Institutional trust,peer dynamics,and culture in mHealth adoption for sexual and reproductive health

Dear Editor,

We read with interest the article titled “Determinants of mHealth adoption for sexual and reproductive health (SRH) services among university students in Ghana: a UTAUT and health belief model analysis” by Nimo et al. ¹ The study makes a valuable contribution by integrating the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Health Belief Model (HBM) to explain the persistent gap between high awareness and low utilization of mHealth for SRH. While the findings are insightful, we offer several alternative viewpoints that may further enrich the discussion and guide future research and interventions. First, the study primarily emphasizes individual-level psychosocial determinants, such as performance expectancy, resistance to change, and privacy concerns. While these factors are undeniably important, this focus may underplay the role of institutional and structural influences on mHealth adoption. Prior research shows that trust in health systems and institutional endorsement significantly shape users’ willingness to engage with digital health tools, particularly for sensitive health concerns.^2,3 Even when students perceive mHealth tools as useful, limited integration with university health services or national health authorities may discourage actual use. Incorporating variables such as institutional trust or formal referral pathways could therefore provide a more comprehensive explanation of adoption behaviors. Second, the finding that social influence negatively predicts mHealth usage warrants a more nuanced interpretation. Rather than viewing social influence solely as a deterrent rooted in stigma, it may be useful to distinguish between inhibiting peer surveillance and supportive peer norms. Evidence suggests that while fear of judgment can suppress engagement with SRH-related technologies, positive peer endorsement and trust-based social networks can facilitate adoption among young adults.^4,5 Treating social influence as a multidimensional construct may help identify conditions under which peer dynamics hinder or promote mHealth use. Third, the non-significant role of perceived health threat challenges assumptions derived from the HBM. ⁶ One possible explanation is that university students may normalize SRH risks as part of everyday youth experience, thereby reducing the motivational impact of perceived susceptibility or severity. Studies among young populations indicate that awareness of risk does not necessarily translate into action when risks are perceived as routine or manageable. ⁷ This suggests that mHealth interventions relying heavily on fear-based messaging may be less effective than those emphasizing empowerment, autonomy, and everyday well-being. ⁸ Finally, while cultural norms are acknowledged as contextual barriers, culture may also shape expectations regarding design, language, and interaction styles of mHealth platforms. Research consistently shows that culturally misaligned digital health tools struggle to sustain engagement, even when technically functional. ⁵ Participatory and youth-centered design approaches may therefore enhance cultural relevance, trust, and long-term adoption.

In sum, Nimo et al. provide important evidence on the determinants of mHealth adoption for SRH among Ghanaian university students. Extending this work through greater attention to institutional trust, differentiated peer influence, youth risk normalization, and culturally responsive design may help bridge the gap between awareness and meaningful use of mHealth technologies.