Information needs of early-stage prostate cancer patients: within- and between-group agreement of patients and health professionals
Bibliographic record
Abstract
PURPOSE: The aims of this study were to analyze agreement on information needs within a group of early-state prostate cancer patients and to compare information preferences of patients with the view of health-care professionals about patients' needs. METHODS: Sample consists of patients (n = 128) and six subgroups of health-care professionals (urologists, n = 32; nurses, n = 95; radiotherapy technologists (RTTs), n = 36; medical oncologists, n = 19; radiation oncologists, n = 12; general practitioners (GPs), n = 10). Information needs have been assessed with 92 questions concerning prostate cancer and its treatment. Respondents judged the importance of addressing each question. Within- and between-group agreements of patients and health-care professional groups were estimated with raw agreement indices as well as chance-corrected Kappa and Gwet's AC1 measures. Finally, group-specific core items rated with high importance as well as high agreement were defined. RESULTS: Patients rated on average (median) half, i.e., 51 out 92 items as essential (interquartile range (IQR) = 36-66), 26 items as desired (IQR = 14-38), and 10 items as avoidable (IQR = 2-22). Within-group agreement on the presented information topics is modest for any participating group (AC1(patients)= 0.319; AC1(professionals) = 0.295-0.398). Agreement between patients and professionals is low too (AC1 = 0.282-0.329). Defining group-specific core sets of information topics results in 51 items being part of at least one core set. Concordance of the item core sets of patients and professionals is moderate with κ = 0.38-0.66, sensitivity of professionals' core sets for patients' preferences varies between 56 and 74%. CONCLUSIONS: Results emphasize the need for dialogue between doctor/professional and patient in identifying the information needed by individual patients and support the importance of shared decision making.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".