系统回顾社区老年人对基于技术的跌倒预防计划的依从性:重新构想未来的干预措施。

PLOS digital health Pub Date : 2024-09-03 eCollection Date: 2024-09-01 DOI:10.1371/journal.pdig.0000579
Maureen C Ashe, Isis Kelly Dos Santos, Jefferson Erome, Jared Grant, Juliana Mollins, Sze-Ee Soh
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引用次数: 0

摘要

背景:预防计划,特别是运动,可以减少社区居住的老年人跌倒,但坚持率低限制了有效干预的益处。技术可以克服一些障碍,提高人们对预防计划的接受度和参与度,但人们对通过这种方式提供预防计划的依从性知之甚少。我们的目的是对 60 岁及以上居住在社区的老年人坚持使用基于技术的跌倒预防计划的证据进行综合。我们按照标准指南进行了一次系统性回顾,以确定针对社区老年人的远程交付(即没有或只有有限的面对面课程)技术型跌倒预防项目的随机对照试验。我们使用医学主题词表(MeSH)术语和关键词搜索了九个资料来源(2007 年至今)。首次搜索于 2023 年 6 月进行,并于 2023 年 12 月更新。我们还对纳入的研究进行了正向和反向引文检索。两位审稿人独立进行筛选和研究评估;一位作者提取数据,另一位作者确认结果。我们对依从性进行了随机效应荟萃分析,依从性是指参与者完成项目内容的情况,目的是进行荟萃回归,研究与依从性相关的因素以及依从性与功能移动性之间的关联。我们纳入了 11 项研究,共有 569 名干预参与者(平均年龄 74.5 岁)。这些研究使用了多种技术,如应用程序、电子游戏或虚拟同步课堂。八项研究的偏倚风险较低。五项干预措施自动收集了监测和完成锻炼课程的数据,两项研究收集了参与者的在线出勤情况,四项研究使用了自我报告的日记或出勤表。这些研究在使用技术的同时还采用了一些行为改变技术或策略。报告坚持数据的方式存在很大差异。未完成计划疗程(即退出或失去随访)的参与者的平均百分比(范围)为 14% (0-32%)。对于报告了已完成锻炼课程平均次数的研究而言,坚持技术预防跌倒计划的参与者比例的汇总估计值为 0.82 (95% CI 0.68, 0.93)。许多研究需要提供互联网接入、培训和/或资源(如平板电脑),以支持参与者参与干预。由于研究数量不足,我们无法对依从性和功能移动性进行元回归。报告该信息的研究中未出现严重不良事件(n = 8)。技术的使用可能会给项目实施和数据收集带来一些益处。但需要更好地报告坚持治疗的数据,并对使用技术的培训和技能发展以及干预措施中的行为改变策略进行常规整合和测量。我们可能有机会重新思考或重新设想如何利用技术来支持人们采用体育锻炼并将其融入日常生活中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Systematic review of adherence to technology-based falls prevention programs for community-dwelling older adults: Reimagining future interventions.

Background: Prevention programs, and specifically exercise, can reduce falls among community-dwelling older adults, but low adherence limits the benefits of effective interventions. Technology may overcome some barriers to improve uptake and engagement in prevention programs, although less is known on adherence for providing them via this delivery mode. We aimed to synthesize evidence for adherence to technology-based falls prevention programs in community-dwelling older adults 60 years and older. We conducted a systematic review following standard guidelines to identify randomized controlled trials for remote delivered (i.e., no or limited in-person sessions) technology-based falls prevention programs for community-dwelling older adults. We searched nine sources using Medical Subject Headings (MeSH) terms and keywords (2007-present). The initial search was conducted in June 2023 and updated in December 2023. We also conducted a forward and backward citation search of included studies. Two reviewers independently conducted screening and study assessment; one author extracted data and a second author confirmed findings. We conducted a random effects meta-analysis for adherence, operationalized as participants' completion of program components, and aimed to conduct meta-regressions to examine factors related to program adherence and the association between adherence and functional mobility. We included 11 studies with 569 intervention participants (average mean age 74.5 years). Studies used a variety of technology, such as apps, exergames, or virtual synchronous classes. Risk of bias was low for eight studies. Five interventions automatically collected data for monitoring and completion of exercise sessions, two studies collected participants' online attendance, and four studies used self-reported diaries or attendance sheets. Studies included some behavior change techniques or strategies alongside the technology. There was substantial variability in the way adherence data were reported. The mean (range) percent of participants who did not complete planned sessions (i.e., dropped out or lost to follow-up) was 14% (0-32%). The pooled estimate of the proportion of participants who were adherent to a technology-based falls prevention program was 0.82 (95% CI 0.68, 0.93) for studies that reported the mean number of completed exercise sessions. Many studies needed to provide access to the internet, training, and/or resources (e.g., tablets) to support participants to take part in the intervention. We were unable to conduct the meta-regression for adherence and functional mobility due to an insufficient number of studies. There were no serious adverse events for studies reporting this information (n = 8). The use of technology may confer some benefits for program delivery and data collection. But better reporting of adherence data is needed, as well as routine integration and measurement of training and skill development to use technology, and behavior change strategies within interventions. There may be an opportunity to rethink or reimagine how technology can be used to support people's adoption and integration of physical activity into daily life routines.

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