Exploring the integration of consumer activity trackers into a community weight management intervention to support physical activity in adults at risk or with type 2 diabetes: A mixed methods study using the RE-AIM framework. (Preprint)

BACKGROUND Globally 483 million adults are living with type 2 diabetes and, this number is increasing. It is estimated that annually 6 million people die prematurely from the disease. A major risk factor of developing type 2 diabetes are low levels of physical activity. Physical activity interventions can reduce the risk of developing type 2 diabetes and for those diagnosed with the disease improve metabolic health. Consumer activity trackers when combined with a behavioral change intervention have been shown to increase levels of physical activity in adults diagnosed with type 2 diabetes. OBJECTIVE To explore the integration of consumer activity trackers into a community weight management intervention to support physical activity in adults at risk or with type 2 diabetes. METHODS A mixed methods (quantitative and qualitative) approach used to allow for a more comprehensive analysis. Participants were recruited at registration for a community-based weight management intervention in Lanarkshire, Scotland, UK, called Weigh to Go. Health care professionals involved in the delivery of this intervention were recruited via email. Weigh to Go participants were provided with a Fitbit Charge 5 consumer activity tracker to record their physical activity data. The recorded activity data included daily steps and moderate and vigorous intensity physical activity. One to one semi-structured interviews were conducted with 10 Weigh to Go participants and 10 health care professionals. Qualitative thematic analysis was undertaken, and themes were identified. Quantitative statistical analysis was conducted on the participants recorded Fitbit data. The RE-AIM framework was used to interpret the data collected. RESULTS Overall, participants’ daily steps increased significantly (p = .002) between week 1 and week 7 (mean difference = 5345 steps, F(3, 45) = 5.93, p = .002, n2 = .19). The qualitative findings revealed that: (i) Providing devices for free was considered important especially for increasing the reach of such interventions; (ii) Educational classes could be beneficial for increasing the effectiveness of such interventions – and should focus on how to use the tracker and how to interpret the data it produces; (iii) Staff would also benefit from understanding more how the devices work, are used and what the data means – this could lead to the wider adoption of the trackers within weight management interventions; (iv) Management involved in the delivery of such interventions would benefit from developing a protocol which sets out in detail the introduction of activity trackers, their use, data analysis, measures of effectiveness and programme costs – this would ensure an effective and efficient implementation of activity trackers into weight management interventions; (v) Extending the compulsory attendance of participants to all weight management intervention classes was suggested – this could improve the long-term maintenance of such programmes. CONCLUSIONS Through this study we showed that it is possible to integrate consumer activity trackers into a community weight management intervention. By using the RE-AIM framework we have revealed that factors such as activity tracker provision and use, education, protocol development and compulsory attendance are likely to increase the success of the use of activity trackers in weight management interventions. CLINICALTRIAL N/A