Individual Psychosocial Support for Breast Cancer Patients
Bibliographic record
Abstract
In a prospective, randomized study, an individual psychosocial support intervention performed by specially trained oncology nurses, or psychologists, were compared with standard care. Consecutive primary breast cancer patients about to start adjuvant therapy (n = 179) were included. Data were supplied by the questionnaires European Organisation for Research and Treatment of Cancer Quality of Life Study Group Core Quality of life questionnaire with 30 questions (EORTC QLQ-C30) and Breast Cancer Module with 23 questions (BR23), the Hospital Anxiety and Depression Scale, Spielberger's State-Trait Anxiety Inventory, and the Impact of Event Scale before randomization and 1, 3, and 6 months later. Patient files provided data on utilization of psychosocial support offered in routine care. Global quality of life/health status, nausea and vomiting, and systemic therapy side effects were the subscales showing significant Group by Time interactions, favoring the interventions. Intervention groups improved statistically significantly more than the standard care group regarding insomnia, dyspnea, and financial difficulties. Nurse patients experienced less intrusion compared with the standard care group. All groups showed statistically and clinically significant improvements with time on several subscales. The intervention groups, however, improved to a greater extent. Fewer patients in the intervention groups used psychosocial hospital support compared with the standard care group. In conclusion, psychosocial support by specially trained nurses using techniques derived from cognitive behavioral therapy is beneficial for breast cancer patients and may be a realistic alternative in routine cancer care.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".