Who's Listening? Experiences of Women with Breast Cancer in Communicating with Physicians
Bibliographic record
Abstract
The purpose of this qualitative study was to describe communication behaviors and attitudes of physicians that were most important to women living with breast cancer. Two focus group sessions were conducted, 1 month apart, involving 15 women who were members of a community-based breast cancer support group in Vancouver, British Columbia, Canada. Group dialogue was audiotaped, and notes were taken at each session by the coinvestigators, also members of the support group. Audiotapes, coinvestigators' written notes from the two focus group sessions, and the written homework assignments were used in the qualitative data analysis. Conceptual themes were identified and grouped to discern patterns within the data. The women were asked the following: (a) What were the most helpful things your doctor said or did at the time of your diagnosis? (b) What does a good intervention feel or look like? They were then asked to describe behaviors and attitudes they would like to influence in medical students who might later be communicating with women facing a diagnosis of breast cancer and to indicate which behaviors and attitudes they felt were most important. Women's positive experiences with physicians were characterized by communication based on active listening, awareness of the women's knowledge of their illness, honesty, and partnership. Physicians who showed interest in their patients as persons and who used touch to communicate caring were perceived as supportive communicators. Not surprisingly, there were similarities between the participants' positive experiences with their own physicians and the behaviors and attitudes desired in future physicians. Once again, "listening" was ranked as most important, followed by willingness to discern the individual patient's knowledge level.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".