Design Principles in mHealth Interventions for Sustainable Health Behavior Changes: Protocol for a Systematic Review

Abstract

Background In recent years, mHealth has increasingly been used to deliver behavioral interventions for disease prevention and self-management. Computing power in mHealth tools can provide unique functions beyond conventional interventions in provisioning personalized behavior change recommendations and delivering them in real time, supported by dialogue systems. However, design principles to incorporate these features in mHealth interventions have not been systematically evaluated. Objective The goal of this review is to identify best practices for the design of mHealth interventions targeting diet, physical activity, and sedentary behavior. We aim to identify and summarize the design characteristics of current mHealth tools with a focus on the following features: (1) personalization, (2) real-time functions, and (3) deliverable resources. Methods We will conduct a systematic search of electronic databases, including MEDLINE, CINAHL, Embase, PsycINFO, and Web of Science for studies published since 2010. First, we will use keywords that combine mHealth, interventions, chronic disease prevention, and self-management. Second, we will use keywords that cover diet, physical activity, and sedentary behavior. Literature found in the first and second steps will be combined. Finally, we will use keywords for personalization and real-time functions to limit the results to interventions that have reported these design features. We expect to perform narrative syntheses for each of the 3 target design features. Study quality will be evaluated using the Risk of Bias 2 assessment tool. Results We have conducted a preliminary search of existing systematic reviews and review protocols on mHealth-supported behavior change interventions. We have identified several reviews that aimed to evaluate the efficacy of mHealth behavior change interventions in a range of populations, evaluate methodologies for assessing mHealth behavior change randomized trials, and assess the diversity of behavior change techniques and theories in mHealth interventions. However, syntheses on the unique features of mHealth intervention design are absent in the literature. Conclusions Our findings will provide a basis for developing best practices for designing mHealth tools for sustainable behavior change. Trial Registration PROSPERO CRD42021261078; https://tinyurl.com/m454r65t International Registered Report Identifier (IRRID) PRR1-10.2196/39093

Accuracy of the Huawei GT2 Smartwatch for measuring Physical Activity and Sleep among Adults during Daily Life: A Validation Study (Preprint)

“…They can also offer real-time feedback through smartwatch screen and connected mobile apps, and thus help individuals become more motivated and better able to self-manage activities. This real-time feedback mechanism can be particularly beneficial in managing chronic conditions, promoting physical fitness, and enhancing overall well-being [55]. This represents great potentials for applying conducting population-based health behavior promotion [56].…”