Advancing Motivational Interviewing Training with Artificial Intelligence: ReadMI

Adv Med Educ Pract. 2021 Jun 4;12:613-618. doi: 10.2147/AMEP.S312373. eCollection 2021.


Background: Motivational interviewing (MI) is an evidence-based, brief interventional approach that has been demonstrated to be highly effective in triggering change in high-risk lifestyle behaviors. MI tends to be underutilized in clinical settings, in part because of limited and ineffective training. To implement MI more widely, there is a critical need to improve the MI training process in a manner that can provide prompt and efficient feedback. Our team has developed and tested a training tool, Real-time Assessment of Dialogue in Motivational Interviewing (ReadMI), that uses natural language processing (NLP) to provide immediate MI metrics and thereby address the need for more effective MI training.

Methods: Metrics produced by the ReadMI tool from transcripts of 48 interviews conducted by medical residents with a simulated patient were examined to identify relationships between physician-speaking time and other MI metrics, including the number of open- and closed-ended questions. In addition, interrater reliability statistics were conducted to determine the accuracy of the ReadMI's analysis of physician responses.

Results: The more time the physician spent talking, the less likely the physician was engaging in MI-consistent interview behaviors (r = -0.403, p = 0.007), including open-ended questions, reflective statements, or use of a change ruler.

Conclusion: ReadMI produces specific metrics that a trainer can share with a student, resident, or clinician for immediate feedback. Given the time constraints on targeted skill development in health professions training, ReadMI decreases the need to rely on subjective feedback and/or more time-consuming video review to illustrate important teaching points.

Keywords: medical education; patient engagement; software development.

Grant support

This project was supported by grant number R21HS026548 from the Agency for Healthcare Research and Quality. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality.