JMIR Hum Factors. 2026 Apr 29;13:e80734. doi: 10.2196/80734.
ABSTRACT
BACKGROUND: The rising popularity of apps that sync with continuous glucose monitors (CGMs) reflects growing interest in on-demand, personalized care. These platforms combine real-time glucose biofeedback with self-monitored behaviors to optimize metabolic health among individuals with and without diabetes. However, little is known about user characteristics, engagement patterns, or factors associated with sustained use of CGM-integrated digital health apps in real-world settings.
OBJECTIVE: This study aimed to describe user demographics, CGM usage patterns, and food logging behaviors among Vively app users and to identify characteristics of sustained engagement with CGM wear and food tracking.
METHODS: We conducted a retrospective observational study of Vively app users between August 2021 and February 2025. Vively is a commercial digital health app that integrates with Abbott FreeStyle Libre CGMs to deliver personalized nutrition guidance. Users with at least 1 day of CGM wear were included. Primary outcomes were CGM wear duration (total days) and food logging engagement. Factors associated with engagement were identified using negative binomial regression for CGM wear and hurdle negative binomial models for food logging, adjusting for age, sex, BMI, baseline glucose, and device connectivity; the food logging model additionally adjusted for CGM wear category.
RESULTS: The analytical sample included 7647 users (4782/6905, 69.3% female, mean age 44.4, SD 10.9 years, mean BMI 27.8, SD 6.1 kg/m²). Users wore CGMs for a median of 15 (IQR 14-30) days, with 42.7% (3263/7647) completing one full wear period (13-15 days) and 30.3% (2315/7647) completing 2 or more wear periods (≥28 days). Most users (7013/7647, 91.7%) logged food at least once, with a median of 47 (IQR 18-91) food entries over 12 days. Food logging declined progressively during CGM wear (mean 63.2%, SD 8) and dropped sharply after sensor removal (mean 2.4%, SD 1.1). In multivariate models, higher baseline glucose was associated with longer CGM wear (incidence rate ratio [IRR] 1.15, 95% CI 1.13-1.17) but fewer food logging days (IRR 0.96, 95% CI 0.94-0.98). Connected device syncing showed the strongest association for both CGM wear (IRR 1.32, 95% CI 1.28-1.37) and food logging (IRR 1.45, 95% CI 1.39-1.51). Older age and female sex were associated with higher engagement in both behaviors.
CONCLUSIONS: This large-scale analysis reveals distinct engagement patterns with CGM-integrated digital health applications. Food logging was largely concurrent with active CGM wear, dropping dramatically in CGM-free periods. The divergent associations of baseline glucose levels, with longer CGM wear but reduced food logging, may reflect different motivational drivers for passive monitoring versus active behavior tracking. These findings have important implications for designing sustainable digital health interventions that maintain user engagement beyond periods of biological feedback, though replication in more diverse samples and studies accounting for diabetes status and socioeconomic factors is needed.
PMID:42054670 | DOI:10.2196/80734
