Trends and Predictors of Publicly Subsidized Chiropractic Service Use Among Adults Age 50+
Bibliographic record
Abstract
OBJECTIVES: This article examines trends in and predictors of publicly subsidized chiropractic use from 1991 to 2000, a decade characterized by health care system reforms throughout North America. SAMPLE: The sample included adults age 50+ who visited a publicly subsidized chiropractor in the Canadian province of British Columbia during the study period. DESIGN: Administrative claims data for chiropractic service use were drawn from the Medical Services Plan (MSP) Master file in the British Columbia Linked Health Data resource. The MSP Master file contains claims reported for every provincially insured medical service and supplementary health benefit including chiropractic visits. RESULTS: Joinpoint regression analyses demonstrate that while annual rates of chiropractic users did not change over the decade, visit rates decreased during this period. Predictors of a greater number of chiropractic visits include increasing age, female gender, urban residence, low to moderate income, and use of chiropractic services earlier in the decade. CONCLUSIONS: The trend toward decreasing visit rates over the 1990s both conflicts with and is consistent with findings from other North American chiropractic studies using similar time periods. Results indicating that low and moderate income and advancing age predict more frequent chiropractic service are novel. However, given that lower income and older individuals were exempted from chiropractic service limits during this period, these results suggest support for the responsive nature of chiropractic use to financial barriers.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".