A comparative analysis of chiropractic and general practitioner patients in North America: Findings from the joint Canada/United States survey of health, 2002–03
Bibliographic record
Abstract
BACKGROUND: Scientifically rigorous general population-based studies comparing chiropractic with primary-care medical patients within and between countries have not been published. The objective of this study is to compare care seekers of doctors of chiropractic (DCs) and general practitioners (GPs) in the United States and Canada on a comprehensive set of sociodemographic, quality of life, and health-related variables. METHODS: Data are from the Joint Canada/U.S. Survey of Health (JCUSH), 2002-03, a random sample of adults in Canada (N = 3505) and the U.S. (N = 5183). Respondents were categorized according to their pattern of health-care use in the past year. Distributions, percentages, and estimates (adjusted odds ratios) weighted to reflect the complex survey design were produced. RESULTS: Nearly 80% of respondents sought care from GPs; 12% sought DC care. Compared with GP only patients, DC patients in both countries tend to be under 65 and white, with arthritis and disabling back or neck pain. U.S. DC patients are more likely than GP only patients to be obese and to lack a regular doctor; Canadian DC patients are more likely than GP only patients to be college educated, to have higher incomes, and dissatisfied with MD care. Compared with seekers of both GP and DC care, DC only patients in both countries have fewer chronic conditions, take fewer drugs, and have no regular doctor. U.S. DC only patients are more likely than GP+DC patients to be uninsured and dissatisfied with health care; Canadian DC only patients are more likely than GP+DC patients to be under 45, male, less educated, smokers, and not obese, without disabling back or neck pain, on fewer drugs, and lacking a regular doctor. CONCLUSION: Chiropractic and GP patients are dissimilar in both Canada and the U.S., with key differences between countries and between DC patients who do and do not seek care from GPs. Such variation has broad and potentially far-reaching health policy and research implications.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".