Quality of life, alexithymia, and defence mechanisms in patients affected by breast cancer across different stages of illness
Bibliographic record
Abstract
Objectives: The aim of this study was to evaluate the effect of alexithymia and defence mechanisms on the quality of life of patients affected by breast cancer at different stages of the disease. Methods A convenience sample of 110 patients with breast cancer was involved in the study: 41 were receiving adjuvant chemotherapyafter surgery, 29 had disease-free survival in follow-up and 40 were receiving chemotherapy for metastatic disease. Quality of life, alexithymia and defence mechanisms were assessed using the following instruments: EORTC QLQ-C30-BR23, Toronto Alexithymia Scale (TAS-20) and Defense Mechanism Inventory (DMI). Results Compared to the other groups, patients receiving chemotherapy for metastatic disease reported poorer quality of life in several domains, more severe cancer-related and treatment-related symptoms and higher levels of alexithymia. When the effect of other potential predictors was taken into account, TAS-20 difficulty in identifying feelings was significantly related to all the EORTC functional subscale. Conclusion: This study underlined the relevance of difficulty in emotional processing and defence mechanisms in modulating psychological adjustment in women affected by breast cancer, suggesting that these might be potential targets of psychological intervention for this population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.000 | 0.007 |
| Scholarly communication | 0.001 | 0.013 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".