Sex-Specific Impact of Pain Severity, Insomnia, and Psychosocial Factors on Disability due to Spinal Degenerative Disease
Bibliographic record
Abstract
Purpose: Pain experience due to spinal degenerative disease decreases activity of daily living and quality of life. The present cross-sectional study was aimed at examining the sex-specific impact of pain severity, psychosocial factors, and insomnia on the disability due to chronic pain arising from spinal degenerative disease. Methods: In total, 111 outpatients with chronic spinal degenerative on initial diagnosis were analyzed. The definition of chronic spinal degenerative disease was (1) pain duration ≥3 months, (2) findings of nerve root compression on neurological examination and imaging, and (3) localized neck or lower back pain (not widespread, upper or lower limb pain). We used Numerical Rating Scale (NRS), Pain Disability Assessment Scale (PDAS), Hospital Anxiety and Depression Scale (HADS), Pain Catastrophizing Scale (PCS), and Athens Insomnia Scale (AIS) to assess patients. Univariate regression analysis was performed to investigate whether sex influences the PDAS score, and sex-stratified multivariate regression analysis was conducted to identify the variables associated with the PDAS score. Results: = 0.40, 95% CI 0.14-0.67) were associated with PDAS in women. HADS-A, HADS-D, and PCS were not associated with PDAS in both sexes. Conclusion: Insomnia was associated with disability in men, whereas aging and pain severity were associated with disability in women. Catastrophic thinking was not associated with disability in both sexes.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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".