Student Research Committee, Faculty of Medicine, Birjand University of Medical Sciences, Birjand, Iran.
Department of Clinical Psychology, Faculty of Psychology and Education, Kharazmi University, Tehran, Iran.
BMC Med Educ. 2023 Aug 15;23(1):577. doi: 10.1186/s12909-023-04553-1.
There are numerous cases where artificial intelligence (AI) can be applied to improve the outcomes of medical education. The extent to which medical practitioners and students are ready to work and leverage this paradigm is unclear in Iran. This study investigated the psychometric properties of a Persian version of the Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS) developed by Karaca, et al. in 2021. In future studies, the medical AI readiness for Iranian medical students could be investigated using this scale, and effective interventions might be planned and implemented according to the results.
In this study, 502 medical students (mean age 22.66(± 2.767); 55% female) responded to the Persian questionnaire in an online survey. The original questionnaire was translated into Persian using a back translation procedure, and all participants completed the demographic component and the entire MAIRS-MS. Internal and external consistencies, factor analysis, construct validity, and confirmatory factor analysis were examined to analyze the collected data. A P ≤ 0.05 was considered as the level of statistical significance.
Four subscales emerged from the exploratory factor analysis (Cognition, Ability, Vision, and Ethics), and confirmatory factor analysis confirmed the four subscales. The Cronbach alpha value for internal consistency was 0.944 for the total scale and 0.886, 0.905, 0.865, and 0.856 for cognition, ability, vision, and ethics, respectively.
The Persian version of MAIRS-MS was fairly equivalent to the original one regarding the conceptual and linguistic aspects. This study also confirmed the validity and reliability of the Persian version of MAIRS-MS. Therefore, the Persian version can be a suitable and brief instrument to assess Iranian Medical Students' readiness for medical artificial intelligence.
人工智能(AI)在改善医学教育成果方面有许多应用案例。在伊朗,医生和学生准备好应用这一模式的程度尚不清楚。本研究旨在调查 Karaca 等人 2021 年开发的医学生医学人工智能准备度量表(MAIRS-MS)的波斯语版本的心理测量学特性。在未来的研究中,可以使用该量表来研究伊朗医学生对医学人工智能的准备情况,并根据研究结果计划和实施有效的干预措施。
本研究中,502 名医学生(平均年龄 22.66(±2.767)岁;55%为女性)通过在线调查对波斯语问卷进行了回复。原始问卷采用反向翻译程序被翻译成波斯语,所有参与者都完成了人口统计学部分和整个 MAIRS-MS。本研究通过内部和外部一致性、因子分析、结构有效性和验证性因子分析来分析收集的数据。P 值≤0.05 被认为具有统计学意义。
探索性因子分析得出四个子量表(认知、能力、愿景和伦理),验证性因子分析也证实了这四个子量表。总量表的内部一致性 Cronbach alpha 值为 0.944,认知、能力、愿景和伦理的 Cronbach alpha 值分别为 0.886、0.905、0.865 和 0.856。
从概念和语言方面来看,MAIRS-MS 的波斯语版本与原版相当。本研究还证实了 MAIRS-MS 的波斯语版本的有效性和可靠性。因此,波斯语版本可以成为评估伊朗医学生对医学人工智能准备程度的一种合适且简洁的工具。