Optimising management of low back pain through the pain and disability drivers management model: Findings from a pilot cluster nonrandomised controlled trial
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Low back pain (LBP) remains the leading cause of disability. The Low Back Pain and Disability Drivers Management (PDDM) model aims to identify the domains driving pain and disability to guide clinical decisions. The objectives of this study were to determine the feasibility of conducting a pragmatic controlled trial of the PDDM model and to explore its effectiveness compared to clinical practice guidelines' recommendations for LBP management. METHODS: A pilot cluster nonrandomised controlled trial. Participants included physiotherapists and their patients aged 18 years or older presenting with a primary complaint of LBP. Primary outcomes were the feasibility of the trial design. Secondary exploratory analyses were conducted on LBP-related outcomes such as pain severity and interference at 12-week follow-up. RESULTS: Feasibility of study procedures were confirmed, recruitment exceeded our target number of participants, and the eligibility criteria were deemed suitable. Lost to follow-up at 12 weeks was higher than expected (43.0%) and physiotherapists' compliance rates to the study protocol was lower than our predefined threshold (75.0% vs. 57.5%). A total of 44 physiotherapists and 91 patients were recruited. Recommendations for a larger scale trial were formulated. The PDDM model group demonstrated slightly better improvements in all clinical outcome measures compared to the control group at 12 weeks. CONCLUSION: The findings support the feasibility of conducting such trial contingent upon a few recommendations to foster proper future planning to determine the effectiveness of the PDDM model. Our results provide preliminary evidence of the PDDM model effectiveness to optimise LBP management. CLINICAL TRIAL REGISTRATION: Clinicaltrial.gov, NCT04893369.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it