Segmenting Women’s Motivational Profiles in mHealth Adoption for Reproductive Health: A Cluster Analysis - Firliani, Alifia; Kurnia, Ari (Jurnal Kesehatan Masyarakat, 2026)
While mHealth has the potential to improve access to reproductive health services, its adoption remains uneven in Indonesia. This study aimed to segment women of reproductive age based on motivational and contextual profiles related to mHealth use, rather than to identify causal determinants. A cross-sectional survey was conducted in 2025 among 350 Indonesian women aged 18–45 years. Guided by the Health Belief Model (HBM) and UTAUT2, k-means cluster analysis was used to identify user segments. Differences in motivational constructs were examined using t-tests, while contextual characteristics were assessed using chi-square tests. Two clusters emerged:  highly motivated users (n = 222) and less motivated users (n = 128). The highly motivated group reported significantly higher self-efficacy (M = 4.71 vs. 3.66), perceived benefits (4.82 vs. 3.86), effort expectancy (4.78 vs. 3.86), and trust in technology (Δ = 0.96; all p < .001). Moderate differences were observed for perceived susceptibility, while perceived barriers were not significant. Significant group differences were also found for income, perceived health literacy, prior use of reproductive health services, and intention to adopt mHealth (p < .05). These findings highlight distinct readiness-based user segments, supporting segmentation-driven digital health interventions.