What can physicians do to promote patient involvement in decision making (DM) in the oncology consultation?
Bibliographic record
Abstract
19553 Background: Facilitating patient involvement in TDM is a desirable feature of the oncology consultation. Greater patient involvement in TDM may lead to improved patient satisfaction, compliance and reduced psychological morbidity. However, there is little empiric evidence defining physician behaviors and attributes that facilitate patient involvement in TDM. This study used qualitative methods to identify such behaviors and attributes suggested by both practicing oncologists and patients. Methods: Semi-structured interviews were conducted with 11 medical, 10 radiation oncologists and 19 patients with breast, lung, GI, or GU cancer to determine physician behaviors and attributes that facilitate patient involvement in TDM. Interviews were audiotaped and transcribed verbatim, then analyzed independently by two researchers using inductively derived coding categories and predetermined coding rules. Behaviors and attributes were identified and coded into common themes. Six focus groups with an additional 37 patients were conducted to review these behaviors and attributes. Results: A total of 231 individual physician behaviors and attributes were identified by physicians (179) and patients (52) that facilitate patient involvement in DM. Common behaviors and attributes identified from the interviews include: assessing patient’s understanding and preferences, providing information, explaining the DM process, providing information on treatment options, allowing time to consider treatment options, checking patient understanding of options and inviting patient input into decisions. Other behaviors such as physicians’ communication skills were reported as facilitating TDM. Specific physician personality attributes, such as empathy, were identified as important facilitators. Conclusions: Physicians and patients identify a large number of physician behaviors and attributes that may facilitate patient involvement in TDM. These include both behaviors that are important in general physician-patient communication, as well as those that are specifically related to the decision making process. Further research is ongoing to determine the importance of these factors and approaches to encourage their use in the oncology consultation. No significant financial relationships to disclose.
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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 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".