Restoring Body Image After Cancer (ReBIC): Results of a Randomized Controlled Trial
Bibliographic record
Abstract
Purpose This study aimed to test a group psychosocial intervention focused on improving disturbances of body image (BI), sexual functioning, and quality of life in breast cancer (BC) survivors. Methods A prospective, randomized controlled trial was conducted to assess the efficacy of an 8-week group intervention in women after BC treatment. The manual-based intervention combined two powerful ingredients: expressive guided-imagery exercises integrated within a model of group-therapy principles. The intervention facilitates exploration of identity, the development of new self-schemas, and personal growth. In addition, the intervention included an educational component on the social and cultural factors affecting women's self-esteem and BI. The control condition included standard care plus educational reading materials. One hundred ninety-four BC survivors who had expressed concerns about negative BI and/or difficulties with sexual functioning participated in the study; 131 were randomly assigned to the intervention, and 63 were assigned to the control condition. Participants were followed for 1 year. Results Women in the intervention group reported significantly less concern/distress about body appearance ( P < .01), decreased body stigma ( P < .01), and lower level of BC-related concerns ( P < .01), compared with women in the control group. BC-related quality of life was also better in the intervention group compared with the control group at the 1-year follow-up ( P < .01). There was no statistically significant group difference in sexual functioning. Conclusion Restoring Body Image After Cancer (ReBIC), a group intervention using guided imagery within a group-therapy approach, is an effective method for addressing BI-related concerns and quality of life post-BC. The manual-based intervention can be easily adapted to both cancer centers and primary care 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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".