Physician‐related facilitators and barriers to patient involvement in treatment decision making in early stage breast cancer: perspectives of physicians and patients
Bibliographic record
Abstract
OBJECTIVE: To identify patients' and physicians' perceptions of physician-related verbal and nonverbal facilitators and barriers to patient involvement in treatment decision making (TDM) occurring during clinical encounters for women with early stage breast cancer (ESBC). METHODS: Eligible women were offered treatment options including surgery and adjuvant therapy. Eligible physicians provided care for women with ESBC in either a teaching hospital or an academic cancer centre. In Phase 1, women were interviewed 1-2 weeks after their initial consultation. In Phase 2, women and their physicians were interviewed separately while watching their own consultation on a digital video disk. All interviews were audiotaped, transcribed and analysed. RESULTS: Forty women with ESBC and six physicians participated. Patients and physicians identified thirteen categories of physician facilitators of women's involvement. Of these, seven categories were frequently identified by women: conveyed a rationale for patient involvement in TDM; explained the risk of cancer recurrence; explained treatment options; enhanced patient understanding of information; gave time for TDM; offered a treatment recommendation; and made women feel comfortable. Physicians described similar information-giving facilitators but less often mentioned other facilitators. Few physician barriers to women's involvement in TDM were identified. CONCLUSIONS: Women with ESBC and cancer physicians shared some views of how physicians involve patients in TDM, although there were important differences. Physicians may underestimate the importance that women's place on understanding the rationale for their involvement in TDM and on feeling comfortable during the consultation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".