Knowledge, attitude and practice towards COVID-19 among pregnant women in Africa: A systematic review and meta-analysis
Bibliographic record
Abstract
Background Pregnant women and recent mothers face a higher risk of severe illness from Coronavirus disease 2019 due to physiological and immunological shifts during pregnancy, rendering them more vulnerable to inflammatory lung conditions. This susceptibility poses serious threats to both maternal and newborn health. Therefore, it is imperative for pregnant women to be fully informed about Coronavirus disease 2019 and to implement preventive measures. This study aimed to evaluate the collective knowledge, attitudes, and practices related to Coronavirus disease 2019 among pregnant women across Africa. Methods The researchers collected studies from multiple databases, including Pub Med/MEDLINE, EMBASE, CINAHL, Science Direct, Scopus, Web of Science, Cochran library, and Google Scholar. A combination of search terms and Boolean operators were utilized to gather relevant literature. Each study underwent quality assessment by five authors independently, using the modified Newcastle Ottawa Scale tailored for cross-sectional research. Statistical analysis was conducted using STATA™ Version 11 software, and meta-analysis was performed using the random-effects (Der Simonian and Laird) method. Heterogeneity was evaluated using I-squared (I 2 ) statistics, and a one-out sensitivity analysis was carried out. Results This systematic review and meta-analysis included 19 articles, involving a total of 7852 participants. It revealed that the combined estimated prevalence of good knowledge about Coronavirus disease 2019, positive attitudes, and good practices among pregnant women was found to be 61.8% (95% CI: 53.0%-70.65%; I 2 = 98.7%), 51.7% (95% CI: 30.34%-73.6%; I 2 = 99.3%), and 52.31% (95% CI: 41.48%-63.15%; I 2 = 98.8%) respectively. Conclusion This study emphasizes a significant concern: pregnant women exhibit a notable lack of knowledge, positive attitudes, and preventive practices regarding Coronavirus disease 2019. Considering their heightened vulnerability, urgent action is required to improve their understanding, attitudes, and behaviours related to the virus. Healthcare professionals should take proactive measures to educate pregnant women, addressing this crucial gap through various strategies..
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How this classification was reachedexpand
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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".