Treatment of whiplash associated disorders with real and sham electro-acupuncture
Bibliographic record
Abstract
The aims of this thesis are to critically examine an acupuncture intervention for sub-acute and chronic whiplash associated disorders (WAD) due to motor vehicle crashes and to suggest methods by which it may be made more effective and efficient. The acupuncture intervention in this thesis, termed electro-acupuncture treatment, was developed linking principles of pain management and self-reported assessment of pain intensity, disability and quality of life questionnaires. A randomised controlled clinical trial, which compared ‘real’ with ‘sham’ electroacupuncture treatment, was conducted. Participating were 124 sequentially enrolled participants between the age of 18 and 65 years who met predetermined inclusion criteria and who were randomly allocated, using a concealed randomisation procedure, to 12 treatments over at 6 weeks with ‘real’ or ‘sham’ electro-acupuncture, and were followed up among 6 weeks, 3 and 6 months after receiving the treatment. Primary outcome measures were pain intensity as assessed by a visual analogue scale (V AS), disability as assessed by the Neck Disability Index (NDI), and quality of life as assessed by the Medical Outcomes Studies short form 36 (SF 36) health status measure. Secondary outcome measures were the mean restriction in four self nominated activities of daily living (4ADL) using a visual analogue scale, and the short form McGill pain questionnaire (SF-McGill). Compared to the sham electro-acupuncture group, participants who received real electro-acupuncture treatment program had reduction in pain intensity at the 3 and 6 months time points. Improvements were also seen in other outcomes. In addition, both the real and sham acupuncture groups improved significantly compared to baseline in pain intensity and other outcome measures. Adverse events associated with acupuncture treatment were rare and non serious. Real electro-acupuncture reduced pain intensity and improved physical functioning significantly statistically, and possibly clinically, compared with sham electro-acupuncture. Given the improvement from baseline, in both the real and sham treatment groups, the beneficial effects of electro-acupuncture for reducing the level of pain intensity and other outcomes may be due to both non-specific and specific effects.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.003 | 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".