Accessing Healthcare Services during Lockdown in an African Semi-urban Community: Influence of the Knowledge of COVID-19
Bibliographic record
Abstract
Aim: Since the covid-19 pandemic began, prevention and treatment services for non-communicable diseases have been significantly interrupted. This study assessed the influence of COVID-19 knowledge on using healthcare services during the lockdown in Nigeria.
 Methods: The study was a descriptive cross-sectional survey conducted in Ado-Odo Ota, local government areas, Ogun State, Nigeria using a structured questionnaire between January and February 2021. A multistage probability sampling technique was employed to collect data from 383 adults aged 20 – 60 years and the data were analyzed using IBM-SPSS version 25.0.
 Results: Although all respondents (100.0%) have heard of COVID-19, only 52.2% believed it was real. The respondents displayed poor overall knowledge of COVID-19 as only 32.1% were knowledgeable about it. Before the COVID-19 pandemic, 44.9% said they visited hospitals for treatment compared to 16.2% during the lockdown. The reasons for not using hospitals include the fear of taking a COVID-19 patient (38.4%) and buying medicines from pharmacies (33.9%). Those who used herbs constituted 20.6%, 15.4% could not afford service charges, 12.0% would pray or use spiritual materials instead, and 7.3% were afraid of being infected with the disease. Only 17.9% of those knowledgeable about COVID-19 would go to the hospital during the lockdown.
 Conclusion: Healthcare workers and the masses should be adequately trained on healthcare management during pandemics to avoid misconceptions about COVID-19. This will help improve access to healthcare services and promote wellbeing among the low-resource setting populations.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".