Brief action planning to facilitate the management of acute low back pain with radiculopathy and yellow flags: a case report.
Bibliographic record
Abstract
INTRODUCTION: Brief action planning (BAP) is a collaborative tool to support patients' self-management goal setting and action planning. BAP facilitates patient self-reflection, and provides opportunity to establish goals of their own priority. CASE PRESENTATION: A 55 year-old female with recentonset low back pain with L5 nerve root distribution, described severe pain in the low back and sharp pain and tingle-sensations down to her right foot. Pain worsened with sitting, coughing, and bending. She was diagnosed with lumbar and other intervertebral disc disorder with radiculopathy (ICD 10: M51.1). TREATMENT: Initial treatment included reassurance, education, promotion of movement, and manual therapies. Symptoms worsened at the eighth visit (five weeks) where she also demonstrated pain-catastrophizing behaviours and an over-reliance on passive treatment strategies (i.e., psychosocial factors or yellow flags). BAP was introduced into her treatment plan to set achievable goals for her care. OUTCOME: Decreased pain and disability were reported after incorporating BAP into care. Reduced pain-catastrophizing and reduced over-dependence on passive strategies were also demonstrated. Clinical gains were sustained at the 10-week follow-up assessment. KEY CLINICAL MESSAGE: We describe the utilization of brief action planning as a technique for improving adherence to evidence-based clinical practice guideline recommendations in a patient with acute low back pain and radiculopathy, and late-onset psychosocial factors.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".