Stroke Experiences and Unmet Needs of Individuals of African Descent Living in High-Income Economy Countries: a Qualitative Meta-Synthesis
Bibliographic record
Abstract
BACKGROUND: Stroke service disparities experienced by individuals of African descent highlight the need to optimize services. While qualitative studies have explored participants' unique experiences and service needs, a comprehensive synthesis is lacking. To address current knowledge gaps, this review aimed to synthesize existing literature on the experiences of individuals of African descent impacted by a stroke living in high-income economy countries in terms of stroke prevention, management, and care. METHODS: A qualitative meta-synthesis incorporating a meta-study approach was conducted to obtain comprehensive and interpretive insights on the study topic. Four databases were searched to identify qualitative English-language studies published in the year 2022 or earlier on the experiences of adults of African descent who were at risk or impacted by a stroke and living in high-income economy countries. Study methods, theory, and data were analyzed using descriptive and interpretive analyses. RESULTS: Thirty-seven studies met our inclusion criteria, including 29 journal articles and 8 dissertations. Multiple authors reported recruitment as a key challenge in study conduct. Multiple existing theories and frameworks of health behaviours, beliefs, self-efficacy, race, and family structure informed research positionality, questions, and analysis across studies. Participant experiences were categorized as (1) engagement in stroke prevention activities and responses to stroke symptoms, (2) self-management and self-identity after stroke, and (3) stroke care experiences. CONCLUSIONS: This study synthesizes the experiences and needs of individuals of African descent impacted by stroke. Findings can help tailor stroke interventions across the stroke care continuum, as they suggest the need for intersectional and culturally humble care approaches.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".