ArticleFrontiers in digital health2025
A modified UTAUT model for acceptance to use telemedicine services and its predictors among healthcare professionals at public hospitals in North Shewa Zone of Oromia Regional State, Ethiopia.
Article in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Effects of Performance and Effort Expectancy on AI-Generated Information Adoption Among Chinese Nursing Professionals: Survey-Based SEM Analysis.Journal of advanced nursing · 2026Article
- Telemedicine readiness and its associated factors among healthcare professionals in primary hospitals of Southern Ethiopia.Scientific reports · 2026Article
- AI in Fracture Detection: A Cross-Disciplinary Analysis of Physician Acceptance Using the UTAUT Model.Diagnostics (Basel, Switzerland) · 2025Article
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6 authors.
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Abstract
Introduction: The shortage of healthcare professionals, long waiting time for treatment, inadequate transportation, and hard-to-reach geographical locations remained challenging in the healthcare service delivery in resource-limited settings. To overcome these challenges, healthcare providers are looking to use telemedicine technologies as an alternative solution. However, user resistance has consistently been identified as a major obstacle to the successful implementation of telemedicine. Thus, this study aimed to assess acceptance to use telemedicine services and its predictors among healthcare professionals at public hospitals in the North Shewa Zone of Oromia Regional State, Ethiopia. Method: A cross-sectional study design was employed among a total of 627 healthcare professionals working at public hospitals in the North Shewa Zone from 3 April to 1 May 2023. The study participants were selected using simple random sampling techniques. A questionnaire, which is adapted from the original instrument developed by Venkatesh et al.'s study and several studies regarding the UTAUT model was used. Data were collected using a self-administered structured questionnaire in English version. The descriptive statistics were estimated using the SPSS version 25, and structural equation modeling analysis was employed using AMOS V.21 software. Results: In this study, 601 (95.85% response rate) study subjects participated. The study has shown that 315 (52.4%) (95% CI: 48.3-56.5) of the participants accepted to use telemedicine in their routine healthcare services. Performance expectancy ( Conclusion: The healthcare professionals' acceptance to use the offered telemedicine services was promising for the future. Additionally, our research found significant effects between healthcare professionals' acceptance to use telemedicine services with the predictors except social influence. Facilitating conditions and digital literacy with acceptance to use were moderated by age. Thus, the health facility should strengthen its telemedicine technology by raising awareness of its usefulness and ease of use.
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