Exploring the Integration of Consumer Activity Trackers Into a Community Weight Management Intervention to Support Physical Activity in Adults at Risk for or With Type 2 Diabetes: Mixed Methods Study Using the RE-AIM Framework.

Background: Type 2 diabetes affects 483 million adults worldwide, with rising prevalence and an estimated 6 million premature deaths annually. Low physical activity is a key risk factor, while increased activity can reduce disease onset and improve metabolic health. Consumer activity trackers, when paired with behavior change strategies, have shown potential to increase physical activity among adults with type 2 diabetes. Objective: This study explored the integration of consumer activity trackers into a community-based weight management intervention to support physical activity in adults at risk for or living with type 2 diabetes. Methods: A mixed methods design was used to generate a comprehensive understanding of implementation. Participants were recruited during registration for "Weigh to Go," a community-based weight management program in Lanarkshire, Scotland. Health care professionals delivering the intervention were recruited by email. Participants received a Fitbit Charge 5 to monitor daily steps and moderate-to-vigorous-intensity physical activity. Semistructured interviews were conducted with 10 participants and 10 health care professionals. Qualitative data were analyzed thematically, and quantitative analysis examined changes in recorded Fitbit activity data. Findings were interpreted using the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework. Results: Daily steps increased significantly between week 1 and week 7 (mean difference 5345 steps; P=.002). Qualitative findings highlighted 5 themes. First, providing devices free of charge enhanced reach by removing financial barriers. Second, educational classes were considered essential for effectiveness, particularly instruction on device use and interpretation of activity data. Third, staff expressed a need for greater understanding of device functionality and data outputs, supporting broader adoption of trackers within weight management services. Fourth, managers would benefit from a detailed protocol outlining tracker introduction, use, data analysis procedures, evaluation metrics, and costs to ensure efficient and consistent implementation. Fifth, extending compulsory attendance at intervention sessions was considered important for long-term maintenance of behavior change. The observed decline in moderate-to-vigorous-intensity physical activity after week 7 was attributed to challenges in sustaining engagement beyond the structured phase of the program. Conclusions: This study demonstrates the feasibility of integrating consumer activity trackers into a community-based weight management intervention. Applying the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework revealed that free device provision, participant and staff education, clearly defined implementation protocols, and structured attendance expectations can strengthen tracker-supported interventions. The use of the Fitbit device as both a measurement and intervention tool also raises methodological considerations, emphasizing the need for future research to differentiate these dual roles. Overall, activity trackers show promise for supporting physical activity among adults at risk for or with type 2 diabetes when embedded within well-designed community programs. These findings underscore the importance of aligning technological tools with supportive behavioral strategies to maximize health outcomes. The results also highlight opportunities for refining community programs through closer integration of digital health tools.