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27-06-2019 | Empirical Research

Adolescent Health Risk Behaviors: Convergent, Discriminant and Predictive Validity of Self-Report and Cognitive Measures

Auteurs: Michael I. Demidenko, Edward D. Huntley, Meghan E. Martz, Daniel P. Keating

Gepubliceerd in: Journal of Youth and Adolescence | Uitgave 9/2019

Abstract

Self-report and cognitive tasks of reward sensitivity and self-regulation have influenced several developmental models that may explain the heightened engagement in risk behaviors during adolescence. Despite some inconsistencies across studies, few studies have explored the convergent, discriminant, and predictive validity of self-report and cognitive measures of these psychological characteristics in adolescence. The present study evaluated the convergent and discriminant validity of self-report and cognitive measures of reward sensitivity and self-regulation among 2017 adolescents (age M = 16.8, SD = 1.1; 56% female; 55% White, 22% Black, 8% Hispanic, 15% other race/ethnic; 49% 10th grade and 51% 12th grade). This study compared the predictive validity of an omnibus measure and specific measures of risk engagement. Convergent and discriminant validity from self-report to cognitive tasks were as predicted, although with weak convergent relationships. As hypothesized, compared to cognitive tasks, self-report measures consistently predicted risky behaviors and explained more variance in the models. These results demonstrate that while cognitive tasks can significantly predict certain risk behaviors, they require increased power to find the very small effects, raising questions about their use as implicit proxies for real world risk behavior.

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Titel: Adolescent Health Risk Behaviors: Convergent, Discriminant and Predictive Validity of Self-Report and Cognitive Measures
Auteurs: Michael I. Demidenko
Edward D. Huntley
Meghan E. Martz
Daniel P. Keating
Publicatiedatum: 27-06-2019
Uitgeverij: Springer US
Gepubliceerd in: Journal of Youth and Adolescence / Uitgave 9/2019
Print ISSN: 0047-2891
Elektronisch ISSN: 1573-6601
DOI: https://doi.org/10.1007/s10964-019-01057-4

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