Understanding Practices and Support Needs of Family Caregivers of People with Dementia in Africa: A Scoping Review Protocol
Bibliographic record
Abstract
Extant literature has reported the challenges and stressors caregivers of people with dementia face globally. Local realities and contexts often shape these challenges. For example, in regions of Africa where the prevalence of caregiving is increasing, beliefs about dementia and limited infrastructures create unique challenges for caregivers, potentially restricting caregivers’ capacities. Yet directions for policy, practice, and research are often informed by research conducted in regions outside of Africa or fail to account for local contexts. This scoping review seeks to understand the knowledge base on regional differences and similarities in the experiences of caregivers supporting persons with dementia in the region of Africa. The review will be guided by Arksey and O’Malley’s five-stage- framework. Five databases: Ageline, MEDLINE, Social Science Abstract, Psych-Info, and African-wide information will be searched. Citations from these databases will be subjected to two levels of screening The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) will describe and document the inclusion and exclusion process. This scoping review will improve our understanding of unique practices and pressures experienced by caregivers of persons with dementia in different localities in Africa. It will also identify support needs and knowledge gaps in African region. Keywords: Dementia, Caregivers, Older Adults, Support Needs, Experiences
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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 | 0.076 | 0.055 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.011 | 0.013 |
| Bibliometrics | 0.017 | 0.012 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.051 | 0.009 |
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".