Breast Cancer Survivorship and South Asian Women: Understanding about the Follow-Up Care Plan and Perspectives and Preferences for Information Post Treatment
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: As more treatment options become available and supportive care improves, a larger number of people will survive after treatment for breast cancer. In the present study, we explored the experiences and concerns of female South Asian (sa) breast cancer survivors (bcss) from various age groups after treatment to determine their understanding of follow-up care and to better understand their preferences for a survivorship care plan (scp). METHODS: Patients were identified by name recognition from BC Cancer Agency records for sa patients who were 3-60 months post treatment, had no evidence of recurrence, and had been discharged from the cancer centre to follow-up. Three focus groups and eleven face-to-face semistructured interviews were audio-recorded, transcribed verbatim, cross-checked for accuracy, and analyzed using thematic and content analysis. Participants were asked about their survivorship experiences and their preferences for the content and format of a scp. RESULTS: Fatigue, cognitive changes, fear of recurrence, and depression were the most universal effects after treatment. "Quiet acceptance" was the major theme unique to sa women, with a unique cross-influence between faith and acceptance. Emphasis on a generalized scp with individualized content echoed the wide variation in breast cancer impacts for sa women. Younger women preferred information on depression and peer support. CONCLUSIONS: For sa bcss, many of the psychological and physical impacts of breast cancer diagnosis and treatment may be experienced in common with bcss of other ethnic backgrounds, but the present study also suggests the presence of unique cultural nuances such as spiritual and language-specific support resource needs. The results provide direction for designing key content and format of scps, and information about elements of care that can be customized to individual patient needs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".