Behind closed doors: systematic analysis of breast cancer consultation communication and predictors of satisfaction with communication
Bibliographic record
Abstract
OBJECTIVE: The purpose of this investigation was to explicate the content of primary adjuvant treatment consultations in breast oncology and examine the predictive relationships between patient and oncologist consultation factors and patient satisfaction with communication. METHODS: The recorded consultations of 172 newly diagnosed breast cancer patients from four Canadian cancer centers were randomly drawn from a larger subset of 481 recordings and examined by three coders using the Medical Interaction Process System (MIPS); a system that categorizes the content and mode of each distinct utterance. The MIPS findings, independent observer ratings of patient and oncologist affective behavior, and derived consultation ratios of patient centeredness, patient directedness, and psychosocial focus, were used to predict patient satisfaction with communication post-consultation and at 12-weeks post-consultation. RESULTS: Biomedical content categories were predominant in the consultations, accounting for 88% of all utterances, followed by administrative (6%) and psychosocial (6%) utterances. Post-consultation satisfaction with communication was significantly higher for older patients, those with smaller primary tumors and those with longer consultations. Smaller tumor, lack of patient assertiveness during the treatment consultation and having the consultation with a radiation rather than medical oncologist were significantly predictive of greater satisfaction at 12-weeks post-consultation. CONCLUSIONS: Adjuvant treatment consultations are characterized by a high degree of information-giving by the physician, a predominance of biomedical discussion and relatively minimal time addressing patients' psychosocial concerns. Controlled trials are needed to further identify and address the contextual features of these consultations that enhance patient satisfaction.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".