Comment about ‘Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis’ (2024)

Peer Review reports

Dear Editor,

We read with interest the recently published article entitled “Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis” by Amiri et al. [1]. Amiri et al. demonstrated that students in the medical field have moderate knowledge levels and positive attitudes toward artificial intelligence (AI) and its applications, suggesting the need for curricular enhancement to improve their knowledge and the facilitate the development of targeted education around AI-related ethics, AI impacts, and human–AI collaborations [1].

In particular, the finding by Ameli et al. that attitudes and knowledge about AI varied widely across target populations – for example, students in developed countries were more knowledgeable about AI than those in developing countries – [1] was an important finding that provided a thought-provoking discussion. However, certain aspects of these findings require further investigation.

First, there is discussion regarding the need to standardize the assessment of attitudes and knowledge toward AI among students in the medical field.

In the study by Ameri et al., the results of the meta-analysis showed very high heterogeneity, with an I² value of 99.47% for attitudes and 98.95% for knowledge [1]. This is a significant finding of the present study. As the authors discussed [1], we agree that a major factor contributing to the high heterogeneity is the differences between the countries in the target populations, and this study demonstrated how the digital divide has led to international disparities in attitudes and knowledge about AI, highlighting future global challenges in AI education for students in the medical field. Another important factor was the difference in methods of assessing knowledge and attitudes among the studies included in the meta-analysis by Amiri et al., as each study used its own questionnaire to assess them [1]. The authors mentioned the differences in assessment methods across studies as a limitation of the research [1]. However, this represents a significant challenge for future studies in this field. Various scales have been used to assess AI literacy, including knowledge and attitudes [2].

An item set was recently developed to assess the AI literacy of non-AI experts [3]; it has also been used in studies to assess the AI literacy of medical students [4]. However, AI literacy is common among non-AI professionals. Students in the medical field are future participants in important decisions regarding patient diagnosis, treatment, and care planning; therefore, they must develop attitudes and knowledge regarding the impact and ethical issues of AI technology in these decision-making processes. Thus, attitudes and knowledge about AI that must be acquired and the content that should be taught differ between the general population and students in the medical field. Therefore, for the future development of research in this field, it is necessary to clarify the attitudes and knowledge of AI that such students are lacking and develop a standardized assessment scale to assess them.

Second, there is discussion of the differences in attitudes and knowledge toward AI among medical, dental, and nursing students. Amiri et al. considered medical, dental, and nursing students as being in the same medical field [1]; however, the attitudes and knowledge about AI may differ among them. Contemporary research on the application of AI-based technologies in nursing is primarily in the early stages of technological development, and there is currently scant evidence on the impact and implementation aspects of these technologies in practice [5].

As indicated by the fact that only one of the 22 studies in the systematic review by Amiri et al. [1] involved nursing students, research on AI in nursing lags behind that of medicine; it is likely that the education lags as well. Furthermore, the field of nursing emphasizes interpersonal care based on compassion, empathy, and listening to patients, making it more difficult to apply AI in clinical practice than in medical fields such as medicine and dentistry. Therefore, nursing students may have different attitudes and knowledge levels, especially those that are less or more negative than those of medical students. In the study by Ameri et al., because of the limited number of studies focusing on nursing students and the significant heterogeneity among them, the meta-analysis did not include subgroup analyses of medical, dental, and nursing students [1]. However, once more studies are conducted in the future, it will be necessary to clarify the differences in attitudes and knowledge among groups and examine which fields require more focused education and research.

Undoubtedly, the study by Amiri et al. [1] provided important insight into the current attitudes and knowledge of students in the medical field regarding AI and its applications, and we believe that it will greatly contribute to and facilitate future discussions about the direction of medical education.