A Meta-analysis of Interventions That Target Children’s Screen Time for Reduction abstract

BACKGROUND: Screen time, especially television viewing, is associated with risk of overweight and obesity in children. Although several interventions have been developed to reduce children’s screen time, no systematic review of these interventions exists to date. OBJECTIVE: This is a systematic review and meta-analysis of interventions targeting a reduction in children’s screen time. METHODS: Effect sizes and associated 95% confidence intervals (CIs) were calculated by using a random-effects model. Heterogeneity tests, moderator analyses, assessment of bias, and sensitivity analyses were conducted. Reliability was assessed with Cohen’s . RESULTS: The systematic search identified 3002 documents; 33 were eligible for inclusion, and 29 were included in analyses. Most reported preintervention and postintervention data and were published in peerreviewed journals. Although heterogeneity was present, no moderators were identified. Overall Hedges g ( 0.144 [95% CI: 0.217 to 0.072]) and standard mean difference (SMD) ( 0.148 [95% CI: 0.224 to 0.071]) indicated that interventions were linked with small but statistically significant reductions in screen time in children. The results were robust; the failsafe N was large, and the funnel plot and trim-and-fill methods identified few missing studies. CONCLUSIONS: Results show that interventions to reduce children’s screen timehave a small but statistically significant effect. As the evidence base expands, and the number of screen-time interventions increases, future research can expand on these findings by examining the clinical relevance and sustainability of effects, conducting a more thorough analysis of effect modifiers, and identifying critical components of effective interventions. Pediatrics 2011;128:e193–e210 AUTHORS: Dayna M. Maniccia, DrPH, MS,a Kirsten K. Davison, PhD, MS,a Simon J. Marshall, PhD, MA,b Jennifer A. Manganello, PhD, MPH,a and Barbara A. Dennison, MDc,d Departments of aHealth Policy, Management, and Behavior and cEpidemiology, School of Public Health, University at Albany, State University of New York, Albany, New York; bSchool of Exercise and Nutritional Sciences, San Diego State University, San Diego, California; and dDivision of Chronic Disease and Injury Prevention, New York State Department of Health, Albany, New York