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The McMaster Narrative Comment Rating Tool: Development and Initial Validity Evidence.

Natalie McGuire1, Anita Acai2, Ranil R Sonnadara3

  • 1Office of Professional Development and Educational Scholarship, Queen's University, Kingston, Ontario, Canada.

Teaching and Learning in Medicine
|November 15, 2023
PubMed
Summary

The McMaster Narrative Comment Rating Tool reliably assesses written feedback quality in medical education. This tool is useful for faculty development and research, including automated feedback analysis.

Keywords:
Assessmentnarrative commentspostgraduate medical educationqualitywritten feedback

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Area of Science:

  • Medical Education Research
  • Assessment and Feedback Quality
  • Competency-Based Medical Education

Background:

  • Narrative comments are crucial for competency-based medical education but vary in quality.
  • Existing tools for assessing feedback quality are often context-specific or exclude learner perspectives.
  • There is a need for a comprehensive, broadly applicable tool to measure narrative comment quality.

Purpose of the Study:

  • To develop and validate the McMaster Narrative Comment Rating Tool (MNCRT) for assessing the quality of written feedback in medical education.
  • To identify critical features of high-quality narrative comments.
  • To create a tool usable by diverse raters for research and faculty development.

Main Methods:

  • Literature review to identify five key feedback features.
  • Development of rating scales for each feature.
  • Validation through multi-rater reliability testing involving researchers, students, residents, faculty, and laypersons.

Main Results:

  • The McMaster Narrative Comment Rating Tool demonstrated moderate to excellent reliability across various rater groups (ICCs = .51-.83 and .91-.98).
  • Most tool domains were significantly correlated, indicating internal consistency.
  • Valence was the only domain not significantly correlated with all others.

Conclusions:

  • The McMaster Narrative Comment Rating Tool is a reliable instrument for assessing narrative comment quality across different surgical contexts and rater types.
  • The tool can support faculty development programs focused on assessment and feedback.
  • It offers potential for research applications, including automated analysis of feedback quality.