Acceptability rate and barriers to COVID-19 vaccination among healthcare workers in Chukwuemeka Odumegwu Ojukwu University Teaching Hospital, Amaku-Awka, Nigeria
Why this work is in the frame
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Bibliographic record
Abstract
Background: Healthcare workers were at the forefront of the COVID-19 pandemic. The acceptability and uptake of COVID-19 vaccines among healthcare workers was an important strategy in halting the spread of the virus as well as the antecedent implications on global health and the world economy. Objectives: This study aims to determine the acceptability rate and barriers to COVID-19 vaccination of frontline healthcare workers in Awka, Nigeria. Design: This is an analytical cross-sectional study. Methods: An online cross-sectional survey was conducted from February 2022 to April 2022 to obtain the data for this study. One hundred healthcare workers were studied. Acceptability rate and barriers to uptake of COVID-19 vaccination were outcome measures. Results: The COVID-19 vaccination rate was 45.0% among healthcare workers in study area of Awka metropolis. Ages 30–39 years had the highest acceptance rate of COVID-19 vaccination, 19 (47.5%; p = 0.262) with a more female preponderance of COVID-19 vaccine acceptance compared to males [26 (41.3%) vs 16 (42.2%), p = 0.721]. The place of residence of respondents (urban vs rural) and their marital status (married vs single) appeared not to influence the acceptance of COVID-19 vaccination [(38 (42.2%) vs 3 (33.3%); p = 0.667; 25 (36.8% vs 17 (54.8%); p = 0.433)]. Years of work experience (<10 years vs >10 years) significantly affected COVID-19 vaccine acceptance [27 (45.8%) vs 12 (52.2%); p = 0.029]. Educational status and monthly income appeared not to influence vaccine uptake ( p > 0.05, for both). A significant number of respondents were not sure why they should or should not take the COVID-19 vaccine [49 (92.5%) vs 35 (83.3%); p = 0.001]. Conclusion: The COVID-19 vaccination rate is still poor among healthcare workers in Awka metropolis. The majority of respondents do not know why they should or should not take COVID-19 vaccine. We therefore recommend robust awareness campaigns that will explain in clear terms the essence and efficacy of COVID-19 vaccination in order to improve vaccine acceptance.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it