Department of Biomedical Informatics, The Ohio State University, Columbus, OH, United States.
Division of Cardiovascular Medicine, The Ohio State University College of Medicine, Columbus, OH, United States.
JMIR Mhealth Uhealth. 2022 Mar 2;10(3):e29415. doi: 10.2196/29415.
Engagement is essential for the effectiveness of digital behavior change interventions. Existing systematic reviews examining hypertension self-management interventions via mobile apps have primarily focused on intervention efficacy and app usability. Engagement in the prevention or management of hypertension is largely unknown.
This systematic review explores the definition and role of engagement in hypertension-focused mobile health (mHealth) interventions, as well as how determinants of engagement (ie, tailoring and interactivity) have been implemented.
A systematic review of mobile app interventions for hypertension self-management targeting adults, published from 2013 to 2020, was conducted. A total of 21 studies were included in this systematic review.
The engagement was defined or operationalized as a microlevel concept, operationalized as interaction with the interventions (ie, frequency of engagement, time or duration of engagement with the program, and intensity of engagement). For all 3 studies that tested the relationship, increased engagement was associated with better biomedical outcomes (eg, blood pressure change). Interactivity was limited in digital behavior change interventions, as only 7 studies provided 2-way communication between users and a health care professional, and 9 studies provided 1-way communication in possible critical conditions; that is, when abnormal blood pressure values were recorded, users or health care professionals were notified. The tailoring of interventions varied at different aspects, from the tailoring of intervention content (including goals, patient education, advice and feedback from health professionals, reminders, and motivational messages) to the tailoring of intervention dose and communication mode. Tailoring was carried out in a number of ways, considering patient characteristics such as goals, preferences, disease characteristics (eg, hypertension stage and medication list), disease self-management experience levels, medication adherence rate, and values and beliefs.
Available studies support the importance of engagement in intervention effectiveness as well as the essential roles of patient factors in tailoring, interactivity, and engagement. A patient-centered engagement framework for hypertension self-management using mHealth technology is proposed here, with the intent of facilitating intervention design and disease self-management using mHealth technology.
参与对于数字行为改变干预措施的有效性至关重要。现有的系统评价检查通过移动应用程序进行的高血压自我管理干预措施主要集中在干预效果和应用程序可用性上。对高血压的预防或管理的参与情况在很大程度上尚不清楚。
本系统评价探讨了以高血压为重点的移动健康（mHealth）干预措施中参与的定义和作用，以及参与的决定因素（即定制和交互性）的实施情况。
对 2013 年至 2020 年期间针对成年人的高血压自我管理的移动应用程序干预措施进行了系统评价。本系统评价共纳入 21 项研究。
参与被定义或操作化为微观层面的概念，操作化为与干预措施的相互作用（即参与的频率、参与程序的时间或持续时间以及参与的强度）。对于所有 3 项测试相关性的研究，增加参与度与更好的生物医学结果（例如，血压变化）相关。数字行为改变干预措施中的交互性有限，因为只有 7 项研究在用户和医疗保健专业人员之间提供了双向通信，并且 9 项研究在可能的危急情况下提供了单向通信；也就是说，当记录到异常血压值时，通知用户或医疗保健专业人员。干预措施的定制在不同方面有所不同，从干预内容的定制（包括目标、患者教育、来自健康专业人员的建议和反馈、提醒和激励信息）到干预剂量和通信模式的定制。考虑到患者特征，例如目标、偏好、疾病特征（例如，高血压阶段和药物清单）、疾病自我管理经验水平、药物依从率以及价值观和信念，以多种方式进行了定制。
现有研究支持参与干预效果的重要性，以及患者因素在定制、交互性和参与方面的重要作用。本文提出了一种基于 mHealth 技术的高血压自我管理的以患者为中心的参与框架，旨在促进使用 mHealth 技术进行干预设计和疾病自我管理。
