A feasibility study assessing a program of care for chiropractors managing spinal pain in Canadian Armed Forces personnel
Bibliographic record
Abstract
Introduction: Chronic back and lower and upper limb disorders are common and responsible for 42% of medical releases from the Canadian Armed Forces (CAF). Chiropractors care for CAF personnel off base, but collaboration with Canadian Forces Health Services (CFHS) varies among Canadian Forces Bases (CFBs). Developing a program of care (PoC) could address such variation. This study aimed to develop and assess the feasibility of implementing a PoC to improve chiropractors' communication with CFHS and delivery of spine care to active duty CAF personnel. Methods: This mixed-methods feasibility study involved two CFBs. Eligible participants included Medavie Blue Cross registered chiropractors, active duty CAF members with spinal pain, and CFHS personnel. Feasibility metrics included participation rates, attendance at meetings, completeness of clinical reports and patient outcome questionnaires, adherence to guidelines, and participants' experiences with study protocols and care. Data were analyzed descriptively and thematically. Results: Participants were 55% (11/20) of invited chiropractors and 85% (22/26) of referred CAF and invited CFHS personnel. All chiropractors and CFHS personnel attended on-base meetings. Training sessions, meetings, and educational materials enhanced understanding of military culture and treatment expectations. 98% of clinical reports and outcome questionnaires were completed, and practice guidelines were followed. Participants suggested that communication between chiropractors and CFHS personnel improved compared with prior experience. Discussion: Implementing a PoC that enhances communication with CFHS personnel and delivers evidence-based spine care to CAF members is feasible. Future work is needed to determine whether such care improves outcomes among CAF members with spinal pain.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".