Antibiotic knowledge, attitudes and reported practice during pregnancy and six months after birth: a follow- up study in Lao PDR
Bibliographic record
Abstract
BACKGROUND: Antibiotics are important medicines to prevent maternal and child morbidity and mortality. Women's knowledge and attitudes towards antibiotic use influence their practice. When they become mothers, this may be mirrored in the use of antibiotics for their newborn children. The current study aimed to assess knowledge, attitudes, and reported practice of pregnant women regarding antibiotic use and antibiotic resistance as well as their approach towards antibiotic use for their newborn babies. METHODS: This was a follow-up study with data collected via structured interviews between September 2019 and August 2020 in Feuang (rural) and Vangvieng (urban) districts in Vientiane province, Lao PDR. We identified and invited all women attending antenatal care in their third trimester of pregnancy in the selected areas. Using a structured questionnaire at third trimester of pregnancy we captured data on knowledge regarding antibiotic use and resistance. We collected information on attitudes and reported practice at two time points: (i) at third trimester of pregnancy and (ii) 6 months after birth. Univariate analysis and frequency distributions were used to study pattern of responses. Chi-square and Mann-Whitney tests were used to compare categorical and continuous variables respectively. P value < 0.05 was considered statistically significant. RESULTS: We surveyed 539 women with a mean age of 25 years. Two oral antibiotics, i) ampicillin and ii) amoxicillin were correctly identified by 68 and 47% of participants respectively. Only 24% of women (19% in Feuang and 29% in Vangvieng) answered correctly that antibiotics are effective against bacterial infections. The most prevalent response was "I don't know" suggesting the questions were challenging. Significantly less women would use antibiotics from a previous illness for their child than for themselves (16% vs 29%), however they would be more willing to use antibiotics for their baby even in case of mild symptoms (29% vs 17% while pregnant). The majority of antibiotics were prescribed by healthcare providers and 46% of children with the common cold received antibiotics. CONCLUSIONS: Women's knowledge was sub-optimal, still, they manifested appropriate attitudes towards antibiotic use during pregnancy and for their child. Nearly half of children received antibiotics for the common cold. There is a need for context adapted programs aiming at improving women's knowledge, as well as healthcare providers, emphasising rational antibiotic prescribing during pregnancy and for children.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".