An Investigation of Chiropractor-Directed Weight-Loss Interventions: Secondary Analysis of O-COAST
Bibliographic record
Abstract
Objective The purpose of this study was to investigate weight-loss interventions offered by Canadian doctors of chiropractic to their adult patients. Methods This paper reports a secondary analysis of data from the Ontario Chiropractic Observation and Analysis STudy (N c = 42 chiropractors, N p = 2162 patient encounters). Multilevel logistic regression was performed to assess the odds of chiropractors initiating or continuing weight management interventions with patients. Two chiropractor variables and 8 patient-level variables were investigated for influence on chiropractor-directed weight management. In addition, the interaction between the effects of patient weight and comorbidity on weight management interventions by chiropractors was assessed. Results Around two-thirds (61.3%) of patients who sought chiropractic care were either overweight or had obesity. Very few patients had weight loss managed by their chiropractor. Among patients with body mass index equal to or greater than 18.5 kg/m 2 , guideline recommended weight management was initiated or continued by Ontario chiropractors in only 5.4% of encounters. Chiropractors did not offer weight management interventions at different rates among patients who were of normal weight, overweight, or obese ( P value=0.23). Chiropractors who graduated after 2005 who may have been exposed to reforms in chiropractic education to include public health were significantly more likely to offer weight management than chiropractors who graduated between 1995 and 2005 (odds ratio 0.02; 95% CI [0.00-0.13]) or before 1995 (odds ratio 0.08; 95% CI [0.01-0.42]). Conclusion The prevalence of weight management interventions offered to patients by Canadian chiropractors in Ontario was low. Health care policy and continued chiropractic educational reforms may provide further direction to improve weight-loss interventions offered by doctors of chiropractic to their patients.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".