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Advancing Motivational Interviewing Training with Artificial Intelligence: ReadMI.

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Real-time Assessment of Dialogue in Motivational Interviewing (ReadMI) provides immediate feedback on physician communication. This tool helps improve motivational interviewing (MI) training by offering objective metrics, reducing reliance on lengthy reviews.

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Area of Science:

  • Medical Education
  • Behavioral Science
  • Natural Language Processing

Background:

  • Motivational interviewing (MI) is effective for behavior change but underutilized due to training gaps.
  • Effective feedback is crucial for improving MI skills in clinical practice.
  • A novel tool, Real-time Assessment of Dialogue in Motivational Interviewing (ReadMI), was developed to address these training needs.

Purpose of the Study:

  • To evaluate the Real-time Assessment of Dialogue in Motivational Interviewing (ReadMI) tool.
  • To examine the relationship between physician speaking time and MI-consistent behaviors.
  • To assess the accuracy of ReadMI's automated analysis.

Main Methods:

  • Analysis of 48 simulated patient interviews using the ReadMI tool.
  • Examination of correlations between physician speaking time and MI metrics (e.g., open-ended questions).
  • Interrater reliability testing to validate ReadMI's analysis accuracy.

Main Results:

  • Increased physician speaking time correlated with decreased MI-consistent behaviors (r = -0.403, p = 0.007).
  • This included fewer open-ended questions, reflective statements, and change ruler uses.
  • ReadMI demonstrated accurate analysis of physician responses.

Conclusions:

  • ReadMI provides objective, immediate metrics for MI training feedback.
  • The tool can enhance skill development for students, residents, and clinicians.
  • ReadMI offers an efficient alternative to subjective feedback and time-consuming video reviews.