Efficacy of cognitive functional therapy for pain intensity and disability in patients with non-specific chronic low back pain: a randomised sham-controlled trial
Bibliographic record
Abstract
OBJECTIVE: This study investigated the efficacy of cognitive functional therapy (CFT) versus a sham procedure for pain intensity and disability for patients with non-specific chronic low back pain (CLBP). METHODS: This is a randomised sham-controlled trial conducted in a primary care public health service. A total of 152 participants were randomly assigned to the CFT group (n=76) and the sham group (n=76). The CFT group received six 1 hour individualised sessions; the sham procedure group received six individual sessions of neutral talking+detuned photobiomodulation (low-level laser therapy) equipment. Both groups received an education booklet with information on strategies for CLBP self-management. Primary outcomes were pain intensity and disability at 6 weeks. Participants were assessed preintervention, postintervention (at 6 weeks), and 3 and 6 months after randomisation. RESULTS: We obtained primary outcome data from 97.4% (n=74) of participants in the CFT group and 98.7% (n=75) from the sham group. The CFT group showed greater effects in pain intensity (mean difference (MD)=-1.8; 95% CI -2.5 to -1.1) and disability (MD=-9.9; 95% CI -13.2 to -6.5) postintervention compared with the sham group. The effect remained at the 3-month and 6-month follow-ups. CONCLUSIONS: CFT showed sustained clinical efficacy compared with a sham procedure for treating pain intensity and disability in patients with CLBP. TRIAL REGISTRATION NUMBER: This trial was registered in ClinicalTrials.gov, NCT04518891 and was previously published https://pubmed.ncbi.nlm.nih.gov/35788240/.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".