A public health concern: Chronic low back pain and the relationship between pain, quality of life, depression, anxiety, and sleep quality
Bibliographic record
Abstract
Aim: Chronic low back pain (CLBP) is a common condition of the musculoskeletal system and a public health concern. CLBP patients suffer from conditions such as muscle weakness and numbness, resulting in diminished quality of life (QoL), poor functioning, psychological disorders and sleep disorders related to disabling pain. The aim of the current study was to reveal relationship between CLBP and patients’ health related QoL, anxiety, depression, and sleep disturbances. Methods: Seventy-three patients with CLBP and 73 healthy controls participated in this questionnaire-based cross-sectional study. The Short form McGill Pain Questionnaire, Roland-Morris disability, Short form-36 (SF-36), Beck Depression (BDI) and anxiety inventory (BAI) and the Pittsburgh Sleep Quality Index (PSQI) were used in the study group, and SF-36, BDI, BAI and PSQI were used in the control group. The relationships between QoL, depression, anxiety, and sleep disorders were examined in the two groups. Results: Two groups did not differ in terms of demographic characteristics (P>0.05). In the sub-scales of SF-36, except vitality and mental health, a significant difference was detected between the study and control groups (P<0.001). The depression, anxiety and PSQI scores did not differ between the two groups (P>0.05). Conclusion: CLBP affects QoL negatively. This should be considered when managing CLBP.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".