031 Just say ‘we don’t know’-shared decision-making in the face of uncertainty: an assessment of the sensibility of a model of shared decision making for children with medical complexity while hospitalised
Bibliographic record
Abstract
Introduction Children with medical complexity (CMC) are the most medically fragile sub-set of paediatric patients who require intensive support from caregivers.1 Due to the co-existence of underlying diseases, caregivers and clinicians of CMC face decisions with unclear answers, with inadequate evidence to support treatment options. A conceptual model of SDM for CMC2 addresses the process of SDM when faced with complex, ambiguous clinical situations in which all possible outcomes cannot be known. This poster will present a how a conceptual model of SDM for CMC was revised and assessed for content and face validity by end users. Methods Virtual focus groups were held with 5 health care providers and 11 caregivers of CMC via Zoom. A video describing the model of SDM for CMC, was presented followed by a series of open-ended questions surrounding the model’s look, language, and usability.3 Suggested changes to the model and attributes to maintain were discussed. The steering committee reviewed the proposed changes which were then approved by consensus. In collaboration with a graphic artist, A revised model was produced with a graphic artist. The revised model was distributed to focus group participants with a survey to appraise sensibility using a 5 point likert scale. Results Mean score visual acceptability was 4.1 with 4.2 for usability. Discussion/Conclusion The changes to the models addressed the need for better reflect the decision maker as a person, the goal of relationship building and continuous nature of knowledge building. The revised model was well received by respondents regarding layout, content, language and usability. References Cohen E, Kuo DZ, Agrawal R, Berry JG, Bhagat SKM, Simon TD, et al. Children with medical complexity: an emerging population for clinical and research initiatives. Pediatrics. 2011;127(3):529–38. Buchanan FE. Making difficult decisions: an activity-theory informed qualitative study of shared decision- making for children with medical complexity [Thesis]. 2021. Légaré F, Stacey D, Pouliot S, Gauvin FP, Desroches S, Kryworuchko J, et al. interprofessionalism and shared decision-making in primary care: a stepwise approach towards a new model. J Interprof Care. 2011;25(1):18–25.
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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 | 0.041 | 0.118 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".