“We Live Our Life Normal”: A Qualitative Analysis of Nigerian Women’s Health-Seeking Behavior during the COVID-19 Pandemic
Bibliographic record
Abstract
BACKGROUND: This study examined where women sought healthcare during the COVID-19 pandemic and their reasons for doing so. We aim to understand further how women accessed care during the COVID-19 pandemic to inform future preparedness and response efforts. This knowledge gained from this study can inform strategies to address existing gaps in access and ensure that women's health needs are adequately considered during emergencies. METHODS: This study used an interpretive phenomenological-analysis approach to analyze data on women's experiences with healthcare in Nigeria as the COVID-19 pandemic progressed. Semi-structured interviews were conducted with 24 women aged 15 to 49 between August and November 2022 and were supplemented with three focus-group discussions. RESULTS: Following our analysis, three superordinate themes emerged: (i) barriers to seeking timely and appropriate healthcare care, (ii) the influence of diverse health practices and beliefs on health-seeking behavior, and (iii) gendered notions of responsibility and of coping with financial challenges. CONCLUSIONS: This paper examined women's decision to seek or not seek care, the type of care they received, and where they went for care. Women felt that the COVID-19 pandemic affected their decision to seek or not seek care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".