Effectiveness of mHealth App–Based Interventions for Increasing Physical Activity and Improving Physical Fitness in Children and Adolescents: Systematic Review and Meta-Analysis

Author:

Wang Jun-WeiORCID,Zhu ZhichengORCID,Shuling ZhangORCID,Fan JiaORCID,Jin YuORCID,Gao Zhan-LeORCID,Chen Wan-DiORCID,Li XueORCID

Abstract

Background The COVID-19 pandemic has significantly reduced physical activity (PA) levels and increased sedentary behavior (SB), which can lead to worsening physical fitness (PF). Children and adolescents may benefit from mobile health (mHealth) apps to increase PA and improve PF. However, the effectiveness of mHealth app–based interventions and potential moderators in this population are not yet fully understood. Objective This study aims to review and analyze the effectiveness of mHealth app–based interventions in promoting PA and improving PF and identify potential moderators of the efficacy of mHealth app–based interventions in children and adolescents. Methods We searched for randomized controlled trials (RCTs) published in the PubMed, Web of Science, EBSCO, and Cochrane Library databases until December 25, 2023, to conduct this meta-analysis. We included articles with intervention groups that investigated the effects of mHealth-based apps on PA and PF among children and adolescents. Due to high heterogeneity, a meta-analysis was conducted using a random effects model. The Cochrane Risk of Bias Assessment Tool was used to evaluate the risk of bias. Subgroup analysis and meta-regression analyses were performed to identify potential influences impacting effect sizes. Results We included 28 RCTs with a total of 5643 participants. In general, the risk of bias of included studies was low. Our findings showed that mHealth app–based interventions significantly increased total PA (TPA; standardized mean difference [SMD] 0.29, 95% CI 0.13-0.45; P<.001), reduced SB (SMD –0.97, 95% CI –1.67 to –0.28; P=.006) and BMI (weighted mean difference –0.31 kg/m2, 95% CI –0.60 to –0.01 kg/m2; P=.12), and improved muscle strength (SMD 1.97, 95% CI 0.09-3.86; P=.04) and agility (SMD –0.35, 95% CI –0.61 to –0.10; P=.006). However, mHealth app–based interventions insignificantly affected moderate to vigorous PA (MVPA; SMD 0.11, 95% CI –0.04 to 0.25; P<.001), waist circumference (weighted mean difference 0.38 cm, 95% CI –1.28 to 2.04 cm; P=.65), muscular power (SMD 0.01, 95% CI –0.08 to 0.10; P=.81), cardiorespiratory fitness (SMD –0.20, 95% CI –0.45 to 0.05; P=.11), muscular endurance (SMD 0.47, 95% CI –0.08 to 1.02; P=.10), and flexibility (SMD 0.09, 95% CI –0.23 to 0.41; P=.58). Subgroup analyses and meta-regression showed that intervention duration was associated with TPA and MVPA, and age and types of intervention was associated with BMI. Conclusions Our meta-analysis suggests that mHealth app–based interventions may yield small-to-large beneficial effects on TPA, SB, BMI, agility, and muscle strength in children and adolescents. Furthermore, age and intervention duration may correlate with the higher effectiveness of mHealth app–based interventions. However, due to the limited number and quality of included studies, the aforementioned conclusions require validation through additional high-quality research. Trial Registration PROSPERO CRD42023426532; https://tinyurl.com/25jm4kmf

Publisher

JMIR Publications Inc.

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