Exploring Characteristics of Patients with Acute Low Back Pain in Ontario Primary Care Settings
Bibliographic record
Abstract
Background: Low back pain (LBP) is a common and disabling condition. It impacts the individual, the community and the healthcare system. Patients with LBP are primarily managed in ambulatory settings such as primary care. Common care providers for patients with LBP include family physicians, physiotherapists and chiropractors. The management of patients with LBP is often not aligned with the evidence-based recommendations of clinical practice guidelines. To improve management practices, a detailed understanding of the health condition, including patient characteristics, is important. There is a lack of recent knowledge about the characteristics of patients with acute LBP in primary care in Ontario. Objective: To describe characteristics of patients with acute LBP in primary care in Ontario, their beliefs about imaging for LBP, and the differences in these characteristics among patients recruited by different practitioners. Methods: A descriptive observational study was completed as part of a longitudinal cohort study. Registered practitioners from seven geographical regions across Ontario were invited to participate. Practitioners then invited consecutive patients with acute LBP to participate, including completion of a questionnaire completed directly after their initial consultation. The questionnaire included questions relating to their current episode of LBP, sociodemographic information, general health information, and beliefs about LBP. Results: In total, 13 family physicians, 33 physiotherapists and 27 chiropractors recruited a total of 445 patients to participate. The mean age of patient participants was 46 years and 48% were female. Patients recruited by chiropractors were younger, more had full time employment and were more confident that their pain would be completely gone or much better in 3 months. Older age, higher pain self-efficacy, and higher markers of psychological distress were associated with the agreement that everyone with LBP should have imaging. Conclusion: There were differences in sociodemographic and pain characteristics among patients who utilized different practitioners, most notable between patients recruited by chiropractors compared to patients recruited by family physicians and physiotherapists. Patient characteristics may influence patients’ beliefs about imaging for LBP. These are key areas for future research and provide a foundation for improving the management of patients with acute LBP in Ontario primary 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".