Shared Decision-Making (SDM) for Female SUI: Current Practice in Three Western Countries
Bibliographic record
Abstract
INTRODUCTION: Different decision-making styles can be used to provide counselling for the multiple reasonable treatment options for patients with stress urinary incontinence (SUI). Shared decision-making (SDM) is currently advocated as the preferred style for preference sensitive decisions, as SDM takes patient preferences into account. This study aimed to map the current decision-making process for SUI in three Western countries. METHODS: We included 124 patients and 18 physicians in a multicentre, prospective study in five hospitals in Canada, the United Kingdom and the Netherlands. We used patient and physician versions of the Control Preference Scale (CPS) questionnaires and examined audio-recordings of consultations with the OPTION-5 instrument to assess the degree of SDM. RESULTS: Most patients (63%) perceived the decision-making as informative, some (29%) as shared and only a few (8%) as paternalistic. Dutch patients more often perceived the decision-making as informative than UK or Canadian patients. Patients' preferred and perceived decision-making styles matched in 70% of consultations. Patients' and physicians' perceptions of decision-making were the same in 60% of consultations, but their perceptions of SDM use did not match. This also did not match the OPTION-5 scores reflecting the use of SDM. Almost all patients were satisfied with the decision-making they perceived. CONCLUSION: Most patients and physicians prefer and perceive the current decision-making process as informative decision-making. However, patients and physicians have different perceptions of their mutual consultation. This highlights the imprecise concept of SDM for both patients and physicians.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".