Association Between Behavioral Phenotypes and Paid Subscription and Renewal Among New mHealth App Users: Six-Month Prospective Cohort Study
Abstract
Background: Mobile health (mHealth) app effectiveness may be limited by low engagement. Increasing understanding of factors influencing engagement may help. Paid mHealth app subscription and renewal are two engagement metrics of particular interest to commercial app developers.
Objective: This study aims to identify homogeneous user subgroups (ie, behavioral phenotypes) within a paid mHealth app context and examine associations with app subscription and renewal.
Methods: A 6-month prospective cohort study was conducted with new users of the WayBetter (WayBetter Inc.) app, a subscription-based mHealth app. Through convenience sampling, users initiating a 7-day free trial between November 2023 and January 2024 were recruited. Latent class analysis (LCA) using the 3-step Bolck-Croon-Hagenaars (BCH) approach derived distinct classes, or phenotypes, from 33 indicator variables spanning three areas: (1) purpose-built survey responses (eg, sociodemographics), (2) device-assessed health data (eg, daily step count), and (3) 7-day free trial period engagement data (eg, app opens). Candidate LCA models ranging from 1 to 7 classes were generated. Model fit was assessed using several fit indices (eg, Vuong-Lo-Mendell Rubin likelihood ratio test [VLMR test]) alongside theoretical interpretability. Phenotypes were named based on distinct indicator probability profiles. Logistic regression was then used to estimate odds ratios (ORs) comparing the likelihood of subscription and renewal among…
How strong is the evidence?
Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence.
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