Segmenting Women’s Motivational Profiles in mHealth Adoption for Reproductive Health: A Cluster Analysis
- 1Communications Science Department, Faculty of Social Science, Universitas Bakrie, South Jakarta 12940, Indonesia
Abstract
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.
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BibTeX
@article{firliani2026segmenting,
title = {{Segmenting Women’s Motivational Profiles in mHealth Adoption for Reproductive Health: A Cluster Analysis}},
author = {Alifia Firliani and Ari Kurnia},
journal = {KEMAS: Jurnal Kesehatan Masyarakat},
year = {2026},
month = jul,
doi = {10.15294/kemas.v21i4.36982},
url = {https://doi.org/10.15294/kemas.v21i4.36982},
note = {CC BY},
}
RIS
TY - JOUR
TI - Segmenting Women’s Motivational Profiles in mHealth Adoption for Reproductive Health: A Cluster Analysis
AU - Alifia Firliani
AU - Ari Kurnia
PY - 2026
DA - 2026/07/01
JO - KEMAS: Jurnal Kesehatan Masyarakat
DO - 10.15294/kemas.v21i4.36982
UR - https://doi.org/10.15294/kemas.v21i4.36982
AB - 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.
SN - 1858-1196
SN - 2355-3596
ER -