Knowledge, attitude and practice towards COVID-19 among pregnant women in a tertiary hospital in Pokhara, Nepal
Bibliographic record
Abstract
Introduction: The study was done to find out the knowledge, attitude, and practice of pregnant women towards COVID-19 in tertiary hospital of Pokhara, Nepal. Methods: A descriptive cross-sectional study was carried out among 385 pregnant women attending antenatal clinics of Gandaki Medical College starting from May 2021 to July 2021, by using self- administered questionnaire. The data was analyzed using statistical package for the social sciences version 21.0 and descriptive statistics were computed. Results: More than four‐fifths respondents were aware about COVID‐19. Half of them thought it transmits via human touch. One-fourth of them mentioned that delivery at the hospital during COVID-19 pandemic was unsafe. Almost half of them regretted conceiving, among which one quarter thought of aborting their fetus, half of them were against breastfeeding, and three-forth had regular antenatal care checkups. Majority of them took precautions to stay safe, where half of them responded that they would not breast fed baby if they got infected. Conclusions: Majority of the study population have good knowledge, attitude, and practice of COVID-19 disease. However, it is worrisome that some respondents thought of terminating her pregnancy, and some were unable to visit the hospital for routine antenatal care checkups and didn’t have proper knowledge about breastfeeding their child. Proper education must be given to the population to avert these negative attitudes while promoting a positive preventive attitude.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".