PDF(Pubmed)
Abstract：
BACKGROUND: 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.
OBJECTIVE: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.
OBJECTIVE: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.
摘要：
背景：人工智能（AI）广泛用于各种医疗领域，包括诊断放射学作为提高效率的工具，精度,和准确性。人工智能作为放射诊断工具的整合有可能减轻诊断延迟，这可能，反过来,影响患者预后和治疗结果。文献显示，关于患者对人工智能作为诊断工具的态度，结果相互矛盾。据我们所知,在沙特阿拉伯没有进行过类似的研究。
目的：本研究的目的是在哈立德国王大学医院检查患者对使用人工智能作为诊断放射学工具的态度。沙特阿拉伯。此外,我们试图探索患者态度与各种社会人口统计学因素之间的潜在关联。
方法：这项描述性分析横断面研究是在一家三级医院进行的。通过经过验证的自我管理问卷从计划进行放射学成像的患者收集数据。主要结果是通过计算5个因素的平均得分来衡量患者对放射学中AI使用的态度，不信任和问责(因素1)，程序性知识(因素2)，个人互动和沟通(因素3)，效率(因子4)，以及向患者提供信息的方法（因素5）。数据分析采用学生t检验，单向方差分析，然后进行事后和多变量分析。
结果：共有382名参与者（n=273，71.5%女性和n=109，28.5%男性）完成了调查并被纳入分析。受访者的平均年龄为39.51（SD13.26）岁。参与者更喜欢医生而不是人工智能来获得程序知识，个人互动,并被告知。然而,与会者对不信任和问责制以及效率表现出中立的态度。婚姻状况被发现与不信任和责任有关，程序性知识，和个人互动。还发现了自我报告的健康状况与知情之间以及专业领域与不信任和问责制之间的关联。
结论：患者热衷于了解AI在放射学中的工作，但倾向于与放射科医生进行个人互动。患者对人工智能取代放射科医生和人工智能的效率持公正态度，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多中心研究的未来研究。
目的：本研究的目的是在哈立德国王大学医院检查患者对使用人工智能作为诊断放射学工具的态度。沙特阿拉伯。此外,我们试图探索患者态度与各种社会人口统计学因素之间的潜在关联。
方法：这项描述性分析横断面研究是在一家三级医院进行的。通过经过验证的自我管理问卷从计划进行放射学成像的患者收集数据。主要结果是通过计算5个因素的平均得分来衡量患者对放射学中AI使用的态度，不信任和问责(因素1)，程序性知识(因素2)，个人互动和沟通(因素3)，效率(因子4)，以及向患者提供信息的方法（因素5）。数据分析采用学生t检验，单向方差分析，然后进行事后和多变量分析。
结果：共有382名参与者（n=273，71.5%女性和n=109，28.5%男性）完成了调查并被纳入分析。受访者的平均年龄为39.51（SD13.26）岁。参与者更喜欢医生而不是人工智能来获得程序知识，个人互动,并被告知。然而,与会者对不信任和问责制以及效率表现出中立的态度。婚姻状况被发现与不信任和责任有关，程序性知识，和个人互动。还发现了自我报告的健康状况与知情之间以及专业领域与不信任和问责制之间的关联。
结论：患者热衷于了解AI在放射学中的工作，但倾向于与放射科医生进行个人互动。患者对人工智能取代放射科医生和人工智能的效率持公正态度，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多中心研究的未来研究。
