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The Reciprocal Relationships of Social Norms and Risk Perceptions to Cigarette, E-Cigarette, and Cannabis Use: Cross-lagged Panel Analyses among US Young Adults in a Longitudinal Study

DRUG AND ALCOHOL DEPENDENCE(2022)

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摘要
Introduction: Given the distinct and evolving social norms, research on health implications, and regulations regarding cigarettes, e-cigarettes, and cannabis, it is important to understand the interplay between social norms, risk perceptions, and use of these products. Methods: We analyzed 3 waves of longitudinal data (Fall 2018, 2019, 2020) from 3006 young adults (M-age =24.56, 54.8% female, 31.6% sexual minority, 39.6% racial/ethnic minority) from 6 US metropolitan statistical areas. Cross-lagged panel models (CLPMs) examined reciprocal relationships of (a) perceived social norms (i.e., peer use, social acceptability) and risk perceptions (i.e., harm, addictiveness) to (b) number of days of cigarette, e-cigarette, and cannabis use in the past 30 days, respectively. Results: At baseline, lifetime and past 30-day use prevalence was: 61.8% and 26.9% for cigarettes, 57.7% and 37.7% for e-cigarettes, and 70.7% and 39.2% for cannabis. Perceived social norms and use of cigarettes and ecigarettes decreased over time, and risk perceptions increased (except cigarettes showed stable perceived harm). Regarding cannabis, perceived social norms and use increased, yet perceived harm and addictiveness also increased. CLPM indicated that greater perceived social norms predicted greater cigarette, e-cigarette, and cannabis use over time, and vice versa. While greater perceived risk predicted less e-cigarette and cannabis use and vice versa, this did not hold true for cigarettes: use predicted lower perceived risk, but risk perceptions did not predict later use. Conclusions: Tobacco and cannabis intervention and regulatory efforts should address health risks of use, particularly of e-cigarettes and cannabis, as well as denormalizing use.
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关键词
Tobacco use,Cannabis use,Young adults,Social norms,Risk perceptions,Cross-lagged panel modeling
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