Kumar Rakesh, Singh Ajay, Kassar Ahmed Subahi Ahmed, Humaida Mohammed Ismail, Joshi Sudhanshu, Sharma Manu
Rakesh Kumar, PhD Department of Health Management, College of Public Health and Health Informatics, University of Hail, Saudi Arabia.
Ajay Singh, PhD Department of Management & Information Systems, College of Business Administration, University of Hail, Saudi Arabia.
Pak J Med Sci. 2025 Mar;41(3):682-686. doi: 10.12669/pjms.41.3.11014.
To investigate the perception of AI among the healthcare workforce and its impact on their performance, with technology readiness acting as a moderating factor.
In this cross-sectional study, a close-ended, self-administered survey questionnaire was used between 02 June to 04 August, 2024 to collect responses from 434 participants working in the public hospitals in Hail health cluster in Saudi Arabia. The study employed demographic summaries, descriptive statistics, regression analysis using Hayes' Process, and regression diagnostics for data analysis. The data were analyzed using SPSS version 27.
The participant demographics indicated a majority of male respondents from the medical field, primarily aged between 36-45 years. Most participants had 9-10 or more years of experience in their current position and held graduate degrees in the healthcare sector of Saudi Arabia. Regression analysis using Hayes' Process showed an insignificant negative impact of AI perception on workforce performance (β_1 = -0.0062, p = .315). However, technology readiness significantly moderated this effect, turning it into a positive and significant impact (β_3 = 0.2512, p = .0209).
The study demonstrates that while AI perception alone has a negligible effect on workforce performance, its influence becomes significant when moderated by higher levels of technology readiness. Future research should examine how factors such as organizational culture and resource availability influence AI perceptions in healthcare.
以技术就绪作为调节因素，调查医疗保健工作人员对人工智能的认知及其对他们工作表现的影响。
在这项横断面研究中，于2024年6月2日至8月4日期间使用了一份封闭式的自填式调查问卷，以收集沙特阿拉伯海勒健康集群公立医院434名工作人员的回复。该研究采用人口统计学总结、描述性统计、使用海斯过程的回归分析以及回归诊断进行数据分析。数据使用SPSS 27版本进行分析。
参与者的人口统计学数据显示，大多数男性受访者来自医疗领域，主要年龄在36 - 45岁之间。大多数参与者在现任职位上有9至10年或更长时间的经验，并在沙特阿拉伯医疗保健领域拥有研究生学位。使用海斯过程的回归分析显示，人工智能认知对工作人员表现有不显著的负面影响（β_1 = -0.0062，p = 0.315）。然而，技术就绪显著调节了这种影响，使其转变为积极且显著的影响（β_3 = 0.2512，p = 0.0209）。
该研究表明，虽然仅人工智能认知对工作人员表现的影响可忽略不计，但当由更高水平的技术就绪进行调节时，其影响变得显著。未来的研究应考察组织文化和资源可用性等因素如何影响医疗保健领域对人工智能的认知。
