Guidelines on Low Back Pain Disability
Bibliographic record
Abstract
STUDY DESIGN: Individual semistructured qualitative interviews. OBJECTIVE: To evaluate barriers to use of management recommendations, aimed at preventing low back pain (LBP) disability, with general practitioners (GPs), occupational therapists (OTs), and physiotherapists (PTs) working in Quebec (Canada), and identify areas of convergence and divergence between health professions. SUMMARY OF BACKGROUND DATA: Studies have demonstrated inadequacies of practices of clinicians with regard to LBP management and prevention of persistent disability. Barriers to use of evidence by clinicians should be evaluated to understand these inadequacies and develop implementation strategies. METHODS: Sixteen PTs, 8 OTs, and 8 GPs were recruited with different levels of experience and practice location (urban or rural). They were asked to follow management recommendations (Clinic on Low-back Pain in Interdisciplinary Practice [CLIP] guidelines), with a minimum of 2 patients. Individual semistructured interviews were used to identify barriers to use of management recommendations aimed at preventing LBP disability. Barriers between health professions were compared. RESULTS: Barriers to use were lesser for OTs and greater for GPs, with divergences among PTs. OTs agreed with the guidelines, found them compatible with their current practice, and thought that using them would prevent persistent disability. GPs and PTs thought that the guidelines did not provide enough information on the pathophysiological management of LBP. GPs thought that it would be difficult to implement the guidelines in everyday practice. All 3 groups thought that management recommendations could conflict with patient expectations. CONCLUSION: To address identified barriers, a process of care is proposed by fitting tasks to the most compatible providers. The task of GPs could focus on pain management through medication, red flag screening, encouragement to stay active, and reassurance. The tasks of PTs could center on pain management, general exercise, and encouragement to stay active. The tasks of OTs could focus on disability prognosis, yellow flags management, and return to activity parameters. The efficacy of this process of care to prevent persistent LBP disability should be assessed in a trial.
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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 | 0.020 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".