RESUMEN
Objectives: Little is known about the association between specific types of screen time and adolescents' substance use. Thus, this study aimed to investigate the associations between screen time for studying, working, watching movies, playing games, and using social media and frequency of alcohol and tobacco use. Methods: In this cross-sectional study, Brazilian adolescents answered survey questions related to frequency of tobacco and alcohol consumption, and reported their daily volume of five types of screen time. Multilevel ordered logistic regression models were performed. Results: Each 1-hour increase in ST for studying was associated with 26% lower odds of smoking (OR = 0.74; 95% CI: 0.61-0.90) and 17% lower odds of drinking alcohol (OR = 0.83; 95% CI: 0.76-0.91) in the past 30 days. The increase of 1 hour of social media use was associated with 10% greater odds of smoking (OR = 1.10; 95% CI: 1.02-1.18) and a 13% greater chance of consuming alcohol (OR = 1.13; 95% CI: 1.08-1.18) in the past 30 days. Conclusion: The association between screen time and substance use appears to be type-specific. Future longitudinal research is needed to explore causal relationships.
Asunto(s)
Conducta del Adolescente , Trastornos Relacionados con Sustancias , Humanos , Adolescente , Estudios Transversales , Brasil/epidemiología , Tiempo de Pantalla , Uso de Tabaco/epidemiología , Consumo de Bebidas Alcohólicas/epidemiologíaRESUMEN
BACKGROUND: Interventions targeting reduce screen time in adolescents are urgently needed, mainly in low and middle-income countries because of the lack of evidence. Thus, the aims of the study were to examine the effect of a cluster-randomized controlled trial on screen time (ST) devices among Brazilian adolescents and to identify possible moderators. METHODS: Movimente was a multicomponent school-based intervention that was performed in 2017 and consisted of teacher training, education curriculum, and environmental improvements. Baseline and post-intervention assessments (over one academic year) were conducted with students aged 10-16 years at baseline (baseline n = 921, [n = 538 intervention group; n = 383 control group]). A self-report questionnaire was used to measure daily minutes of device specific screen time (TV, computer, video games and smartphone) and demographic variables. Linear mixed models were used to examine intervention effects and an exploratory moderation analysis (sex, grade and socioeconomic status) was performed. RESULTS: The intervention had no significant effects on TV time (ß = - 6.4, 95% CI: - 6.1;13.4), game time (ß = - 8.2, 95% CI: - 7.2;10.8), computer time (ß = 1.1, 95% CI: - 6.3;18.5), smartphone time (ß = - 10.2, 95% CI: - 32.5;12.1), screen time (ß = - 12.8, 95% CI: - 50.5;24.8), meeting screen time guidelines (OR: 1.29, 95% CI: 0.65,2.57) and meeting screen time guidelines with smartphone (OR: 1.66, 95% CI: 0.37,7.40). There was a significant intervention effect on reducing TV time (ß = - 37.1, 95% CI: - 73.0, - 1.3) among 8th grade students only. CONCLUSIONS: The Movimente intervention was effective only for TV time among 8th grade students. Understanding how school-based interventions can improve adolescents' device specific screen time across age groups is needed. Future strategies should cover all screen-based devices. Further, there is a need for more studies in low- and-middle income countries to assist in the development of effective strategies. TRIAL REGISTRATION: Clinicaltrials.gov identifier NCT02944318 (25/10/2016).