Using the International Classification of Functioning, Disability, and Health (ICF) to explore the experiences of family caregivers of stroke survivors in Burkina Faso: a qualitative study
Bibliographic record
Abstract
Purpose In Sub-Saharan Africa, family caregivers (FCs) almost systematically—and sometimes indefinitely—assist stroke survivors with activities of daily living and the stroke rehabilitation process. This study explored the experiences of FCs of stroke survivors in Burkina Faso.Materials and methods A descriptive qualitative study was conducted with FCs recruited through convenience sampling. Semi-structured interviews were recorded and transcribed verbatim. A deductive thematic analysis based on the ICF framework was performed.Results Eleven FCs (female: 7; male: 4) participated in the study. Four main themes were identified: (1) Health and well-being (impact on health and well-being, and coping strategies); (2) Activities related to the caregiving role and social participation (activities and social participation); (3) Environmental factors (social support and lack of social security); (4) Personal factors (skills and knowledge about stroke). Furthermore, the facilitators and barriers associated with the caregiving role were synthesized.Conclusion FCs, particularly the wives of stroke survivors, experienced a significant impact on their physical and emotional well-being due to their caregiving responsibilities. Social support helped alleviate the burden, while its absence increased distress. Improving health services and policies, and promoting awareness of stroke knowledge, appear to be important in strengthening support for FCs.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".