• Users Online: 282
  • Print this page
  • Email this page


 
 Table of Contents  
ORIGINAL ARTICLE
Year : 2020  |  Volume : 3  |  Issue : 3  |  Page : 78-82

Triggering altruism increases the willingness to get vaccinated against COVID-19


Department IV, University of Trier, Trier, Germany

Date of Submission20-Jun-2020
Date of Decision07-Jul-2020
Date of Acceptance08-Jul-2020
Date of Web Publication27-Jul-2020

Correspondence Address:
Marc Oliver Rieger
University of Trier, 54296 Trier
Germany
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/SHB.SHB_39_20

Rights and Permissions
  Abstract 


Introduction: Once a vaccine against COVID-19 is available, the question of how to convince as many people as possible to get vaccinated will arise. We test three different strategies to reach this goal: two selfish motivations (highlighting personal survival risk or the inconveniences in the event of getting infected) and altruism (reducing the danger for individuals who cannot be vaccinated or remain vulnerable even after getting vaccinated). Methods: We conduct an online experiment with N = 303 subjects (64% female, 79% university students, average age 26 years) with the three aforementioned treatments and compare the treatment effects on vaccination willingness with the baseline. Results: Results suggest a positive effect of all treatments, but the treatment where reducing the danger for individuals who cannot be vaccinated was highlighted was by far the most effective. Conclusion: This result implies that this rarely discussed aspect should be given more attention to increase the willingness to get vaccinated against COVID-19.

Keywords: COVID-19, SARS-CoV-2, vaccination


How to cite this article:
Rieger MO. Triggering altruism increases the willingness to get vaccinated against COVID-19. Soc Health Behav 2020;3:78-82

How to cite this URL:
Rieger MO. Triggering altruism increases the willingness to get vaccinated against COVID-19. Soc Health Behav [serial online] 2020 [cited 2020 Nov 24];3:78-82. Available from: https://www.shbonweb.com/text.asp?2020/3/3/78/290981




  Introduction Top


The current COVID-19 pandemic will likely remain a public health concern until a vaccine against SARS-CoV-2 is widely available. Availability of the vaccine, however, is not the only hurdle: there also has to be enough willingness among the population to get vaccinated or, alternatively, a consensus on mandatory vaccination. This hurdle has already been studied in connection with other diseases[1],[2] and, in particular, for the H1N1 pandemic in 2009/2010.[3] In case of COVID-19, first survey results by Neumann-Böhme et al.[4] indicate a fairly large but not an overwhelming willingness to get vaccinated against COVID-19, with rates ranging between 62% and 80%. In a US survey, Thunstrom et al. find similar rates.[5] There are also some differences regarding age and gender that are studied in the EU sample, but they are not as substantial as one would expect (65%–75% for women and 73%–82% for men).

To reach herd immunity, it is important to increase these rates as much as possible. Thunstrom et al. estimate that with current vaccination willingness rates in the US, herd immunity would probably not be achievable.[5] While a mandatory vaccination seems to be the easiest way to solve this problem, in many democratic countries, it is unlikely to be implementable, simply due to political reasons. Therefore, it is of utmost importance to adopt efficient strategies to increase the willingness to get vaccinated. Here, social science can play an important role in identifying and testing such strategies.[6],[7]

The problem is essentially similar to other measures that have already been implemented to curtail the disease, in particular, enforcing social distancing and wearing face masks: these measures were also met with opposition, and compliance was and still remains an issue.[8],[9]

In this article, we present results from an online experiment with N = 303 (mostly young participants) that tested three different strategies to increase the willingness to get vaccinated against COVID-19 (similar experiments have previously been conducted for other diseases to test factors influencing vaccination willingness, e.g., Brown et al.[10]). The results suggest that triggering altruistic behavior by highlighting the danger for persons who cannot get vaccinated, and thus implying an indirect positive effect of vaccination in protecting these people, is the most promising strategy. This connects to a rich literature on motivations for altruistic behavior and its impact on subjective well-being.[11],[12]

The article is structured as follows: Section 2 summarizes the survey methodology, Section 3 presents the empirical findings, and Section 4 concludes.


  Methods Top


We conducted the online experiment between May 17 and June 6, 2020. The survey was conducted on Unipark and was advertised at two German universities (in Trier and Magdeburg). The study was approved by Trier University statutes of the ethic committee (Ref Code: Trier, 02.06.2020 VP M-F/MC). The participants were, therefore, mostly university students and employees. Of the total 331 participants, after removing incomplete and inconsistent responses, 318 responses remained for further analysis, 303 of which contained responses to all the relevant questions. Demographic characteristics of the participants are summarized in [Table 1]. While the sample was not representative, it covers a broad range of the population, in particular, many young people who might be more reluctant to get vaccinated, given the statements that COVID-19 poses a significantly greater risk to older adults (corresponding to the very age-dependent mortality rate).
Table 1: Sample characteristics for the two surveys

Click here to view


We used a within-subject design to measure the impact of a treatment and a between-subject design to compare the efficiency of the different treatments: all subjects were asked three initial questions about vaccinations [Table 2]. All subjects who did not state that they would “definitely” get vaccinated (N = 180) were then randomly assigned to one of the three treatment groups [Table 3] using the automatic random assign function of Unipark. In each treatment, after being asked to read an information text (specific to the treatment), participants were once again asked about their willingness to get vaccinated, once a vaccine would be available.
Table 2: List of the initial questions on COVID-19 vaccination

Click here to view
Table 3: List of the “convincing” texts in the three treatment groups

Click here to view


After being asked to read the text, the subjects could once again state their willingness to get vaccinated (no, definitely not/probably no/probably yes/yes, definitely).

The text in the first treatment tried to evoke altruistic motives by explaining that some people cannot get vaccinated or remain vulnerable even after getting vaccinated and that they could get infected or even die. Getting vaccinated would mean reducing the risk of infection of these people. Vaccination is in this case an altruistic act. The other two texts, instead, triggered selfish motivations. In Treatment 2, the focus was on the fact that even younger adults who are not in high-risk groups may die of COVID-19. Thus, a vaccination will also be beneficial for them. Treatment 3 stressed the inconveniences that an infection may cause, even if these are not major inconveniences (having to go to hospital or being sick for a week).

In the following, we will study whether the treatments had an effect on the willingness to get vaccinated (among subjects) and whether there were significant differences between the three treatment groups (altruistic, selfish/mortality risk, and selfish/inconvenience).

Besides the demographic items and the questions concerning vaccination, the survey had a number of other COVID-19-related items that are not discussed in the present study.


  Results Top


Descriptive results

We first measured what participants thought about vaccination before the treatment. [Table 4] shows that they expected a vaccine to be available in the spring of 2021; the average participant would “probably” get vaccinated once the vaccine was available and he/she had a slightly positive opinion on mandatory vaccination.
Table 4: Descriptive results of pretreatment answers for all subjects and the subsample of nonstudents

Click here to view


We compared the results for university students (N = 243) and others (N = 60) but did not find statistically significant differences.

Treatment effects

Next, we studied the difference between the three treatments. We measured the willingness to get vaccinated on a scale from 1 (definitely not) to 4 (definitely yes) and defined the “change” as the difference between willingness after and before the treatment.

First, we found a significant difference in the overall willingness across the three treatments, but a particularly large effect for Treatment 1 [Table 5]. While 42.4% of the participants in Treatment 1 expressed an increased willingness to get vaccinated, only 15.4% and 19.0% of the participants did this in Treatment 2 and 3, respectively. In total, our treatments still had an average effect on 25% of the participants.
Table 5: Treatment effects on the willingness to get vaccinated are significantly positive for all treatments, but particularly large for Treatment 1

Click here to view


The difference between Treatment 1 and the other two treatments was also significant after controlling for age, gender, student status, and university degree where we used an OLS regression (P < 0.001). We mention that other variables in the regression were not significant on a 5% level, i.e., we did not find any evidence that some demographic group might be differently affected by the treatments. We, therefore, concluded that Treatment 1 seems to be, in general, the most effective choice.

Relationship between voluntary, mandatory vaccination, and estimated time of vaccine availability

Opinions on mandatory vaccination and the willingness to get vaccinated (elicited before the treatment) were – as had to be expected – highly correlated (Pearson's correlation 0.67, Spearman's rho 0.65, for both P < 0.001). [Table 6] gives an overview on the willingness to get vaccinated of people with different opinions, regarding mandatory vaccination, and how people expressing different degrees of willingness to get vaccinated think of a mandatory vaccination. In general, there are very few people who deviate from the diagonal line of [Table 6], and if they do, then in the direction of getting vaccinated themselves, but not favoring a mandatory vaccination.
Table 6: Relation between vaccination willingness and opinions on mandatory vaccination

Click here to view


We did not find any significant relation between the estimates on the availability of a vaccine and the willingness to get vaccinated.

[Table 6] on the top shows the distribution of participants expressing different degrees of acceptance with regard to mandatory vaccination; [Table 6] on the bottom shows the distribution of participants with different degrees of vaccination willingness.


  Conclusion Top


Once a vaccine against COVID-19 is available, we will have to find a way to convince as many people as possible to get vaccinated if we want to stop the spread of the disease and the need for ongoing restrictions with their high social and economic costs. Our study gives some first empirical evidence on the strategies that might help achieve this goal. The best approach seems to be to explain the risks that unvaccinated individuals may present to others, and in particular, to individuals who remain vulnerable even if they get vaccinated. More than 40% of the participants expressed an increased willingness to get vaccinated after this treatment. Pointing out that people who do not belong to a high-risk group may also face complications, also increased the willingness to get vaccinated, but to a lesser degree. Still, 15%–19% of the participants expressed an increased willingness to get vaccinated following these treatments.

All in all, we see that providing reasonable information can increase the willingness to get vaccinated, and we also see that some information (protection of others) works particularly well. We, therefore, suggest putting the emphasis on the altruistic idea of protecting others in the process of convincing people to get vaccinated against COVID-19.

This study is, of course, only a first empirical test. While we do not find evidence for significant differences between students and nonstudents in our sample, repeating the experiment with a more balanced population would definitely be worthwhile. Moreover, there are more interventions possible that could be tested. We hope that our study can motivate further research in this direction and that it will help develop effective strategies for increasing vaccination rates once a vaccine is available.

Acknowledgment

I thank my student assistants Yanping He and Karine Nanyan for their help with the survey and the preparation of this manuscript.

Financial support

Financial support by the state of Rhineland-Palatinate through the research initiative “Transculturality” at the University of Trier is gratefully acknowledged.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Kata A. Anti-vaccine activists, Web 2.0, and the postmodern paradigm—An overview of tactics and tropes used online by the anti-vaccination movement. Vaccine 2012;30:3778-89.  Back to cited text no. 1
    
2.
Larson H, de Figueiredo A, Karafillakis E, Rawal M. State of vaccine confidence in the EU 2018. Luxembourg: European Union; 2018.  Back to cited text no. 2
    
3.
Blasi F, Aliberti S, Mantero M, Centanni S. Compliance with anti-H1N1 vaccine among healthcare workers and general population. Clin Microbiol Infect 2012;18:37-41.  Back to cited text no. 3
    
4.
Neumann-Böhme S, Varghese NE, Sabat I, Barros PP, Brouwer W, van Exel J, et al. Once we have it, will we use it? A European survey on willingness to be vaccinated against COVID-19. Eur J Health Econ 2020. doi: https://doi.org/10.1007/s10198-020-01208-6.  Back to cited text no. 4
    
5.
Linda T, Madison A, David F, Stephen N, Hesitancy Towards a COVID-19 Vaccine and Prospects for Herd Immunity. SSRN Working paper. 2020. doi: http://dx.doi.org/10.2139/ssrn.3593098.  Back to cited text no. 5
    
6.
Bavel JJ, Baicker K, Boggio PS, Capraro V, Cichocka A, Cikara M, et al. Using social and behavioural science to support COVID-19 pandemic response. Nat Hum Behav 2020;4:460-71.  Back to cited text no. 6
    
7.
Lin CY. Social reaction toward the 2019 novel coronavirus (COVID-19). Soc Health Behav 2020;3:1-2.  Back to cited text no. 7
  [Full text]  
8.
Rieger MO, Wang M. Secret erosion of the “lockdown” ? Patterns in daily activities during the SARS-CoV2 pandemics around the world. Rev Behav Econom 2020;7. doi: http://dx.doi.org/10.1561/105.00000124.  Back to cited text no. 8
    
9.
Rieger MO. To wear or not to wear? Factors influencing wearing face masks in Germany during the COVID-19 pandemic. Soc Health Behav 2020;3:50-4.  Back to cited text no. 9
  [Full text]  
10.
Brown DS, Johnson FR, Poulos C, Messonnier ML. Mothers' preferences and willingness to pay for vaccinating daughters against human papillomavirus. Vaccine 2010;28:1702-8.  Back to cited text no. 10
    
11.
Post SG. Altruism, happiness, and health: It's good to be good. Int J Behav Med 2005;12:66-77.  Back to cited text no. 11
    
12.
Moynihan DP, deLeire T, Enami K. A life worth living: Evidence on the relationship between prosocial values and happiness. Am Rev Public Adm 2015;45:311-26.  Back to cited text no. 12
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]


This article has been cited by
1 Threat, Coping, and Social Distance Adherence During COVID-19: Cross-Continental Comparison Using an Online Cross-Sectional Survey
Abrar Al-Hasan,Jiban Khuntia,Dobin Yim
Journal of Medical Internet Research. 2020; 22(11): e23019
[Pubmed] | [DOI]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
Abstract
Introduction
Methods
Results
Conclusion
References
Article Tables

 Article Access Statistics
    Viewed750    
    Printed39    
    Emailed0    
    PDF Downloaded159    
    Comments [Add]    
    Cited by others 1    

Recommend this journal