microbial composition could influence sleep health.

Mendelian randomization↗
PubMed2006

ITT analysis of randomized encouragement design studies with missing data.

In this paper, we considered a missing outcome problem in causal inferences for a randomized encouragement design study. We proposed both moment and maximum likelihood estimators for the marginal distributions of potential outcomes and the local complier average causal effect (CACE) parameter. We illustrated our methods in a randomized encouragement design study on the effectiveness of flu shots.

Biometry↗
PubMed2007

Conditional probability versus spatial contiguity in causal learning: Preschoolers use new contingency evidence to overcome prior spatial assumptions.

This study examines preschoolers' causal assumptions about spatial contiguity and how these assumptions interact with new evidence in the form of conditional probabilities. Preschoolers saw a toy that activated in the presence of certain objects. Children were shown evidence for the toy's activation rule in the form of patterns of probability: The toy was more likely to activate either when objects made contact with its surface (on condition) or when objects were several inches above its surface (over condition). In Experiment 1, 61 three-year-olds saw a deterministic activation rule. In Experiments 2 and 3, 48 four-year-olds saw an activation rule that was probabilistic. In Experiment 4, 30 four-year-olds saw a screening-off pattern of activation. In all 4 experiments, children used new evidence in the form of patterns of probability to make accurate causal inferences, even in the face of conflicting prior beliefs about spatial contiguity. However, children were more likely to make correct inferences when causes were spatially contiguous, particularly when faced with ambiguous evidence.

Association Learning↗
PubMed2025

Causal relationship between albumin, total protein, and colorectal cancer risk: A 2-sample Mendelian randomization study.

Albumin (ALB) and total protein (TP) are vital constituents of the blood, and their levels and roles in the risk of colorectal cancer (CRC) are of significance. Previous observational studies have reported correlations among ALB, TP, and CRC. However, the existence of a causal relationship between ALB and CRC in European populations has not been adequately investigated and the causal link between TP and CRC remains unexplored. To address these gaps, we applied Mendelian randomization (MR) to investigate the potential causal relationship between ALB, TP, and CRC. Two-sample MR analysis was used to investigate whether there was a causal relationship between ALB, TP, and CRC. Our exposure data were extracted from genome-wide association study (GWAS) databases sourced from the UK Biobank, containing 315,268 and 314,921 Europeans participants for ALB and TP analyses, respectively. Single nucleotide polymorphisms that were significantly associated with ALB and TP were assessed using GWAS datasets. Our data were derived from the FinnGen Consortium CRC GWAS, which contained 6509 CRC cases and 28,7137 controls. Causal inference between ALB, TP, and CRC was performed using 3 MR methods: inverse variance weighting (IVW), MR-Egger, and weighted median. The IVW analysis showed no significant causal association between ALB and CRC (OR = 1.04, 95% CI = 0.89-1.21, P = .65). In contrast, the IVW analysis for TP and CRC showed a significant causal association (OR = 0.78, 95% CI = 0.66-0.92, P = .003), suggesting a reduced risk of CRC. Through a 2-sample MR study investigating the causal relationship between ALB, TP, and CRC in a European population, our findings revealed a significant causal relationship between TP and a reduced risk of CRC.

Humans↗