PREPARING FOR CBME: HOW OFTEN ARE FACULTY OBSERVING RESIDENTS?
Bibliographic record
Abstract
Abstract BACKGROUND Transitioning to competency-based medical education (CBME) necessitates change in resident assessment. A greater frequency of resident observation will be required to adequately assess whether entrustable professional activities have been achieved. OBJECTIVES Characterize faculty and resident experiences of direct observation in a single Canadian Paediatric Residency program, pre-CBME implementation. Describe faculty and residents’ perceived barriers and incentives to participating in direct observation. DESIGN/METHODS Surveys were sent to faculty and residents asking for demographic information, the frequency of resident observation during an average 4-week rotation in several domains (taking a history, performing a physical examination, delivering a plan,...), perceived ideal frequency of observation, and factors influencing observation frequency. Descriptive data was analyzed. Institutional research ethics board approval was received. RESULTS The response rate was 54% (34/68 faculty and 16/25 residents). When asked the MAXIMUM frequency faculty observed a resident take a history, perform a physical examination, or deliver a plan, the median FACULTY reply was 1, 2, and 3, for outpatient settings and 0, 1, and 2, for inpatient settings, respectively. The median RESIDENT reply was 2, 4, and 10 for outpatient settings and 1, 2, and 20 for inpatient settings, respectively. When asked the MINIMUM frequency for each domain, the median FACULTY AND RESIDENT reply was 0, except for delivering a plan in the inpatient setting (median RESIDENT reply was 2). FACULTY and RESIDENT median replies for how frequently residents should ideally be observed for each domain were the same, 3–4, 3–4, and 5–6 times. 4% of faculty reported regularly scheduling observations, and 77% of residents regularly ask to be observed. The most common responses to barriers to observation were too many patients to see and that both faculty and residents were seeing patients at the same time. Most faculty and resident responders felt that observation frequency could be improved if they were scheduled at the start of the rotation, if faculty were provided a better tool for assessment, and if residents asked to be observed. CONCLUSION This study provides baseline data on how infrequent faculty observation of residents is occurring and at a frequency lower than what faculty and residents feel is necessary. The time needed for observation is felt to compete with clinical service demands, but better scheduling strategies and assessment tools may help increase the frequency of resident observation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".