Anxiety, depression and defense mechanisms associated with treatment decisional preferences and quality of life in non‐metastatic breast cancer: a 1‐year prospective study
Bibliographic record
Abstract
OBJECTIVE: Treatment decisional preferences impact breast cancer patients' health-related quality of life (HRQoL) and may relate to psychological variables, although many aspects of this relationship remain unknown. This prospective study aimed to assess psychological correlates of treatment decisional preferences and predictors of HRQoL in women with early non-metastatic breast cancer. METHODS: Of the 124 women initially assessed for anxiety (Spielberger's State-Trait Anxiety Inventory) and depressive (Center for Epidemiologic Studies-Depression (CES-D)) symptoms, HRQoL (WHOQOL-BREF), and defense mechanisms (Life Style Index), 82 (66.1%) completed the 1-year follow-up. Mean age was 54.6 years (SD = 9.76), and mean disease duration was 19.4 months (SD = 25.55); 19.5% had stage I, 63.4% stage II and 17.1% stage III disease. The predictive power and moderator effects of psychological variables were tested using multiple and hierarchical regression models. RESULTS: Depressive symptoms and physical HRQoL improved significantly, state anxiety and mental and environment HRQoL remained stable, and social relations HRQoL deteriorated over the 1-year period. Older age (p = 0.021) and higher scores in repression defense (p = 0.044) were independently associated with passive decisional preferences. Earlier stage of cancer (p = 0.043), lower state anxiety (p = 0.039), lower repression scores (p = 0.021) and improvement in depressive symptoms (p < 0.001) predicted physical HRQoL improvement. Moderation analysis showed that active decisional preferences predicted physical HRQoL improvement, but only in those women with lower repression levels. CONCLUSIONS: Defense mechanisms are associated with treatment decisional preferences and interact with factors predicting HRQoL in women with breast cancer. Clinicians should address the patients' anxiety and depressive symptoms and refer patients with high repression tendencies for psychological evaluation and management.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".