A pilot study of low-power laser therapy in the management of chronic neck pain
Bibliographic record
Abstract
This pilot study was undertaken to test techniques of application of laser, appropriate outcome measures, and determine effect sizes in order to facilitate the performance of a larger, clinical trial of laser therapy in chronic neck pain. Methods. We conducted a randomised double blind, placebo controlled study of low level laser therapy in 20 patients with chronic neck pain. The primary outcome measure was change in a 10 cm Visual Analogue Scale (VAS) for pain. Other measures used included a Self-Reported Improvement in pain (SRI), measured by a VAS, Short-Form 36 Quality-of-Life questionnaire (SF-36), Northwick Park Neck Pain Questionnaire (NPNPQ) and the McGill Pain Questionnaire (MPQ). Measurements were taken at baseline, at the end of seven weeks treatment and at 12 weeks from baseline. Results. We found a positive, pain relieving effect in the treated group compared with those given placebo using the VAS (P<0.039), SRI (P<0.001), NPNPQ (P<0.002), and the MPQ (P<0.009). The results of the SF-36 did not differ significantly between the two groups. Patients in the treated group experienced an average pain score improvement of 66.7%, compared with 16.6% in the placebo group. Conclusion. Low-Level Laser Therapy (LLLT), at the parameters used in this pilot study, may provide a non-invasive, non-pharmaceutical therapy for chronic neck pain for patients in general practice. Further study of this technique in a large scale trial would be justified on the basis of the findings of this pilot study. (author abstract)
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".