A multicenter study of supportive‐expressive group therapy for women with BRCA1/BRCA2 mutations
Bibliographic record
Abstract
BACKGROUND: Women with a BRCA1/BRCA2 mutation experience significant challenges. These include decision-making regarding surgical options and notification to offspring and family, along with a sense of isolation, which may lead to psychological and emotional distress. The current study developed, standardized, and conducted preliminary testing of a supportive-expressive group therapy intervention designed to address these challenges. METHODS: Seventy women with a BRCA1/BRCA2 mutation recruited from familial cancer risk clinics participated in 12 sessions of supportive-expressive group therapy that lasted 6 months. Before and after measures of psychosocial functioning, knowledge, and surveillance/surgery activities were completed. RESULTS: Sixty-seven women completed the intervention. Significant improvements were observed in psychosocial functioning: cancer worries (P = 0.005), anxiety (P = 0.033), and depression (P = 0.015). Knowledge level and surveillance levels were high at baseline and there were no significant changes postintervention. A significant number of women made decisions concerning prophylactic surgery (oophorectomy/mastectomy) during and after the intervention. CONCLUSIONS: The feasibility of a supportive-expressive group for BRCA1/BRCA2 mutation carriers was demonstrated. Findings from the study are consistent with an effective intervention. However, further research is required using a randomized controlled study design.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".