Centre for Epidemiology and Biostatistics, The University of Melbourne, Carlton, Australia.
Centre for Digital Transformation of Health, The University of Melbourne, Carlton, Australia.
J Med Internet Res. 2022 Feb 9;24(2):e27735. doi: 10.2196/27735.
Digital health interventions have revolutionized multiple sclerosis (MS) care by supporting people with MS to better self-manage their disease. It is now understood that the technological elements that comprise this category of digital health interventions can influence participant engagement in self-management programs, and people with MS can experience significant barriers, influenced by these elements, to remaining engaged during a period of learning. It is essential to explore the influence of technological elements in mitigating attrition.
This study aimed to examine the study design and technological elements of documented digital health interventions targeted at people with MS-digital health interventions that were intended to support a program of engagement over a defined period-and to explore how these correlated with attrition among participants of randomized controlled trials (RCTs).
We conducted a systematic review and meta-analysis of RCTs (n=32) describing digital health self-management interventions for people with MS. We analyzed attrition in included studies, using a random-effects model and meta-regression to measure the association between potential moderators.
There were no measured differences in attrition between the intervention and control arms; however, some of the heterogeneity observed was explained by the composite technological element score. The pooled attrition rates for the intervention and control arms were 14.7% and 15.6%, respectively.
This paper provides insight into the technological composition of digital health interventions designed for people with MS and describes the degree of attrition in both study arms. This paper will aid in the design of future studies in this area, particularly for digital health interventions of this type.
数字健康干预措施通过支持多发性硬化症（MS）患者更好地自我管理疾病，彻底改变了 MS 的治疗方式。现在人们已经认识到，构成这一类数字健康干预措施的技术要素可以影响参与者参与自我管理计划的程度，而 MS 患者在学习期间可能会受到这些要素的影响，从而面临着保持参与的重大障碍。因此，探索技术要素对减少流失率的影响至关重要。
本研究旨在检查针对 MS 患者的数字健康干预措施的研究设计和技术要素——旨在支持在规定时间段内参与计划的数字健康干预措施——并探讨这些要素与随机对照试验（RCT）参与者的流失率之间的相关性。
我们对描述针对 MS 患者的数字健康自我管理干预措施的 RCT（n=32）进行了系统评价和荟萃分析。我们使用随机效应模型和荟萃回归分析来衡量潜在调节因素之间的关联，对纳入研究的流失率进行了分析。
干预组和对照组之间的流失率没有差异；然而，观察到的部分异质性可以用综合技术要素评分来解释。干预组和对照组的综合流失率分别为 14.7%和 15.6%。
本文深入了解了专为 MS 患者设计的数字健康干预措施的技术组成，并描述了两个研究组的流失程度。这将有助于该领域未来研究的设计，特别是对于这种类型的数字健康干预措施。
