Assessing Information and Decision Preferences of Men With Prostate Cancer and Their Partners
Bibliographic record
Abstract
The purpose of this study was to identify and compare information and decision preferences of men with prostate cancer and their partners at the time of diagnosis. A convenience sample of 80 couples was recruited from The Prostate Centre in Vancouver, Canada. Participants used a computerized version of two previously used measures with this population: Control Preferences Scale and Information Survey Questionnaire. Results showed that men had a preference to play either an active or a collaborative role in decision making with their physician (92.5%) and partners (100%). The majority (55%) of partners wanted to play a collaborative role in treatment decision making. Couples identified prognosis, stage of disease, treatment options, and side effects as the top 4 information preferences. Men ranked information on sexuality more important than partners, and partners ranked information on home self-care higher than men. Men who had sons, a positive family history, and lower levels of education ranked heredity risk significantly higher. Profiles of information categories did not differ according to role preferences of either men or partners. The computer program has been shown to be a reliable and acceptable method of assessing information and decision preferences of these couples. An individualized approach is suggested, given the high reliability of individual's profiles.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.010 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".