Purpose: Although adolescence is often marked by declining physical activity participation, some individuals maintain physical activity throughout this period. The objectives were to identify sub-groups of youth who present distinct physical activity profiles and factors contributing to these physical activity profiles during adolescence.  A better understanding of these profiles and their determinants would provide guidance for tailored interventions.

Methods: A purposeful sample of 23 physically active participants [mean age=12.2 (0.6) years; 52% female at study inception] enrolled in the Monitoring Activities of Teenagers to Comprehend their Habits (MATCH) prospective study were interviewed once a year for five years for this qualitative descriptive study. The semi-structured interview guide was anchored in the self-determination theory, the developmental model of sport participation, and the socio-ecological model, and designed to enable participants to describe their physical activity experience during adolescence. Verbatim transcripts were coded inductively and iteratively to characterize each participant’s personal trajectory. Physical activity profiles were then created by grouping participants based on the similarities and differences of their longitudinal experiences.

Results/findings: Four distinct profiles captured participants’ physical activity experiences throughout adolescence. Profiles identified include the Independents (i.e., physical activity participation in harmony with the need for autonomy); Multitaskers (i.e., involvement in a large variety of sports and activities as a way of life); Specialists (i.e., high achievement aspirations); and Unintentionals (i.e., engagement in physical activity as a way to pass time or to conform to others’ expectations). Each profile presents a unique physical activity participation trajectory, key defining characteristics, and distinct motives for participation. Moreover, the different profiles are associated with different likelihoods of maintaining physical activity throughout adolescence.

Conclusions: The characterisation of these profiles and physical activity-related experiences has implications for development of theories and physical activity participation models. Moreover, since motives and determinants for participation in physical activity vary considerably across physical activity profiles, consideration of these variations could advance initiatives aimed at promoting sustained physical activity throughout adolescence.   

Although sufficient sleep is important for adolescents’ mental and physical health, more than half report less than the recommended eight hours of sleep on school days. The current study aims to investigate which psychosocial determinants (i.e., knowledge, attitude, social influence, self-efficacy, barriers and facilitators) predict a 1-year change in adolescents’ sleeping duration. This can subsequently guide the development of new and successful interventions. So far, research into multiple psychosocial determinants of sleeping behavior in adolescents has been scarce. Moreover, previous studies were mostly cross-sectional, while the current study investigated determinants of sleeping behavior longitudinally. Psychosocial determinants of sleep, as well as sleep quantity at school days and free days were assessed at baseline and one year later by means of a questionnaire in 1097 Flemish adolescents (M_age = 15.01, SD = 0.65, 46.3 % girls). The questionnaire included items of the Munich Chronotype Questionnaire for Children, as well as questions on psychosocial determinants of sleep. Multiple linear regression analyses were conducted in SPSS. Results show that a more positive attitude at baseline predicted a positive change in sleeping duration on school days after one year (β = .08, p = 0.02), while external barriers at baseline negatively predicted a change in sleeping duration on school days after one year (β  = -.12, p = p < .001). Moreover, a more positive attitude at baseline predicted a positive change in sleeping duration on free days after one year (β = .07, p = .04), while external barriers, especially screen use before bedtime at baseline negatively predicted a change in sleeping duration on free days after one year (β = -.08, p = .01). The current results imply that interventions to promote healthy sleep in adolescents might target the perceived benefits of sleeping behavior, external barriers, and screen time before bed, in order to successfully improve sleep duration. By using a longitudinal framework to investigate multiple psychosocial determinants of sleeping behavior in adolescents, the current study adds to the existing body of knowledge.

Background: Body image variables, like body size perception (BSP) and body size dissatisfaction (BSD), can influence health-related behaviors. However, few studies have investigated these body image variables in adolescent girls participating in a physical activity intervention. Therefore, the study objectives was to examine 1) the association between health-related behaviors (physical activity, screen time, eating habits and sleep duration) with BSP and BSD among girls participating in FitSpirit, a physical activity intervention for girls only; 2) the influence of weight control practices on the association between health-related behaviors with BSP and BSD.

Methods: A sample of 545 adolescent girls (15.0±1.5 years) from different schools participated in this cross-sectional study. Body mass index, health-related behaviors, perceived actual body size and desired body size variables, were self-reported and collected via an online questionnaire at the end of the FitSpirit intervention. A negative BSP score [perceived actual body size – calculated BMI z-score] indicates an underestimation of body size. A positive BSD score [perceived actual body size – desired body size] indicates a desire to reduce body size. A multiple linear regression analysis examined the effects of age, zBMI and health behaviors on BSP and BSD. A second multiple linear regression analysis examines the independent association of BSP and BSD by weight control practice. The linear relationships between BSP and BSD were evaluated with Pearson’s correlation.

Results: Underestimation and dissatisfaction of body size are more prevalent in participants living with overweight/obesity. Screen time and sleep duration were significantly, independently associated with BSP score (Beta=0.02; P<0.05 and Beta=-0.07; P<0.05, respectively), whereas only screen time was associated with BSD score (Beta=0.07; P<0.001). Physical activity was independently associated with BSP score only in participants trying to control their weight (Beta=-0.18; P<0.05).

Conclusions: Body size overestimation and dissatisfaction are associated with health-related behaviors, specifically with more screen time and less than optimal sleeping habits. Physical activity level does not appear to be associated with body image in girls engaged in a physical activity intervention and who want to lose or gain weight. Health promotion interventions could include screen time and sleep components as it may influenced body image. 

Importance: Experimental data assessing the mediation of physical activity (PA) and screen time (ST) on the relationship between school-based interventions and adolescents’ health-related quality of life (HRQoL) is required further to understand the complex pathways towards effective health promotion.

Purpose: To evaluate the direct and indirect effects of changes in PA, ST, and psychosocial determinants (self-efficacy, outcome expectations, and social support) on the relationship between a school-based intervention and the HRQoL.

Methods: The Movimente program was performed in Florianopolis, Brazil, over an academic year in 2017. Six out of eighteen eligible schools agreed to participate and were randomized as intervention or control. The strategies consisted of teacher training about PA and ST, educational strategies through the availability of folders/posters, and the creation of PA spaces at the schools. Validated questionnaires were used to measure HRQoL(Kidscreen-27), PA, ST, psychosocial determinants, sex, age, and socioeconomic status. A structural equation modeling approach was performed to examine the direct (whether pre-post changes on mediators were associated with HRQoL) and indirect effects (mediation) through the product-of-coefficients.

Results: A total of 734 (1.5:1 intervention-control ratio) out of the 921 (girls=51.7%, age mean=13.0) students assessed at the baseline completed the trial. There was no significant indirect effects. We found the following direct effects: (i) PA self-efficacy (b=0.072, p=0.026), PA outcome expectations (b=0.135, p<0.001), parents support for PA (b=0.086, p=0.008), and friends support for PA (b=0.075, p=0.022) on physical well-being; (ii) PA self-efficacy (b=0.074, p=0.024), PA outcome expectations (b=0.086, p=0.009), parents support for PA (b=0.070, p=0.034), and family support for reducing ST (b=0.121, p<0.001) on psychological well-being; (iii) ST self-efficacy (b=0.079, p=0.022), and friends support for PA (b=0.095, p=0.006) on peers & social support; (iv) parents support for PA (b=0.140, p<0.001) on autonomy & parent’s relation; (v) PA outcome expectations (b=0.089, p=0.010), friends support for PA (b=0.138, p<0.001); and ST (b=0.081, p=0.025) on school environment.

Conclusions: Pre-post changes in PA and ST psychosocial determinants were related to HRQoL. However, we found difficulties in changing PA and ST through the intervention strategies, which partially explains no mediation effects.