Addressing the needs of diverse and marginalised groups when implementing change in aged care: A scoping review
Bibliographic record
Abstract
Objective: This scoping review seeks to identify the extent and nature of the existing literature in relation to implementing change within aged care services catering for diverse and marginalised groups.Introduction: Innovating and implementing change in the aged care sector is integral to meeting future challenges. However, despite increasing diversity among the ageing population, older people accessing aged care services are often treated as a relatively homogenous group, leaving those with different needs and priorities with inappropriate or inadequate care. To implement change in the aged care sector successfully will require meeting the needs of a diverse ageing population. Understanding how change has been implemented with diverse groups of older people will help inform more inclusive and appropriate future implementation efforts in the sector. Inclusion criteria: This scoping review will include peer-reviewed primary studies, systematic and scoping reviews that focus on the implementation of best practice or innovation within aged care services that provide services for diverse and marginalised older people. Methods: This review will be conducted in accordance with JBI methodology for scoping reviews and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis for Scoping Reviews (PRISMA-ScR). The databases to be searched include PubMed, CINAHL, SCOPUS and PsycINFO. The search will be limited to articles published after December 31, 2012. Screening and data extraction will occur independently in duplicate. The review outcomes will be presented in tabular format and supported by a narrative summary.
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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 | 0.052 | 0.153 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.019 | 0.019 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".