Abstract / Summary
Background: Digital health platforms can expand access to HIV care, but among men who have sex with men (MSM) and transgender people living with HIV and AIDS in Nigeria, adoption is shaped by structural stigma, criminalization, and fear of disclosure as much as by system functionality. Teleconsultation and medication-delivery platforms offer alternative pathways to care, but their acceptance within marginalized populations cannot be assumed and requires empirical investigation.
Objective: This study aimed to examine the factors influencing behavioral intention (BI) to adopt TechAids, a confidentiality-oriented digital health platform designed to support HIV consultation and service access among MSM and transgender individuals in Nigeria, using an extended Unified Theory of Acceptance and Use of Technology (UTAUT) framework.
Methods: A cross-sectional survey was conducted in Lagos, Nigeria, through HIV service delivery and outreach settings facilitated by partnering nongovernmental organizations, supplemented by online LGBTQ+ (lesbian, gay, bisexual, transgender, queer, and other sexual and gender minorities) networks. The study used nonprobability convenience sampling with prespecified eligibility criteria. Data collection was conducted from January 2025 to May 2025. The sample comprised 141 platform users and 27 health care providers (N=168). An extended UTAUT model incorporated performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), trust, and perceived stigma (PS). Data were analyzed using correlation analysis and ordinary least squares (OLS) regression. Age and educational attainment were examined as potential moderating variables. Qualitative feedback was also collected to contextualize quantitative findings.
Results: FC emerged as the strongest predictor of BI to use the platform (β=.813; P<.001), explaining a substantial proportion of variance in adoption intention (R²=0.652). Age demonstrated a modest but statistically significant positive effect on BI (β=.105; P=.03). Contrary to theoretical expectations, PE, EE, SI, trust, and PS did not significantly predict intention to adopt the platform. Qualitative feedback highlighted practical infrastructure-related concerns, including reliable internet access, offline functionality, and availability of technical support, as more salient than psychological or feature-based considerations.
Conclusions: In resource-constrained, highly stigmatized contexts, enabling infrastructure and practical support may outweigh cognitive, social, and attitudinal determinants of technology acceptance. Successful digital health interventions for marginalized populations therefore require privacy-conscious, user-centered design alongside sustained investment in the infrastructure that supports real-world use.