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Published on: June 1, 2015
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Clinical reasoning performance assessment: using situated cognition theory as a conceptual framework.
Joseph Rencic1, Lambert W T Schuwirth2, Larry D Gruppen3
1Department of Medicine, Boston University School of Medicine, 72 E. Concord Street, Boston, MA 02118, USA.
Diagnosis (Berlin, Germany)
|February 8, 2020
Summary
Assessing clinical reasoning requires understanding how context influences performance. A new model shows interactions between clinicians and situational factors are key for valid assessment.
Area of Science:
- Medical Education
- Cognitive Science
- Assessment Science
Background:
- Assessing clinical reasoning performance presents significant challenges.
- Situated cognition theory offers a framework for understanding cognition within context.
- Understanding the interplay between clinicians and situational factors is crucial for effective assessment.
Purpose of the Study:
- To apply situated cognition theory to develop a conceptual model for assessing clinical reasoning.
- To elucidate the impact of contextual factors on clinical reasoning performance assessment outcomes.
Main Methods:
- Development of a conceptual model based on situated cognition theory.
- Identification and analysis of six key contextual factors: assessee, patient, rater, environment, assessment method, and task.
- Exploration of the interactions between these factors and their influence on assessment outcomes.
Main Results:
- The conceptual model highlights the complex interactions between contextual factors influencing clinical reasoning assessment.
- Six contextual factors identified: assessee, patient, rater, environment, assessment method, and task.
- Interactions among these factors significantly impact clinical reasoning performance assessment outcomes.
Conclusions:
- Valid clinical reasoning assessment necessitates broad sampling of learners by expert raters in diverse contexts.
- Explicit definition and exploration of contextual factors are essential for accurate assessment.
- Non-linear statistical models may be required to capture complex interactions in clinical reasoning assessment.
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