Strategies for engaging senior citizens and their informal caregivers in health policy development: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Care for senior citizens is a global policy issue. There has been limited focus on senior citizen and informal caregiver engagement in policy development. Encouraging senior citizen participation through active engagement in the policymaking process enhances the provision of better services and the creation of responsive policies and is critical to better healthcare. Accordingly, this review aims to map the available evidence to provide an overview of strategies for engaging senior citizens and informal caregivers in health policy development. METHODS AND ANALYSIS: A scoping review will be conducted. This study will use the updated methodological guidance for conducting a scoping review developed by the Joanna Briggs Institute. This review aims to answer the question: 'What is known in the literature about strategies for engaging senior citizens and informal caregivers in health policy development?' Titles and abstracts will be screened to determine eligibility for full-text review based on already established eligibility criteria. Data will be extracted from relevant articles. A summary of extracted data will be presented. The results will be interpreted within the Multidimensional Framework for Patient and Family Engagement in Health and Healthcare. ETHICS AND DISSEMINATION: Ethical review is not required as scoping reviews are a form of secondary data analysis that synthesises data from publicly available sources. Findings from this proposed review will be disseminated in conferences and to the global scientific community through published academic papers in reputable health policy-related journals.
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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 | 0.157 | 0.111 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.009 | 0.012 |
| Bibliometrics | 0.019 | 0.015 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.068 | 0.017 |
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".