Decision‐making preferences and information needs among Greek breast cancer patients
Bibliographic record
Abstract
OBJECTIVES: We aimed at assessing Greek breast cancer patients' preferences for participation in treatment decision making and their information needs. METHODS: In a cross-sectional study, 329 breast cancer patients were administered at the Control Preferences Scale, a card-sort measurement designed to elicit preferences for participation in decision making. Information needs were assessed with Cassileth's Information Styles Questionnaire. RESULTS: The majority of patients (71.1%) preferred to play a passive role in treatment decision making, with most of them wanting to delegate responsibility of the decision completely to their doctor (45.3%). A collaborative role was preferred by 24%, whereas only 4.6% chose an active role. Most women expressed a general desire for as much information as possible about their illness (62.6%), but a substantial proportion (37.4%) did not want detailed information; instead, they wished to avoid awareness of bad news. Women who desired less informational details and preferred a passive role requested less frequently a mammography (p<0.001) and/or Pap test (p<0.0005) prediagnostically. CONCLUSIONS: This study's findings showed that the proportion of patients who wanted to play a passive role in decision making is the highest reported compared to similar studies from other countries, indicating the impact of the dominating paternalistic model of the doctor-patient relationship in the Greek medical encounter. The association of desired information details and decision-making preferences with screening for cancer procedures prediagnostically highlights the significance of providing the patients with the appropriate information and the choices available for their treatment.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".