Affiliation:
1. New York University New York New York USA
2. Seton Hall University South Orange New Jersey USA
3. Gangneung‐Wonju National University Gangneung Republic of Korea
Abstract
AbstractIn a Registered Report, the authors propose a new survey‐bias‐mitigation method—incorporating inverse probability weighting via boosted regression—to better understand lesbian, gay, bisexual, or questioning (LGBQ)‐heterosexual youth risk disparities. This method is tested using the 2019 US Centers for Disease Control and Prevention‐collected Youth Risk Behavior Survey (YRBS) national data, which contain 12,847 observations (ages 12–18 [M = 16, SD = 1.25]; 49.1% male [8.7% LGBQ] and 50.9% female [22.4% LGBQ]; nationally representative regarding race and ethnicity). Looking across 44 outcomes, the authors found that the YRBS contains responses that are potentially biased against LGBQ youth in systematic ways, inflating perceived risk for this group in some outcomes. This potential bias is more pronounced among reported males than among reported females, and it is more pronounced for low‐incidence outcomes. For example, the steroid‐use disparity estimate among reported males reduced by 67%, while the reduction in bullying victimization was small and not statistically significant. The authors discuss robustness of results, the new method, and data policy implications.
Subject
Developmental and Educational Psychology,Education,Pediatrics, Perinatology and Child Health
Cited by
1 articles.
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