ArticleJournal of medical Internet research2026
Development of an mHealth Intervention for Reducing Sedentary Behavior in Older Adults: Delphi Study.
Article in Journal of medical Internet research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
Background: Sedentary behavior among older adults is a major public health concern, contributing to the increased risk of chronic diseases and functional decline. With aging populations worldwide, prolonged sitting time (averaging up to 13 h/d in older adults) has been independently associated with cardiovascular disease, metabolic disorders, cognitive decline, and all-cause mortality. Mobile health (mHealth) interventions offer a promising approach to address this issue. However, there remains a lack of evidence-based, systematically developed mHealth programs specifically targeting sedentary behavior in older populations. Objective: This study aimed to develop an mHealth intervention program for reducing sedentary behavior in older adults using the Delphi consensus method. Methods: Guided by the Behavior Change Wheel framework, a preliminary mHealth intervention was developed using a combination of qualitative and quantitative methods, including a comprehensive literature review, clinical guidelines analysis, qualitative interviews, and a cross-sectional survey. The intervention was then refined through 2 rounds of Delphi surveys with 16 multidisciplinary experts in geriatric care, behavioral science, and health promotion. Consensus criteria were predefined as mean importance score >3.5 and coefficient of variation ≤0.25 on a 5-point Likert scale. Results: Both Delphi rounds achieved 100% response rates, with high expert authority coefficients (Cr=0.900 for Round 1 and Cr=0.907 for Round 2). The Kendall coordination coefficients (Kendall W) were 0.151 (P<.001) and 0.214 (P=.001) for the 2 rounds, respectively. Following 2 rounds of expert consultation, a total of 27 intervention items were finalized, comprising 3 core components addressing capability (eg, knowledge provision and behavioral skills training), opportunity (eg, social support and environmental restructuring), and motivation (eg, goal-setting, feedback, and incentives) factors influencing sedentary behavior. Conclusions: This study developed a theoretical framework-based, consensus-driven mHealth intervention program for reducing sedentary behavior in older adults. The intervention uniquely integrates the Behavior Change Wheel framework with expert validation, offering a comprehensive approach that simultaneously targets capability, opportunity, and motivation. The findings provide a structured foundation for future feasibility testing and effectiveness evaluation of mHealth interventions in aging populations. Future researchers should translate the developed mHealth intervention into an adaptive mHealth platform, followed by pilot testing and large-scale randomized controlled trials to evaluate its feasibility and effectiveness in real-world settings.
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