A systematic review of chiropractic management of adults with whiplash-associated disorders: Recommendations for advancing evidence-based practice and research
Bibliographic record
Abstract
UNLABELLED: The literature relevant to the treatment of Whiplash-Associated Disorders (WAD) is extensive and heterogeneous. METHODS: A Participatory Action Research (PAR) approach was used to engage a chiropractic community of practice and stakeholders in a systematic review to address a general question: 'Does chiropractic management of WAD clients have an effect on improving health status?' A systematic review of the empirical studies relevant to WAD interventions was conducted followed by a review of the evidence. RESULTS: The initial search identified 1,155 articles. Ninety-two of the articles were retrieved, and 27 articles consistent with specific criteria of WAD intervention were analyzed in-depth. The best evidence supporting the chiropractic management of clients with WAD is reported. Further review identified ways to overcome gaps needed to inform clinical practice and culminated in the development of a proposed care model: the WAD-Plus Model. CONCLUSIONS: There is a baseline of evidence that suggests chiropractic care improves cervical range of motion (cROM) and pain in the management of WAD. However, the level of this evidence relevant to clinical practice remains low or draws on clinical consensus at this time. The WAD-Plus Model has implications for use by chiropractors and interdisciplinary professionals in the assessment and management of acute, subacute and chronic pain due to WAD. Furthermore, the WAD-Plus Model can be used in the future study of interventions and outcomes to advance evidence-based care in the management of WAD.
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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 | 0.084 | 0.230 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.012 |
| Bibliometrics | 0.026 | 0.021 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".