Providing quality feedback to general internal medicine residents in a competency-based assessment environment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Construct: Competence Based Medical Education (CBME) is designed to use workplace-based assessment (WBA) tools to provide observed assessment and feedback on resident competence. Moreover, WBAs are expected to provide evidence beyond that of more traditional mid- or end-of-rotation assessments [e.g., In Training Evaluation Records (ITERs)]. In this study we investigate competence in General Internal Medicine (GIM), by contrasting WBA and ITER assessment tools.Background: WBAs are hypothesized to improve and differentiate written and numerical feedback to support the development and documentation of competence. In this study we investigate residents’ and faculty members’ perceptions of WBA validity, usability, and reliability and the extent to which WBAs differentiate residents’ performance when compared to ITERs. Approach: We used a mixed methods approach over a three-year period, including perspectives gathered from focus groups, interviews, along with numerical and narrative comparisons between WBA and ITERs in one GIM program.Results: Residents indicated that the narrative component of feedback was more constructive and effective than numerical scores. They perceived the focus on specific workplace-based feedback was more effective than ITERs. However, quantitative analysis showed that overall rates of actionable feedback, including both ITERs and WBAs, were low (26%), with only 9% providing an improvement strategy. The provision of quality feedback was not statistically significantly different between tools; although WBAs provided more actionable feedback, ITERs provided more strategies. Statistical analyses showed that more than half of all assessments came from 11 core faculty.Conclusions: Participants in this study viewed narrative, actionable and specific feedback as essential, and an overall preference was found for written feedback over numerical assessments. However, quantitative analyses showed that specific actionable feedback was rarely documented, despite qualitative emphasis from both groups of its importance for developing competency. Neither formative WBAs or summative ITERs clearly provided better feedback, and both may still have a role in overall resident evaluation. Participant views differed in roles and responsibilities, with residents stating that faculty should be responsible for initiating assessments and vice-versa. These results reveal a disconnect between resident and faculty perceptions and practice around giving feedback and emphasize opportunities for programs adopting and implementing CBME to address how best to support residents and frontline clinical teachers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.009 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.048 | 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 it