THE PREGNANT FACTORS OF ANXIETY IN PREGNANT MOTHERS DURING THE COVID-19 PANDEMIC : A SYSTEMATIC REVIEW
Bibliographic record
Abstract
Introduction: The COVID-19 pandemic has a negative impact on the mental health of pregnant women. Women are prone to psychological problems such as fatigue, emotional disturbances, mood disorders and anxiety disorders. Anxiety of pregnant women must be prevented so as not to cause negative impacts on pregnant women and their fetuses. Objectives: The purpose of this study is to identify the triggers for anxiety in pregnant women during the COVID-19 pandemic based on a systematic review. Method: The method used to search in PubMed, ProQuest, Google Scholar with the publication year starting 2020-2021. The critical appraisal used is The Joanna Briggs Institute JBI. Results: 20 articles met the inclusion criteria. Research and studies were conducted in China, Iran, Canada, Turkey, Indonesia and the USA. Anxiety trigger factors are identified into 2, namely threats to physical integrity and threats to the integrity of one's own system. Threats to physical integrity consist of age, parity, physical activity, trimester of pregnancy, pregnancy complications, food availability, COVID-19 prevention efforts. Threats to the integrity of the self system consist of education, occupation, history of depression, unplanned pregnancy, family income, location of residence, presence of caregivers, health facility services, COVID-19 information, life partners, social support, counseling, telemedicine and insurance services. Discussion and conclusion: There are many factors that cause anxiety during a pandemic. There is a need for new identification to identify risk factors for anxiety in pregnant women so that more comprehensive prevention efforts can be carried out involving various health professions in the service.
 
 Keywords: Pregnancy, Anxiety Triggers, COVID-19
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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 | 0.027 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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".