Does Every Patient Require Imaging after Cervical Spine Trauma? A Knowledge Translation Project to Support Evidence-Informed Practice for Physiotherapists
Bibliographic record
Abstract
Purpose: This article evaluates, describes, and addresses a gap in British Columbia physiotherapists' knowledge of the decision making required for the diagnostic imaging of patients after traumatic neck injury. Method: An online survey of orthopaedic physiotherapists in British Columbia was undertaken to explore their awareness of, knowledge of, and attitudes toward the Canadian Cervical Spine Rule (C-Spine Rule) and decision making regarding the need for diagnostic imaging in managing patients with traumatic neck injury. The survey included questions about managing clinical scenarios; respondents' awareness, knowledge, and use of a specific clinical decision rule—the C-Spine Rule—and any perceived barriers to using clinical practice guidelines in general and the C-Spine Rule in specific. The survey also included questions about the facilitators of and barriers to using the C-Spine Rule. These data were used to guide development of a tool kit to facilitate use of the rule. Results: Of 889 physiotherapists, 467 (52.5%) completed the survey. Given a scenario in which imaging was indicated according to the C-Spine Rule, 95.2% of the respondents correctly recommended imaging. However, in a scenario in which imaging was not indicated, 42.7% incorrectly recommended it. The barriers to using the guidelines included their perceived rigidity, role limitation, and reliance on clinical judgment. The results indicated a need for, and guided development of, resources to facilitate the use of the C-Spine Rule by British Columbia physiotherapists. Conclusions: We identified a gap in the knowledge of British Columbia physiotherapists in identifying which patients were most likely to require imaging after sustaining a traumatic neck injury. We developed a tool kit to address these barriers. British Columbia physiotherapists have accessed this resource extensively. Evaluating its impact on clinical practice, although desirable, was not feasible.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".