Application of the Unified Theory of Acceptance and Use of Technology (UTAUT) in Predicting Telerehabilitation Acceptance among Rehabilitation Professionals in Nigeria
Telerehabilitation, a subset of digital health, offers a promising approach to overcoming access and resource barriers in rehabilitation service delivery, particularly in low- and middle-income countries such as Nigeria. Despite its potential, the adoption of telerehabilitation by rehabilitation professionals remains limited. This study examined the factors influencing the acceptance of telerehabilitation among rehabilitation professionals in Nigeria using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. A cross-sectional survey was conducted among 100 rehabilitation professionals, including physiotherapists, occupational therapists, and speech-language therapists. Data were collected using an online questionnaire assessing five UTAUT constructs: Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Social Influence (SI), Facilitating Conditions (FC), and Behavioral Intention (BI) to use telerehabilitation. Descriptive statistics, correlation analysis, and multiple regression were performed using SPSS. Perceived usefulness emerged as the only statistically significant predictor of Behavioral Intention (β = 0.37, p = 0.013). While PEOU, SI, and FC showed positive correlations with BI, they did not significantly predict adoption in the regression model. Urban professionals reported significantly higher PU scores than their rural counterparts, and location moderated the relationship between PU and BI. No significant differences were observed across gender, age, or professional groups. The study highlights that perceived clinical utility is the strongest driver of telerehabilitation adoption among Nigerian rehabilitation professionals. Despite infrastructural limitations and limited organizational support, professionals expressed strong behavioral intention to adopt telerehabilitation. These findings underscore the need for policy and institutional efforts to strengthen enabling conditions and infrastructure, especially in rural settings, to support wide-spread and sustainable implementation.
Cite this paper
Salako, I. A. , Jimoh, M. A. and Ogunronbi, S. (2026). Application of the Unified Theory of Acceptance and Use of Technology (UTAUT) in Predicting Telerehabilitation Acceptance among Rehabilitation Professionals in Nigeria. Open Access Library Journal, 13, e14740. doi: http://dx.doi.org/10.4236/oalib.1114740.
Cottrell, M.A., Galea, O.A., O’Leary, S.P., Hill, A.J. and Russell, T.G. (2016) Real-Time Telerehabilitation for the Treatment of Musculoskeletal Conditions Is Effective and Comparable to Standard Practice: A Systematic Review and Meta-Analysis. Clinical Rehabilitation, 31, 625-638. https://doi.org/10.1177/0269215516645148
Kim, J., Kelley, J., Choi, S. and Weir, P. (2024) Impact of Transportation Barriers on Telehealth Use during the COVID-19 Pandemic. INQUIRY: The Journal of Health Care Organization, Provision, and Financing, 61, 1-7. https://doi.org/10.1177/00469580241266345
Oshomoji, O.I., Ajiroba, J.O., Semudara, S.O. and Olayemi, M.A. (2024) Tele-Rehabilitation in African Rural Areas: A Systematic Review. Bulletin of Faculty of Physical Therapy, 29, Article No. 89. https://doi.org/10.1186/s43161-024-00256-w
Arntz, A., Weber, F., Handgraaf, M., Lällä, K., Korniloff, K., Murtonen, K., et al. (2023) Technologies in Home-Based Digital Rehabilitation: Scoping Review. JMIR Rehabilitation and Assistive Technologies, 10, e43615. https://doi.org/10.2196/43615
Olusanjo, A., Okoye, E.C. and Salawu, M.A. (2018) Barriers to Rehabilitation Services for Individuals with Physical Disabilities in Nigeria. African Journal of Disability, 7, 1-7.
Ogundunmade, A. and Chigbo, N.N. (2023) Health System Strengthening and Rehabilitation in Developing and Emerging Economies: A Nigerian Perspective. Tropical Journal of Medical Research, 1, 26.
Willingham, T.B., Stowell, J., Collier, G. and Backus, D. (2024) Leveraging Emerging Technologies to Expand Accessibility and Improve Precision in Rehabilitation and Exercise for People with Disabilities. International Journal of Environmental Research and Public Health, 21, Article 79. https://doi.org/10.3390/ijerph21010079
Allegue, D.R., Sweet, S.N., Higgins, J., Archambault, P.S., Michaud, F., Miller, W.C., et al. (2022) Lessons Learned from Clinicians and Stroke Survivors about Using Telerehabilitation Combined with Exergames: Multiple Case Study. JMIR Rehabilitation and Assistive Technologies, 9, e31305. https://doi.org/10.2196/31305
Black, A.D., Car, J., Pagliari, C., Anandan, C., Cresswell, K., Bokun, T., et al. (2011) The Impact of eHealth on the Quality and Safety of Health Care: A Systematic Overview. PLOS Medicine, 8, e1000387. https://doi.org/10.1371/journal.pmed.1000387
Soopramanien, A., Jamwal, S. and Thomas, P.W. (2020) Digital Health Rehabilitation Can Improve Access to Care in Spinal Cord Injury in the UK: A Proposed Solution. International Journal of Telerehabilitation, 12, 3-16. https://doi.org/10.5195/ijt.2020.6312
Odetunde, M.O., Okonji, A.M., Adeoye, A.P. and Onigbinde, A.T. (2024) Acceptance and Adoption of Tele-Rehabilitation by Physiotherapists from Nigeria, a Low Resource Setting: A Mixed-Method Study. Bulletin of Faculty of Physical Therapy, 29, Article No. 23. https://doi.org/10.1186/s43161-024-00181-y
Morris, J., Thompson, N., Wallace, T., Jones, M. and DeRuyter, F. (2020) Survey of Rehabilitation Clinicians in the United States: Barriers and Critical Use-Cases for mRehab Adoption. In: Miesenberger, K., Manduchi, R., Covarrubias Rodriguez, M. and Peňáz, P., Eds., Computers Helping People with Special Needs, Springer, 250-258. https://doi.org/10.1007/978-3-030-58805-2_30
Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D. (2003) User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27, 425-478. https://doi.org/10.2307/30036540
Al Aufa, B., Renindra, I.S., Putri, J.S. and Nurmansyah, M.I. (2020) An Application of the Unified Theory of Acceptance and Use of Technology (UTAUT) Model for Understanding Patient Perceptions on Using Hospital Mobile Application. Enfermería Clínica, 30, 110-113. https://doi.org/10.1016/j.enfcli.2020.06.025
Zayyad, M.A. and Toycan, M. (2018) Factors Affecting Sustainable Adoption of E-Health Technology in Developing Countries: An Exploratory Survey of Nigerian Hospitals from the Perspective of Healthcare Professionals. PeerJ, 6, e4436. https://doi.org/10.7717/peerj.4436
Walle, Y.M., Ayalew, A.A. and Mohammed, M.A. (2023) Adoption of Digital Health Tools in Sub-Saharan Africa: An Extension of the UTAUT Model. BMC Medical Informatics and Decision Making, 23, Article No. 44.
Magsamen-Conrad, K., Wang, F., Tetteh, D. and Lee, Y. (2019) Using Technology Adoption Theory and a Lifespan Approach to Develop a Theoretical Framework for eHealth Literacy: Extending UTAUT. Health Communication, 35, 1435-1446. https://doi.org/10.1080/10410236.2019.1641395
Oyediran, K.A., Makinde, O.A. and Adelakin, O. (2020) The Role of Telemedicine in Addressing Access to Sexual and Reproductive Health Services in Sub-Saharan Africa during the COVID-19 Pandemic. African Journal of Reproductive Health, 24, 49-55.
Amin, J., Ahmad, B., Amin, S., Siddiqui, A.A. and Alam, M.K. (2022) Rehabilitation Professional and Patient Satisfaction with Telerehabilitation of Musculoskeletal Disorders: A Systematic Review. BioMed Research International, 2022, Article ID: 7366063. https://doi.org/10.1155/2022/7366063
Williams, I. and Dickinson, H. (2010) Can Knowledge Management Enhance Technology Adoption in Healthcare? A Review of the Literature. Evidence & Policy, 6, 309-331. https://doi.org/10.1332/174426410x524811
Cimperman, M., Makovec Brenčič, M. and Trkman, P. (2016) Analyzing Older Users’ Home Telehealth Services Acceptance Behavior—Applying an Extended UTAUT Model. International Journal of Medical Informatics, 90, 22-31. https://doi.org/10.1016/j.ijmedinf.2016.03.002
Adenuga, K.I., Iahad, N.A. and Miskon, S. (2017) Towards Reinforcing Telemedicine Adoption Amongst Clinicians in Nigeria. International Journal of Medical Informatics, 104, 84-96. https://doi.org/10.1016/j.ijmedinf.2017.05.008
Chau, P.Y.K. and Hu, P.J. (2002) Examining a Model of Information Technology Acceptance by Individual Professionals: An Exploratory Study. Journal of Management Information Systems, 18, 191-229. https://doi.org/10.1080/07421222.2002.11045699
Venkatesh, V., Thong, J.Y.L. and Xu, X. (2012) Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36, 157-178. https://doi.org/10.2307/41410412
Wang, M., Huang, K., Li, X., Zhao, X., Downey, L., Hassounah, S., et al. (2025) Health Workers’ Adoption of Digital Health Technology in Low- and Middle-Income Countries: A Systematic Review and Meta-Analysis. Bulletin of the World Health Organization, 103, 126-135F. https://doi.org/10.2471/blt.24.292157