Western journal of nursing research · 2025
Impact of Mobile App-Based Self-Monitoring Engagement on Self-Care Self-Efficacy, Health Behaviors, and Hemoglobin A1c Among Patients With Type 2 Diabetes Mellitus: A Secondary Analysis of a Randomized Controlled Trial.
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Park Gaeun, Lee Haejung, Lee Min Jin, Khang Ahreum
Аннотация
BACKGROUND: Higher engagement in mobile app-based self-monitoring is associated with better outcomes among patients with type 2 diabetes mellitus (T2DM). Previous studies were limited by short follow-up periods or focusing solely on hemoglobin A1c (HbA1c).
OBJECTIVE: We aimed to identify mobile app-based self-monitoring engagement patterns among patients with T2DM and explore their long-term impact on self-care self-efficacy, health behaviors, and HbA1c.
METHODS: Latent class growth analysis was used to examine data from 103 participants in the intervention group of a randomized controlled trial of a self-care program over 18 months. The program included goal setting, education, self-monitoring, and feedback through automated algorithms, primarily delivered through a mobile app platform. Differences in general characteristics, self-care self-efficacy, health behaviors, and HbA1c at baseline and 18-month follow-up were analyzed based on latent classes. Longitudinal changes were explored using generalized estimating equations.
RESULTS: Three latent classes were identified: high (21.36%), medium (20.39%), and low-engagement groups (58.25%) within the intervention group. Significant differences in age, self-care self-efficacy, regular exercise, and grain and vegetable intake were observed between the groups. Longitudinal analysis showed significant differences in self-care self-efficacy, health behaviors, and HbA1c over the 18-month follow-up.
CONCLUSIONS: This study informs tailored strategies to enhance mobile app-based self-monitoring engagement, which may improve outcomes for patients with T2DM.
OBJECTIVE: We aimed to identify mobile app-based self-monitoring engagement patterns among patients with T2DM and explore their long-term impact on self-care self-efficacy, health behaviors, and HbA1c.
METHODS: Latent class growth analysis was used to examine data from 103 participants in the intervention group of a randomized controlled trial of a self-care program over 18 months. The program included goal setting, education, self-monitoring, and feedback through automated algorithms, primarily delivered through a mobile app platform. Differences in general characteristics, self-care self-efficacy, health behaviors, and HbA1c at baseline and 18-month follow-up were analyzed based on latent classes. Longitudinal changes were explored using generalized estimating equations.
RESULTS: Three latent classes were identified: high (21.36%), medium (20.39%), and low-engagement groups (58.25%) within the intervention group. Significant differences in age, self-care self-efficacy, regular exercise, and grain and vegetable intake were observed between the groups. Longitudinal analysis showed significant differences in self-care self-efficacy, health behaviors, and HbA1c over the 18-month follow-up.
CONCLUSIONS: This study informs tailored strategies to enhance mobile app-based self-monitoring engagement, which may improve outcomes for patients with T2DM.