Topic
Risk factor (computing)
About: Risk factor (computing) is a research topic. Over the lifetime, 5352 publications have been published within this topic receiving 120786 citations.
Papers published on a yearly basis
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Papers
TL;DR: It is argued that social factors such as socioeconomic status and social support are likely 'fundamental causes" of disease that affect multiple disease outcomes through multiple mechanisms, and consequently maintain an association with disease even when intervening mechanisms change.
Abstract: Over the last several decades, epidemiological studies have been enormously
successful in identifying risk factors for major diseases However, most of this
research has focused attention on risk factors that are relatively proximal causes of
disease such as diet, cholesterol level, exercise and the like We question the
emphasis on such individually-based risk factors and argue that greater attention
must be paid to basic social conditions if health reform is to have its maximum
effect in the time ahead There are two reasons for this claim First we argue that
individually-based risk factors must be contextualized, by examining what puts
people at risk of risks, if we are to craft effective interventions and improve the
nation's health Second, we argue that social factors such as socioeconomic status
and social support are likely 'fundamental causes" of disease that, because they
embody access to important resources, affect multiple disease outcomes throughmultiple mechanisms, and consequently maintain an association with disease even when intervening mechanisms change Without careful attention to these
possibilities, we run the risk of imposing individually-based intervention strategies
that are ineffective and of missing opportunities to adopt broad-based societal
interventions that could produce substantial health benefits for our citizens
3,484 citations
McMaster University1, University Hospital of Basel2, Autonomous University of Barcelona3, Mayo Clinic4, University at Buffalo5, University of South Florida6, Case Western Reserve University7, Oregon Health & Science University8, Duke University9, United States Department of Veterans Affairs10, University Medical Center Freiburg11
TL;DR: In the GRADE approach, randomized trials start as high-quality evidence and observational studies as low- quality evidence, but both can be rated down if most of the relevant evidence comes from studies that suffer from a high risk of bias.
2,644 citations
TL;DR: This meta-analytic review of prospective and experimental studies reveals that several accepted risk factors for eating pathology have not received empirical support or have received contradictory support, and the predictive power of individual risk and maintenance factors was limited.
Abstract: This meta-analytic review of prospective and experimental studies reveals that several accepted risk factors for eating pathology have not received empirical support (e.g., sexual abuse) or have received contradictory support (e.g.. dieting). There was consistent support for less-accepted risk factors(e.g., thin-ideal internalization) as well as emerging evidence for variables that potentiate and mitigate the effects of risk factors(e.g., social support) and factors that predict eating pathology maintenance(e.g., negative affect). In addition, certain multivariate etiologic and maintenance models received preliminary support. However, the predictive power of individual risk and maintenance factors was limited, suggesting it will be important to search for additional risk and maintenance factors, develop more comprehensive multivariate models, and address methodological limitations that attenuate effects.
2,555 citations
TL;DR: The child CR literature is reviewed, comparing CR to alternative multiple risk measurement models, and strengths and weaknesses of developmental CR research are discussed, offering analytic and theoretical suggestions to strengthen this growing area of scholarship.
Abstract: Childhood multiple risk factor exposure exceeds the adverse developmental impacts of singular exposures. Multiple risk factor exposure may also explain why sociodemographic variables (e.g., poverty) can have adverse consequences. Most research on multiple risk factor exposure has relied upon cumulative risk (CR) as the measure of multiple risk. CR is constructed by dichotomizing each risk factor exposure (0 = no risk; 1 = risk) and then summing the dichotomous scores. Despite its widespread use in developmental psychology and elsewhere, CR has several shortcomings: Risk is designated arbitrarily; data on risk intensity are lost; and the index is additive, precluding the possibility of statistical interactions between risk factors. On the other hand, theoretically more compelling multiple risk metrics prove untenable because of low statistical power, extreme higher order interaction terms, low robustness, and collinearity among risk factors. CR multiple risk metrics are parsimonious, are statistically sensitive even with small samples, and make no assumptions about the relative strengths of multiple risk factors or their collinearity. CR also fits well with underlying theoretical models (e.g., Bronfenbrenner's, 1979, bioecological model; McEwen's, 1998, allostasis model of chronic stress; and Ellis, Figueredo, Brumbach, & Schlomer's, 2009, developmental evolutionary theory) concerning why multiple risk factor exposure is more harmful than singular risk exposure. We review the child CR literature, comparing CR to alternative multiple risk measurement models. We also discuss strengths and weaknesses of developmental CR research, offering analytic and theoretical suggestions to strengthen this growing area of scholarship. Finally, we highlight intervention and policy implications of CR and child development research and theory.
1,684 citations
TL;DR: A variety of new investigations of the helplessness reformulation that employ five research strategies that converge in their support for the learned helplesshood reformulation are described.
Abstract: The attributional reformulation of the learned helplessness model claims that an explanatory style in which bad events are explained by internal, stable, and global causes is associated with depressive symptoms. Furthermore, this style is claimed to be a risk factor for subsequent depression when bad events are encountered. We describe a variety of new investigations of the helplessness reformulation that employ five research strategies: (a) cross-sectional correlational studies, (b) longitudinal studies, (c) experiments of nature, (d) laboratory experiments, and (e) case studies. Taken together, these studies converge in their support for the learned helplessness reformulation.
1,595 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2022 | 4 |
| 2021 | 283 |
| 2020 | 256 |
| 2019 | 241 |
| 2018 | 271 |
| 2017 | 236 |