Department of Family and Community Medicine, College of Medicine, King Saud University, Riyadh, Saudi Arabia.
College of Medicine, King Saud University, Riyadh, Saudi Arabia.
JMIR Hum Factors. 2024 Aug 7;11:e53108. doi: 10.2196/53108.
Artificial intelligence (AI) is widely used in various medical fields, including diagnostic radiology as a tool for greater efficiency, precision, and accuracy. The integration of AI as a radiological diagnostic tool has the potential to mitigate delays in diagnosis, which could, in turn, impact patients' prognosis and treatment outcomes. The literature shows conflicting results regarding patients' attitudes to AI as a diagnostic tool. To the best of our knowledge, no similar study has been conducted in Saudi Arabia.
The objectives of this study are to examine patients' attitudes toward the use of AI as a tool in diagnostic radiology at King Khalid University Hospital, Saudi Arabia. Additionally, we sought to explore potential associations between patients' attitudes and various sociodemographic factors.
This descriptive-analytical cross-sectional study was conducted in a tertiary care hospital. Data were collected from patients scheduled for radiological imaging through a validated self-administered questionnaire. The main outcome was to measure patients' attitudes to the use of AI in radiology by calculating mean scores of 5 factors, distrust and accountability (factor 1), procedural knowledge (factor 2), personal interaction and communication (factor 3), efficiency (factor 4), and methods of providing information to patients (factor 5). Data were analyzed using the student t test, one-way analysis of variance followed by post hoc and multivariable analysis.
A total of 382 participants (n=273, 71.5% women and n=109, 28.5% men) completed the surveys and were included in the analysis. The mean age of the respondents was 39.51 (SD 13.26) years. Participants favored physicians over AI for procedural knowledge, personal interaction, and being informed. However, the participants demonstrated a neutral attitude for distrust and accountability and for efficiency. Marital status was found to be associated with distrust and accountability, procedural knowledge, and personal interaction. Associations were also found between self-reported health status and being informed and between the field of specialization and distrust and accountability.
Patients were keen to understand the work of AI in radiology but favored personal interaction with a radiologist. Patients were impartial toward AI replacing radiologists and the efficiency of AI, which should be a consideration in future policy development and integration. Future research involving multicenter studies in different regions of Saudi Arabia is required.
人工智能（AI）在各种医学领域得到广泛应用，包括诊断放射学领域，作为提高效率、精度和准确性的工具。将 AI 作为放射学诊断工具进行整合具有减轻诊断延误的潜力，这反过来可能影响患者的预后和治疗结果。文献表明，患者对 AI 作为诊断工具的态度存在矛盾的结果。据我们所知，在沙特阿拉伯还没有进行过类似的研究。
本研究旨在调查沙特阿拉伯哈利德国王大学医院患者对 AI 在诊断放射学中作为工具的使用态度。此外，我们还试图探讨患者态度与各种社会人口学因素之间的潜在关联。
这是一项在三级保健医院进行的描述性分析性横断面研究。通过经过验证的自我管理问卷，从计划进行放射影像学检查的患者中收集数据。主要结果是通过计算不信任和问责制（第 1 因素）、程序知识（第 2 因素）、个人互动和沟通（第 3 因素）、效率（第 4 因素）以及向患者提供信息的方法（第 5 因素）这 5 个因素的平均分数来衡量患者对放射学中使用 AI 的态度。使用学生 t 检验、单因素方差分析，随后进行事后检验和多变量分析对数据进行分析。
共有 382 名参与者（n=273，71.5%为女性，n=109，28.5%为男性）完成了调查并被纳入分析。受访者的平均年龄为 39.51（SD 13.26）岁。参与者更倾向于让医生而不是 AI 提供程序知识、个人互动和信息。然而，参与者对不信任和问责制以及效率表现出中立态度。婚姻状况与不信任和问责制、程序知识和个人互动有关。自我报告的健康状况与信息获取以及专业领域与不信任和问责制之间也存在关联。
患者热衷于了解放射学中 AI 的工作原理，但希望与放射科医生进行个人互动。患者对 AI 取代放射科医生和 AI 的效率持公正态度，这应该是未来政策制定和整合的一个考虑因素。需要在沙特阿拉伯不同地区进行涉及多中心研究的未来研究。
