The relative effectiveness of proprioceptive exercises as an adjunct to cervical spine manipulation in the treatment of chronic cervical spine pain and disability associated with whiplash injury
Bibliographic record
Abstract
Whiplash injuries are thought to occur in as many as one-fifth of all MVA’s in the United States and Canada. South Africa may have a higher incidence of whiplash injuries due to the exceptionally high road accident rate when compared with international norms (Burger 1996:478). The incidence rate is higher among female subjects and people aged 20-24 years (Teasell and Shapiro 1998: 72, Spitzer et al. 1995). Whiplash injuries or whiplash-associated disorders (WAD) often result in chronic pain with a poor response to conventional therapeutics. Manipulation, exercise and anti-inflammatories have been identified as the options with scientifically established validity in the management of WAD (Spitzer et al. 1995) Patients with WAD have a distortion of the posture control system as a result of disorganised neck proprioceptive activity. It would therefore appear that proprioceptive rehabilitative exercises would benefit WAD sufferers (Revel et al. 1994, Gimse et al. 1996). Spinal manipulation has also been shown to have a significant effect on proprioceptive-dependent abilities in subjects with chronic neck pain (Rogers 1997). This suggests that a combination of manipulation and proprioceptive rehabilitation may offer an improved treatment protocol for WAD (Fitz-Ritson 1995). The purpose of this investigation is to evaluate the relative effectiveness of proprioceptive exercises and cervical spine manipulation compared to manipulation alone, in terms of subjective and objective measures, in the treatment of whiplash-associated disorders.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".