Employment-Related Factors in Chronic Pain and Chronic Pain Disability
Bibliographic record
Abstract
BACKGROUND: Disability is a multifactorial phenomenon. Social scientists suggest that nonclinical factors, including age, education, and job status, correlate with disability. OBJECTIVE: Do employment-related factors predict chronic pain and/or chronic pain disability? METHODOLOGY: The literature search identified 15 observational studies to provide the evidence about this question. RESULTS: Review topics included job satisfaction, type of work, modified work and work autonomy, other employment-related factors, and socioeconomic status. Most subjects in the studies had low back pain. The studies used return to work as an outcome predicting chronic pain disability. CONCLUSIONS: Lack of modified work and lack of work autonomy predicted chronic pain disability (level 2). There was limited evidence (level 3) that lack of job satisfaction, perception of difficult job conditions and demands, heavy physical demands of the job, private rather than public employment, and lower socioeconomic group predict chronic pain disability. The number of years employed varied as a predictor in different studies (level 4b).
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.054 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".