Supporting decision making for individuals living with dementia and their care partners with knowledge translation: an umbrella review
Bibliographic record
Abstract
Living with dementia requires decision making about numerous topics including daily activities and advance care planning (ACP). Both individuals living with dementia and care partners require informed support for decision making. We conducted an umbrella review to assess knowledge translation (KT) interventions supporting decision making for individuals living with dementia and their informal care partners. Four databases were searched using 50 different search-terms, identifying 22 reviews presenting 32 KT interventions. The most common KT decision topic was ACP (N=21) which includes advanced care directives, feeding options, and placement in long-term care. The majority of KT interventions targeted care partners only (N=16), or both care partners and individuals living with dementia (N=13), with fewer interventions (N=3) targeting individuals living with dementia. Overall, our umbrella review offers insights into the beneficial impacts of KT interventions, such as increased knowledge and confidence, and decreased decisional conflicts.
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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 | 0.015 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.017 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| 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".