Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Apr 9, 2021
Date Accepted: Dec 15, 2021
mHealth Interventions for Self-Management of Hypertension: A Framework and Systematic Review on Engagement, Interactivity, and Tailoring
ABSTRACT
Background:
Engagement is essential for the effectiveness of digital behavior change interventions (DBCIs). 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.
Objective:
This systematic review explores the definition and role of engagement in hypertension-focused mHealth interventions, as well as how determinants of engagement (i.e., tailoring, and interactivity) have been implemented.
Methods:
A systematic review of mobile app interventions for hypertension self-management targeting adults, published from 2013-2020, was conducted. A total of 21 interventions were included in the systematic review.
Results:
Engagement was defined or operationalized as a micro-level concept, operationalized as interaction with the interventions (i.e., frequency of engagement, time or duration of engagement with the program, and intensity of engagement). For all three studies that tested the relationship, increased engagement was associated with better clinical outcomes (e.g., blood pressure change). Interactivity was limited in DBCIs, as only seven interventions provided two-way communication between users and a healthcare professional and nine interventions provided one-way communication in possible critical conditions, i.e., when abnormal blood pressure values were recorded, users or healthcare 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, 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 (e.g., hypertension stage and medication list), disease self-management experience levels, medication adherence rate, as well as values and beliefs.
Conclusions:
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 to facilitate intervention design and disease self-management using mHealth technology. Clinical Trial: Does not apply
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