ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2014
A risk prediction model for smoking experimentation in Mexican American youth.
Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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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
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Punitive school discipline as a mechanism of structural marginalization with implications for health inequity: A systematic review of quantitative studies in the health and social sciences literature.Annals of the New York Academy of Sciences · 2023Pooled it
- Machine Learning Helps in Prediction of Tobacco Smoking in Adolescents.International journal of preventive medicine · 2025Article
- Identity, Acculturation, and E-Cigarette Use among Bicultural Hispanic Youth and Young Adults.Health equity · 2024Article
- Testing mediating pathways between school segregation and health: Evidence on peer prejudice and health behaviors.Social science & medicine (1982) · 2023Article
- Reducing Children's Exposure to Passive Smoking in Rural Communities of Bangladesh: An Application of the Theory of Planned Behavior.Journal of research in health sciences · 2019Article
- Identifying demographic and psychosocial factors related to the escalation of smoking behavior among Mexican American adolescents.Preventive medicine · 2017Article
- Using the weighted area under the net benefit curve for decision curve analysis.BMC medical informatics and decision making · 2016Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundSmoking experimentation in Mexican American youth is problematic. In light of the research showing that preventing smoking experimentation is a valid strategy for smoking prevention, there is a need to identify Mexican American youth at high risk for experimentation.
methodsA prospective population-based cohort of 1,179 adolescents of Mexican descent was followed for 5 years starting in 2005-06. Participants completed a baseline interview at a home visit followed by three telephone interviews at intervals of approximately 6 months and additional interviews at two home visits in 2008-09 and 2010-11. The primary endpoint of interest in this study was smoking experimentation. Information about social, cultural, and behavioral factors (e.g., acculturation, susceptibility to experimentation, home characteristics, and household influences) was collected at baseline using validated questionnaires.
resultsAge, sex, cognitive susceptibility, household smoking behavior, peer influence, neighborhood influence, acculturation, work characteristics, positive outcome expectations, family cohesion, degree of tension, ability to concentrate, and school discipline were found to be associated with smoking experimentation. In a validation dataset, the proposed risk prediction model had an area under the receiver operating characteristic curve (AUC) of 0.719 (95% confidence interval, 0.637-0.801) for predicting absolute risk for smoking experimentation within 1 year.
conclusionsThe proposed risk prediction model is able to quantify the risk of smoking experimentation in Mexican American adolescents. IMPACT: Accurately identifying Mexican American adolescents who are at higher risk for smoking experimentation who can be intervened will substantially reduce the incidence of smoking and thereby subsequent health risks.
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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.