沙特阿拉伯王国接受远程保健:UTAUT模式的应用

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
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引用次数: 0

摘要

了解远程医疗用户的接受程度对于确保有效实施至关重要,并可能导致成功,更高质量和更安全的远程医疗计划。因此,本研究旨在衡量沙特阿拉伯人口对远程医疗的接受程度,并探讨社会人口统计学变量与使用远程医疗的意愿之间的关系。材料与方法本研究于2024年5月1日至2024年6月30日在线进行。问卷的第一部分收集了社会人口统计数据。第二部分采用技术接受与使用统一理论(UTAUT),其中包括绩效期望(PE)、努力期望(EE)、社会影响(SF)和促进条件(FC)以及行为意向(BI)子量表来研究影响远程医疗接受的因素。使用双变量逻辑回归来评估预测因子,分析了社会人口变量与UTAUT每个结构之间的关联,以及同意每个结构和BI使用远程医疗的参与者的社会人口变量之间的关联。结果共2234人完成调查。95.7%的参与者对使用远程医疗持积极态度。PE是使用远程医疗意愿的显著预测因子(p < 0.01)。情感表达也是使用远程医疗的积极意向的显著预测因子(p < 0.01)。SI显著地预测了远程医疗的使用(p < 0.01), FC结构也是如此(p < 0.01)。结论远程医疗在沙特阿拉伯地区的接受程度较高。用户对远程保健的好处、易用性、社会压力以及计算机和互联网等便利物流的可用性的看法影响了他们对远程保健的接受程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Acceptance of telehealth in the Kingdom of Saudi Arabia: an application of the UTAUT model

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.
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