Achieving competency in wound care: an innovative training module using the long‐term care setting
Bibliographic record
Abstract
Structured academic teaching on wound care was developed, based on the long-term care (LTC) setting, with the goal of ensuring that postgraduate family medicine residents attain competency in assessment and treatment of wounds and pressure ulcers (PUs). The curriculum for the 1-month learning module was based on clinical practice guidelines for the prevention, assessment, and treatment of PUs and wounds. The learning techniques used include a learners' needs assessment, a small-group didactic session, interdisciplinary bedside case discussions and a toolkit. The curriculum is delivered in four weekly, 90-minute interdisciplinary teaching sessions during the mandatory 1-month geriatrics rotation for postgraduate family medicine trainees. Competency is evaluated by the end of the module by reviewing trainees' documentation of a thorough objective clinical wound assessment, diagnosis of underlying cause, significant contributing risk factors and proposed treatment plan. This approach can be used to train family medicine, hospitalist, and geriatric residents in other acute or LTC teaching facilities where there is a prevalence of PUs.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".