COVID-19 vaccine hesitancy among Nigerian youths: Case study of students in Southwestern Nigeria
Bibliographic record
Abstract
BACKGROUND AND AIM: Vaccination has been appraised to be one of the most significant public health achievements in human history. However, in countries like Nigeria, vaccine hesitancy is a public health challenge that has consistently forestalled concerted efforts made by health authorities to curb the spread of communicable diseases such as COVID-19. To improve COVID-19 vaccine acceptance via targeted interventions, it is imperative to examine the public's perception. Thus, this study aims to evaluate vaccine hesitancy among university students in Southwestern Nigeria. MATERIALS AND METHODS: The study utilized a descriptive cross-sectional design. A self-administered questionnaire was administered to a total of 366 respondents who were recruited using the convenience sampling technique and snowball approach. Data were entered and analyzed using SPSS. RESULTS: The majority of the respondents were over 18 years (88%) and were between their first and third years (81%). Over a tenth of the respondents reported having at least a loved one that had tested positive for the virus, while only 88% believed the virus is real. Furthermore, only 17% of the students had a positive attitude toward the vaccine. Although 90% of the respondents were aware of the administration of COVID-19 vaccine in Nigeria, only around a quarter were willing to take the vaccine, while 5.5% had been vaccinated. The major reasons for COVID-19 vaccine hesitancy highlighted by the respondents were concerns about vaccine side effects (21.3%), lack of trust in the authorities (26.5%), vaccine efficacy (13.1%), and diverse mystical possibilities (39.1%). CONCLUSION: The results indicate that a significant communication gap exists between the respondents and local health authorities. To enhance the acceptance of COVID-19 vaccines, extensive and targeted health promotion campaigns are required to allay specific concerns raised by the public.
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 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".