Zhang Yan, Ngai Fei Wan, Yang Qingling, Xie Yao Jie
Department of Cardiology, Affiliated Hospital of Qingdao University, Qingdao, China.
School of Nursing, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Rd, Hung Hom, Hong Kong, 999077, China, 852 34003798, 852 23649663.
JMIR Mhealth Uhealth. 2025 Jun 24;13:e59943. doi: 10.2196/59943.
BACKGROUND: Individuals with chronic diseases commonly engage in a sedentary lifestyle, which may exacerbate poor disease progression and increase the burden of care. Digital health interventions have been broadly used in promoting healthy lifestyles in recent decades, while their effectiveness on sedentary behavior (SB) remains inconsistent and inconclusive. OBJECTIVE: This review aimed to evaluate the effectiveness of digital health interventions in reducing SB among patients with chronic diseases. METHODS: PubMed, Embase, Scopus, Web of Science, CINAHL Complete, Cochrane Library, and ACM Digital Library were searched for randomized controlled trials published from January 2000 to October 2023. Two researchers independently screened studies and evaluated study quality. The revised Cochrane risk-of-bias tool was used to assess the risk of bias. Mean differences (MDs) were calculated for intervention effect comparison. RESULTS: Twenty-six trials were selected and 3800 participants were included. The mean age was 57.32 (SD 9.91) years. The typical chronic diseases reported in the studies included obesity (n=6), arthritis (n=5), coronary artery disease (n=4), cancer (n=4), type 2 diabetes mellitus (n=3), metabolic syndrome (n=2), and stroke (n=2). Phone, web, and activity trackers were 3 digital technologies adopted in the interventions and they were used in combination in most studies (18/26, 69.2%). The functions included facilitating self-monitoring of SB, reminding interruption of long undisturbed sitting, and promoting goal attainment. Approaches targeting SB reduction included standing (n=6), walking (n=9), light physical activity (n=5), moderate to vigorous physical activity (n=4), screen time limitation (n=2), and contextual-related activities based on patients' preference (n=4). The majority (80.8%) of studies had a low to moderate risk of bias. Meta-analysis revealed significant decreases in overall sitting time (MD -30.80; 95% CI -49.79 to-11.82; I2=65%; P=.001), pre-post sitting time changes (MD -50.28; 95% CI -92.99 to -7.57; I2=92%; P=.02), and SB proportions (MD -4.65%; 95% CI -7.02 to -2.28; I2=20%; P<.001) after digital health interventions, compared with nondigital interventions such as usual care, wait-list, or other active controls, with a small effect size (Cohen d=-0.27 to -0.47). No significant differences in the length of sedentary bouts and breaks were found. Subgroup analyses showed that studies with objective SB measurements and those younger than 65 years had significant reductions in sitting time. CONCLUSIONS: Digital health interventions significantly reduced the SB among patients with chronic illness. More research with rigorous design to promote a long-term decrease in sitting time, differentiate primary and compensatory SB reductions, and explore the underlying mechanisms is needed.
背景:慢性病患者通常久坐不动,这可能会加剧疾病进展不佳并增加护理负担。近几十年来,数字健康干预措施已广泛用于促进健康的生活方式,但其对久坐行为(SB)的有效性仍不一致且尚无定论。 目的:本综述旨在评估数字健康干预措施在减少慢性病患者久坐行为方面的有效性。 方法:检索了PubMed、Embase、Scopus、Web of Science、CINAHL Complete、Cochrane图书馆和ACM数字图书馆,以查找2000年1月至2023年10月发表的随机对照试验。两名研究人员独立筛选研究并评估研究质量。使用修订后的Cochrane偏倚风险工具评估偏倚风险。计算干预效果比较的平均差值(MDs)。 结果:选取了26项试验,纳入3800名参与者。平均年龄为57.32(标准差9.91)岁。研究中报告的典型慢性病包括肥胖(n = 6)、关节炎(n = 5)、冠状动脉疾病(n = 4)、癌症(n = 4)、2型糖尿病(n = 3)、代谢综合征(n = 2)和中风(n = 2)。电话、网络和活动追踪器是干预措施中采用的3种数字技术,大多数研究(18/26,69.2%)将它们结合使用。其功能包括促进对久坐行为的自我监测、提醒打断长时间不间断的坐姿以及促进目标达成。针对减少久坐行为的方法包括站立(n = 6)、步行(n = 9)、轻度体育活动(n = 5)、中度至剧烈体育活动(n = 4)、限制屏幕时间(n = 2)以及根据患者偏好进行的情境相关活动(n = 4)。大多数(80.8%)研究的偏倚风险为低至中度。荟萃分析显示,与常规护理、等待名单或其他积极对照等非数字干预措施相比,数字健康干预措施后总体久坐时间显著减少(MD -30.80;95%CI -49.79至-11.82;I² = 65%;P = 0.001),久坐前后时间变化(MD -50.28;95%CI -92.99至-7.57;I² = 92%;P = 0.02)以及久坐行为比例(MD -4.65%;95%CI -7.02至-2.28;I² = 20%;P < 0.001),效应量较小(Cohen d = -0.27至-0.47)。久坐时长和休息时长未发现显著差异。亚组分析表明,采用客观久坐行为测量的研究以及65岁以下人群的研究久坐时间显著减少。 结论:数字健康干预措施显著减少了慢性病患者的久坐行为。需要进行更多设计严谨的研究,以促进久坐时间的长期减少,区分主要和代偿性久坐行为的减少,并探索潜在机制。
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