Challenges of PregnantWomen Accessing Focused Antenatal Clinic During Covid-19 Pandemic Lockdown in Wuse District Hospital, Abuja, Nigeria
Bibliographic record
Abstract
Background: Most maternal deaths are linked to pregnancy and childbearing. In an attempt to improve maternal and child health, World Health Organisation introduced focused Antenatal care (ANC). All the activities of the world were at a standstill at the outbreak of COVID-19 in 2020, including obstetric care. Aim: To explore pregnant women's challenges in accessing ANC in Wuse district hospital Abuja during the COVID-19 lockdown. Methods: A descriptive crosssectional survey was conducted among mothers attending ANC at Wuse District Hospital. A purposive sampling technique was employed to select 99 participants for the study. Data were collected via a semi-structured questionnaire and analyzed using descriptive statistics. Results: More than one-quarter (25.3%) were between the age range of 25-30 years, while 57.6% had tertiary education. Also, 80.8% of the participants lived outside the hospital environment, and 62.6% were either civil servants or self-employed. The findings reveal that most (78.8%) of the participants could not attend antenatal appointments as scheduled while only 21.2% could receive ANC at the appropriate time. Challenges of the participants in receiving ANC include closing down of the antenatal clinic because of COVID-19 (28.3%), the difficulty of movement due to COVID-19 lockdown (41.4%), unavailability of staff as they have been drafted into isolation centers (9%) and transport problem (21.2%). Conclusion: The majority of the participants could not attend ANC as recommended during the COVID-19 pandemic lockdown. Adequate provision needs to be provided for pregnant women to have access to quality healthcare during pandemics.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".