Treatment Decision Making Among Chinese Women with DCIS
Bibliographic record
Abstract
One result of the widespread screening mammography is a 200% increase in the rates of breast ductal carcinoma in situ (DCIS). Treatment decision making among Chinese women diagnosed with DCIS remains understudied. This study examined Chinese-Canadian women's experiences (N = 26): (1) with treatment decision making (mastectomy or breast conserving surgery) and (2) their reflections on the decision-making process. Interviews in Cantonese, Mandarin, or English were transcribed and translated, and a content analysis conducted. Women's treatment decisions reflected a lack of understanding of DCIS, the desire to rid themselves of breast cancer forever, and the influence of significant others. English as a second language and use of medical jargon impeded their ability to make informed treatment decisions. Women's reflections on the decision-making process provided insights into how to improve information and support treatment decision making in ways that are accessible to them.
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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) | 0.001 | 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".