‘Social screens’ and ‘the mainstream’: longitudinal competitors of non-organized physical activity in the transition from childhood to adolescence

Abstract

Background: Physical activity (PA) tends to decline during late childhood and adolescence. In Australia, this decline has been shown to occur particularly in non-organized PA (e.g. active play and informal sport). Using a social marketing approach, segments of youth may be identified and targeted based on their profile of alternative activities that compete with non-organized PA during the transition to adolescence. The objectives of this study were to identify and describe segments of youth whose participation in non-organized PA declined between 11 and 13 years, based on changes in other potential competing activities during this period. Methods: Data were sourced from Waves 4 and 5 of the Longitudinal Study of Australian Children. Participation in non-organized PA and thirteen alternative activities (e.g. video games, homework, sleep) were measured using 24-h time-use diaries. Analyses were limited to participants whose non-organized PA had declined between 11 and 13 years (n = 1043). Two-stage cluster analysis was conducted and segments were described using chi-square and ttests. Results: Among the analytic sample, average non-organized PA participation declined by 87 min/day between 11y and 13y (p < 0.001). Two segments were identified (κ = 0.66). The 'Social Screens' segment (n = 143) had large increases in texting, emailing and social media use (+ 56 min/day, p < 0.001) and other internet use (+ 32 min/day, p < 0.001). Conversely, 'the Mainstream' segment (n = 900) had smaller increases in a wider range of activities, including other PA (organized PA, active transport, active chores/work) (+ 16.0 min/day, p < 0.001), homework/study (+ 9.5 min/day, p < 0.001) and electronic gaming (+ 6.7 min/day, p < 0.05). 'Social Screens' were more likely to attend public school, live in urban areas and have more advanced pubertal development (girls only). 'The Mainstream' were more likely to participate in PA and out-of-school activities. Conclusions: The 'Social Screens' segment had a much larger increase in texting, emailing, social media and other internet use, and lower participation in overall PA and out-of-school activities, compared with 'the Mainstream'. Future research may trial PA promotion strategies to replace benefits that this segment may seek in competing activities (e.g. social PA apps).

Are There Differences in Video Gaming and Use of Social Media among Boys and Girls?—A Mixed Methods Approach

“…Further, the analysis showed that the adolescent boys and girls had different views on playing and gaming. Previous studies have reported that teenage girls are often keen [ 36 ] to create their identities around new practices associated with adolescence, while distancing themselves from childhood-associated play activities [ 37 , 38 , 39 , 40 ]. Our findings are similar in that many girls linked video games to childhood.…”

The efficacy of using mobile applications in changing adolescent girls’ physical activity behaviour during weekends

“…mobile apps) with attractive functions and features to encourage and motivate adolescent girls to be physically active beyond physical and health education (PHE) lessons (e.g. weekends) could be another option to promote PA (Kemp et al, 2020).…”

“…There are many reasons contributing to the sedentary lifestyle of young adolescents. Longer screen time due to the usage of digital platforms such as apps, tweeting, blogging and social networking sites are changing adolescents’ priorities or preference for PA on a daily basis (Greenhow and Lewin, 2016; Kemp et al, 2020). Indeed, the use of digital devices such as smartphones is ubiquitous worldwide.…”

“…In Singapore, students as young as nine years old were reported to already own one (Singapore Press Holdings, 2017). Given that smartphones not only bring convenience to daily life but also easy accessibility to information and connectivity among young people (Casey et al, 2017; Greenhow and Lewin, 2016), their influence in the lives of most adolescents cannot be underestimated (Kemp et al, 2020).…”

Beyond Body Weight: Design and Validation of Psycho-Behavioural Living and Eating for Health Segments (LEHS) Profiles for Social Marketing

“…Importantly, while valuable as a predictor of risk, BMI is not particularly useful as a tool for informing interventions designed to reduce risks and induce the behavioural changes necessary to engender healthy lifestyles. Studies have shown that behavioural and psychographic segmentation is appropriate for tackling obesity [15,16]. However, the majority of papers on the topic continue to use physical and economic characteristics such as BMI, income, age, and education as a means to profile or segment the people in their research [17][18][19].…”