Chiropractic Care of Musculoskeletal Disorders in a Unique Population Within Canadian Community Health Centers
Bibliographic record
Abstract
OBJECTIVE: This study was part of a larger demonstration project integrating chiropractic care into publicly funded Canadian community health centers. This pre/post study investigated the effectiveness of chiropractic care in reducing pain and disability as well as improving general health status in a unique population of urban, low-income, and multiethnic patients with musculoskeletal (MSK) complaints. METHODS: All patients who presented to one of two community health center-based chiropractic clinics with MSK complaints between August 2004 and December 2005 were recruited to participate in this study. Outcomes were assessed by a general health measure (Short Form-12), a pain scale (VAS), and site-specific disability indexes (Roland-Morris Questionnaire and Neck Disability Index), which were administered before and after a 12-week treatment period. RESULTS: Three hundred twenty-four patients with MSK conditions were recruited into the study, and 259 (80.0%) of them were followed to the study's conclusion. Clinically important and statistically significant positive changes were observed for all outcomes (Short Form-12: physical composite score mean change = 4.9, 95% confidence interval [CI] = 3.8-6.0; VAS: current pain mean change = 2.3, 95% CI = 1.9-2.6; Neck Disability Index: mean change = 6.8, 95% CI = 5.4-8.1; Roland-Morris Questionnaire: mean change = 4.3, 95% CI = 3.6-5.1). No adverse events were reported. CONCLUSIONS: Patients of low socioeconomic status face barriers to accessing chiropractic services. This study suggests that chiropractic care reduces pain and disability as well as improves general health status in patients with MSK conditions. Further studies using a more robust methodology are needed to investigate the efficacy and cost-effectiveness of introducing chiropractic care into publicly funded health care facilities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".