My paper is called ‘What causes COVID-19 vaccine hesitancy? Ignorance and the lack of bliss in the United Kingdom.’ and it was conducted by J Bullock, J.E Lane, & F.L Shults in 2022.
My paper is about vaccination hesitancy and knowledge in the COVID-19 pandemic. These both became increasingly prominent problems for all governments around the world due to Anti-vaxxer movements affecting the need to protect vulnerable populations.
The study aims to work out why people may or may not have taken the vaccinations that were offered. It uses many social factors in order to try and find trends between the populations which chose to either take or not take the vaccine. Later on in the study it also uses fake vaccine names to investigate people’s actual knowledge of vaccinations or if it has been warped. One of the main aims of this study was to look into social media’s effect on people’s choices and fears. They believed that different social media such as Twitter, Facebook and Instagram would have effects on people’s knowledge and willingness to take the vaccines
One of the main factors they study throughout is people’s willingness to take fake vaccines if they are from the US or UK, whereas their hesitations arise when the vaccines are labelled as coming from China or Russia. This helps to indicate whether it is foreign anxiety stopping people from taking vaccinations or if there are other social reasons behind decisions.
This is a preregistration of an extension project for the following study:
Bullock, J., Lane, J. E., & Shults, F. L. (2022). What causes COVID-19 vaccine hesitancy? Ignorance and the lack of bliss in the United Kingdom. Humanities and Social Sciences Communications, 9(1). https://doi.org/10.1057/s41599-022-01092-w
In my replication project I am focusing on the following argument made in the study:
The claim I have chosen to investigate is how age effects the likeliness to take unavailable or made up vaccinations. I believe this follows on nicely from the current study, as age will have an impact on where people receive their information from, especially in regards to social media. Age has been featured in many different studies on vaccine hesitancy. It has been found that vaccines are understood and approached differently depending on age group (Hudson and Montelpare, 2021).
For example, a study conducted by Troiano and Nardi (2021) found that 86.1% of students or 77.6% of the general population had decided to take a covid vaccination. Although both are fairly high, this presents an almost 10% difference in the likelihood of taking. Students in the UK are on a ratio of 4:1 in terms of them being under 21 compared to a “mature” student (above 21), therefore since their likelihood of choosing to vaccinate is high suggesting more of a willingness throughout younger age groups (Bolton, 2024).
A study into Influenza vaccinations, although not covid, did prove some interesting results on vaccinations. This study, conducted by Eilers et al (2017) found that people especially those over 60 were more likely to get the vaccination if it was only one dose, the disease has a high mortality rate and if side effects were not severe. These results do not bode well for likelihood to take covid vaccinations, especially ones that information is limited (not available) on.
I also think age will be interesting in relation to social media usage and how much it is believed and followed. It must be considered that different age groups will use different media more (Bontcheva, Gorrell and Wessels, 2013). For example, older age groups are much less likely to use social media than younger generations, especially apps like Instagram. This will mean their likelihood of finding the information of fake vaccination on social media will also vary with age.
Hypothesis: Age will have an impact on the likliness to take unavalible or made up vaccinations, with the middle ages being the least likely and the youngest and oldest being the most likely
Do you expect to get the same or different results from the original study? Why? I believe it will be interesting to see if Twitter and Instagram are still the biggest influences for all age groups or if it will vary depending. However, I do still believe they will have the biggest influence over all.
I will test the hypothesis using the same regression model applied in the original study. Simple OLS regression was used for each unavailable or made up vaccine and then complied into one larger table. I will do the same but add another independent variable of age.
Dependent variable(s): How strongly they agreed they would take the vaccine if offered. Ranked from 1-6. 1 was strongly agreed, 2 agreed, 3 slightly agreed, 4 slightly disagreed, 5 disagreed and 6 strongly disagreed.
Independent variables (IVs):
I will use the p value to determine if age is a statistically significant factor. If >0.05 it porves that age does have an impact, varying from the null hypothesis.
The only participants that were excluded from my analysis were the ones with NA answers to any of my independent or dependent variables. This was carried out by simply coding to remove any observations with NA in their answers.
I will be removing any participants with NA as one of their answers.
Possibly an investigation into age and the amount of usage of different social medias. It cannot just be assumed that age alone has an effect, as social media usage is likely to correlate with age.
This preregistration form was completed in the following R environment:
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## [17] bslib_0.6.1 yaml_2.3.8 rlang_1.1.3 jsonlite_1.8.8Bartlett J. (2021). OSF preregistration template.Rmd. GitHub (accessed 03/05/2023)
Bolton, P. (2024). Higher education student numbers. House of Commons Library, [online] (7857). Available at: https://commonslibrary.parliament.uk/research-briefings/cbp-7857/.
Bontcheva, K., Gorrell, G. and Wessels, B. (2013). Social Media and Information Overload: Survey Results. [online] Available at: https://arxiv.org/pdf/1306.0813 (Accessed 17 May 2024).
Bowman, S. D., DeHaven, A. C., Errington, T. M., Hardwicke, T. E., Mellor, D. T., Nosek, B. A., & Soderberg, C. K. (2020). OSF Prereg Template. https://doi.org/10.31222/osf.io/epgjd. OSF (accessed 03/05/2023)
Bullock, J., Lane, J. E., & Shults, F. L. (2022). What causes COVID-19 vaccine hesitancy? Ignorance and the lack of bliss in the United Kingdom. Humanities and Social Sciences Communications, 9(1). doi:https://doi.org/10.1057/s41599-022-01092-w
Eilers, R., de Melker, H.E., Veldwijk, J. and Krabbe, P.F.M. (2017). Vaccine preferences and acceptance of older adults. Vaccine, 35(21), pp.2823–2830. doi:https://doi.org/10.1016/j.vaccine.2017.04.014.
Hudson,A. and Montelpare, W.J. (2021). Predictors of Vaccine Hesitancy: Implications for COVID-19 Public Health Messaging. International Journal of Environmental Research and Public Health, 18(15), p.8054. doi:https://doi.org/10.3390/ijerph18158054.
Troiano, G. and Nardi, A. (2021). Vaccine hesitancy in the era of COVID-19. Public Health, 194(1), pp.245–251. doi:https://doi.org/10.1016/j.puhe.2021.02.025.