Erin E Brannon1, Christopher C Cushing2. 1. Department of Psychology, Oklahoma State University and Clinical Child Psychology Program, University of Kansas. 2. Department of Psychology, Oklahoma State University and Clinical Child Psychology Program, University of Kansas christopher.cushing@ku.edu.
Abstract
OBJECTIVE: Systematically review and meta-analyze the pediatric literature on behavior-change techniques (BCT) as defined by Abraham & Michie (Health Psychology, 27, 379-387, 2008), and describe whether the most effective BCTs are incorporated in physical activity (PA) and dietary mobile apps. METHODS: Randomized controlled trials (n = 74) targeting diet or PA were meta-analyzed. Metaregressions were used to determine which BCTs predict aggregate effect size (ES). iTunes™ apps were coded for presence/absence of BCTs that produce larger ES. RESULTS: Modeling was the only predictor of PA ES in children (aged 6-13 years). Consequences for behavior, other's approval, self-monitoring, intention formation, and behavioral contracting significantly predicted PA for adolescents. Modeling and social support predicted dietary ES in adolescents and children, respectively. Practice was also a significant predictor for children. A majority of effective strategies for children were not widely incorporated in apps; however, the picture is more optimistic for adolescents. CONCLUSIONS: More collaboration is needed between pediatric psychologists and technologists to incorporate evidence-based BCTs into developmentally appropriate mobile apps.
OBJECTIVE: Systematically review and meta-analyze the pediatric literature on behavior-change techniques (BCT) as defined by Abraham & Michie (Health Psychology, 27, 379-387, 2008), and describe whether the most effective BCTs are incorporated in physical activity (PA) and dietary mobile apps. METHODS: Randomized controlled trials (n = 74) targeting diet or PA were meta-analyzed. Metaregressions were used to determine which BCTs predict aggregate effect size (ES). iTunes™ apps were coded for presence/absence of BCTs that produce larger ES. RESULTS: Modeling was the only predictor of PA ES in children (aged 6-13 years). Consequences for behavior, other's approval, self-monitoring, intention formation, and behavioral contracting significantly predicted PA for adolescents. Modeling and social support predicted dietary ES in adolescents and children, respectively. Practice was also a significant predictor for children. A majority of effective strategies for children were not widely incorporated in apps; however, the picture is more optimistic for adolescents. CONCLUSIONS: More collaboration is needed between pediatric psychologists and technologists to incorporate evidence-based BCTs into developmentally appropriate mobile apps.
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