Resident and attending perceptions of direct observation in internal medicine: a qualitative study
Bibliographic record
Abstract
OBJECTIVES: Direct observation is the foundation of assessment and learning in competency-based medical education (CBME). Despite its importance, there is significant uncertainty about how to effectively implement frequent and high-quality direct observation. This is particularly true in specialties where observation of non-procedural skills is highly valued and presents unique challenges. It is therefore important to understand perceptions of direct observation to ensure successful acceptance and implementation. In this study, we explored perceptions of direct observation in internal medicine. METHODS: We interviewed internal medicine attending physicians (n = 9) and residents (n = 8) at the University of Toronto, purposively sampled for diversity. Using a constructivist grounded theory approach, constant comparative analysis was performed to develop a framework to understand perceptions of direct observation on the clinical teaching units. RESULTS: Participants articulated a narrow perception of what constitutes direct observation, in contrast to their own descriptions of skills that were observed. This resulted in the perception that certain valuable skills that participants felt were routinely observed were nonetheless not 'directly observable', such as clinical reasoning, observed through case presentations and patient care discussions. Differentiating direct observation from informal observation led to overestimation of the time and resource requirements needed to enhance direct observation, which contributed to scepticism and lack of engagement related to CBME implementation. CONCLUSIONS: In an internal medicine training programme, perceptions of what constitutes direct observation can lead to under-recognition and hinder acceptance in workplace-based assessment and learning. Our results suggest a reframing of 'direct observation' for residents and attending physicians, by explicitly identifying desired skills in non-procedurally-based specialties. These findings may help CBME-based training programmes improve the process of direct observation, leading to enhanced assessment and learning.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".