Relationships between Self-Efficacy and Post-Stroke Activity Limitations, Locomotor Ability, Physical Activity, and Community Reintegration in Sub-Saharan Africa: A Cross-Sectional Study
Bibliographic record
Abstract
Stroke self-efficacy is under-investigated in sub-Saharan Africa. In particular, studies focusing on the relationship between self-efficacy and post-stroke functional outcomes are scarce. This cross-sectional study aimed to explore the association between self-efficacy and post-stroke activity limitations, locomotor ability, physical activity, and community reintegration in Benin, a sub-Saharan African country. To achieve this purpose, a selection of stroke patients was made from the admission registers of the physiotherapy clinics (rehabilitation units) of three reference hospitals in Benin from January to April 2018. Stroke patients who were still continuing their rehabilitation sessions were informed by direct contact. Those who had already finished their sessions were informed by telephone. Sixty stroke patients of those contacted gave their consent and were recruited for this study. The sample consisted of 44 men and 16 women with a mean age of 56.7 ± 10.4 years. Activity limitations, locomotor ability, physical activity, community reintegration, and self-efficacy were self-reported using ACTIVLIM-Stroke, Abiloco-Benin, the Africa francophone version of the International Physical Activity Questionnaire (IPAQ-AF), the Reintegration to Normal Living Index (RNLI), and a French version of the Stroke Self-efficacy Questionnaire (SSEQ-F), respectively. Spearman’s rank correlation coefficients (ρ) were calculated to characterize the relationship between self-efficacy and activity limitations, locomotor ability, physical activity, and community reintegration. According to the results, self-efficacy showed a moderate correlation with physical activity (ρ = 0.65; p < 0.001) and high correlations with activity limitations (ρ = 0.81; p < 0.001), locomotor ability (ρ = 0.72; p < 0.001), and community reintegration (ρ = −0.84; p < 0.001). Thus, self-efficacy emerges as an important factor associated with the functional recovery of stroke patients in sub-Saharan 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".