Urinary incontinence in Africa: Experiences of women and healthcare workers in Nigeria and Kenya and opportunities for expanding care
Bibliographic record
Abstract
Urinary incontinence (UI) is prevalent among women worldwide, however perspectives from African women with UI and healthcare workers (HCWs) involved in their care are lacking. To understand UI in Africa through the perspectives of women with UI and HCWs to inform effective, accessible, and patient-centered treatment. A total of 175 participants were interviewed August—September 2023 about the healthcare environment, digital health, and UI care, management, and treatment options in this qualitative study: 88 women with UI (37 Nigerian, 51 Kenyan) and 87 HCWs (29 Nigerian, 58 Kenyan). All participants provided written informed consent; the study was approved by institutional and national ethics’ committees in Nigeria and Kenya. Amongst women: •Health literacy, cultural and religious beliefs, and healthcare system interactions influence healthcare decision-making •UI symptoms are frustrating; education, treatment and dismantling of stigma are desired •Lack of awareness of UI as a medical condition is pervasive and care-seeking is extremely low Amongst HCWs: •Recognition that UI is a burdensome and highly prevalent medical condition that is underdiagnosed and undertreated •Gaps identified, including training needs, prevalence studies and other research, and national guidelines for fistulous and non-fistulous incontinence This research highlights the pervasive and distressing nature of UI among women in two African countries. Despite high prevalence, low health-seeking behaviors persist. Sensitization efforts focused on pelvic health and UI could improve health literacy. Cultural values of community and collective responsibility could serve as enablers for raising awareness and encouraging treatment-seeking. Expanding research and training in UI management and access to treatment could strengthen healthcare systems in these settings.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 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".