Background and Aims: Health researchers often struggle with challenges such as translating complex texts, interpreting nuanced information, conducting detailed statistical analyses, and more. Artificial Intelligence (AI) models, by providing easy access to information, offer a promising solution to these challenges. This study aims to examine university students' perspectives on the impact of AI models in overcoming these challenges. Methods: This survey study was conducted in 2023 by using a researcher-developed questionnaire. A total of 445 students from the Kerman University of Medical Sciences participated and completed the questionnaire. Descriptive statistics and linear regression were used to analyze the relationship between independent variables and the impact of AI models on health research. Open-ended responses were coded and stored in MAXQDA. Results: = 9) were the most significant risks of using AI models in health research. Conclusions: AI models show promise for improving research efficiency and quality, but further efforts are necessary to mitigate perceived risks and encourage broader adoption.
Montazeri et al. (2026) studied this question.