Utilisation des médicaments traditionnels chez les praticiens de la médecine conventionnelle au Burkina Faso
Bibliographic record
Abstract
INTRODUCTION: The integration of traditional medicine into biomedical health care practice is highly dependent on its acceptability by conventional medical practitioners. Its use by conventional practitioners was previously unknown in Burkina Faso. PURPOSE OF RESEARCH: The purpose of this study was to estimate the prevalence of traditional medicine use and the frequency of occurrence of adverse events associated with this use among conventional medical practitioners in Burkina Faso. RESULTS: The majority of the practitioners surveyed were women (56.1%) and the average age was 39.7±7 years. Nurses (56.1%), midwives (31.4%) and physicians (8.2%) were the most represented professions. The prevalence of the use of traditional medicines in the 12 months preceding the survey was 75.6%. Malaria was the main medical reason for using traditional medicines (28%). The frequency of reported adverse events was 10% and mainly concerned gastrointestinal disorders (78.3%). CONCLUSIONS: The majority of conventional medical practitioners in Burkina Faso use traditional medicines for their health problems. This finding suggests the effective integration of traditional medicine into biomedical health care practice which could benefit from good acceptability by these professionals.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".