Two-part models identifying predictors of cigarette, e-cigarette, and cannabis use and change in use over time among young adults in the US.
Autor: | Wang Y; Department of Prevention and Community Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia, USA.; George Washington Cancer Center, George Washington University, Washington, District of Columbia, USA., Romm KF; TSET Health Promotion Research Center, Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA.; Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA., Edberg MC; Department of Prevention and Community Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia, USA., Bingenheimer JB; Department of Prevention and Community Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia, USA., LoParco CR; Department of Prevention and Community Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia, USA., Cui Y; Department of Prevention and Community Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia, USA., Berg CJ; Department of Prevention and Community Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia, USA.; George Washington Cancer Center, George Washington University, Washington, District of Columbia, USA. |
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Jazyk: | angličtina |
Zdroj: | The American journal on addictions [Am J Addict] 2024 Sep; Vol. 33 (5), pp. 559-568. Date of Electronic Publication: 2024 Apr 29. |
DOI: | 10.1111/ajad.13569 |
Abstrakt: | Background and Objectives: Limited longitudinal research has examined differential interpersonal and intrapersonal correlates of young adult use and use frequency of cigarettes, e-cigarettes, and cannabis. This study aimed to address these limitations. Methods: We analyzed five waves of longitudinal data (2018-2020) among 3006 US young adults (M Results: Regarding baseline past-month use (27% cigarettes, 38% e-cigarettes, 39% cannabis), depressive symptoms, ACEs, and parental substance use predicted use outcomes (i.e., likelihood, frequency) for each product; extraversion predicted cigarette and e-cigarette use outcomes; openness predicted e-cigarette and cannabis use outcomes; conscientiousness negatively predicted cigarette and cannabis use outcomes; and agreeableness negatively predicted cannabis use frequency. Regarding longitudinal changes, conscientiousness predicted accelerated increase of cigarette use frequency at later timepoints; depressive symptoms predicted increases in likelihood of e-cigarette use but the association weakened over time; and parental cannabis use predicted decreased cannabis use frequency but the association weakened over time. Discussion and Conclusions: Young adult substance use interventions should target high-risk subgroups and focus on distinct factors impacting use, including chronic, escalating, and decreasing use. Scientific Significance: This study advances the literature regarding distinct predictors of different substance use outcomes and provides unique data to inform interventions targeting young adult cigarette, e-cigarette, and cannabis use. (© 2024 The American Academy of Addiction Psychiatry (AAAP).) |
Databáze: | MEDLINE |
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