SEARCH · PubMed Health

Results for “causality”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 595 records · Page 33Linked to original sources

PubMed1987

[Mediators in septic shock: strategies of securing them and assessment of their causal significance].

More than 100 different mediators are discussed as being responsible for the progression of the septic shock syndrome. A new concept is described to establish the causal role of a single mediator by using a decision tree which excludes different non-causal associations (different kinds of bias and chance). By definition of several criteria and methodological standards, the published studies on mediator release/formation could be analysed and evaluated (meta-analysis). Furthermore, the classical concept of one cause--one disease (Koch-Dale) is extended to a concept of multiple determining factors. The role of a single mediator can be assessed quantitatively by notation of conditional probabilities in the presence of other causal factors. A mediator can be classified as a necessary, sufficient or contributory determinant in septic shock. Improved therapeutic concepts can be expected from this approach.

Biogenic Amines↗

PubMed1983

Otitis media and learning disabilities: the case for a causal relationship.

Despite an extensive literature suggesting a relationship between otitis media in early childhood and later learning disabilities, controversy still exists as to whether this link is causal. The hallmarks of otitis media, including decreased hearing and delayed language acquisition, and the characteristics of learning disabilities are reviewed. Further analysis of the studies that support a relationship between otitis media and learning disabilities strongly suggests that the relationship is causal in spite of methodologic limitations of some individual studies. If a causal relationship is accepted, then otitis media in early childhood is a disease with significant long-term morbidity that deserves careful follow-up and, when indicated, preventive interventions.

Achievement↗

PubMed1983

Multiple causality: consequences for medical practice.

When a scientifically trained health professional is called upon to deal with patients holding differing causal views of illness, the resulting lack of communication is frustrating to both. This discussion traces some implications for medical practice of significant cultural differences in two aspects of causal paradigms of illness: (1) terms accepted and (2) dimension or level of causality typically sought. The second is the more pervasive and intractable problem, having distinctive consequences for the role of curer, symptomatology, diagnosis and treatment.

Cross-Cultural Comparison↗

PubMed1980

The stability of causal attributions.

The stability of causal attribution over repeated test days was examined using a 2 (win, loss) X 2 (immediate, one day delay) X 3 (post game, 2 weeks, 4 weeks) design. Male high school football players outlined the degree of causality attributed to ability, effort, luck, task difficulty and officiating. The results from an ANOVA analysis supported a view that attributions are stable over a four week interval. However, a correlational analysis revealed that there is only a moderate to low consistency of individual differences in attribution over repeated tests. Thus, retrospective judgements for causality may not be reliable.

Adolescent↗

PubMed1993

Querying physicians' beliefs in career choice studies: the limitations of introspective causal reports.

Numerous studies in family medicine literature explore the determinants of physicians' specialty and practice location choices. A research approach frequently used in these studies has been to ask study physicians what led them to make specific career choices, labeled here as the introspective causal reports study design. This paper explores the validity of introspective causal reports and their usefulness in making health manpower policy recommendations. The accuracy of people's beliefs about the causes of their own behaviors is examined, and social psychology literature is drawn upon in this examination. Data are presented characterizing the use of introspective causal reports in recent family medicine literature. Recommendations are made for stronger research designs in future physician career choice determinant studies.

Behavior↗

PubMed1997

Causal modeling and alternative medicine.

Many problems of health promotion or prevention call for an understanding of relations among variables embedded in complex causal webs that may include psychosocial, cultural, or environmental factors as well as biological dysfunction. Experimental investigation of these kinds of research problems is frequently impossible or not feasible. Causal modeling, particularly latent variable structural modeling, can provide a useful alternative to manipulative experimentation when one is trying to build and test explanatory models in a rigorous and systematic fashion. A hypothetical model of fibromyalgia is presented to illustrate how latent variable models can prove useful when the malady under investigation is of relatively complex multifactorial origin. Topics discussed include the fundamental notion underlying causal models, how such models solve problems due to measurement error, and why both cross-sectional and longitudinal models deserve consideration. A number of applications in medical research are described.

Complementary Therapies↗

PubMed1993

Smoking and major depression. A causal analysis.

Among 1566 personally evaluated female twins from a population-based register, average lifetime daily cigarette consumption was strongly related to lifetime prevalence and to prospectively assessed 1-year prevalence of major depression (MD). Using the cotwin control method, we evaluated whether the association between smoking and lifetime MD was causal or noncausal. While the relative risk (95% confidence interval) for ever smoking given a lifetime history of MD was 1.48 (1.30 to 1.65) in the entire sample, it was 1.18 (0.88 to 1.47) and 0.98 (0.71 to 1.26), respectively, in dizygotic and monozygotic twin pairs discordant for a history of MD. The relative risk for a history of MD given ever smoking was 1.60 (1.39 to 1.83) in the entire sample, while in dizygotic and monozygotic twins discordant for smoking, it was 1.29 (0.87 to 1.74) and 0.96 (0.59 to 1.42), respectively. Controlling for personal smoking history, family history of smoking predicted risk for MD; controlling for the personal history of MD, family history of MD predicted smoking. The best-fitting bivariate twin model suggested that the relationship between lifetime smoking and lifetime MD resulted solely from genes that predispose to both conditions. These results suggest that the association between smoking and MD in women is not a causal one but arises largely from familial factors, which are probably genetic, that predispose to both smoking and MD.

Adult↗

PubMed2002

Estimating the causal effect of zidovudine on CD4 count with a marginal structural model for repeated measures.

Even in the absence of unmeasured confounding factors or model misspecification, standard methods for estimating the causal effect of a time-varying treatment on the mean of a repeated measures outcome (for example, GEE regression) may be biased when there are time-dependent variables that are simultaneously confounders of the effect of interest and are predicted by previous treatment. In contrast, the recently developed marginal structural models (MSMs) can provide consistent estimates of causal effects when unmeasured confounding and model misspecification are absent. We describe an MSM for repeated measures that parameterizes the marginal means of counterfactual outcomes corresponding to prespecified treatment regimes. The parameters of MSMs are estimated using a new class of estimators - inverse-probability of treatment weighted estimators. We used an MSM to estimate the effect of zidovudine therapy on mean CD4 count among HIV-infected men in the Multicenter AIDS Cohort Study. We estimated a potential expected increase of 5.4 (95 per cent confidence interval -1.8,12.7) CD4 lymphocytes/l per additional study visit while on zidovudine therapy. We also explain the theory and implementation of MSMs for repeated measures data and draw upon a simple example to illustrate the basic ideas.

Anti-HIV Agents↗

PubMed2007

The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials.

For estimating causal effects of treatments, randomized experiments are generally considered the gold standard. Nevertheless, they are often infeasible to conduct for a variety of reasons, such as ethical concerns, excessive expense, or timeliness. Consequently, much of our knowledge of causal effects must come from non-randomized observational studies. This article will advocate the position that observational studies can and should be designed to approximate randomized experiments as closely as possible. In particular, observational studies should be designed using only background information to create subgroups of similar treated and control units, where 'similar' here refers to their distributions of background variables. Of great importance, this activity should be conducted without any access to any outcome data, thereby assuring the objectivity of the design. In many situations, this objective creation of subgroups of similar treated and control units, which are balanced with respect to covariates, can be accomplished using propensity score methods. The theoretical perspective underlying this position will be presented followed by a particular application in the context of the US tobacco litigation. This application uses propensity score methods to create subgroups of treated units (male current smokers) and control units (male never smokers) who are at least as similar with respect to their distributions of observed background characteristics as if they had been randomized. The collection of these subgroups then 'approximate' a randomized block experiment with respect to the observed covariates.

Biometry↗

PubMed1991

Causality assessment in epidemiology.

Epidemiology relies upon a broad interpretation of determinism. This paper discusses analogies with the evolution of the concept of cause in physics, and analyzes the classical nine criteria proposed by Sir Austin Bradford Hill for causal assessment. Such criteria fall into the categories of enumerative induction, eliminative induction, deduction and analogy. All of these four categories are necessary for causal assessment and there is no natural hierarchy among them, although a 'deductive' analysis of the study design is preliminary to any assessment.

Bayes Theorem↗

PubMed1997

Unemployment and cardiovascular diseases: a causal relationship?

Unemployment has become a socio-political problem of great importance in the Western industrialised countries. Although negative effects on social life and psyche resulting from unemployment are regarded as scientifically accepted today, a possible causal relationship between job loss and somatic illnesses is still a matter of controversy. A possible target organ is the cardiovascular system. The aim of this study was therefore to check by means of extensive literature analysis to what extent unemployment can be seen to influence cardiovascular morbidity. Particular attention was paid to the methods used and the clinical relevance of the results. Person-related epidemiological studies published since 1980 which investigated changes in cardiovascular risk factors associated with unemployment or prevalence rates of manifest disease influenced by unemployment were included in the final evaluation. In some cases statistically significant associations were found between unemployment and the increase in cholesterol levels or systolic/diastolic blood pressure, but the clinical relevance of such slight changes is questionable. To consider unemployment as an independent, social, cardiovascular risk factor is at present unwarranted. An increase in the prevalence rates of coronary heart disease or arterial hypertension causally linked in some studies with unemployment is scientifically questionable due to severe methodological shortcomings. On the basis of the currently available methodologically acceptable studies, the question of a quantitative contribution of unemployment to cardiovascular disease cannot be answered conclusively.

Adult↗

PubMed2006

Some causal limitations of pharmacogenetic concepts.

Pharmacogenetics and pharmacogenomics are related facets of cutting edge therapeutic research in a field that relates pharmacological properties to the genetic characteristics of human beings. An optimistic interpretation suggests that "One-Size-Fits-All" therapeutics, whose effects can only be predicted in probabilistic terms, will give way eventually to individual tailor-made therapies with entirely predictable properties in each patient. Yet the concept of anticipating individual pharmacotherapeutic response appears to disregard some of the fundamental limitations of causal understanding in the biological world of structure-action relationships. It is not simply a problem of confronting complexity - which might be overcome in time with advances in biotechnology and computing power - but the inescapable paradox of the genetic characteristics of individuals within the human species. The aleatory process of evolution ensures that with the exception of monozygotic twins, every human being is genetically unique. At the same time there appears to be more in common than divides. Pharmacogenomics provides a climate in which to explore and better understand the variable causal relationships between genetic element, protein and therapeutic or toxic actions, but can only do so in abstraction. Thus predictive power may be enhanced but is ultimately constrained by insuperable probabilistic considerations.

Causality↗

PubMed1991

Sleep apnea and systemic hypertension: a causal association review.

OBJECTIVE: To critically examine the causal association between sleep apnea syndrome and hypertension. METHODS: A retrospective systematic critique of five epidemiologic studies published in the English literature during 1978 to 1989 identified on Medline and manual literature searches. The evidence was evaluated using the standard observational criteria for causation: strength of association, consistency, dose-response relationship, temporal sequence, specificity, and biologic plausibility. RESULTS: We found evidence to support a causal association between sleep apnea syndrome and hypertension in consistency and specificity and some evidence to suggest a dose-response relationship. Review of the data dealing with the mechanisms important in the pathogenesis of sleep apnea and hypertension allowed us to advance several theories to provide support for biologic plausibility. CONCLUSION: We concluded that there is a positive association--relative risk estimate between 1.3 and 40--for sleep apnea syndrome and hypertension, but the risk association is unstable. Thus, we believe that there is insufficient data to justify doing polysomnography as part of the routine diagnostic work-up for patients with hypertension.

Causality↗

PubMed1991

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

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.

Adolescent↗

PubMed1994

Religion and health: is there an association, is it valid, and is it causal?

This paper reviews evidence for a relationship between religion and health. Hundreds of epidemiologic studies have reported statistically significant, salutary effects of religious indicators on morbidity and mortality. However, this does not necessarily imply that religion influences health; three questions must first be answered: "Is there an association?", "Is it valid?", and, "Is it causal?" Evidence presented in this paper suggests that the answers to these respective questions are "yes," "probably," and "maybe." In answering these questions, several issues are addressed. First, key reviews and studies are discussed. Second, the problems of chance, bias, and confounding are examined. Third, alternative explanations for observed associations between religion and health are described. Fourth, these issues are carefully explored in the context of Hill's well-known features of a causal relationship. Despite the inconclusiveness of empirical evidence and the controversial and epistemologically complex nature of religion as an epidemiologic construct, this area is worthy of additional investigation. Further research can help to clarify these provocative findings.

Bias↗

PubMed1993

Causality assessment of adverse reactions to drugs--I. A novel method based on the conclusions of international consensus meetings: application to drug-induced liver injuries.

Despite the great number of methods proposed, assessing the causal role of a drug in the occurrence of an adverse medical event remains one of the most controversial issues. Qualifying terms for criteria, such as "compatible", "suggestive" of "inconclusive", have never been strictly defined, leading to low reproducibility. Weights of the criteria are usually not adapted to the injured organ, decreasing the specificity of the method. In this paper, a new method for drug causality assessment is described. Contents and limits of the criteria have been defined by experts convened to organ-oriented international consensus meetings. Additional criteria have been introduced and weights attributed. The method was applied to reports of acute liver injuries. The reproducibility was tested by an independent team. The validity of this novel method is studied in the following paper, based on an original approach using reports with positive rechallenge as external standard.

Age Factors↗

PubMed2006

The probability of causal conditionals.

Conditionals in natural language are central to reasoning and decision making. A theoretical proposal called the Ramsey test implies the conditional probability hypothesis: that the subjective probability of a natural language conditional, P(if p then q), is the conditional subjective probability, P(q/p). We report three experiments on causal indicative conditionals and related counterfactuals that support this hypothesis. We measured the probabilities people assigned to truth table cases, P(pq), P(p notq), P( notpq) and P( notp notq). From these ratings, we computed three independent predictors, P(p), P(q/p) and P(q/ notp), that we then entered into a regression equation with judged P(if p then q) as the dependent variable. In line with the conditional probability hypothesis, P(q/p) was by far the strongest predictor in our experiments. This result is inconsistent with the claim that causal conditionals are the material conditionals of elementary logic. Instead, it supports the Ramsey test hypothesis, implying that common processes underlie the use of conditionals in reasoning and judgments of conditional probability in decision making.

Analysis of Variance↗

PubMed2026

Causal assessment of Bayesian gene regulatory networks from single-cell transcriptomics.

Gene regulatory network (GRN) inference is an essential tool for revealing dysregulated relationships between genes in different cell types from single-cell transcriptomic (SCT) data. GRNs based on Bayesian networks (BNs) learned from SCT data can elucidate directed regulatory relationships representing complex disease mechanisms and their interplay through graphical modeling. However, software for learning BNs from SCT data is not widely available, nor is software for evaluating the BNs' structural accuracy in representing causal relationships between genes. Here, we describe the scstruc R package. This package provides a suite of BN structure learning algorithms specifically designed to handle SCT data, to evaluate the resulting networks based on the causal relationships they represent regardless of the availability of established molecular interaction networks, and to compare regulatory relationships between conditions. We demonstrated that scstruc can identify biologically relevant differential regulatory relationships between groups on a per-cell basis.

Bayesian networks↗