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Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties
Published on: September 27, 2020
Enabling positive practice improvement through data-driven feedback: A model for understanding how data and
Rana Kamhawy1, Teresa M Chan2, Shawn Mondoux2
1Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada.
Purpose:
This article aims to identify the factors that affect physicians' experiences of receiving practice data and to use these data to develop a model describing how individuals interact with the data.
Methods:
We designed an interview guide to study physicians' perspectives on audit and feedback. By intentional sampling, we recruited 15 physicians amongst gender groups, types of practice (academic vs community), and durations of practice. The interviews were conducted by a single author and transcribed without identifiers. We then began with an open coding analysis for all of the transcripts, and thereafter conducted axial coding to group the data into larger themes.
Results:
Several attributes were identified as either enabling or counterproductive attributes for participant improvement. The final proposed model identifies different zones of engagement on the basis of both the individual practitioner's growth mindset and the quality of the existing data system. In the highest engagement zone, the mindset of the collective leadership is one of growth. Systemic supports are in place, which potentiates learning that may come from an individual motivated to use their own data.
Conclusion:
Our novel model depicts the relationship between data feedback systems and individuals' mindsets interact to augment or hinder clinical practice improvement. This model may provide leaders with a framework to examine their academic and administrative structures and how they might interface with performance feedback systems with clinicians.
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