
Thesis Format
Alternative Format
Degree
Master of Science
Program
Kinesiology
Supervisor
Marc, Mitchell
Abstract
BACKGROUND: Low mobile health (mHealth) app engagement leading to little or no effect is typical. In partnership with WayBetter Inc., makers of the deposit contract-based WayBetter (WB) mHealth app, we aim to begin to address the low app engagement issue. PURPOSE: To identify homogenous subgroups (“behavioural phenotypes”) of new WB app users. METHODS: A cross-sectional study was conducted between November 2, 2023 and January 3, 2024. New WB app users creating an account during the study period and engaging in a seven-day free trial were recruited via email to complete a short 27-item study survey. Previously validated survey items purported to predict mHealth app engagement were included. Latent class analyses were conducted using survey responses to identify behavioural phenotypes. RESULTS: The total sample included 1084 users (age [mean, SD]=42.00, 9.65) years; % women=90.59). Four behavioural phenotypes were identified based on key model fit statistics (e.g., AIC=39681.76), the results of likelihood ratio tests (Vuong-Lo-Mendell-Rubin LRT p
Summary for Lay Audience
Health promoting interventions delivered though mobile apps have increased in popularity and may help promote healthy lifestyle behaviours (i.e., physical activity, healthy eating, and mindfulness) among the general population. Although, in order to be effective, users must remain engaged with the intervention to achieve their desired health goals and adopt long- term behaviour change. Partnered with WayBetter Inc., creators of the WayBetter (WB) app, makers of the innovative deposit contract based lifestyle modification app (e.g., physical activity and eating behaviours), this study aimed to identify types of WB app users who might be at risk of low engagement to better understand and improve user engagement. New WB users were invited to complete a survey that collected information on their sociodemographic, psychological, and past health behaviours. This data was used to identify groups of individuals with similar characteristics who are likely to engage in similar ways with health behaviour change interventions. Analyzing 1084 user responses, four subgroups were identified. The next phase of this study will build on these identified groups by examining how different subgroups interact with the app using various key engagement metrics. The findings of this study may inform the design of interventions targeting groups of users that are less likely to engage with deposit contract-based mHealth apps, such as WB.
Recommended Citation
Hasan, Roshan, "Identifying behavioural phenotypes among 1,084 healthy living app users." (2024). Electronic Thesis and Dissertation Repository. 10622.
https://ir.lib.uwo.ca/etd/10622