Screen media activity does not displace other recreational activities among 9-10 year-old youth: a cross-sectional ABCD study

• Published in: BMC public health 2020-11, Vol.20 (1), p.1783-1783, Article 1783
• Main Authors: Lees, Briana, Squeglia, Lindsay M, Breslin, Florence J, Thompson, Wesley K, Tapert, Susan F, Paulus, Martin P
• Format: Article
• Language: English
• Subjects: Adolescents; Amusements; Baseball; Behavior; Child; Children; Children & youth; Cognition; Cognition & reasoning; Cognitive ability; Cognitive development; Computers and children; Cross-Sectional Studies; Demographic aspects; Displacement; Economic factors; Economic models; Economics; Endorsements; Ethnicity; Exercise; Female; Hobbies - statistics & numerical data; Humans; Hypotheses; Independent variables; Leisure; Male; Music; Psychopathology; Public health; Questionnaires; Recreation; Screen Time; Soccer; Social aspects; Social environment; Social factors; Social interactions; Social media; Social networks; Social research; Sociodemographics; Socioeconomic Factors; Socioeconomics; Sports - statistics & numerical data; Swimming; Technology application; Teenagers; Television and children; Variables; Variance; Youth
• ISSN: 1471-2458; 1471-2458
• DOI: 10.1186/s12889-020-09894-w

Screen media is among the most common recreational activities engaged in by children. The displacement hypothesis predicts that increased time spent on screen media activity (SMA) may be at the expense of engagement with other recreational activities, such as sport, music, and art. This study examined associations between non-educational SMA and recreational activity endorsement in 9-10-year-olds, when accounting for other individual (i.e., cognition, psychopathology), interpersonal (i.e., social environment), and sociodemographic characteristics. Participants were 9254 youth from the Adolescent Brain Cognitive Development Study®. Latent factors reflecting SMA, cognition, psychopathology, and social environment were entered as independent variables into logistic mixed models. Sociodemographic covariates included age, sex, race/ethnicity, education, marital status, and household income. Outcome variables included any recreational activity endorsement (of 19 assessed), and specific sport (swimming, soccer, baseball) and hobby (music, art) endorsements. In unadjusted groupwise comparisons, youth who spent more time engaging with SMA were less likely to engage with other recreational activities (ps  .05). Some marginal effects were observed: for every one SD increase in time spent on games and movies over more social forms of media, youth were at lower odds of engaging in recreational activities (adjusted odds ratio = 0·83, 95% CI 0·76-0·89). Likewise, greater general SMA was associated with lower odds of endorsing group-based sports, including soccer (0·93, 0·88-0·98) and baseball (0·92, 0·86-0·98). Model fit comparisons indicated that sociodemographic characteristics, particularly socio-economic status, explained more variance in rates of recreational activity engagement than SMA and other latent factors. Notably, youth from higher socio-economic families were up to 5·63 (3·83-8·29) times more likely to engage in recreational activities than youth from lower socio-economic backgrounds. Results did not suggest that SMA largely displaces engagement in other recreational activities among 9-10-year-olds. Instead, socio-economic factors greatly contribute to rates of engagement. These findings are important considering recent shifts