A characterization of clinical questions asked by rehabilitation therapists
Bibliographic record
Abstract
OBJECTIVE: This study explored the information needs of rehabilitation therapists (occupational therapists, physical therapists, and speech-language pathologists) working with patients who have had strokes in order to characterize their clinical questions, defined as their formalized information needs arising in the context of everyday clinical practice. METHODS: The researchers took a constructivist, interpretive approach, in which fifteen rehabilitation therapists working in various settings were recruited. Data were gathered using diaries, followed by diary-guided interviews, and thematically analyzed using template analysis. RESULTS: Rehabilitation therapists' clinical questions were characterized as having one or more of twelve foci and containing one or more of eight possible structural elements. CONCLUSIONS: Findings demonstrate that the evidence-based practice framework currently applied for questions relating to rehabilitation is inadequate for representing rehabilitation therapists' clinical questions. A new framework that is more comprehensive and descriptive is proposed. IMPLICATIONS: Librarians working with students and clinicians in rehabilitation can employ knowledge of the twelve foci and the question structure for rehabilitation to guide the reference interview. Instruction on question formulation in evidence-based practice can employ the revised structure for rehabilitation, offering students and clinicians an alternative to the traditional patient, intervention, comparison, outcome (PICO) structure. Information products, including bibliographic databases and synopsis services, can tailor their interfaces according to question foci and prompt users to enter search terms corresponding to any of the eight possible elements found in rehabilitation therapists' clinical questions.
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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 | 0.019 | 0.109 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".