He Zihao, Wu Hua, Zhao Guanggao, Zhang Yiming, Li Chao, Xing Yachen, Xu Anjie, Yang Junchao, Wang Ronghui
School of Sport Science, Beijing Sport University, No. 48 Xinxi Road, Haidian District, Beijing, China.
School of Physical Education, Nanchang University, Nanchang, China.
BMC Public Health. 2025 Jan 7;25(1):71. doi: 10.1186/s12889-024-21251-9.
To explore the impact of the digital implementation of the Otago Exercise Program (OEP) on balance ability (static and dynamic), muscle strength, and fall efficacy in elderly people; and analyze different potential influencing factors in subgroups to find the most suitable training plan.
EBSCO, PubMed, Web of Science, and China Knowledge Network databases (core) were searched up to August 1, 2023. Experimental studies of implementing OEP based on digital technology to improve outcomes related to falls in the elderly were included. Bias risks were assessed using the Cochrane collaboration tool. Meta-analysis was performed to assess the pooled effect of balance ability (static and dynamic), muscle strength, and fall efficacy using a random effects model. Subgroup analyses were conducted to examine the potential modifying effects of different factors (e.g., training period, frequency, duration, age).
Twelve articles were included from the literature, including 10 randomized controlled trials, one single-group quasi-experimental study, and one case report. Digital technologies used in the studies were categorized into three types: (1) online interventions (Zoom, WeChat), (2) recorded videos (via computers, TVs, DVDs), and (3) wearable technologies (motion sensors, augmented reality systems). The implementation of OEP based on digital technology showed significantly improved on static balance (SMD = 0.86, 95% CI 0.35-1.37), dynamic balance (SMD = 1.07, 95% CI 0.90-1.24), muscular strength (SMD = 0.43, 95% CI 0.17-0.69), and fall efficacy (SMD=-0.70, 95% CI -0.98, -0.41); Subgroup analysis by period '≥12 weeks', frequency '≥3 times/week', and duration '≤45 minutes per session', respectively, showed significant improvements on static balance (SMD = 0.73, 95% CI 0.21-1.25; SMD = 0.86, 95% CI 0.35-1.37; SMD = 1.10, 95% CI 0.31-1.89), dynamic balance (SMD = 1.08, 95% CI 0.88-1.28; SMD = 1.01, 95% CI 0.93-1.27; SMD = 1.07, 95% CI 0.89-1.25), muscle strength (SMD = 0.43, 95% CI 0.10-0.75; SMD = 0.54, 95% CI 0.30-0.77; SMD = 0.53, 95% CI 0.19-0.87), and fall efficacy (SMD=-0.75, 95% CI -1.39, -0.11; SMD=-0.70, 95% CI -0.98, -0.41; SMD=-0.74, 95% CI -1.10, -0.39).
OEP implemented through digital technology effectively enhances static and dynamic balance, muscle strength, and self-efficacy in older adults. A training regimen of 12 weeks or more, with sessions occurring three or more times per week for 30 to 45 min, appears to be an effective approach for improving these outcomes based on the available evidence from the included studies. Future research should prioritize specific digital technologies and target populations, employing high-quality research designs to further explore these interventions, and consider new technologies such as wearables, to assess changes in fall prevalence.
探讨奥塔哥运动计划(OEP)数字化实施对老年人平衡能力(静态和动态)、肌肉力量和跌倒效能的影响;分析亚组中不同的潜在影响因素,以找到最合适的训练方案。
检索截至2023年8月1日的EBSCO、PubMed、Web of Science和中国知网数据库(核心)。纳入基于数字技术实施OEP以改善老年人跌倒相关结局的实验研究。使用Cochrane协作工具评估偏倚风险。采用随机效应模型进行荟萃分析,以评估平衡能力(静态和动态)、肌肉力量和跌倒效能的合并效应。进行亚组分析以检验不同因素(如训练周期、频率、持续时间、年龄)的潜在调节作用。
从文献中纳入12篇文章,包括10项随机对照试验、1项单组准实验研究和1例病例报告。研究中使用的数字技术分为三种类型:(1)在线干预(Zoom、微信),(2)录制视频(通过计算机、电视、DVD),(3)可穿戴技术(运动传感器、增强现实系统)。基于数字技术实施OEP在静态平衡(标准化均数差[SMD]=0.86,95%置信区间[CI]0.35 - 1.37)、动态平衡(SMD = 1.07,95% CI 0.90 - 1.24)、肌肉力量(SMD = 0.43,95% CI 0.17 - 0.69)和跌倒效能(SMD = - 0.70,95% CI - 0.98, - 0.41)方面均有显著改善;分别按周期“≥12周”、频率“≥每周3次”和持续时间“每次≤45分钟”进行亚组分析,结果显示在静态平衡(SMD = 0.73,95% CI 0.21 - 1.25;SMD = 0.86,95% CI 0.35 - 1.37;SMD = 1.10,95% CI 0.31 - 1.89)、动态平衡(SMD = 1.08,95% CI 0.88 - 1.28;SMD = 1.01,95% CI 0.93 - 1.27;SMD = 1.07,95% CI 0.89 - 1.25)、肌肉力量(SMD = 0.43,95% CI 0.10 - 0.75;SMD = 0.54,95% CI 0.30 - 0.77;SMD = 0.53,95% CI 0.19 - 0.87)和跌倒效能(SMD = - 0.75,95% CI - 1.39, - 0.11;SMD = - 0.70,95% CI - 0.98, - 0.41;SMD = - 0.74,95% CI - 1.10, - 0.39)方面均有显著改善。
通过数字技术实施的OEP能有效提高老年人的静态和动态平衡能力、肌肉力量及自我效能。根据纳入研究的现有证据,12周或更长时间的训练方案,每周进行3次或更多次训练,每次30至45分钟,似乎是改善这些结局的有效方法。未来的研究应优先关注特定的数字技术和目标人群,采用高质量的研究设计进一步探索这些干预措施,并考虑可穿戴设备等新技术,以评估跌倒发生率的变化。