Physician-Identified Factors Affecting Patient Participation in Reaching Treatment Decisions
Bibliographic record
Abstract
PURPOSE: Cancer physicians report high comfort with shared decision making but a lower frequency of using this approach in practice. Information regarding physicians' perceptions of what helps and what hinders patient involvement in decision making may facilitate understanding of this discrepancy. METHODS: We surveyed 604 Australian cancer physicians treating breast, colorectal, gynecologic, hematologic, or urologic cancer to investigate barriers and facilitators to reaching treatment decisions with their patients and their support of strategies to encourage patient involvement and reflection on treatment options. Factor analysis and regression analyses were used to investigate relationships between variables and identify predictors of greater reporting of barriers to sharing treatment decisions with patients. RESULTS: Insufficient information at the first consultation (28.9%) and insufficient time (28.4%) were the most frequently reported barriers to reaching treatment decisions with patients. Multivariate analysis revealed that less experienced physicians more commonly reported system barriers (P = .00). Patients trusting their physician and being accompanied at the consultation were most helpful to reaching a treatment decision. Providing written information about treatment options, making a further appointment to reach a decision, encouraging the patient to speak with their family physician and treatment team, and the presence of a third person during the consultation were felt to encourage involvement and reflection on treatment decisions. CONCLUSION: Cancer physicians experience difficulties when reaching treatment decisions with their patients. Interventions and strategies that physicians support are required to enhance patient involvement in reaching a treatment decision.
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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 | 0.005 | 0.073 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".