Coping, Anxiety, and Pain Intensity in Patients Requiring Thoracic Surgery
Bibliographic record
Abstract
Stress, anxiety, and post-surgical chest pain are common problems among patients with thoracic surgical pathology. The way in which psychological distress is managed—the coping style—can influence the postsurgical evolution and quality of life of patients. In our study, we monitored the influence of coping style on patients’ anxiety and the intensity of post-operative chest pain. We conducted a cross-sectional study on 90 subjects with thoracic surgical pathology. One month after their surgeries, patients completed the following scales and questionnaires, translated, adapted, and validated for the Romanian population: COPE scale inventory, Generalized Anxiety Disorder-7 Questionnaire, McGill Pain Questionnaire, and Numeric Pain Rating Scale. Anxiety (evaluated using the Generalized Anxiety Disorder-7 Questionnaire) and postoperative thoracic pain intensity (evaluated by means of the Numeric Pain Rating Scale, Number of Words Chosen, and McGill Pain Questionnaire) were significantly higher in patients exhibiting social-focused coping than in patients presenting emotion-focused or problem-focused coping as their main coping style (Kruskal–Wallis, p = 0.028, p = 0.022, p = 0.042, p = 0.007). In our study, there were no differences observed in pain intensity relative to level of anxiety. Coping style is an important concept in the management of anxiety and pain experienced by patients undergoing chest surgery. Therefore, a multidisciplinary approach should be considered in clinical practice.
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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 | 0.000 | 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) | 0.001 | 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".