A modified UTAUT2 for the study of telemedicine adoption

References

• Ranganathan C, Balaji S. Key factors affecting the adoption of telemedicine by ambulatory clinics: insights from a statewide survey. Telemed e-Health. 2020;26(2):218–225.
   PubMed Web of Science ®Google Scholar
• Yusif S, Hafeez-Baig A, Soar J. Change management and adoption of health information technology (HIT)/eHealth in public hospitals in Ghana: a qualitative study. Appl Comput Informat. 2020.
   Google Scholar
• Owusu Kwateng K, Appiah C, Atiemo KAO. Adoption of health information systems: Health professionals perspective. International Journal of Healthcare Management. 2021;14(2):517–533.
   Web of Science ®Google Scholar
• Dodoo JE, Al-Samarraie H, Alzahrani AI. Telemedicine use in sub-Saharan Africa: barriers and policy recommendations for Covid-19 and beyond. Int J Med Inf. 2021;151:104467.
   PubMed Web of Science ®Google Scholar
• Rahi S, Khan MM, Alghizzawi M. Factors influencing the adoption of telemedicine health services during COVID-19 pandemic crisis: an integrative research model. Enterprise Information Syst. 2020;15(6):769–793.
   Web of Science ®Google Scholar
• Rizzi AM, Polachek WS, Dulas M, et al. The new ‘normal’: rapid adoption of telemedicine in orthopaedics during the COVID-19 pandemic. Injury. 2020;51(12):2816–2821.
   PubMed Web of Science ®Google Scholar
• Bokolo AJ. Application of telemedicine and eHealth technology for clinical services in response to COVID–19 pandemic. Health Technol (Berl). 2021;11(2):359–366.
   PubMed Web of Science ®Google Scholar
• Bawack RE, Kala Kamdjoug JR. Adequacy of UTAUT in clinician adoption of health information systems in developing countries: the case of Cameroon. Int J Med Inf. 2018;109:15–22.
   PubMed Web of Science ®Google Scholar
• Vest JR, Jung HY, Wiley K, et al. Adoption of health information technology among US nursing facilities. J Am Med Dir Assoc. 2019;20(8):995–1000.
   PubMed Web of Science ®Google Scholar
• Lee JM, Carlson E, Albanese-O’Neill A, et al. Adoption of telemedicine for type 1 diabetes care during the COVID-19 pandemic. Diabetes Technol Ther. 2021;23(9):642–651.
   PubMed Web of Science ®Google Scholar
• Mahfuz MA, Khanam L, Hu W. Mobile banking services adoption: insight from brand name perspectives based on UTAUT2 model. Independ. Bus. Rev. 2017;10(1–2):21–42. Available from: http://dir.iub.edu.bd:8080/xmlui/bitstream/handle/123456789/454/v-2.pdf?sequence¼1&isAllowed¼y.
   Google Scholar
• World Health Organization World Health Report. Working Together for Health. 2006ß, World Health Organization. Geneva: WHO Press; 2006. p. 1–209
   Google Scholar
• Ahmed T, Bloom G, Iqbal M, et al. (2014). E-health and M-Health in Bangladesh: Opportunities and Challenges. (No. IDS Evidence Report; 60). IDS.
   Google Scholar
• Odekunle FF, Srinivasan S, Odekunle RO. Why Sub-Saharan Africa lags in electronic health record (EHR) adoption and possible strategies to increase EHR adoption in this region. J Health Informatics Africa. 2018;5(1):8–15.
   Google Scholar
• Kane CK, Gillis K. The use of telemedicine by physicians: still the exception rather than the rule. Health Aff. 2018;37(12):1923–1930.
   Web of Science ®Google Scholar
• Acheampong F, Vimarlund V. Business models for telemedicine services: a literature review. Health Syst. 2015;4(3):189–203.
   Web of Science ®Google Scholar
• Yamin MAY, Alyoubi BA. Adoption of telemedicine applications among Saudi citizens during COVID-19 pandemic: an alternative health delivery system. J Infect Public Health. 2020;13(12):1845–1855.
   PubMed Web of Science ®Google Scholar
• Albarrak AI, Mohammed R, Almarshoud N, et al. Assessment of physician’s knowledge, perception and willingness of telemedicine in Riyadh region, Saudi Arabia. J Infect Public Health. 2021;14(1):97–102.
   PubMed Web of Science ®Google Scholar
• Chu C, Cram P, Pang A, et al. Rural telemedicine use before and during the COVID-19 pandemic: repeated cross-sectional study. J Med Internet Res. 2021;23(4):e26960.
   PubMed Web of Science ®Google Scholar
• Alanazi B, Butler-Henderson K, Alanazi M. Perceptions of healthcare professionals about the adoption and use of EHR in Gulf Cooperation Council countries: a systematic review. BMJ Health & Care Informatics. 2020a;27(1).
   PubMedGoogle Scholar
• Alanazi B, Butler-Henderson K, Alanazi MR. Factors influencing healthcare professionals’ perception towards EHR/EMR systems in Gulf Cooperation Council countries: a systematic review. Oman Med J. 2020b;35(6):e192, doi:10.5001/omj.2020.85.
   PubMedGoogle Scholar
• Al-Rawajfah O, Tubaishat A. Barriers and facilitators to using electronic healthcare records in Jordanian hospitals from the nurses’ perspective: a national survey. Informatics for Health and Social Care. 2019;44(1):1–11.
   PubMed Web of Science ®Google Scholar
• Xie J, Prahalad P, Lee TC, et al. Pediatric subspecialty adoption of telemedicine amidst the COVID-19 pandemic: an early descriptive analysis. Front Pediatr. 2021;9:283.
   Web of Science ®Google Scholar
• Venkatesh V, Sykes TA, Zhang X. ‘Just what the doctor ordered’: a revised UTAUT for EMR system adoption and use by doctors. In 2011 44th Hawaii International Conference on System Sciences. IEEE; 2011. p. 1–10.
   Google Scholar
• Yu J, Mink PJ, Huckfeldt PJ, et al. Population-level estimates of telemedicine service provision using an all-payer claims database. Health Aff. 2018;37(12):1931–1939.
   Web of Science ®Google Scholar
• Tamilmani K, Rana NP, Dwivedi YK. Consumer acceptance and use of information technology: A meta-analytic evaluation of UTAUT2. Information Systems Frontiers. 2021;23(4):987–1005.
   Web of Science ®Google Scholar
• Venkatesh V, Morris MG, Davis GB, et al. User acceptance of information technology: toward a unified view. MIS Q. 2003;27(3):425–478.
   Web of Science ®Google Scholar
• Nurhayati S, Anandari D, Ekowati W. Unified theory of acceptance and usage of technology (UTAUT) model to predict health information system adoption. KEMAS: J Kesehatan Masyarakat. 2019;15(1):89–97.
   Google Scholar
• Kohnke A, Cole ML, Bush R. Incorporating UTAUT predictors for understanding home care patients’ and clinician’s acceptance of healthcare telemedicine equipment. J Technol Manag Innov. 2014;9(2):29–41.
   Google Scholar
• DeLone WH, McLean ER. The DeLone and McLean model of information systems success: a ten-year update. J Manage Inf Syst. 2003;19(4):9–30.
   Web of Science ®Google Scholar
• Venkatesh V, Thong JY, Xu X. Unified theory of acceptance and use of technology: a synthesis and the road ahead. J Assoc Information Syst. 2016;17(5):328–376.
   Web of Science ®Google Scholar
• Liao C, Tsou C, Huang M. Factors influencing the usage of 3G mobile services in Taiwan. Information Review. 31(6):759–774. https://doi.org/10.1108/14684520710841757
   Google Scholar
• Lu J, Yu C, Liu C, Yao JE. Technology acceptance model for wireless Internet. Internet Research. 13(3):206–222. https://doi.org/10.1108/10662240310478222
   Google Scholar
• Owusu Kwateng K, Appiah C, et al. Adoption of health information systems: health professionals perspective. Int J Healthc Manag. 2021;14(2):517–533.
   Web of Science ®Google Scholar
• Venkatesh V, Thong JY, Xu X. Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Q. 2012;36(1):157–178.
   Web of Science ®Google Scholar
• Cunningham JB, McCrum-Gardner E. Power, effect and sample size using GPower: practical issues for researchers and members of research ethics committees. Evidence-Based Midwifery. 2007;5(4):132–137.
   Google Scholar
• Hair JF, Money AH, Samouel P, et al. Research methods for business. Education+ Training. 2007;49(4):336–337. doi:10.1108/et.2007.49.4.336.2.
   Google Scholar
• Hair JF, Hult GT, Ringle CM, et al. A primer on partial least squares structural equation modeling (PLS-SEM). 1 ed. Thousand Oaks (CA): Sage; 2014.
   Google Scholar
• Aldholay A, Isaac O, Abdullah Z, et al. An extension of Delone and McLean IS success model with self-efficacy. Int J Information Learn Technol. 2018;35(4), 285–304. doi:10.1108/IJILT-11-2017-0116
   Web of Science ®Google Scholar
• Mohammadi H. Investigating users’ perspectives on e-learning: an integration of TAM and IS success model. Comput Human Behav. 2015;45(1):359–374. Available from: https://doi.org/10.1016/j.chb.2014.07.044.
   Google Scholar
• Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate Data Analysis (7th Edition). NJ: Prentice Hall; 2010.
   Google Scholar
• Nyaga GN, Whipple JM, Lynch DF. Examining supply chain relationships: do buyer and supplier perspectives on collaborative relationships differ? J Oper Manage. 2010;28(2):101–114.
   Web of Science ®Google Scholar
• Byrne BM. Structural equation modeling with EQS: Basic concepts, applications, and programming (2nd ed.). Mahwah, NJ: Lawrence Erlbaum Associates; 2006.
   Google Scholar
• Bokolo AJ. Exploring the adoption of telemedicine and virtual software for care of outpatients during and after COVID-19 pandemic. Irish Journal of Medical Science. 2021;190(1):1–10.
   PubMed Web of Science ®Google Scholar
• Hollander JE, Carr BG. Virtually perfect? Telemedicine for COVID-19. New England Journal of Medicine. 2020;382(18):1679–1681.
   PubMed Web of Science ®Google Scholar
• Mann DM, Chen J, Chunara R, Testa PA, Nov O. COVID-19 transforms health care through telemedicine: evidence from the field. Journal of the American Medical Informatics Association. 2020;27(7):1132–1135.
   PubMed Web of Science ®Google Scholar
• Morosan C, DeFranco A. It’s about time: revisiting UTAUT2 to examine consumers’ intentions to use NFC mobile payments in hotels. Int J Hosp Manag. 2016;53:17–29.
   Web of Science ®Google Scholar
• Dwivedi YK, Rana NP, Jeyaraj A, et al. Re-examining the unified theory of acceptance and use of technology (UTAUT): towards a revised theoretical model. Inf Syst Front. 2019;21(3):719–734.
   Web of Science ®Google Scholar
• Al-Saedi K, Al-Emran M, Ramayah T, et al. Developing a general extended UTAUT model for M-payment adoption. Technol Soc. 2020;62:101293.
   Web of Science ®Google Scholar
• Cidral W, Aparicio M, Oliveira T. Students’ long-term orientation role in e-learning success: A Brazilian study. Heliyon. 2020; 6(12):e05735.
   PubMed Web of Science ®Google Scholar
• Ho KF, Ho CH, Chung MH. Theoretical integration of user satisfaction and technology acceptance of the nursing process information system. PLoS One. 2019;14(6):e0217622.
   PubMed Web of Science ®Google Scholar
• Demissie D, Rorissa A. The effect of information quality and satisfaction on a parent’s behavioral intention to use a learning community management system. Libri. 2015;65(2):143–150.
   Web of Science ®Google Scholar
• Wang EST, Lin RL. Perceived quality factors of location-based apps on trust, perceived privacy risk, and continuous usage intention. Behav Inf Technol. 2017;36(1):2–10.
   Web of Science ®Google Scholar