Preparing entry-level practitioners for evidence-based practice
Bibliographic record
Abstract
The authors report on a collaborative instructional method used to prepare entry-level practitioners with strategies for systematically employing an evidence-based practice process as an approach to clinical inquiry, while acknowledging the students' shortage of clinical experience and knowledge of critical appraisal. Challenges to evidence-based practice can be categorized as difficulties in obtaining evidence, analyzing evidence, and transferring evidence into practice decisions. For student occupational therapists, additional challenges are encountered as they seek to fill gaps in their knowledge about client-centred occupational therapy (OT) practice, acquire necessary background information regarding clinical conditions, and formulate a clinical question. Students need to develop literature search skills and learn effective strategies to locate appropriate information to answer the clinical question. This paper will encourage OT faculty to begin a dialogue with librarian colleagues at their institution to develop an evidence-based approach to the teaching of both the clinical inquiry and the literature search process.
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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 | 0.096 | 0.238 |
| Meta-epidemiology (narrow) | 0.001 | 0.003 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.016 | 0.010 |
| Open science | 0.005 | 0.017 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.015 | 0.008 |
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".