Developing a decision support intervention regarding choice of dialysis modality.
Bibliographic record
Abstract
UNLABELLED: Predialysis nurses have an important role in supporting patients who must make decisions when renal replacement therapy is needed. However, no effective interventions have been established for nurses who provide this decision support. The Ottawa Decision Support Framework provides a structure to develop such interventions, which include a patient decision aid and decision coaching. GOAL: To propose a method for developing and implementing a decision support intervention. METHOD AND RESULTS: Guided by this model, a mixed method design is proposed to develop and evaluate the intervention. The intervention includes a decision aid intended for patients and their families and training in decision coaching intended for nurses. Its development requires knowledge synthesis and a decisional needs assessment with key informants. The development of decision coaching competencies for nurses will include an interactive skill building workshop. A constructivist evaluation approach will be used to evaluate the intervention. CONCLUSION: This study proposes an innovative approach to develop interventions and should contribute to improving the quality of decision-making regarding dialysis modality and to developing nurses' skills in providing decision support.
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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 | 0.009 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".