American University of Beirut, Beirut, Lebanon.
JMIR Mhealth Uhealth. 2022 Apr 8;10(4):e35479. doi: 10.2196/35479.
The effectiveness of smartphone apps for weight loss is limited by the diversity of interventions that accompany such apps. This research extends the scope of previous systematic reviews by including 2 subgroup analyses based on nonmobile interventions that accompanied smartphone use and human-based versus passive behavioral interventions.
The primary objective of this study is to systematically review and perform a meta-analysis of studies that evaluated the effectiveness of smartphone apps on weight loss in the context of other interventions combined with app use. The secondary objective is to measure the impact of different mobile app features on weight loss and mobile app adherence.
We conducted a systematic review and meta-analysis of relevant studies after an extensive search of the PubMed, MEDLINE, and EBSCO databases from inception to January 31, 2022. Gray literature, such as abstracts and conference proceedings, was included. Working independently, 2 investigators extracted the data from the articles, resolving disagreements by consensus. All randomized controlled trials that used smartphone apps in at least 1 arm for weight loss were included. The weight loss outcome was the change in weight from baseline to the 3- and 6-month periods for each arm. Net change estimates were pooled across the studies using random-effects models to compare the intervention group with the control group. The risk of bias was assessed independently by 2 authors using the Cochrane Collaboration tool for assessing the risk of bias in randomized trials.
Overall, 34 studies were included that evaluated the use of a smartphone app in at least 1 arm. Compared with controls, the use of a smartphone app-based intervention showed a significant weight loss of -1.99 kg (95% CI -2.19 to -1.79 kg; I=81%) at 3 months and -2.80 kg (95% CI -3.03 to -2.56 kg; I=91%) at 6 months. In the subgroup analysis, based on the various intervention components that were added to the mobile app, the combination of the mobile app, tracker, and behavioral interventions showed a statistically significant weight loss of -2.09 kg (95% CI -2.32 to -1.86 kg; I=91%) and -3.77 kg (95% CI -4.05 to -3.49 kg; I=90%) at 3 and 6 months, respectively. When a behavioral intervention was present, only the combination of the mobile app with intensive behavior coaching or feedback by a human coach showed a statistically significant weight loss of -2.03 kg (95% CI -2.80 to -1.26 kg; I=83%) and -2.63 kg (95% CI -2.97 to -2.29 kg; I=91%) at 3 and 6 months, respectively. Neither the type nor the number of mobile app features was associated with weight loss.
Smartphone apps have a role in weight loss management. Nevertheless, the human-based behavioral component remained key to higher weight loss results.
智能手机应用程序在减肥方面的效果受到伴随这些应用程序的干预措施多样性的限制。本研究通过纳入基于非移动干预措施和基于人与被动行为干预措施的 2 个子组分析，扩展了以前系统综述的范围。
本研究的主要目的是系统地回顾和进行荟萃分析，评估在使用智能手机应用程序的同时结合其他干预措施的情况下，智能手机应用程序对减肥的效果。次要目的是衡量不同移动应用程序功能对减肥和移动应用程序坚持使用的影响。
我们对从开始到 2022 年 1 月 31 日的 PubMed、MEDLINE 和 EBSCO 数据库进行了广泛搜索后，进行了系统评价和荟萃分析。纳入了灰色文献，如摘要和会议记录。两名研究人员独立从文章中提取数据，并通过共识解决分歧。所有使用智能手机应用程序至少在 1 个臂中减肥的随机对照试验均被纳入。减肥结果是每个臂的基线到 3 个月和 6 个月期间的体重变化。使用随机效应模型汇总研究之间的净变化估计值，以比较干预组和对照组。两名作者使用 Cochrane 协作工具独立评估偏倚风险，以评估随机试验的偏倚风险。
总体而言，纳入了 34 项研究，评估了至少在 1 个臂中使用智能手机应用程序的效果。与对照组相比，使用基于智能手机应用程序的干预措施在 3 个月时体重显著减轻-1.99 公斤（95%置信区间-2.19 至-1.79 公斤；I=81%），在 6 个月时体重减轻-2.80 公斤（95%置信区间-3.03 至-2.56 公斤；I=91%）。在亚组分析中，基于添加到移动应用程序的各种干预组件，移动应用程序、跟踪器和行为干预措施的组合显示出统计学上显著的体重减轻，分别为-2.09 公斤（95%置信区间-2.32 至-1.86 公斤；I=91%）和-3.77 公斤（95%置信区间-4.05 至-3.49 公斤；I=90%），分别在 3 个月和 6 个月时。当存在行为干预时，只有移动应用程序与密集行为指导或人类教练的反馈相结合时，体重才会出现统计学上显著的减轻，分别为-2.03 公斤（95%置信区间-2.80 至-1.26 公斤；I=83%）和-2.63 公斤（95%置信区间-2.97 至-2.29 公斤；I=91%），分别在 3 个月和 6 个月时。移动应用程序的类型或数量与减肥均无关。
智能手机应用程序在减肥管理中发挥作用。然而，基于人的行为成分仍然是取得更高减肥效果的关键。
