针对腰痛患者的数字治疗护理与决策支持干预措施:系统评价

Digital Therapeutic Care and Decision Support Interventions for People With Low Back Pain: Systematic Review.

作者信息

Lewkowicz Daniel, Slosarek Tamara, Wernicke Sarah, Winne Antonia, Wohlbrandt Attila M, Bottinger Erwin

机构信息

Digital Health Center, Hasso Plattner Institute, University of Potsdam, Potsdam, Germany.

Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York City, NY, United States.

出版信息

JMIR Rehabil Assist Technol. 2021 Nov 19;8(4):e26612. doi: 10.2196/26612.

Abstract

BACKGROUND

Low back pain (LBP) is the leading cause of worldwide years lost because of disability, with a tremendous economic burden for health care systems. Digital therapeutic care (DTC) programs provide a scalable, universally accessible, and low-cost approach to the multidisciplinary treatment of LBP. Moreover, novel decision support interventions such as personalized feedback messages, push notifications, and data-driven activity recommendations amplify DTC by guiding the user through the program while aiming to increase overall engagement and sustainable behavior change.

OBJECTIVE

This systematic review aims to synthesize recent scientific literature on the impact of DTC apps for people with LBP and outline the implementation of add-on decision support interventions, including their effect on user retention and attrition rates.

METHODS

We searched bibliographic databases, including MEDLINE, Cochrane Library, Web of Science, and the Physiotherapy Evidence Database, from March 1, 2016, to October 15, 2020, in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and conducted this review based on related previously published systematic reviews. Besides randomized controlled trials (RCTs), we also included study designs with the evidence level of at least a retrospective comparative study. This enables the consideration of real-world user-generated data and provides information regarding the adoption and effectiveness of DTC apps in a real-life setting. For the appraisal of the risk of bias, we used the Risk of Bias 2 Tool and the Risk of Bias in Non-Randomized Studies of Interventions Tool for the RCTs and nonrandomized trials, respectively. The included studies were narratively synthesized regarding primary and secondary outcome measures, DTC components, applied decision support interventions, user retention, and attrition rates.

RESULTS

We retrieved 1388 citations, of which 12 studies are included in this review. Of the 12 studies, 6 (50%) were RCTs and 6 (50%) were nonrandomized trials. In all included studies, lower pain levels and increased functionality compared with baseline values were observed in the DTC intervention group. A between-group comparison revealed significant improvements in pain and functionality levels in 67% (4/6) of the RCTs. The study population was mostly homogeneous, with predominantly female, young to middle-aged participants of normal to moderate weight. The methodological quality assessment revealed moderate to high risks of biases, especially in the nonrandomized trials.

CONCLUSIONS

This systematic review demonstrates the benefits of DTC for people with LBP. There is also evidence that decision support interventions benefit overall engagement with the app and increase participants' ability to self-manage their recovery process. Finally, including retrospective evaluation studies of real-world user-generated data in future systematic reviews of digital health intervention trials can reveal new insights into the benefits, challenges, and real-life adoption of DTC programs.

摘要

背景

腰痛(LBP)是全球因残疾导致寿命损失年数的首要原因,给医疗保健系统带来了巨大的经济负担。数字治疗护理(DTC)计划为腰痛的多学科治疗提供了一种可扩展、普遍可及且低成本的方法。此外,诸如个性化反馈消息、推送通知和数据驱动的活动建议等新型决策支持干预措施,通过在程序中引导用户,同时旨在提高整体参与度和实现可持续行为改变,从而增强了DTC的效果。

目的

本系统评价旨在综合近期关于DTC应用程序对腰痛患者影响的科学文献,并概述附加决策支持干预措施的实施情况,包括其对用户留存率和流失率的影响。

方法

我们按照PRISMA(系统评价和Meta分析的首选报告项目)指南,检索了2016年3月1日至2020年10月15日期间的文献数据库,包括MEDLINE、Cochrane图书馆、科学网和物理治疗证据数据库,并基于之前发表的相关系统评价进行了本评价。除随机对照试验(RCT)外,我们还纳入了证据水平至少为回顾性比较研究的研究设计。这使得能够考虑真实世界中用户生成的数据,并提供有关DTC应用程序在现实生活环境中的采用情况和有效性的信息。对于偏倚风险评估,我们分别对RCT和非随机试验使用了偏倚风险2工具和干预非随机研究中的偏倚风险工具。对纳入研究的主要和次要结局指标、DTC组件、应用的决策支持干预措施、用户留存率和流失率进行了叙述性综合分析。

结果

我们检索到1388条引文,其中12项研究纳入了本评价。在这12项研究中,6项(50%)为RCT,6项(50%)为非随机试验。在所有纳入研究中,DTC干预组与基线值相比,疼痛水平降低,功能增强。组间比较显示,67%(4/6)的RCT在疼痛和功能水平方面有显著改善。研究人群大多同质,主要是体重正常至中等的年轻至中年女性参与者。方法学质量评估显示存在中度至高偏倚风险,尤其是在非随机试验中。

结论

本系统评价证明了DTC对腰痛患者的益处。也有证据表明,决策支持干预措施有利于提高对应用程序的整体参与度,并增强参与者自我管理康复过程的能力。最后,在未来数字健康干预试验的系统评价中纳入对真实世界用户生成数据的回顾性评估研究,可以揭示有关DTC计划的益处、挑战和现实生活采用情况的新见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7d6/8663573/437f7620c1e0/rehab_v8i4e26612_fig1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索