Immersive training of clinical decision making with AI driven virtual patients - a new VR platform called medical tr.AI.ning

Medical students' AI literacy and attitudes towards AI: a cross-sectional two-center study using pre-validated assessment instruments

BACKGROUND

Artificial intelligence (AI) is becoming increasingly important in healthcare. It is therefore crucial that today's medical students have certain basic AI skills that enable them to use AI applications successfully. These basic skills are often referred to as "AI literacy". Previous research projects that aimed to investigate medical students' AI literacy and attitudes towards AI have not used reliable and validated assessment instruments.

METHODS

We used two validated self-assessment scales to measure AI literacy (31 Likert-type items) and attitudes towards AI (5 Likert-type items) at two German medical schools. The scales were distributed to the medical students through an online questionnaire. The final sample consisted of a total of 377 medical students. We conducted a confirmatory factor analysis and calculated the internal consistency of the scales to check whether the scales were sufficiently reliable to be used in our sample. In addition, we calculated t-tests to determine group differences and Pearson's and Kendall's correlation coefficients to examine associations between individual variables.

RESULTS

The model fit and internal consistency of the scales were satisfactory. Within the concept of AI literacy, we found that medical students at both medical schools rated their technical understanding of AI significantly lower (MMS1 = 2.85 and MMS2 = 2.50) than their ability to critically appraise (MMS1 = 4.99 and MMS2 = 4.83) or practically use AI (MMS1 = 4.52 and MMS2 = 4.32), which reveals a discrepancy of skills. In addition, female medical students rated their overall AI literacy significantly lower than male medical students, t(217.96) = -3.65, p <.001. Students in both samples seemed to be more accepting of AI than fearful of the technology, t(745.42) = 11.72, p <.001. Furthermore, we discovered a strong positive correlation between AI literacy and positive attitudes towards AI and a weak negative correlation between AI literacy and negative attitudes. Finally, we found that prior AI education and interest in AI is positively correlated with medical students' AI literacy.

CONCLUSIONS

Courses to increase the AI literacy of medical students should focus more on technical aspects. There also appears to be a correlation between AI literacy and attitudes towards AI, which should be considered when planning AI courses.

Reviewing the current state of virtual reality integration in medical education - a scoping review protocol

BACKGROUND

Due to an increasing focus of medical curricula on clinical decision-making skills, new learning tools are constantly developed. Virtual reality (VR) is one of the emerging technologies with the potential to improve health professionals' education. Highly realistic learning experiences with repeatable training scenarios can be created within a protected environment that is independent from real patients' presence. Our project "medical tr.AI.ning" is following this approach aiming to simulate immersive virtual first-person scenarios with intelligent, interactable virtual patients. So far, VR has been mainly used in surgical training, but there is evidence for effectiveness in training different procedural skills, such as cardiopulmonary resuscitation, knowledge acquisition, and improvement of reasoning and creativity, while still being cost-effective. The objective of this scoping review is to explore the usage and identify key areas of VR applications in the field of medical education. Furthermore, the corresponding requirements, evaluation methods and outcomes, advantages, and disadvantages will be covered.

METHODS

This scoping review protocol implements the updated JBI Scoping Review Methodology. In March 2022, a preliminary literature research in PubMed was performed by two independent reviewers to refine search terms and strategy as well as inclusion criteria of the protocol, accounting for actuality and scientific relevance. The final search will be conducted using PubMed, ScienceDirect, Cochrane Library, Web of Science Core Collection, and JBI Evidence Synthesis. Search, study screening, and data extraction will be done in parallel and independently by two reviewers. Discrepancies will be handled by consensus or consulting a third review author.

DISCUSSION

With this scoping review, we anticipate collating the range of application of VR in medical education while using a transparent and reproducible search strategy. This may contribute to the design and development of novel educational VR platforms and their integration into medical curricula while pointing out previous omissions and pitfalls.