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Engagement and nonusage attrition with a free physical activity promotion program : the case of 10,000 Steps Australia
journal contributionposted on 06.12.2017, 00:00 by D Guertler, Corneel VandelanotteCorneel Vandelanotte, Morwenna KirwanMorwenna Kirwan, Mitchell DuncanMitchell Duncan
Background: Data from controlled trials indicate that Web-based interventions generally suffer from low engagement and high attrition. This is important because the level of exposure to intervention content is linked to intervention effectiveness. However, data from real-life Web-based behavior change interventions are scarce, especially when looking at physical activity promotion. Objective: The aims of this study were to (1) examine the engagement with the freely available physical activity promotion program 10,000 Steps, (2) examine how the use of a smartphone app may be helpful in increasing engagement with the intervention and in decreasing nonusage attrition, and (3) identify sociodemographic- and engagement-related determinants of nonusage attrition. Methods: Users (N=16,948) were grouped based on which platform (website, app) they logged their physical activity: Web only, app only, or Web and app. Groups were compared on sociodemographics and engagement parameters (duration of usage, number of individual and workplace challenges started, and number of physical activity log days) using ANOVA and chi-square tests. For a subsample of users that had been members for at least 3 months (n=11,651), Kaplan-Meier survival curves were estimated to plot attrition over the first 3 months after registration. A Cox regression model was used to determine predictors of nonusage attrition. Results: In the overall sample, user groups differed significantly in all sociodemographics and engagement parameters. Engagement with the program was highest for Web-and-app users. In the subsample, 50.00% (5826/11,651) of users stopped logging physical activity through the program after 30 days. Cox regression showed that user group predicted nonusage attrition: Web-and-app users (hazard ratio=0.86, 95% CI 0.81-0.93, P<.001) and app-only users (hazard ratio=0.63, 95% CI 0.58-0.68, P<.001) showed a reduced attrition risk compared to Web-only users. Further, having a higher number of individual challenges (hazard ratio=0.62, 95% CI 0.59-0.66, P<.001), workplace challenges (hazard ratio=0.94, 95% CI 0.90-0.97, P<.001), physical activity logging days (hazard ratio=0.921, 95% CI 0.919-0.922, P<.001), and steps logged per day (hazard ratio=0.99999, 95% CI 0.99998-0.99999, P<.001) were associated with reduced nonusage attrition risk as well as older age (hazard ratio=0.992, 95% CI 0.991-0.994, P<.001), being male (hazard ratio=0.85, 95% CI 0.82-0.89, P<.001), and being non-Australian (hazard ratio=0.87, 95% CI 0.82-0.91, P<.001). Conclusions: Compared to other freely accessible Web-based health behavior interventions, the 10,000 Steps program showed high engagement. The use of an app alone or in addition to the website can enhance program engagement and reduce risk of attrition. Better understanding of participant reasons for reducing engagement can assist in clarifying how to best address this issue to maximize behavior change.