Salud Publica

Teaching is frequently judged inferior to research by academic leaders. Professors
too often boast about how they have escaped their teaching responsibilities to pursue
the exalted goal of science. Teaching versus research is a false dichotomy, of course.
But the academic reward system weighs heavily in favour of those who prioritise grants
and papers over students and tutorials. Teachers sit in the permanent shadow of scientists.
And so it was a refreshing contrast last week to observe the International Conference
on the Future of Health Professions Education, convened by the University of Miami,
FL, USA.

Background: The COVID-19 pandemic was accompanied by the spread of uncontrolled health information and fake news, which also quickly became an infodemic. Emergency communication is a challenge for public health institutions to engage the public during disease outbreaks. Health professionals need a high level of digital health literacy (DHL) to cope with difficulties; therefore, efforts should be made to address this issue starting from undergraduate medical students.
Objective: The aim of this study was to investigate the DHL skills of Italian medical students and the effectiveness of an informatics course offered by the University of Florence (Italy). This course focuses on assessing the quality of medical information using the “dottoremaeveroche” (DMEVC) web resource offered by the Italian National Federation of Orders of Surgeons and Dentists, and on health information management.
Methods: A pre-post study was conducted at the University of Florence between November and December 2020. First-year medical students participated in a web-based survey before and after attending the informatics course. The DHL level was self-assessed using the eHealth Literacy Scale for Italy (IT-eHEALS) tool and questions about the features and quality of the resources. All responses were rated on a 5-point Likert scale. Change in the perception of skills was assessed using the Wilcoxon test.
Results: A total of 341 students participated in the survey at the beginning of the informatics course (women: n=211, 61.9%; mean age 19.8, SD 2.0) and 217 of them (64.2%) completed the survey at the end of the course. At the first assessment, the DHL level was moderate, with a mean total score of the IT-eHEALS of 2.9 (SD 0.9). Students felt confident about finding health-related information on the internet (mean score of 3.4, SD 1.1), whereas they doubted the usefulness of the information they received (mean score of 2.0, SD 1.0). All scores improved significantly in the second assessment. The overall mean score of the IT-eHEALS significantly increased (P<.001) to 4.2 (SD 0.6). The item with the highest score related to recognizing the quality of health information (mean score of 4.5, SD 0.7), whereas confidence in the practical application of the information received remained the lowest (mean of 3.7, SD 1.1) despite improvement. Almost all students (94.5%) valued the DMEVC as an educational tool.
Conclusions: The DMEVC tool was effective in improving medical students’ DHL skills. Effective tools and resources such as the DMEVC website should be used in public health communication to facilitate access to validated evidence and understanding of health recommendations.

Hojman et al. discuss the role of exercise in controlling cancer progression through
direct effects on tumor-intrinsic factors, interplay with whole-body exercise effects,
alleviation of cancer-related adverse events, and improvement of cancer treatment
efficacy. Understanding these mechanistic interactions is warranted for pursuing exercise
as cancer medicine.

Hojman et al. discuss the role of exercise in controlling cancer progression through
direct effects on tumor-intrinsic factors, interplay with whole-body exercise effects,
alleviation of cancer-related adverse events, and improvement of cancer treatment
efficacy. Understanding these mechanistic interactions is warranted for pursuing exercise
as cancer medicine.

Background: The use of artificial intelligence (AI) in medicine is expected to increase significantly in the upcoming years. Advancements in AI technology have the potential to revolutionize health care, from aiding in the diagnosis of certain diseases to helping with treatment decisions. Current literature suggests the integration of the subject of AI in medicine as part of the medical curriculum to prepare medical students for the opportunities and challenges related to the use of the technology within the clinical context.
Objective: We aimed to explore the relevant knowledge and understanding of the subject of AI in medicine and specify curricula teaching content within medical education.
Methods: For this research, we conducted 12 guideline-based expert interviews. Experts were defined as individuals who have been engaged in full-time academic research, development, or teaching in the field of AI in medicine for at least 5 years. As part of the data analysis, we recorded, transcribed, and analyzed the interviews using qualitative content analysis. We used the software QCAmap and inductive category formation to analyze the data.
Results: The qualitative content analysis led to the formation of three main categories (“Knowledge,” “Interpretation,” and “Application”) with a total of 9 associated subcategories. The experts interviewed cited knowledge and an understanding of the fundamentals of AI, statistics, ethics, and privacy and regulation as necessary basic knowledge that should be part of medical education. The analysis also showed that medical students need to be able to interpret as well as critically reflect on the results provided by AI, taking into account the associated risks and data basis. To enable the application of AI in medicine, medical education should promote the acquisition of practical skills, including the need for basic technological skills, as well as the development of confidence in the technology and one’s related competencies.
Conclusions: The analyzed expert interviews’ results suggest that medical curricula should include the topic of AI in medicine to develop the knowledge, understanding, and confidence needed to use AI in the clinical context. The results further imply an imminent need for standardization of the definition of AI as the foundation to identify, define, and teach respective content on AI within medical curricula.
Trial Registration:

AI in Medicine explores the history and vast potential of artificial intelligence and machine learning across all areas of health care.