Advance Care Planning in Cancer: Patient Preferences for Personnel and Timing
Bibliographic record
Abstract
PURPOSE: Opportunities for advance care planning (ACP) discussions continue to be missed despite the demonstrated benefit of such conversations. This is in part because of a poor understanding of patient preferences. We aimed to determine oncology patients' preferences surrounding ACP with a focus on the choice of which health care providers to have the conversation with and the timing of conversations. METHODS: A cross-sectional 19-question survey of surgical and medical oncology patients in a tertiary care hospital was conducted that assessed knowledge, experience, and preferences surrounding ACP. Quantitative variables were reported with descriptive statistics, and a coding structure was developed to analyze qualitative data. RESULTS: Two hundred patients were surveyed. Only 24% of patients reported previously having ACP discussions with their physicians despite 82.5% reporting a wish to do so. Patients felt that these discussions were a priority for them (to alleviate familial guilt, maintain control, and prevent others' values from guiding end-of-life care), but they reported that previous experiences with ACP had been neither comprehensive nor effective. Most patients (43.5%) preferred to have ACP discussions with their primary care providers (PCPs) compared with 7% preferring their surgeon and 5.5% preferring their oncologist. Trust and familiarity with PCPs arose as the dominant theme underlying this selection. Most patients (94%) preferred to have ACP discussions early, with 45% wishing such a discussion had been initiated before their cancer diagnosis. CONCLUSION: Patients with cancer prefer to have ACP discussions with their PCPs and prefer to do so early in their disease course.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".