Latent profile analysis of implementation outcomes and willingness to use a digital health appointment system among university students in Ghana
Douglas Aninng Opoku, Eric Kojo Nsa Oduro, Julius Kwabena Karikari, Emmanuel Konadu, Mercy Addae, Nana Akua Abruquah, Elizabeth Oppong-Kyekyeku, Francis Akabo, Godknows Mensah Kunkpe, Phanuel Seli Kwadzo Asense, Phyllis Tawiah, Nana Kwame Ayisi-BoatengObjectives
The adoption of digital health technologies has accelerated over the past decade, reflecting increasing institutional commitment to technology-enabled healthcare delivery. Its adoption may be influenced by a range of factors, including user attitudes and infrastructure. This study examined latent profiles of implementation outcomes for Students’ Online Health Appointment System (SOHAS) at a public university in Ghana, identified predictors of profile membership, and explored pathways linking attitudes to willingness to use the system.
Methods
A cross-sectional study was conducted among students at the Kwame Nkrumah University of Science and Technology in Kumasi, Ghana. Data were collected using a pretested, structured online questionnaire. Latent profile analysis was used to identify implementation outcome profiles using implementation outcome measures (acceptability, appropriateness, and feasibility). Structural equation modelling was fitted to assess the relationship between implementation outcome profiles and willingness to use SOHAS.
Results
Four distinct implementation outcome profiles were identified: Enthusiastic Adopters (40.8%), Conditional Supporters (17.2%), Ambivalent Users (30.6%), and Skeptical or Resistant (11.4%). Students who reported poor internet connectivity as a barrier had approximately a 44.0% lower likelihood of belonging to the Ambivalent Users profile (RRR = 0.56, 95% CI: 0.32–0.98). Male students reported a greater willingness to use the SOHAS (Estimate = 0.15, β = 0.18, 95% CI: 0.08–0.23) than females. Poor internet connectivity was positively associated with willingness to use SOHAS (Estimate = 0.12, β = 0.14, 95% CI: 0.03–0.21).
Conclusion
The adoption of digital health solutions, such as SOHAS, is multifaceted and is driven by both infrastructural and attitudinal factors. Although students may express willingness to use digital systems, targeted engagement strategies and supportive infrastructure are essential to maximise adoption. This study highlights the need to prioritise integrated, user-centred, and infrastructure-sensitive approaches to digital health implementation to enhance adoption.