A comparison of patient, intervention, comparison, outcome (PICO) to a new, alternative clinical question framework for search skills, search results, and self-efficacy: a randomized controlled trial
Bibliographic record
Abstract
OBJECTIVE: In educating students in the health professions about evidence-based practice, instructors and librarians typically use the patient, intervention, comparison, outcome (PICO) framework for asking clinical questions. A recent study proposed an alternative framework for the rehabilitation professions. The present study investigated the effectiveness of teaching the alternative framework in an educational setting. METHODS: A randomized controlled trial was conducted with students in occupational therapy (OT) and physical therapy (PT) to determine if the alternative framework for asking clinical questions was effective for identifying information needs and searching the literature. Participants were randomly allocated to a control or experimental group to receive ninety minutes of information literacy instruction from a librarian about formulating clinical questions and searching the literature using MEDLINE. The control group received instruction that included the PICO question framework, and the experimental group received instruction that included the alternative framework. RESULTS: There were no significant differences in search performance or search skills (strategy and clinical question formulation) between the two groups. Both the control and experimental groups demonstrated a modest but significant increase in information literacy self-efficacy after the instruction; however, there was no difference between the two groups. CONCLUSION: When taught in an information literacy session, the new, alternative framework is as effective as PICO when assessing OT and PT students' searching skills. Librarian-led workshops using either question formulation framework led to an increase in information literacy self-efficacy post-instruction.
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 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".