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Motivational interviewing skills practice enhanced with artificial intelligence: ReadMI.

Paul J Hershberger1, Yong Pei2, Dean A Bricker3

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Medical students improved motivational interviewing (MI) skills with AI feedback. The ReadMI tool enhanced learning by providing objective metrics, aiding skill acquisition and reducing facilitator burden.

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Area of Science:

  • Medical Education
  • Human-Computer Interaction
  • Behavioral Science

Background:

  • Integrating motivational interviewing (MI) training into medical curricula presents a significant challenge.
  • A novel software tool, ReadMI, was developed to facilitate MI skill acquisition in medical students.
  • The ReadMI tool leverages human-artificial intelligence teaming to potentially decrease facilitator cognitive load.

Purpose of the Study:

  • To evaluate the effectiveness of the ReadMI software tool in enhancing medical students' motivational interviewing skills.
  • To assess the impact of AI-driven feedback on MI skill acquisition compared to traditional facilitator feedback.

Main Methods:

  • 125 third-year medical students participated in a 90-minute MI training session during their Family Medicine clerkship.
  • Students engaged in two role-play scenarios, with the intervention group receiving both facilitator and ReadMI feedback after the first role-play.
  • The control group received only facilitator feedback after their first role-play.

Main Results:

  • Both groups demonstrated improvement in MI approach from the first to the second role-play.
  • Students receiving ReadMI feedback utilized significantly more open-ended questions.
  • The intervention group exhibited fewer closed-ended questions and a higher ratio of open-to-closed questions.

Conclusions:

  • Motivational interviewing skills can be effectively practiced with minimal student time investment.
  • Artificial intelligence serves as a valuable tool for measuring MI skill development.
  • AI can function as an effective instructional aid in medical training programs.