Participation of haemato-oncological patients in medical decision making and their confidence in decisions
Bibliographic record
Abstract
ERNST J., WEISSFLOG, G., BRÄHLER E., NIEDERWIESER D., KÖRNER A. & SCHRÖDER C. (2010) European Journal of Cancer CareParticipation of haemato-oncological patients in medical decision making and their confidence in decisions Increasingly more clinical care and research acknowledge the patients' interest in participating in medical decision making. However, for haematological patients, there are as yet only modest findings. The current study explores patients' perceptions of their role in the medical decision-making process in a sample of 117 haematological patients. The majority of patients surveyed (63.9%) took a passive role in the medical decision-making process, which is a significantly greater proportion compared with individuals suffering from solid cancers. Despite passive majority, most of the participants reported a positive evaluation of the decision-making process. Importantly, patients' evaluations were significantly more negative either if patients were treated as inpatients (vs. outpatients), or if they experienced no control over the decision (vs. collaboration with the doctor, or deciding autonomously). The results and limitations of the study are discussed.
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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 | 0.004 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".