Empowering patients: qualitative insights into decisional needs in shared decision-making for post-operative rehabilitation after distal radius fracture
Bibliographic record
Abstract
PURPOSE: Post-surgical rehabilitation may benefit patients after distal radius fractures, yet evidence guiding referral to supervised versus home-based rehabilitation remains unclear. Shared decision-making may facilitate a patient-centered decision about the most appropriate rehabilitation option. This study explores patients' decisional needs before shared decision-making regarding post-operative rehabilitation options following distal radius fracture surgery. METHODS: = 15) were analyzed deductively using the Ottawa Decision Support Framework, followed by an inductive analysis. Personal and clinical needs were linked to the International Classification of Functioning, Health, and Disability domains. RESULTS: Observations indicated that decisions about the most appropriate rehabilitation option were mainly made by clinicians based on clinical assessments. In focus group interviews, a wish was expressed for decision-making to be shared, emphasizing that adequate patient information was a prerequisite. Decisional needs were related to decision timing, the possibility of expressing preferences, and rehabilitation options. Participants emphasized empowering patients in identifying their individual rehabilitation needs and becoming aware of their own preferences. Multiple factors were considered essential for making a patient-centered decision about the most appropriate rehabilitation option. CONCLUSION: Both patients and clinicians were in favor of shared decision-making regarding rehabilitation options, but patients need information to empower their involvement in the decision-making process.
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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 | 0.022 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".