Abdullah A. Almojaibel , Assim M. AlAbdulKader , Mohammad A. Al-Bsheish , Abdulelah M. Aldhahir , Saeed M. Alghamdi , Fatma I. Almaghlouth , Abdullah S. Alqahtani , Jaber S. Alqahtani , Yousef D. Alqurashi , Mohammed E. Alsubaiei , Abdulrahman M. Jabour , Mu’taman K. Jarrar , Jithin K. Sreedharan , Shoug Y. Al Humoud
{"title":"Acceptance of telehealth in the Kingdom of Saudi Arabia: an application of the UTAUT model","authors":"Abdullah A. Almojaibel , Assim M. AlAbdulKader , Mohammad A. Al-Bsheish , Abdulelah M. Aldhahir , Saeed M. Alghamdi , Fatma I. Almaghlouth , Abdullah S. Alqahtani , Jaber S. Alqahtani , Yousef D. Alqurashi , Mohammed E. Alsubaiei , Abdulrahman M. Jabour , Mu’taman K. Jarrar , Jithin K. Sreedharan , Shoug Y. Al Humoud","doi":"10.1016/j.ceh.2025.08.002","DOIUrl":null,"url":null,"abstract":"<div><h3>Introduction</h3><div>Understanding telehealth users’ acceptance is essential for ensuring effective implementation and may lead to successful, higher quality, and safer telehealth programs. Therefore, this study aimed to measure telehealth acceptance in the population of Saudi Arabia and to explore the associations between sociodemographic variables and intention to use telehealth.</div></div><div><h3>Materials and methods</h3><div>This study was conducted online from May 1, 2024, to June 30, 2024. Part 1 of the questionnaire collected sociodemographic data. Part 2 employed the Unified Theory of Acceptance and Use of Technology (UTAUT), which includes performance expectancy (PE), effort expectancy (EE), social influence (SF), and facilitating conditions (FC) in addition to the Behavioral Intention (BI) subscale to examine factors influencing telehealth acceptance. The associations between the sociodemographic variables and each construct of the UTAUT and the associations between the sociodemographic variables of participants who agreed for each construct and BI to use telehealth were analyzed using bivariate logistic regression to evaluate predictors.</div></div><div><h3>Results</h3><div>A total of 2234 participants completed the survey. 95.7 % of the participants were positive about using telehealth. PE was a significant predictor of the intention to use telehealth (p < 0.01). EE was also a significant predictor of the positive intention to use telehealth (p < 0.01). SI significantly predicted telehealth usage (p < 0.01), as did the FC construct (p < 0.01).</div></div><div><h3>Conclusion</h3><div>Telehealth was highly accepted by the population in KSA. User acceptance of telehealth was influenced by their perception of its benefits, ease of use, social pressure, and the availability of facilitating logistics such as a computer and the internet.</div></div>","PeriodicalId":100268,"journal":{"name":"Clinical eHealth","volume":"8 ","pages":"Pages 162-174"},"PeriodicalIF":0.0000,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical eHealth","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2588914125000218","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction
Understanding telehealth users’ acceptance is essential for ensuring effective implementation and may lead to successful, higher quality, and safer telehealth programs. Therefore, this study aimed to measure telehealth acceptance in the population of Saudi Arabia and to explore the associations between sociodemographic variables and intention to use telehealth.
Materials and methods
This study was conducted online from May 1, 2024, to June 30, 2024. Part 1 of the questionnaire collected sociodemographic data. Part 2 employed the Unified Theory of Acceptance and Use of Technology (UTAUT), which includes performance expectancy (PE), effort expectancy (EE), social influence (SF), and facilitating conditions (FC) in addition to the Behavioral Intention (BI) subscale to examine factors influencing telehealth acceptance. The associations between the sociodemographic variables and each construct of the UTAUT and the associations between the sociodemographic variables of participants who agreed for each construct and BI to use telehealth were analyzed using bivariate logistic regression to evaluate predictors.
Results
A total of 2234 participants completed the survey. 95.7 % of the participants were positive about using telehealth. PE was a significant predictor of the intention to use telehealth (p < 0.01). EE was also a significant predictor of the positive intention to use telehealth (p < 0.01). SI significantly predicted telehealth usage (p < 0.01), as did the FC construct (p < 0.01).
Conclusion
Telehealth was highly accepted by the population in KSA. User acceptance of telehealth was influenced by their perception of its benefits, ease of use, social pressure, and the availability of facilitating logistics such as a computer and the internet.