Do Psychological Factors, Pain, and Sleep Quality Correlate With Disability and Occupational Performance in Hand Burns?
Bibliographic record
Abstract
Background and Objectives: Burn injuries are one of the most common traumas after traffic accidents, falls, and interpersonal violence. This study was done to investigate the correlation between psychological factors, pain, and sleep quality, and disability and occupational performance in subjects with hand and upper extremity burns. Methods: A total of 80 patients with hand and upper extremity burn injuries (16 females and 64 males) with a Mean±SD age of 39.9±10.79 years, mean burn depth (Deep Partial Thickness/ Full Thickness) of 3.42±2.66, and Mean±SD burns extent 1.06±0.24 participated in this non-experimental cross-sectional study using a non-probability sampling method. Their psychological disorders were measured using the Beck Anxiety Disorder Scale and the Self-Rating Depression Scale. The pain was assessed using the Visual Analogue Scale, sleep quality was measured by the Pittsburgh Sleep Quality Index (PSQI), disability was assessed using the Shortened Disabilities of the Arm, Shoulder, and Hand (DASH) Questionnaire, level of independence in daily living activity was measured by the Modified Barthel Index, and occupational performance was measured by the Canadian Occupational Performance Measure (COPM). Results: Psychological factors, pain, and sleep quality were significantly correlated with disability and occupational performance. The regression models explained up to 34.4% of the variance for disability outcome and 12.4% for occupational performance. By assessing the correlation between the psychological disorders, pain, and sleep quality, and disability and occupational performance in these patients, we found that sleep quality was the strongest contributing factor Followed by PSQI. Conclusion: Sleep quality is one of the important factors affecting the occupational performance of patients with hand and upper extremity burns injury that should be considered by therapists.
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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 | 0.002 |
| 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) | 0.002 | 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".