A decision aid for men with early stage prostate cancer: theoretical basis and a test by surrogate patients
Bibliographic record
Abstract
BACKGROUND: We developed a decision aid for patients with curable prostate cancer based on Svenson's DiffCon Theory of Decision Making. This study was designed to determine if surrogate patients using the aid could understand the information presented, complete all tasks, show evidence of differentiation, and arrive at a preferred treatment choice. METHODS: Men, at least 50 years old and never diagnosed with prostate cancer, were recruited through local advertisements. Participants were asked to imagine that they were a case-scenario patient. Then they completed the decision aid interview, which included three components: (i) information presentation, with comprehension questions, (ii) exercises to help identify attributes important to the decision, and (iii) value-clarification exercises. RESULTS: Sixty-nine men volunteered. They had a mean age of 61.2 (range 50-83) years, 37% had no formal education beyond high school, and 87% were living with a partner. All participants completed all aspects of the interview. They answered an average of 10 comprehension questions each, with a mean of 94.7% correct without a prompt. Each attribute in the information presented was identified by at least one participant as important to his decision. Participants identified a median of five attributes as important (ranges 1-14) at each of three points during the interview; 75% changed at least one important attribute during the interview. Forty-nine per cent of participants also identified attributes as important that were not included in the presented information. Participants showed a wide range of values in each of seven trade-off exercises. Eighty-eight per cent of participants showed evidence of differentiation; 75% had a clear treatment preference by the end of the interview. CONCLUSIONS: Our decision aid appears to meet its goals for surrogate patients and illustrates the strengths of the DiffCon theory. The ability of the aid to accommodate wide variability, both in information needs and in important attributes, is a particular strength of the decision aid. It now requires testing in patients with prostate cancer.
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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 | 0.001 |
| 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 | 0.000 |
| 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".