Exploring the lived experiences of family caregivers of patients with stroke in Africa: a scoping review of qualitative evidence
Bibliographic record
Abstract
OBJECTIVE: The burden of stroke is immense in African countries, with post-stroke care usually becoming the responsibility of family. This review sought to determine the current breadth and depth of qualitative evidence regarding the lived experiences of family caregivers of patients with stroke in Africa. METHODS: Informed by Joanna Briggs Institute (JBI) methodology for scoping reviews, six databases were searched. Included articles were appraised for quality using the JBI checklist. A priori themes developed using the study objectives were used to synthesize study findings. RESULTS: The review included 22 articles, which outlined key patterns in stroke outcomes with most articles focused on rehabilitation and the experiences, outcomes, burdens, and coping mechanisms of caregiving. The intersectionality of socio-economic status, socio-political structures, and religious or traditional beliefs, attitudes, and practices characterized etiology beliefs, treatment trajectories of stroke, and caregiving role assignment. Whereas burdens were driven by limited resources, adopted coping strategies involved spiritual or religious beliefs, optimism, resilience, and social support networks. CONCLUSIONS: Family caregivers' values must be acknowledged, supported, and integrated into the traditional healthcare system to provide comprehensive stroke care. Caregivers' health and well-being should be given more attention given their necessary contribution to stroke survivorship in Africa.
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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 | 0.017 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".