A Biopsychosocial Profile of Adult Canadians with and without Chronic Back Disorders: A Population-Based Analysis of the 2009-2010 Canadian Community Health Surveys
Bibliographic record
Abstract
Chronic back disorders (CBD) are a significant public health concern. Profiling Canadians with CBD and the associated biopsychosocial factors at a national population level is important to understand the burden of this condition and how clinicians, health systems, and related policies might address this potentially growing problem. We performed a secondary analysis of the 2009 and 2010 Canadian Community Health Surveys to calculate prevalence and to better understand the differences between people with and without CBD. An estimated 20.2% of the adult Canadian population reports having back problems lasting for 6 months or more. Among people with CBD, there was significantly greater likelihood of living in a more rural or remote location, being Aboriginal, being a former or current smoker, being overweight, having other chronic health conditions, having greater activity limitations, having higher levels of stress, and having lower perceived mental health. People who were single/never married or had an ethnicity other than Caucasian or Aboriginal were less likely to report having CBD. These results contribute to a growing body of research in the area that may assist with strategic prioritization and tailoring of health promotion efforts and health services for people with CBD, particularly among vulnerable groups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 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) | 0.002 | 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".