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Assessing AI Awareness and Identifying Essential Competencies: Insights From Key Stakeholders in Integrating AI Into

Julia-Astrid Moldt1, Teresa Festl-Wietek1, Wolfgang Fuhl2,3

  • 1Tübingen Institute for Medical Education, University of Tübingen, Tübingen, Germany.

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Summary

Healthcare professionals need more artificial intelligence (AI) education. This study surveyed stakeholders to define essential AI competencies and curriculum changes for medical students, highlighting the need for integrated AI training.

Keywords:
qualitative analysisAI in medicineartificial intelligencemedical educationmedical studentsneeds assessmentqualitative approach

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Area of Science:

  • Medical Education
  • Artificial Intelligence in Healthcare
  • Health Informatics

Background:

  • The growing significance of artificial intelligence (AI) in healthcare necessitates enhanced AI literacy among medical professionals.
  • Current medical education frameworks require adaptation to incorporate AI technologies effectively.

Purpose of the Study:

  • To explore stakeholder perceptions and expectations of AI in medicine.
  • To assess AI awareness and experiences among diverse stakeholders.
  • To identify essential AI topics and competencies for integration into medical curricula.

Main Methods:

  • Qualitative study conducted within the TüKITZMed project (August 2022 - March 2023).
  • Semistructured interviews with 38 participants from various stakeholder groups (lecturers, clinicians, students, AI experts, institutional representatives).
  • Qualitative content analysis of interview data using MAXQDA software.

Main Results:

  • Analysis revealed commonalities and differences in stakeholder understanding of AI.
  • Six primary categories and 24 subcategories emerged, focusing on curriculum content, skills, competencies, programming, scope, and structure.
  • Key themes identified include necessary AI skills, curriculum design, and integration strategies.

Conclusions:

  • Integrating AI into medical curricula is vital for equipping students with necessary clinical application skills.
  • Standardized AI understanding is crucial for developing effective medical education content.
  • Incorporating diverse stakeholder perspectives is essential for defining AI in medicine and optimizing its use in future medical studies.