Assessing Digital and AI-Readiness in Medical Education: A Delphi-Based Development of a Digital Health Competency Questionnaire

  1. Marciana Nona Duma
  2. Stefan Knippen
  3. Britta Wulfhorst
  4. Inka Susanne Eisfeld
  5. Christian Gerhard Erker
  6. Catharina Escales
  7. Anna Lena Fischer
  8. Maren Kuhne
  9. Holger Joswig
  10. Luca Kollar
  11. Jens Peters
  12. Rainer Petzina
  13. Susann Schweitzer
  14. Melanie Isabelle Stefan
  15. Kristina Wardelmann
  16. Franziska Baessler
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Abstract

Background With digital health and artificial intelligence (AI) increasingly shaping medical practice, assessing medical students’ digital competencies, attitudes, and educational needs is essential for designing future-oriented medical curricula. This study aimed to develop and refine a comprehensive, evidence-based questionnaire to assess digital literacy and AI-related competencies among medical students, ensuring alignment with educational needs and healthcare trends. Methods A multi-round Delphi process involving medical educators and senior medical students was conducted to evaluate and revise an initial 26-item questionnaire. Panelists assessed each item’s relevance, clarity, and completeness. Revisions were guided by panel feedback and supported by targeted literature searches in PubMed. Only evidence-based changes were accepted. The final instrument contains 25 questions organized into four thematic sections: (1) Demographics and Background, (2) Proficiency in Technical Tools and Software, (3) Attitudes Toward Technology in Medical Practice, and (4) Expectations for Medical Education and Support. Results Twelve experts participated in the Delphi panel, including ten medical educators and two medical students. After two consensus rounds, the final questionnaire retained 25 items with an average agreement rate of 96%. Items were refined between rounds to improve clarity and align with contemporary digital health practices. Notably, attitude statements were structured to reflect the CanMEDS physician roles. The questionnaire captures students’ familiarity with digital and AI tools, usage frequency, device ownership, and educational expectations. Conclusions The resulting questionnaire offers a literature based, structured instrument for assessing digital literacy and AI readiness among medical students. It responds to gaps in existing tools and provides a foundation for curricular development, institutional benchmarking, and further research.

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  1. Version published to 10.21203/rs.3.rs-9150280/v1 on Research Square