Effectiveness of Digital Health Interventions on Sedentary Behavior Among Patients With Chronic Diseases: Systematic Review and Meta-Analysis.

IF 6.2 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Yan Zhang, Fei Wan Ngai, Qingling Yang, Yao Jie Xie
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引用次数: 0

Abstract

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.

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数字健康干预对慢性病患者久坐行为的影响:系统回顾和荟萃分析
背景:患有慢性疾病的个体通常从事久坐不动的生活方式,这可能会加剧疾病的不良进展并增加护理负担。近几十年来,数字健康干预措施被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:本综述旨在评价数字健康干预在降低慢性疾病患者SB中的有效性。方法:检索PubMed、Embase、Scopus、Web of Science、CINAHL Complete、Cochrane Library和ACM Digital Library,检索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。采用修订后的Cochrane风险偏倚工具评估偏倚风险。计算干预效果的平均差异(md)。结果:共纳入26项试验,3800名受试者。平均年龄57.32岁(SD 9.91)。研究中报告的典型慢性疾病包括肥胖(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,在大多数研究中它们是联合使用的(18/26,69.2%)。其功能包括促进SB的自我监测,提醒长时间不受干扰的坐着的中断,以及促进目标的实现。针对SB减少的方法包括站立(n=6)、步行(n=9)、轻度体力活动(n=5)、中度至剧烈体力活动(n=4)、屏幕时间限制(n=2)和基于患者偏好的情境相关活动(n=4)。大多数(80.8%)的研究具有低至中等偏倚风险。荟萃分析显示,总体坐着时间显著减少(MD -30.80;95% CI -49.79 -11.82;I2 = 65%;P=.001),前后坐位时间变化(MD -50.28;95% CI -92.99 ~ -7.57;I2 = 92%;P=.02), SB比例(MD -4.65%;95% CI -7.02 ~ -2.28;I2 = 20%;结论:数字健康干预显著降低了慢性疾病患者的SB。需要更多严格设计的研究来促进长期坐着时间的减少,区分原发性和代偿性脑脊液减少,并探索潜在的机制。
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来源期刊
JMIR mHealth and uHealth
JMIR mHealth and uHealth Medicine-Health Informatics
CiteScore
12.60
自引率
4.00%
发文量
159
审稿时长
10 weeks
期刊介绍: JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a spin-off journal of JMIR, the leading eHealth journal (Impact Factor 2016: 5.175). JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, and Science Citation Index Expanded (SCIE), and in June 2017 received a stunning inaugural Impact Factor of 4.636. The journal focusses on health and biomedical applications in mobile and tablet computing, pervasive and ubiquitous computing, wearable computing and domotics. JMIR mHealth and uHealth publishes since 2013 and was the first mhealth journal in Pubmed. It publishes even faster and has a broader scope with including papers which are more technical or more formative/developmental than what would be published in the Journal of Medical Internet Research.
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