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基于移动健康应用程序的干预措施对增加儿童和青少年身体活动和改善身体适应性的有效性:系统评价和荟萃分析。

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

机构信息

School of Sport Medicine and Health, Chengdu Sport University, Chengdu, China.

School of Sports Science, Beijing Sport University, Beijing, China.

出版信息

JMIR Mhealth Uhealth. 2024 Apr 30;12:e51478. doi: 10.2196/51478.


DOI:10.2196/51478
PMID:38687568
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11094610/
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/m, 95% CI -0.60 to -0.01 kg/m; 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.

摘要

背景:COVID-19 大流行显著降低了身体活动 (PA) 水平,增加了久坐行为 (SB),这可能导致身体适应性 (PF) 恶化。儿童和青少年可能受益于移动健康 (mHealth) 应用程序来增加 PA 并改善 PF。然而,mHealth 应用程序干预的有效性及其在该人群中的潜在调节因素尚不完全清楚。

目的:本研究旨在综述和分析 mHealth 应用程序干预在促进 PA 和改善 PF 方面的有效性,并确定 mHealth 应用程序干预在儿童和青少年中的疗效的潜在调节因素。

方法:我们在 PubMed、Web of Science、EBSCO 和 Cochrane Library 数据库中搜索了截至 2023 年 12 月 25 日发表的随机对照试验 (RCT),以进行这项荟萃分析。我们纳入了干预组调查 mHealth 应用程序对儿童和青少年 PA 和 PF 影响的文章。由于存在高度异质性,我们使用随机效应模型进行了荟萃分析。使用 Cochrane 偏倚风险评估工具评估偏倚风险。进行了亚组分析和荟萃回归分析,以确定潜在影响效应大小的因素。

结果:我们纳入了 28 项 RCT,共有 5643 名参与者。总体而言,纳入研究的偏倚风险较低。我们的研究结果表明,mHealth 应用程序干预显著增加了总身体活动 (TPA;标准化均数差 [SMD] 0.29,95%置信区间 [CI] 0.13-0.45;P<.001)、减少了久坐行为 (SB;SMD -0.97,95% CI -1.67 至 -0.28;P=.006) 和 BMI (体重加权均数差 -0.31 kg/m,95% CI -0.60 至 -0.01 kg/m;P=.12),并改善了肌肉力量 (SMD 1.97,95% CI 0.09-3.86;P=.04) 和敏捷性 (SMD -0.35,95% CI -0.61 至 -0.10;P=.006)。然而,mHealth 应用程序干预对中度至剧烈身体活动 (MVPA;SMD 0.11,95% CI -0.04 至 0.25;P<.001)、腰围 (体重加权均数差 0.38 cm,95% CI -1.28 至 2.04 cm;P=.65)、肌肉力量 (SMD 0.01,95% CI -0.08 至 0.10;P=.81)、心肺适能 (SMD -0.20,95% CI -0.45 至 0.05;P=.11)、肌肉耐力 (SMD 0.47,95% CI -0.08 至 1.02;P=.10) 和灵活性 (SMD 0.09,95% CI -0.23 至 0.41;P=.58) 的影响则不显著。亚组分析和荟萃回归显示,干预持续时间与 TPA 和 MVPA 相关,年龄和干预类型与 BMI 相关。

结论:我们的荟萃分析表明,mHealth 应用程序干预可能对儿童和青少年的 TPA、SB、BMI、敏捷性和肌肉力量产生小到中等的有益影响。此外,年龄和干预持续时间可能与 mHealth 应用程序干预的更高效果相关。然而,由于纳入研究的数量和质量有限,上述结论需要通过更多高质量的研究来验证。

试验注册:PROSPERO CRD42023426532;https://tinyurl.com/25jm4kmf。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a137/11094610/216b755dfb30/mhealth_v12i1e51478_fig13.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a137/11094610/9168ff9711e7/mhealth_v12i1e51478_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a137/11094610/5252fc861f2a/mhealth_v12i1e51478_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a137/11094610/23b20d3fda3d/mhealth_v12i1e51478_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a137/11094610/51eb49b6d4cb/mhealth_v12i1e51478_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a137/11094610/9fce7e6fbdfd/mhealth_v12i1e51478_fig5.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a137/11094610/3203e6ec5e4f/mhealth_v12i1e51478_fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a137/11094610/f934275369d5/mhealth_v12i1e51478_fig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a137/11094610/6f7dcc64af72/mhealth_v12i1e51478_fig9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a137/11094610/caa627a92034/mhealth_v12i1e51478_fig10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a137/11094610/8db43cf35fc6/mhealth_v12i1e51478_fig11.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a137/11094610/216b755dfb30/mhealth_v12i1e51478_fig13.jpg

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