ArticleAmerican journal of epidemiology2013
Invited commentary: Off-roading with social epidemiology--exploration, causation, translation.
Article in American journal of epidemiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed.
- Effect of a Randomized Controlled Trial of Housing Vouchers on Adolescent Risky Sexual Behavior Over a 15-Year Period.Archives of sexual behavior · 2024Trial
- Modification of Housing Mobility Experimental Effects on Delinquency and Educational Problems: Middle Adolescence as a Sensitive Period.Journal of youth and adolescence · 2018Trial
- Co-evolution of epidemiology and artificial intelligence: challenges and opportunities.International journal of epidemiology · 2023Article
- A quantitative assessment of the frequency and magnitude of heterogeneous treatment effects in studies of the health effects of social policies.SSM - population health · 2023Article
- Reproducibility and Scientific Integrity of Big Data Research in Urban Public Health and Digital Epidemiology: A Call to Action.International journal of environmental research and public health · 2023Article
- Heterogeneous treatment effects in social policy studies: An assessment of contemporary articles in the health and social sciences.Annals of epidemiology · 2022Article
- Artificial intelligence in clinical and translational science: Successes, challenges and opportunities.Clinical and translational science · 2022Review
- G-Computation and Agent-Based Modeling for Social Epidemiology: Can Population Interventions Prevent Posttraumatic Stress Disorder?American journal of epidemiology · 2022Article
- Do peer social relationships mediate the harmful effects of a housing mobility experiment on boys' risky behaviors?Annals of epidemiology · 2020Article
- Predicting mortality from 57 economic, behavioral, social, and psychological factors.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Towards a People's Social Epidemiology: Envisioning a More Inclusive and Equitable Future for Social Epi Research and Practice in the 21st Century.International journal of environmental research and public health · 2019Article
- Putting the data before the algorithm in big data addressing personalized healthcare.NPJ digital medicine · 2019Review
- Machine learning approaches to the social determinants of health in the health and retirement study.SSM - population health · 2018Article
- Big Data's Role in Precision Public Health.Frontiers in public health · 2018Review
- Housing mobility and adolescent mental health: The role of substance use, social networks, and family mental health in the Moving to Opportunity Study.SSM - population health · 2017Article
- Heterogeneous Effects of Housing Vouchers on the Mental Health of US Adolescents.American journal of public health · 2016Article
- Commentary: Epidemiology in the era of big data.Epidemiology (Cambridge, Mass.) · 2015Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Population health improvements are the most relevant yardstick against which to evaluate the success of social epidemiology. In coming years, social epidemiology must increasingly emphasize research that facilitates translation into health improvements, with continued focus on macro-level social determinants of health. Given the evidence that the effects of social interventions often differ across population subgroups, systematic and transparent exploration of the heterogeneity of health determinants across populations will help inform effective interventions. This research should consider both biological and social risk factors and effect modifiers. We also recommend that social epidemiologists take advantage of recent revolutionary improvements in data availability and computing power to examine new hypotheses and expand our repertoire of study designs. Better data and computing power should facilitate underused analytic approaches, such as instrumental variables, simulation studies and models of complex systems, and sensitivity analyses of model biases. Many data-driven machine-learning approaches are also now computationally feasible and likely to improve both prediction models and causal inference in social epidemiology. Finally, we emphasize the importance of specifying exposures corresponding with realistic interventions and policy options. Effect estimates for directly modifiable, clearly defined health determinants are most relevant for building translational social epidemiology to reduce disparities and improve population health.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.