Adjuvant Psychological Therapy for Alexithymia in Women with Breast Cancer
Bibliographic record
Abstract
Many psychological factors play an important role in diagnosis and treatment of cancer. One of the reasons could be due to deficits in emotional processing and affect regulation. These deficits could lead to an inability to verbalize and identify emotions which is known as alexithymia. To this end the objective of the study was to examine the effectiveness of adjuvant psychological therapy in breast cancer in terms of alexithymia (within the intervention group and between the two groups). The study consisted of 20 patients in the intervention and control groups each. They were administered the following scale namely, Toronto Alexithymia Scale (TAS-20). Results indicated that between the intervention and control groups, on total alexithymia, difficulty describing feelings and externally oriented thinking there was a statistically significant difference between the intervention and control groups. On the subscale of difficulty identifying feelings there were no statistically significant differences between the two groups. Within the intervention group too, significant differences were found on alexithymia and subscales both, following therapy and at follow up. This study reveals the effectiveness of psychological interventions in those with breast cancer. It is imperative that psychological care is the need of the hour in oncology settings.
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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 | 0.001 |
| 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".