Suchergebnisse

Purpose To examine associations between past-year mental illness (MI) diagnoses and e-cigarette use status. Design Data were obtained from the National College Health Assessment, a nationally recognized cross-sectional survey of university students. Setting Participants were recruited from 2-year and 4-year public and private universities across the United States from 2017-2019. Subjects The analytic sample included 277 291 university students. Measures Self-reported past-year MI diagnosis, binarily coded, served as the primary predictor. The outcome was e-cigarette use status (never, noncurrent, and current user). Analysis Multinomial logistic regression models were used to estimate relative risk ratios (RRR) of e-cigarette use, as predicted by past-year MI diagnoses, age, race/ethnicity, sex and gender, sexual identity, geographic region, and other combustible tobacco, alcohol, and marijuana use. Results Compared to those who had never received any MI diagnosis in the past year, those who did had a 16% higher relative risk (RRR = 1.16, 95% CI: 1.11, 1.20) of being a noncurrent e-cigarette user and a 33% higher relative risk (RRR = 1.33, 95% CI: 1.28, 1.38) of being a current e-cigarette user. Schizophrenia, substance use or addiction, bipolar disorder, and attention deficit and hyperactivity disorder (ADHD) diagnoses demonstrated the strongest associations with noncurrent and current e-cigarette use. Conclusion Results suggest the need to screen young adults for e-cigarette use and mental health indicators to facilitate early detection and timely intervention for at-risk university students.

Purpose This study examines the pathways through which e-cigarette users' awareness of the truth® campaign influences e-cigarette use frequency over time. Design and Setting Data included four waves (2020–2023) of the Truth Longitudinal Cohort, a probability-based, nationally representative survey. Participants The analytic sample was 15-24-year-olds who reported current e-cigarette use at baseline (N = 718). Wave-by-wave retention rates were 64% to 69%. Measures Respondents' cumulative awareness of truth® ads was calculated (Waves 1–2). Strength of agreement with campaign-targeted attitudes was measured on five-point scales (Wave 2). The outcome was change in the 4-level frequency of e-cigarette use (Waves 2–4). Analysis Latent growth structural equation modeling examined the pathway from cumulative ad awareness to the frequency of e-cigarette use via campaign-targeted attitudes. Results Model fit estimates identified a three-step pathway by which awareness of the campaign reduced e-cigarette use. Ad awareness was significantly associated with stronger campaign-targeted attitudes: perceived risk (β = .20, P < .0001); anti-vape industry (β = .13, P = .003); independence from addiction (β = .13, P = .004); and affinity with groups that reject vaping (β = .18, P < .0001). Each attitude was significantly associated with stronger perceived norms against e-cigarette use (respectively: β = .25, P < .0001; β = .15, P < .0001; β = .12, P = .018; β = .27, P < .0001). Perceived norms against e-cigarette use had a significant negative relationship with growth in e-cigarette use frequency over time (β = −.23, P < .0001). Conclusion Greater truth® anti-vaping ad awareness strengthens campaign-targeted attitudes among current users, increasing perceived norms against e-cigarette use and reducing use over time.