Alcohol use self report in chronic back pain—relationships to psychosocial factors, function performance, and medication use
Bibliographic record
Abstract
BACKGROUND CONTEXT: Alcohol consumption is a known risk factor for spinal disability, but there is no data on the relationship between reported alcohol consumption and behaviours in persons who are disabled. PURPOSE: To determine the interaction between reported alcohol consumption, physical performance, and medication use in this group. To determine psychosocial correlates of reported alcohol consumption in this group. METHODS: A retrospective review 147 men and 136 women with more than 3 months disability who underwent a multidisciplinary physical, functional and psychosocial Spine Team Assessment. Questions about alcohol consumption were related to outcome measures. RESULTS: None of the women reported more than 5 drinks/week. Ten men reported more than 12 drinks per week. These performed significantly better on the Progressive Isoinertial Lifting Evaluation (PILE) low lift and the Functional Assessment Screening Test (FAST) 5 minute twisting test, and trended towards better performance on all other tests (the PILE high lift, all 4 other FAST components, Sorenson trunk extension test, and bicycle ergometer submaximal stress test). They had less back pain disability (Quebec p = 0.061), but no difference in depression (CESD), pain (visual analog scale) or fear (Tampa). They used fewer Non-steroidal medications, but similar narcotic medications as the others. No significant differences in the SF-36 were noted. CONCLUSIONS: This first assessment of the relationship of alcohol consumption with back pain disability suggests that women with chronic back pain disability seldom report heavy alcohol consumption. Men with back pain disability who consume large amounts of alcohol have less physical disability despite similar pain. Despite potential interactions, heavy drinkers with pain do not use fewer narcotic analgesics than light drinkers.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".