The relationship between depression, anxiety, and pain catastrophising in cancer patients
Bibliographic record
Abstract
Introduction: Catastrophising is a person's view of an unreasonable belief and a worse situation than exaggerating its consequences.It is defined as individuals believing that their current condition and physical discomfort will worsen each time or that something will be worse than it actually is.The aim of this study was to evaluate the relationship between depression and anxiety and pain catastrophising in cancer patients.Material and methods: Fifty-five cancer patients who were followed and treated in the Oncology Outpatient Clinic were included in the study.The age, gender, marital status, occupation, and psychiatric history of the participants were recorded.A socio-demographic data form, Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), and the Pain Catastrophising Scale (PCS) were applied to the participants. Results:The mean age of the participants was 59.2 ±12.7 years, and 40% were female.When the total BDI and BAI scale scores of cancer patients were evaluated, it was seen that they were not depressed in terms of mean value (p = 0.112), but they were in the anxiety scale (p < 0.05).There was a positive correlation between depression and anxiety, as well as depression and anxiety and pain catastrophising (p < 0.001, r = 0.782).While the PCS subscales "helplessness" and "rumination" scores were significantly higher in cancer patients with depression and anxiety (p < 0.001), the "magnification" score was significantly higher in cancer patients with anxiety (p < 0.001).The Pain Catastrophising Scale total score increased with increasing BDI and BAI severity (p < 0.001), while the BDI and BAI scores were found to be significantly higher in females than males (p < 0.001).Conclusions: It was found that cancer patients were generally not depressed but were anxious, and the catastrophising of pain increased with increasing depression and anxiety severity.Health professionals giving care to cancer patients need to be alert to signs of psychological distress in patients experiencing 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 | 0.007 |
| 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 | 0.001 |
| 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".