ArticleDigital health
Latent profile analysis of implementation outcomes and willingness to use a digital health appointment system among university students in Ghana.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: 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.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.