App Engagement as a Predictor of Weight Loss in Blended-Care Interventions: Retrospective Observational Study Using Large-Scale Real-World Data (Preprint)
Authors: Lehmann Marco , Jones Lucy , Schirmann Felix 
Published: June 2024

BACKGROUND

Early weight loss is an established predictor for treatment outcomes in weight management interventions for people with obesity. However, there is a paucity of additional, reliable, and clinically actionable early predictors in weight management interventions. Novel blended-care weight management interventions combine coach and app support and afford new means of structured, continuous data collection, informing research on treatment adherence and outcome prediction.

OBJECTIVE

Against this backdrop, this study analyzes app engagement as a predictor for weight loss in large-scale, real-world, blended-care interventions. We hypothesize that patients who engage more frequently in app usage in blended-care treatment (eg, higher logging activity) lose more weight than patients who engage comparably less frequently at 3 and 6 months of intervention.

METHODS

Real-world data from 19,211 patients in obesity treatment were analyzed retrospectively. Patients were treated with 3 different blended-care weight management interventions, offered in Switzerland, the United Kingdom, and Germany by a digital behavior change provider. The principal component analysis identified an overarching metric for app engagement based on app usage. A median split informed a distinction in higher and lower engagers among the patients. Both groups were matched through optimal propensity score matching for relevant characteristics (eg, gender, age, and start weight). A linear regression model, combining patient characteristics and app-derived data, was applied to identify predictors for weight loss outcomes.

RESULTS

For the entire sample (N=19,211), mean weight loss was –3.24% (SD 4.58%) at 3 months and –5.22% (SD 6.29%) at 6 months. Across countries, higher app engagement yielded more weight loss than lower engagement after 3 but not after 6 months of intervention (<i>P</i><sub>3 months</sub>&lt;.001 and <i>P</i><sub>6 months</sub>=.59). Early app engagement within the first 3 months predicted percentage weight loss in Switzerland and Germany, but not in the United Kingdom (<i>P</i><sub>Switzerland</sub>&lt;.001, <i>P</i><sub>United Kingdom</sub>=.12, and <i>P</i><sub>Germany</sub>=.005). Higher age was associated with stronger weight loss in the 3-month period (<i>P</i><sub>Switzerland</sub>=.001, <i>P</i><sub>United Kingdom</sub>=.002, and <i>P</i><sub>Germany</sub>&lt;.001) and, for Germany, also in the 6-month period (<i>P</i><sub>Switzerland</sub>=.09, <i>P</i><sub>United Kingdom</sub>=.46, and <i>P</i><sub>Germany</sub>=.03). In Switzerland, higher numbers of patients’ messages to coaches were associated with higher weight loss (<i>P</i><sub>3 months</sub>&lt;.001 and <i>P</i><sub>6 months</sub>&lt;.001). Messages from coaches were not significantly associated with weight loss (all <i>P</i>&gt;.05).

CONCLUSIONS

Early app engagement is a predictor of weight loss, with higher engagement yielding more weight loss than lower engagement in this analysis. This new predictor lends itself to automated monitoring and as a digital indicator for needed or adapted clinical action. Further research needs to establish the reliability of early app engagement as a predictor for treatment adherence and outcomes. In general, the obtained results testify to the potential of app-derived data to inform clinical monitoring practices and intervention design.