Background Mobile health (mHealth) is widely used as an innovative approach to delivering physical activity (PA) programs. Users’ adherence to mHealth programs is important to ensure the effectiveness of mHealth-based programs. Objective Our primary aim was to review the literature on the methods used to assess adherence, factors that could affect users’ adherence, and the investigation of the association between adherence and health outcomes. Our secondary aim was to develop a framework to understand the role of adherence in influencing the effectiveness of mHealth PA programs. Methods MEDLINE, PsycINFO, EMBASE, and CINAHL databases were searched to identify studies that evaluated the use of mHealth to promote PA in adults aged ≥18 years. We used critical interpretive synthesis methods to summarize the data collected. Results In total, 54 papers were included in this review. We identified 31 specific adherence measurement methods, which were summarized into 8 indicators; these indicators were mapped to 4 dimensions: length, breadth, depth, and interaction. Users’ characteristics (5 factors), technology-related factors (12 factors), and contextual factors (1 factor) were reported to have impacts on adherence. The included studies reveal that adherence is significantly associated with intervention outcomes, including health behaviors, psychological indicators, and clinical indicators. A framework was developed based on these review findings. Conclusions This study developed an adherence framework linking together the adherence predictors, comprehensive adherence assessment, and clinical effectiveness. This framework could provide evidence for measuring adherence comprehensively and guide further studies on adherence to mHealth-based PA interventions. Future research should validate the utility of this proposed framework.

BACKGROUND Mobile health (mHealth) is widely used as an innovative approach to delivering physical activity (PA) programs. Users’ adherence to mHealth programs is important to ensure the effectiveness of mHealth-based programs. OBJECTIVE Our primary aim was to review the literature on the methods used to assess adherence, factors that could affect users’ adherence, and the investigation of the association between adherence and health outcomes. Our secondary aim was to develop a framework to understand the role of adherence in influencing the effectiveness of mHealth PA programs. METHODS MEDLINE, PsycINFO, EMBASE, and CINAHL databases were searched to identify studies that evaluated the use of mHealth to promote PA in adults aged ≥18 years. We used critical interpretive synthesis methods to summarize the data collected. RESULTS In total, 54 papers were included in this review. We identified 31 specific adherence measurement methods, which were summarized into 8 indicators; these indicators were mapped to 4 dimensions: length, breadth, depth, and interaction. Users’ characteristics (5 factors), technology-related factors (12 factors), and contextual factors (1 factor) were reported to have impacts on adherence. The included studies reveal that adherence is significantly associated with intervention outcomes, including health behaviors, psychological indicators, and clinical indicators. A framework was developed based on these review findings. CONCLUSIONS This study developed an adherence framework linking together the adherence predictors, comprehensive adherence assessment, and clinical effectiveness. This framework could provide evidence for measuring adherence comprehensively and guide further studies on adherence to mHealth-based PA interventions. Future research should validate the utility of this proposed framework.

The European Commission Horizon 2020 project—PreventIT—evaluated two approaches to delivering Lifestyle-Integrated Functional Exercise (LiFE) programs for maintaining older adults’ physical function: the paper-based adapted LiFE and mobile health device delivered enhanced LiFE. A self-reported method was used to measure users’ monthly adherence over 12 months. This analysis aimed to explore young seniors’ adherence patterns between enhanced LiFE and adapted LiFE groups. Results showed that adherence level decreased with time in both groups. The enhanced LiFE group had slightly higher adherence than the adapted LiFE group during most of the 12 months. However, the overall adherence levels were not significantly different during either intervention or follow-up periods. Monthly self-reported adherence measurement can help to understand users’ adherence comprehensively. The comparable adherence levels between both groups indicate mobile health could be an alternative to delivering home-based physical activity for young seniors. However, this feasibility study was not powered to detect differences between groups.