Understanding data collection strategies for the ethical inclusion of older adults with disabilities in transitional care research: A scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: A growing body of evidence suggests that older adults are particularly vulnerable to poor care as they transition across care environments. Thus, they require transitional care services as they transition across healthcare settings. To help make intervention research meaningful to the older adults the intervention aims to serve, many researchers aim to study their experiences, by actively involving them in research processes. However, collecting data from older adults with various forms of disability often assumes that the research methods selected are appropriate for them. This scoping review will map the evidence on research methods to collect data from older adults with disabilities within the transitional care literature. METHODS: The proposed scoping review follows the framework originally described by the Joanna Briggs Institute (JBI) Manual: (1) developing a search strategy, (2) evidence screening and selection, (3) data extraction; and (4) analysis. We will include studies identified through a comprehensive search of peer-reviewed and empirical literature reporting on research methods used to elicit the experiences of older adults with disabilities in transitional care interventions. In addition, we will search the reference lists of included studies. The findings of this review will be narratively synthesized. The Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews will guide the reporting of the methods and results. DISCUSSION: The overarching goal of this study is to develop strategies to assist the research community in increasing the inclusion of older adults with disabilities in transitional care research. The findings of this review will highlight recommendations for research to inform data collection within future intervention research for older adults with disabilities. Study findings will be disseminated via a publication and presentations.
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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 | 0.362 | 0.349 |
| Meta-epidemiology (narrow) | 0.005 | 0.008 |
| Meta-epidemiology (broad) | 0.010 | 0.015 |
| Bibliometrics | 0.030 | 0.026 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.008 | 0.013 |
| Research integrity | 0.013 | 0.011 |
| Insufficient payload (model declined to judge) | 0.057 | 0.018 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".