A comparison of the relationship between depression, perceived disability, and physical performance in persons with chronic pain
Bibliographic record
Abstract
This study examined the relationships between self-report of depressive symptoms, perceived disability, and physical performance among 267 persons with chronic pain. Prior research has reported a relationship between depression and disability using self-report measures. However, self-report instruments may be prone to biases associated with depression as depressed persons with pain may have an exaggerated negative view of their level of function. In addition, we examined whether the relationship between depression and functional activity was mediated by physiologic effort (as measured by heart rate). The results indicated that self-report of depressive symptoms (using the Center for Epidemiological Studies-Depression Scale (CES-D)) was significantly correlated with self-report of disability on the Quebec Back Pain Disability Scale (QBPDS) and physical performance on the Progressive Isoinertial Lifting Evaluation (PILE). Regression analyses revealed that depression assessed by the CES-D significantly contributed to the prediction of QBPDS scores and PILE performance even when controlling for age, gender, site of pain, and pain intensity. The magnitude of the relationships between depression and self-report and functional activity were similar, suggesting that a self-report bias associated with depression is not responsible for an observed relationship between depression and disability. Physiologic effort partially mediated the relationship between depression and physical performance. The findings further highlight the importance of depression in the experience of chronic pain.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".