Background: Mobile health (mHealth) interventions can increase physical activity (PA); however, their long-term impact is not well understood. Objective: The primary aim of this study is to understand the immediate and long-term effects of mHealth interventions on PA. The secondary aim is to explore potential effect moderators. Methods: We performed this study according to the Cochrane and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We searched PubMed, the Cochrane Library, SCOPUS, and PsycINFO in July 2020. Eligible studies included randomized controlled trials of mHealth interventions targeting PA as a primary outcome in adults. Eligible outcome measures were walking, moderate-to-vigorous physical activity (MVPA), total physical activity (TPA), and energy expenditure. Where reported, we extracted data for 3 time points (ie, end of intervention, follow-up ≤6 months, and follow-up >6 months). To explore effect moderators, we performed subgroup analyses by population, intervention design, and control group type. Results were summarized using random effects meta-analysis. Risk of bias was assessed using the Cochrane Collaboration tool. Results: Of the 2828 identified studies, 117 were included. These studies reported on 21,118 participants with a mean age of 52.03 (SD 14.14) years, of whom 58.99% (n=12,459) were female. mHealth interventions significantly increased PA across all the 4 outcome measures at the end of intervention (walking standardized mean difference [SMD] 0.46, 95% CI 0.36-0.55; P<.001; MVPA SMD 0.28, 95% CI 0.21-0.35; P<.001; TPA SMD 0.34, 95% CI 0.20-0.47; P<.001; energy expenditure SMD 0.44, 95% CI 0.13-0.75; P=.01). Only 33 studies reported short-term follow-up measurements, and 8 studies reported long-term follow-up measurements in addition to end-of-intervention results. In the short term, effects were sustained for walking (SMD 0.26, 95% CI 0.09-0.42; P=.002), MVPA (SMD 0.20, 95% CI 0.05-0.35; P=.008), and TPA (SMD 0.53, 95% CI 0.13-0.93; P=.009). In the long term, effects were also sustained for walking (SMD 0.25, 95% CI 0.10-0.39; P=.001) and MVPA (SMD 0.19, 95% CI 0.11-0.27; P<.001). We found the study population to be an effect moderator, with higher effect scores in sick and at-risk populations. PA was increased both in scalable and nonscalable mHealth intervention designs and regardless of the control group type. The risk of bias was rated high in 80.3% (94/117) of the studies. Heterogeneity was significant, resulting in low to very low quality of evidence. Conclusions: mHealth interventions can foster small to moderate increases in PA. The effects are maintained long term; however, the effect size decreases over time. The results encourage using mHealth interventions in at-risk and sick populations and support the use of scalable mHealth intervention designs to affordably reach large populations. However, given the low evidence quality, further methodologically rigorous studies are warranted to evaluate the long-term effects.

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中文翻译：

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移动健康身体活动干预措施的长期有效性：随机对照试验的系统回顾和荟萃分析


背景：移动健康（mHealth）干预措施可以增加体力活动（PA）；然而，它们的长期影响尚不清楚。目的：本研究的主要目的是了解移动健康干预措施对 PA 的近期和长期影响。第二个目标是探索潜在的影响调节因素。方法：我们根据 Cochrane 和 PRISMA（系统评价和荟萃分析的首选报告项目）指南进行本研究。我们于 2020 年 7 月检索了 PubMed、Cochrane 图书馆、SCOPUS 和 PsycINFO。符合条件的研究包括以 PA 作为成人主要结局的 mHealth 干预措施的随机对照试验。合格的结果指标包括步行、中度至剧烈体力活动（MVPA）、总体力活动（TPA）和能量消耗。在报告时，我们提取了 3 个时间点的数据（即干预结束、随访≤6 个月和随访 >6 个月）。为了探索效应调节因素，我们按人群、干预设计和对照组类型进行了亚组分析。使用随机效应荟萃分析总结结果。使用 Cochrane 协作工具评估偏倚风险。结果：在 2828 项已确定的研究中，纳入了 117 项。这些研究报告了 21,118 名参与者，平均年龄为 52.03 (SD 14.14) 岁，其中 58.99% (n=12,459) 为女性。移动健康干预措施在干预结束时显着提高了所有 4 项结果指标的 PA（步行标准化平均差 [S​​MD] 0.46，95% CI 0.36-0.55；P<.001；MVPA SMD 0.28，95% CI 0.21-0.35； P<.001；TPA SMD 0.34，95% CI 0.20-0.47；P<.001；能量消耗 SMD 0.44，95% CI 0.13-0.75； 只有 33 项研究报告了短期随访测量结果，8 项研究除了干预结束结果外还报告了长期随访测量结果。短期内，步行（SMD 0.26，95% CI 0.09-0.42；P=.002）、MVPA（SMD 0.20，95% CI 0.05-0.35；P=.008）和 TPA（SMD 0.53）的效果持续存在。 ，95% CI 0.13-0.93；P=.009)。从长远来看，步行（SMD 0.25，95% CI 0.10-0.39；P=.001）和 MVPA（SMD 0.19，95% CI 0.11-0.27；P<.001）的效果也持续存在。我们发现研究人群是效应调节因素，患病和高危人群的效应得分较高。无论对照组类型如何，PA 在可扩展和不可扩展的移动医疗干预设计中均有所增加。 80.3% (94/117) 的研究中偏倚风险被评为高。异质性显着，导致证据质量低至极低。结论：移动健康干预措施可以促进 PA 小到中度增加。效果长期维持；然而，效果大小会随着时间的推移而减小。研究结果鼓励对高危人群和患病人群使用移动医疗干预措施，并支持使用可扩展的移动医疗干预设计，以经济实惠的方式惠及大量人群。然而，鉴于证据质量较低，有必要进行进一步的方法学严格研究来评估长期影响。


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