095 Engagement of older adults receiving home care services and their caregivers in health decisions in partnership with clinical teams to prioritize and culturally adapt decision aids for home care
Bibliographic record
Abstract
Introduction We aimed to prioritize and culturally adapt patient decision aids (PtDAs) for older adults receiving home care in Quebec. Method A steering committee comprising older adults, caregivers, health professionals, policy makers, community representatives, and researchers oversaw this multimethod study. This committee selected 10 PtDAs based on relevance and quality from among 33 identified in a systematic review. We aimed to recruit 60 participants (older adults, caregivers, health professionals, policy makers and PtDA experts) using the snowball method for a 2-round eDelphi to prioritize the PtDAs. In the 1st round, participants ranked PtDAs according to criteria regarding the decision point (prevalence, difficulty, values and preferences, evidence update), with the importance of each criterion rated on a 5-point Likert scale. PtDAs with one or more criteria judged as important by at least 75% of participants were retained for a 2nd round using the same criteria. We expect to retain a maximum of 3 PtDAs for cultural adaptation to the Quebec health care system. Results Email and social media invitations generated 60 potential participants, 42 of whom completed the 1st eDelphi round. Participants were older adults (14.3%), caregivers (28.5%), healthcare professionals (30.9%), managers (16.7%), members of community organizations (4.8%) and PtDA experts (4.8%). Most were women (85.7%), aged 35 to 54 years (50.0%), urban residents (53.7%) and university-educated (42.9%). They prioritized 6 PtDAs for the 2nd round. The 2 criteria most frequently identified as important were decision difficulty and values and preferences. The 2nd Delphi round is being prepared. Discussion This study was developed in response to the decisional needs of older adults and their families. Conclusion Our findings will provide relevant, culturally appropriate PtDAs for older adults making difficult decisions in the province of Quebec.
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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 | 0.067 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".