Rowland Sheri, Bach Christina, Simon Krystyna, Westmark Danielle M, Sperling Edie
University of Nebraska Medical Center College of Nursing, Lincoln, USA.
Baptist Health, Jacksonville, USA.
Digit Health. 2024 Oct 7;10:20552076241282381. doi: 10.1177/20552076241282381. eCollection 2024 Jan-Dec.
Interventions using commercial digital health tools do favorably affect health outcomes. However, the effect of digital tools on cardiorespiratory fitness, a more novel indicator cardiovascular risk, is unclear.
Synthesize the digital health intervention literature and answer the following question: What is the effect of interventions using mobile health apps, wearable activity trackers, and/or text messaging on cardiorespiratory fitness?
A systematic review and a meta-analysis (PROSPERO CRD42023423925) were conducted to evaluate the immediate digital health intervention effect on adult cardiorespiratory fitness. In March 2023, a search of databases Embase, MEDLINE, CINHAL, and Cochrane Library was completed. Studies were included if the intervention used a mobile health app, text messaging, and/or activity tracker. Studies were excluded if an objective measure of fitness was not used; the sample included children; the setting was hospital-based; and the digital health technology was only used for data collection or described as virtual reality. Using a random-effects model, two separate meta-analyses were completed: one for single-group studies and one for multi-group studies. Standardized mean difference effect sizes (Cohen's ) were calculated. Study quality was evaluated with the Cochrane Risk of Bias tool and ROBINS-I tool.
Fifty-three studies (3657 individuals) with pre-post designs (12 single-group, 41 multi-group) were included. Most studies targeted participants with a specific chronic health condition. Digital health interventions in the single-group studies had a moderate-to-large effect size (= 0.62, 95% confidence interval () [0.41-0.84], < 0.001), and multi-group studies had small-to-moderate effect size (= 0.38, 95% 0.21-0.55, < 0.001). Significant heterogeneity of effects was observed in both the single-group and multi-group studies.
Interventions using text messaging, a mobile app, or activity tracker alone or in combination are effective in improving cardiorespiratory fitness in adults, particularly for those with a chronic health condition.
使用商业数字健康工具的干预措施确实会对健康结果产生积极影响。然而,数字工具对心肺适能(一种更新颖的心血管风险指标)的影响尚不清楚。
综合数字健康干预文献,并回答以下问题:使用移动健康应用程序、可穿戴活动追踪器和/或短信进行的干预对心肺适能有何影响?
进行了一项系统评价和荟萃分析(PROSPERO CRD42023423925),以评估数字健康干预对成人心肺适能的即时影响。2023年3月,完成了对Embase、MEDLINE、CINHAL和Cochrane图书馆数据库的检索。如果干预措施使用了移动健康应用程序、短信和/或活动追踪器,则纳入研究。如果未使用客观的体能测量方法;样本包括儿童;研究环境为医院;以及数字健康技术仅用于数据收集或被描述为虚拟现实,则排除研究。使用随机效应模型,完成了两项单独的荟萃分析:一项针对单组研究,一项针对多组研究。计算标准化平均差效应量(科恩d值)。使用Cochrane偏倚风险工具和ROBINS-I工具评估研究质量。
纳入了53项前后设计的研究(3657名个体)(12项单组研究,41项多组研究)。大多数研究针对患有特定慢性健康状况的参与者。单组研究中的数字健康干预具有中等到较大的效应量(d = 0.62,95%置信区间[CI] [0.41 - 0.84],P < 0.001),多组研究具有小到中等的效应量(d = 0.38,95% CI 0.21 - 0.55,P < 0.001)。在单组和多组研究中均观察到显著的效应异质性。
单独或联合使用短信、移动应用程序或活动追踪器进行干预,对改善成人心肺适能有效,尤其是对患有慢性健康状况的人。