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University students find Artificial Intelligence (AI) models helpful for health research tasks like translation and rephrasing, but express concerns about risks such as inaccurate information and ethical considerations.

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Area of Science:

  • Health Research
  • Medical Education
  • Artificial Intelligence

Background:

  • Health researchers face challenges in text translation, information interpretation, and statistical analysis.
  • Artificial Intelligence (AI) models offer potential solutions by simplifying access to information and automating complex tasks.

Purpose of the Study:

  • To examine university students' perspectives on the impact of AI models in addressing health research challenges.
  • To assess student familiarity, usage, and perceived benefits and risks of AI in health research.

Main Methods:

  • A survey study was conducted in 2023 involving 445 students from Kerman University of Medical Sciences.
  • A researcher-developed questionnaire was used, with data analyzed using descriptive statistics and linear regression.
  • Open-ended responses were coded and analyzed using MAXQDA software.

Main Results:

  • 60% of students reported moderate to high familiarity with AI, but only 52% reported moderate to high usage.
  • AI models were rated most favorably for article translation and rephrasing (Mean=3.33).
  • Significant risks identified include AI providing false information (n=34) and failing to adhere to ethical standards (n=10).

Conclusions:

  • AI models demonstrate potential for enhancing health research efficiency and quality.
  • Further efforts are needed to mitigate identified risks and promote wider AI adoption in health research.