Association of Chiropractic Care With Receiving an Opioid Prescription for Noncancer Spinal Pain Within a Canadian Community Health Center: A Mixed Methods Analysis
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to examine the association between receipt of chiropractic services and initiating a prescription for opioids among adult patients with noncancer spinal pain in a Canadian community health center. METHODS: In this sequential explanatory mixed methods analysis, we conducted a retrospective study of 945 patient records (January 2014 to December 2020) and completed interviews with 14 patients and 9 general practitioners. We used Cox proportional hazards regression analyses, adjusted for patient demographics, comorbidities, visit frequency, and calendar year to evaluate the association between receipt of chiropractic care and time to first opioid prescription up to 1 year after presentation. Qualitative data were analyzed thematically and integrated with our quantitative findings. RESULTS: There were 24% of patients (227 of 945) with noncancer spinal pain who received a prescription for opioids. The risk of initiating a prescription for opioids at 1 year after presentation was 52% lower in chiropractic recipients vs nonrecipients (hazard ratio [HR], 0.48; 99% confidence interval [CI], 0.29-0.77) and 71% lower in patients who received chiropractic services within 30 days of their index visit (HR, 0.29; 99% CI, 0.13-0.68). Patients whose index visit date was in a more recent calendar year were also less likely to receive opioids (HR, 0.86; 99% CI, 0.76-0.97). Interviews suggested that self-efficacy, access to chiropractic services, opioid stigma, and treatment impact were influencing factors. CONCLUSION: Patients with noncancer spinal pain who received chiropractic care were less likely to obtain a prescription for opioids than patients who did not receive chiropractic care.
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".