Psychosocial assessment of patients with chronic pain
Bibliographic record
Abstract
The main object of this study is to evaluate the psychological status of chronic pain patients (CPP) and describe the characteristics and frequency of psychological disorders of CPP. Two hundred sixty-three patients with complaints of chronic pain longer than 1 year and fifty healthy volunteers were included in the study. Patients with cancer were not included. Turkish version of Symptom Checklist-90 Revised (SCL- 90-R) was used for the assessment of the psychological status of participants. CPP were divided into 5 subgroups regarding their painful regions: Headache, cervical or upper extremity pain, axial or radicular back pain, lower extremity pain, and diffuse pain. Global severity index (GSI) and subscales of SCL-90-R were analyzed. In CPP, GSI and almost all subscale scores of SCL-90-R were significantly higher than the control group. Headache patients had worse psychological symptoms than other subgroups of CPP. SCL-90-R scores of female patients were significantly higher than males. 24.7% of patients had moderate and 14.8% had severe psychological symptoms. While the intensity of the pain had a moderate correlation with increased psychological symptoms, the level of education and age had a weak negative correlation with SCL- 90-R scores. Patients with chronic pain are convenient to have phycological symptoms. While almost half of the patients have increased psychological symptoms, the degree of the symptoms can be serious in some of them. Thus, treatment of chronic pain necessitates a multidisciplinary approach.
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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 | 0.002 |
| 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".