Exploring User Behavior, Profiles, and Generation of Missed Reading Alerts in Long-Term Users of a Technology-Enabled Intervention for Self-Monitoring of Blood Pressure in Public Primary Care Setting in Singapore: Longitudinal Observational Study.

Background: Technology-enabled interventions for chronic disease management, such as telehealth systems for hypertension self-monitoring, have demonstrated effectiveness but face challenges with sustained usage and high attrition rates. Understanding the factors associated with continued engagement is crucial for enhancing intervention design and sustainability. Objective: This study aimed to explore the user behavior and user profiles under the Primary Technology Enhanced Care for Hypertension Program (PTEC-HT) intervention by: (1) quantitatively describing characteristics of participants generating Missed Reading (MR) alerts, (2) identifying factors associated with MR alert generation, (3) profiling participant subgroups based on MR alert patterns and blood pressure (BP) control, and (4) examining temporal trajectories of MR alerts and associated conversion rates over 12 months. Methods: A longitudinal observational study was conducted using backend data from the PTEC-HT system. The study included 491 participants, recruited before June 30, 2022, enrolled in the program for 1 year or more, categorized into MR alert generator and nongenerator groups, recruited before June 2022. Logistic regression identified factors associated with MR alert generation in an index month (August 2023), while latent class analysis profiled participant subgroups. Generalized estimating equations examined temporal trajectories of MR alerts and conversion rates. Statistical significance was set at 5%. Results: Being younger (odds ratio [OR] 0.97, 95% CI 0.95-0.99; P=.007) and having a longer program duration (OR 1.11, 95% CI 1.01-1.22; P=.03) were significantly associated with MR alert generation. Latent class analysis identified 3 latent classes: (1) Compliant Triers (low MR alerts, poor BP control; 56/491, 11.4%), (2) Compliant Achievers (low MR alerts, good BP control; 368/491, 74.9%), and (3) Non-Compliant Achievers (high MR alerts, good BP control; 67/491, 13.6%). Temporal analysis showed consistent trajectories for Missed Reading Reminder message counts and conversion rates, with MR alert generators having higher Missed Reading Reminder message counts but lower conversion rates compared to nongenerators. Conclusions: Our study reported that younger participants and longer program durations were linked to higher MR alert generation. The identification of distinct user profiles suggests that tailored intervention features could enhance engagement and BP control. The study underscores the importance of monitoring compliance patterns and optimizing message content to improve conversion rates. These insights contribute to the understanding of telehealth engagement dynamics and support targeted interventions for hypertension management.