Unfavorable public attitude toward people with epilepsy in Ethiopia: A systematic review and meta‐analysis study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: This systematic review and meta-analysis aims to show the pooled prevalence of unfavorable public attitude toward people with epilepsy (UPATPWE) as well as the effect estimates of associated factors in Ethiopia. METHODS: Between December 1 and 31, 2022, we searched for the English version of published research reports on public attitude toward epilepsy in Ethiopia in PubMed/Medline, Science Direct, Cochrane Library, Google Scholar, and PsycINFO. The research reports' quality was assessed using the Newcastle-Ottawa Scale. We extracted the relevant information from the searched papers in a Microsoft Excel format and imported it to STATA version 15.0, for analysis. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) reports guideline was used. A random-effects meta-analysis model was used to estimate the Der Simonian and Laird's pooled prevalence of unfavorable public attitude and its associated factors. RESULTS: Nine out of the accessed 104 research papers meeting the pre-specified criteria were included in this study. The overall pooled prevalence of UPATPWE in Ethiopia is 52.06 (95% CI: 37.54, 66.59), resulting in excommunication, physical punishments, and assaults against people with epilepsy as well as frequent lack of diagnosis and proper treatment. The pooled effect estimates for witnessing a seizure episode were done and it was (AOR = 2.70 [95% CI: 1.13, 6.46]). SIGNIFICANCE: As interventions and new strategies to change attitudes and facilitate a supportive, positive, and socially inclusive environment for PWE may root in education and scientific research outputs, our result hopefully evokes the policy makers' attention for building a well-designed and comprehensive health education and campaign strategy.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.002 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it