Supported decision-making with persons with dementia: a scoping review protocol in partnership with lived experts
Bibliographic record
Abstract
INTRODUCTION: The United Nations Convention on the Rights of Persons with Disabilities asserts that all persons with disabilities have the right to receive the support they require to participate in decisions that affect them. Yet, persons with dementia continue to be excluded from decisions on issues that matter to them. Our planned scoping review seeks to address this gap by documenting the current knowledge on supported decision-making for persons with dementia and informing the next steps for research and practice. METHODS AND ANALYSIS: We will use Arksey and O'Malley's (2005) six-stage framework to guide our review of the English scientific literature (2005 onwards), searching the following databases: MEDLINE, PsycINFO, CINAHL, AgeLine and the Social Science Abstracts. Our review will focus on primary studies examining supported decision-making for persons with dementia, including the voices of those with dementia. Guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews, we will identify (1) domains of supported decision-making discussed in the empirical literature and (2) practices/factors that facilitate or inhibit supported decision-making. Consultations with persons with dementia and their care partners will provide insights into lived experiences, helping identify gaps between research literature and lived realities. The preliminary title and abstract search for eligible articles were conducted between August and October 2023 and updated in June 2024, yielding 56 eligible articles for review. ETHICS AND DISSEMINATION: This scoping review will be conducted following the standards of the Tri-Council Policy Statement for Ethical Conduct for Research Involving Humans (1998 with 2000, 2002 and 2005 amendments). The procedures for eliciting feedback from persons with dementia and their care partners were approved by the Office of Research Ethics Board at McGill University (Reference # 23-08-048). Dissemination of review findings to persons with dementia and care partners will occur during ongoing community consultations. Visual aids and brief lay summaries will be used to facilitate input and dialogue. Dissemination to the broader practice and research communities will include workshops conducted in collaboration with study partners and presentations and publications in peer-reviewed forums.
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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 | 0.189 | 0.154 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.015 | 0.014 |
| Bibliometrics | 0.025 | 0.023 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.008 | 0.011 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.061 | 0.015 |
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".