Prevalence, determinants and attitude towards herbal medicine use in the first trimester of pregnancy in Cameroon: A survey in 20 hospitals
Bibliographic record
Abstract
To examine the prevalence, determinants and attitude towards herbal medication (HM) use in the first trimester of pregnancy in Cameroon women. Between March to August 2015, we surveyed 795 pregnant women attending 20 randomly selected urban or rural hospitals in South West Cameroon on first trimester orthodox medication (OM) and HM use. Data was obtained by interviews using structured questionnaires. First trimester HM use was reported by 293 (36∙9%) women, 76% of whom used it in combination with OM. The most frequent indication for taking HM was prevention/treatment of anaemia (26∙3%). The HM were usually self-prescribed (33∙3%) or by family (56∙2%), and obtained from the woman's own garden (69∙3%). Twenty percent of women believed that HM was always safe to take in pregnancy, compared to 69.3% for OM. Intake of HM was significantly influenced by women's opinion on OM or HM safety-the odds of taking HM was 3 time higher among women who were unsure about the safety of OM (AOR: 3∙0, 95%CI = 1∙5-6∙1), while women who thought HM were never safe or who were unsure about its safety, were 91% or 84% respectively less likely to take HM compared to women who believed HM were always safe. We identified a high prevalence of HM use and concomitant use with OM, strongly influenced by women's perception of HM and OM safety. These findings indicate the need for WHO to specifically address safety in pregnancy in its policy to integrate traditional medicine use into existing healthcare systems in 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 | 0.001 | 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) | 0.002 | 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".