Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Virtual reality reduces COVID-19 vaccine hesitancy in the wild: a randomized trial

Abstract

Vaccine hesitancy poses one of the largest threats to global health. Informing people about the collective benefit of vaccination has great potential in increasing vaccination intentions. This research investigates the potential for engaging experiences in immersive virtual reality (VR) to strengthen participants’ understanding of community immunity, and therefore, their intention to get vaccinated. In a pre-registered lab-in-the-field intervention study, participants were recruited in a public park (tested: \(n = 232\), analyzed: \(n = 222\)). They were randomly assigned to experience the collective benefit of community immunity in a gamified immersive virtual reality environment (\(\frac{2}{3}\) of sample), or to receive the same information via text and images (\(\frac{1}{3}\) of sample). Before and after the intervention, participants indicated their intention to take up a hypothetical vaccine for a new COVID-19 strain (0–100 scale) and belief in vaccination as a collective responsibility (1–7 scale). The study employs a crossover design (participants later received a second treatment), but the primary outcome is the effect of the first treatment on vaccination intention. After the VR treatment, for participants with less-than-maximal vaccination intention, intention increases by 9.3 points (95% CI: 7.0 to \(11.5,\, p < 0.001\)). The text-and-image treatment raises vaccination intention by 3.3 points (difference in effects: 5.8, 95% CI: 2.0 to \(9.5,\, p = 0.003\)). The VR treatment also increases collective responsibility by 0.82 points (95% CI: 0.37 to \(1.27,\, p < 0.001\)). The results suggest that VR interventions are an effective tool for boosting vaccination intention, and that they can be applied “in the wild”—providing a complementary method for vaccine advocacy.

Introduction

Vaccination against most infectious diseases is an individual decision with positive externalities. That is, when individuals get vaccinated, they not only protect themselves, but typically also limit the probability that they will transmit the disease to others1. As such, even unvaccinated citizens can be indirectly protected from infection, known as community immunity or herd immunity1. With regard to the COVID-19 pandemic, it has been estimated that 60–90% of the population needs to be vaccinated (depending, for instance, on the vaccine’s efficacy) to stop the spread of SARS-CoV-22,3. Therefore, vaccine hesitancy—defined as “the delay in acceptance or refusal of vaccination despite availability of vaccination services”4—is a key obstacle to ending the COVID-19 pandemic.

Vaccine hesitancy is complex and may be affected by several factors5,6: lack of confidence (i.e., the tendency to trust in the safety and effectiveness of vaccines and to trust health authorities and experts who develop, license, and recommend vaccines), complacency (i.e., low perceived risk of infectious diseases), constraints (i.e., structural or psychological barriers in daily life that make vaccination difficult or costly), calculation (i.e., the degree to which personal costs and benefits of vaccination are weighted), lack of collective responsibility (i.e., the willingness to protect others and eliminate infectious diseases), lack of compliance (i.e., the support for societal monitoring and sanctioning of people who are not vaccinated), and conspiracy (i.e., conspiracy thinking and belief in fake news related to vaccination). Accordingly, fully informed vaccination decisions require that people know and understand the individual costs and benefits of a vaccination, as well as its collective benefit.

In line with the assumption that people care not only about their own but also about others’ welfare, informing them about community immunity has sometimes (e.g.,7) but not always (e.g.,8) been shown to increase vaccination intentions (for a review, see9). Interactive simulations have been particularly effective in increasing vaccine intentions10,11,12, potentially because they are more engaging13 and, therefore, increase people’s learning motivation10,14. In other words, using novel technologies that help people to better understand the collective benefit of vaccination-and the impact that their own vaccination may have on (vulnerable) others—may be a promising strategy to increase collective responsibility and, in turn, decrease vaccine hesitancy15.

Building on these findings, in this study we investigate whether vaccination intention is increased by a gamified immersive VR experience showing how community immunity works. Immersive VR is a promising medium for health communication (cf.16), because compared to other media it facilitates a high level of presence (the feeling of being in the virtual environment)17 and agency (the psychological experience of controlling one’s own actions)18, which results in higher levels of enjoyment and engagement19,20. Still, it has only just started to be tested as a tool for vaccine advocacy, with one study showing no significant impact on vaccination intentions21, and a second study finding a noticeable effect22.

In our VR simulation, participants must either try not to infect other non-player characters in a virtual scene, or try not to get infected by them. All participants play two scenarios—starting with an environment in which few characters are vaccinated, followed by an environment where many characters are vaccinated. The simulation thus allows participants to experience community immunity from a first-person perspective, learning how much more slowly infection spreads when vaccination rates are high versus low. Moreover, by using gamification in an immersive VR simulation, participants are likely to be motivated and engaged with the learning content18,23. We compare the effectiveness of this simulation against a typical information treatment using text and images.

We hypothesized that:

  1. H1.

    Vaccination intention increases after the VR treatment.

  2. H2.

    Vaccination intention increases more after the VR treatment than after the text-and-image treatment.

  3. H3.

    Collective responsibility increases after the VR treatment.

  4. H4.

    Collective responsibility increases more after the VR than than after the text-and-image treatment.

Method

The design and analysis plan of this randomized control trial was preregistered on 03/06/2021, prior to accessing any data. See https://osf.io/cjgfe/?view_only=ac57eafb9fe54ed8bcd9d3bee16cc8a4 for the anonmyized plan. Registration DOI is https://doi.org/10.17605/OSF.IO/WUFXK. Unless otherwise noted, all steps below follow the pre-registration plan. The full study procedure was approved by the Institutional Review Board at the Psychology Department, University of Copenhagen. The study was performed in accordance with the ethical standards of the Declaration of Helsinki (1964) and its subsequent amendments. Informed consent was obtained from all participants.

Recruitment

Participants (tested: \(n = 232\), analyzed: \(n = 222\)) were 207 passersby recruited in a public park in Copenhagen during the first weekend in June 2021, plus 15 passersby recruited one week earlier on campus at the University of Copenhagen. All adults with basic understanding of English were eligible. The sample size was determined by the number of passersby who agreed to participate during the pre-registered study period. Respondents (aged 18 to 63) participated in exchange for drinks and snacks. Table 1 contains key descriptive statistics.

Table 1 Characteristics of the analyzed study sample (\(n=222\)).

Design

After filling out a pre-treatment questionnaire, \(\frac{2}{3}\) of the participants were randomly assigned to the VR treatment. The other \(\frac{1}{3}\) were randomly assigned to read a text and see images explaining community immunity. All participants then filled out a post-treatment questionnaire. Finally, all participants also received the treatment they had not been assigned to initially (VR or text-and-image), and filled out a second post-treatment questionnaire (crossover design). Figure 1 shows the trial profile.

Figure 1
figure 1

Trial profile showing flow of participants into treatment arms and analyses. Because participants largely self-administered the questionnaires and treatments, needing assistance only to start up the VR simulation, dropout reasons are sometimes unknown.

Below, we detail the content of both treatments: the VR simulation and the text-and-image treatment.

VR

In the VR treatment, participants wore an Oculus Quest headset for a 5–10 min simulation developed at SIPLAB (ETH Zurich). They were embodied as an older character matching their gender. They were told that their character is vulnerable to COVID-19.

Participants were randomly assigned to one of two versions of the VR simulation. In the avoid spreading version, the player character (“avatar”) is already infected and the player must try not to infect others. In the avoid infecting version, the player character is uninfected and the player must try not to be exposed to infected characters.

In a first step, a tutorial showed the mechanics of the game. There were healthy-and-unvaccinated, infected (red clothing) and healthy-and-vaccinated (blue clothing) characters in the environment. Infected characters could spread the disease when coming too close to a healthy-and-unvaccinated character. Close contact was defined as a 2 m radius around the character.

In a second step, participants were tasked with crossing a busy square to reach a marked destination, while avoiding contact with the other 130 characters in the square. In the first scenario, they did so in an environment where 20% of the virtual characters were vaccinated. In the second scenario, they crossed the busy square again, but with 70% of the characters being vaccinated. Instructions clarified that the difference between the two scenarios was the avatars’ vaccination rate.

When participants came into close contact with a character (infecting them or being exposed to their infection), they were made aware through graphics and haptic feedback (vibrating controllers). A small graph also helped them see how the disease spread between characters in the square, increasing the count of infected characters as they moved through the scenario. Figure 2 shows the square scene and spreading graph.

Figure 2
figure 2

The busy square scene in VR, with feedback graph showing the number of infected, healthy and vaccinated characters.

Text-and-image

The alternative treatment, using text and images, displayed the definition of community immunity by the US Centers for Disease Control and Prevention24, followed by two pictures (adapted from10) with captions. The pictures represented communities where few or many people are vaccinated. Captions explained that in a low-vaccination community, many healthy but unvaccinated people are at risk of infection. In a high-vaccination community, few are at risk.

Both the VR and text-and-image treatment ended with a brief summary, highlighting the takeaway message (“As you can see, when many people are vaccinated the virus does not spread as fast and it creates a world that is safer for everyone. You can see the difference in [...] the low and high vaccination scenarios”). A more detailed description of both treatments, including video, can be found in the study repository (https://osf.io/wufxk/?view_only=56e83d061c6d469fb6378d29c2940a4a).

Randomization and masking

Simple randomization between treatment orderings (VR first or text first) happened within the Qualtrics survey software. Random assignment to a version of the VR simulation (avoid spreading or avoid infection) was tied to participants’ ID numbers (even or uneven), which were allocated consecutively to both VR-first and text-first participants. Experimenters only assisted participants in starting up the VR simulation. They were blind to both the treatment ordering and the VR simulation version that each participant was assigned to.

Outcome measures

Two key measurements were taken before and after participants’ first treatment, as well as after their second treatment: First, vaccination intention for a hypothetical new COVID-19 strain was assessed (0–100 scale; adapted from10). This primary outcome measure was pretested in a pilot study available in the supplemental material. Second, seeing COVID-19 vaccination as a collective responsibility was assessed (1–7 scale)5. The supplemental material details the wording of these two items, and all other measures collected in the study.

All preregistered hypotheses are about the effect of the participants’ first treatment on the two outcome measures, either the VR treatment or the text-and-image treatment. The supplemental material section describes the models used to test these hypotheses; they are simple regressions of first differences in the outcome measures on medium of first treatment (VR or text).

Results

Figure 3 (left panel) illustrates the effect of each treatment on vaccination intention as the difference between measurements before and after the first treatment. The supplemental material presents the full distribution of individual treatment effects, as well as analyses that do not exclude maximum-score participants.

Figure 3
figure 3

Average effect on vaccination intention of first treatment (n = 195, left panel) and second treatment (n = 189, right panel), leaving out participants with maximum pre-treatment vaccination intention. Error bars are 95% CIs.

Comparing vaccination intention between the pre-treatment and first post-treatment measure, for participants who did not already have maximally positive vaccination intention (n = 195), we find that the VR treatment increased vaccination intention by 9.3 points (95% CI: 7.0 to \(11.5,\ p < 0.001\)). The VR treatment is more effective than the text-and-image treatment, which only increases vaccination intention by 3.3 points (difference in effects: 5.8, 95% CI: 2.0 to \(9.5,\ p = 0.003\)).

Comparing collective responsibility pre- and post-treatment, for participants who did not already score the maximum on collective responsibility (n = 104), we find that the VR treatment increases collective responsibility by 0.82 points (95% CI: 0.37 to \(1.27,\ p < 0.001\)). The VR treatment is once again more effective than a text-and-image treatment, which increases collective responsibility by just 0.43 points, though the difference is not significant (difference in effects: 0.39, 95% CI: 0.36 to \(1.14,\ p = 0.275\)). The power to detect significant treatment differences is lower here, due to the smaller number of “moveable” participants with less-than-maximum perceptions of collective responsibility.

Further, we conducted an exploratory analysis on whether the VR treatment further increases vaccination intentions after a text-and-image treatment. Indeed, as shown in the right panel of Fig. 3, we find that for participants who experienced the text-and-image treatment first and did not have maximum pre-treatment vaccination intention, the subsequent VR treatment further increased vaccination intention by 6.3 points (95% CI: 4.2 to \(8.3,\ p < 0.001\)). In contrast, for those who received the text-and-image treatment after the VR treatment, there was no significant further increase in vaccination intention (effect: 0.8, 95% CI: \(-0.6\) to \(2.3,\ p = 0.309\)).

We also explored any potential difference between the effectiveness of the two versions of the VR treatment: the one where participants avoided spreading COVID-19 and the one where they avoided infection with COVID-19. There is no difference in the effect of these two versions on either vaccination intention (difference in effects: 0.2, 95% CI: \(-4.2\) to \(47,\ p = 0.912\)) or collective responsibility (difference in effects: \(-0.003\), 95% CI: \(-0.46\) to \(0.45,\ p = 0.989\)).

Finally, we asked all participants who completed the full study (n = 208) whether learning about community immunity via VR and text/pictures was fun, and whether they would like to receive more health communications via VR and text/pictures (1–5 scale). Compared to their ratings of text, participants rated VR as more fun (difference in means: 0.23, 95% CI: 0.11 to \(0.35,\ p < 0.001\)). There was no difference on how much participants wanted to receive future health communications via the two media (difference in means: \(-0.06\), 95% CI: \(-0.18\) to \(0.05,\ p = 0.301\)).

Discussion

We provide seminal evidence that a first-person experience of vaccinations’ collective benefits in immersive VR can increase vaccination intentions. Further, the VR treatment is nearly three times more effective than communicating the same content via text and images. As the intended effect of both treatments is quite clear, the VR treatment’s greater effectiveness shows that its impact cannot be reduced to demand characteristics. This is further supported by the finding that adding the VR treatment after the text-and-image treatment further increased vaccination intention, whereas adding the text-and-image treatment after the VR treatment did not provide any further benefit.

Our results suggest that, due to the unique type of content it allows for, a VR intervention communicating about the collective benefit of vaccination can go beyond merely providing information. The results fit into a growing literature on the effectiveness of communicating about community immunity on vaccination intentions (see9 for a review) and builds on the finding that such interventions appear more effective when they are more engaging, such as via interactive simulations10,11,12, and when they elicit emotions, such as empathy7. As we demonstrate here, immersive VR is an effective alternative communication medium that can convey the collective benefit of vaccination in a highly engaging and emotional way.

There are several potential mechanisms for why the VR treatment leads to changes in behavioral intentions that deserve further investigation in future research. Our participants reported greater fun with the VR treatment than with the text-and-image treatment. Previous research has shown that immersive VR increases participants’ interest in the content domain25 and enjoyment26, which can increase attention and effort18 to understand a topic. Immersive simulations also induce a sense of presence17 and agency, which are essential for experiencing embodiment (the feeling of being in and controlling a virtual body)27. This can cause participants to associate negative and positive emotions with low and high vaccination rates, respectively. All of these features make it possible to create intense experiences of scenarios from another person’s perspective—increasing empathy with vulnerable others by allowing users to share their emotional processes28. Such effects are likely to further increase when elements of gamification are used23, as in the present study. Taken together, there are both cognitive and emotional features of the VR treatment that are likely influence behavioral intentions.

The current research has some limitations. Firstly, because is difficult to differentiate between mechanisms, it is currently unclear which aspects of the intervention may be modified by practitioners, and which ones must be kept. In future work, we will further investigate the mechanisms behind the effect of this intervention type, by developing more versions of the simulation, and measuring more intermediate variables (e.g., empathy).

Secondly, our outcome measures were vaccination intention and collective responsibility. We used established measures for these constructs and both have been linked to self-reported vaccine uptake6,29. Nevertheless, future research should investigate the effects on actual vaccination behaviour.

Thirdly, in contexts with limited funds and technological know-how, VR interventions are less feasible. Still, headsets have fallen dramatically in price, and they have become easier and more versatile in use—a trend that is expected to continue, making VR a more accessible option in the future.

Finally, since our sample was composed of passersby in a public park, people who had greater interest in VR may have been more likely to participate. Further, despite the fact that the study was advertised as a “VR experiment on COVID-19”, with no mention of vaccines or advocacy, it is possible that participants anticipated our objectives. This means that individuals with strong (anti-)vaccine beliefs may have declined to take part. Indeed, the strength of our invention lies in motivating the vaccine-hesitant to engage with vaccine-related content, rather than in persuading strong vaccine deniers.

Despite these limitations of the sample, showing the effectiveness of VR in increasing vaccination intentions “in the wild” indicates the generalizability of our findings to non-research settings. Moreover, the fact that VR attracts a specific audience may be beneficial. In fact, most volunteers in our study were younger adults—an age group that currently has lower COVID-19 vaccine uptake, including in countries where the vaccine is widely available30,31.

Although we found a substantial change in vaccination intentions, future research could develop an even more effective VR treatment. For example, subsequent versions may improve the experience’s narrative, or create more empathy with a main character who is especially vulnerable to the target disease. And while the present study focused on COVID-19 vaccination intentions, the VR treatment can also easily be adapted to, and tested for, different infectious diseases.

Our research contributes to a potential paradigm shift in health communication generally, and vaccine advocacy in particular. Finding novel methods to reduce vaccine hesitancy is critical4,32,33. Immersive, gamified VR provides a flexible tool to create more engaging and interactive learning experiences—alongside other media and technology, such as gamified apps and augmented reality. For vaccine and community immunity information in particular, it is crucial to reach and engage healthy members of the population (including young adults). Immersive VR has strong potential to complement more traditional communication channels and, therefore, contribute to decreasing the threat from infectious diseases.

Data availability

Anonymous individual participant data, plus analysis files a data dictionary with variable descriptions, are available to anyone from the study repository (https://osf.io/wufxk/?view_only=56e83d061c6d469fb6378d29c2940a4a). The repository also includes the study protocol, pre-analysis plan and informed consent form.

References

  1. Fine, P., Eames, K. & Heymann, D. L. Herd immunity: A rough guide. Clin. Infect. Dis. 52, 911–916 (2011).

    Article  Google Scholar 

  2. Haas, E. J. et al. Impact and effectiveness of mRNA BNT162b2 vaccine against SARSCoV-2 infections and COVID-19 cases, hospitalisations, and deaths following a nationwide vaccination campaign in Israel: An observational study using national surveillance data. Lancet 397, 1819–1829 (2021).

    CAS  Article  Google Scholar 

  3. Anderson, R. M., Vegvari, C., Truscott, J. & Collyer, B. S. Challenges in creating herd immunity to SARS-CoV-2 infection by mass vaccination. Lancet 396, 1614–1616 (2020).

    CAS  Article  Google Scholar 

  4. MacDonald, N. E. et al. Vaccine hesitancy: Definition, scope and determinants. Vaccine 33, 4161–4164 (2015).

    Article  Google Scholar 

  5. Geiger, M. et al. Measuring the 7Cs of vaccination readiness. Eur. J. Psychol. Assess. (2021).

  6. Betsch, C. et al. Beyond confidence: Development of a measure assessing the 5C psychological antecedents of vaccination. PLoS ONE 13, e0208601 (2018).

    CAS  Article  Google Scholar 

  7. Pfattheicher, S., Petersen, M. B. & Böhm, R. Information about herd immunity through vaccination and empathy promote COVID-19 vaccination intentions. Health Psychol. (2021). (Forthcoming).

  8. Hendrix, K. S. et al. Vaccine message framing and parents’ intent to immunize their infants for MMR. Pediatrics 134, e675–e683 (2014).

    Article  Google Scholar 

  9. Hakim, H. et al. Interventions to help people understand community immunity: A systematic review. Vaccine 37, 235–247 (2019).

    Article  Google Scholar 

  10. Betsch, C., Böhm, R., Korn, L. & Holtmann, C. On the benefits of explaining herd immunity in vaccine advocacy. Nat. Hum. Behav. 1, 1–6 (2017).

    Article  Google Scholar 

  11. Betsch, C. & Böhm, R. Moral values do not affect prosocial vaccination. Nat. Hum. Behav. 2, 881–882 (2018).

    Article  Google Scholar 

  12. Sprengholz, P. & Betsch, C. Herd immunity communication counters detrimental effects of selective vaccination mandates: Experimental evidence. EClinicalMedicine 22, 100352 (2020).

    Article  Google Scholar 

  13. Allcoat, D. & von Mühlenen, A. Learning in virtual reality: Effects on performance, emotion and engagement. Res. Learn. Technol. 26 (2018).

  14. Annetta, L., Mangrum, J., Holmes, S., Collazo, K. & Cheng, M.-T. Bridging realty to virtual reality: Investigating gender effect and student engagement on learning through video game play in an elementary school classroom. Int. J. Sci. Educ. 31, 1091–1113 (2009).

    Article  Google Scholar 

  15. Böhm, R. & Betsch, C. Prosocial vaccination. Curr. Opin. Psychol. 43, 307–311 (2022).

    Article  Google Scholar 

  16. Freeman, D. et al. Automated psychological therapy using immersive virtual reality for treatment of fear of heights: A single-blind, parallel-group, randomised controlled trial. Lancet Psychiatry 5, 625–632 (2018).

    Article  Google Scholar 

  17. Sanchez-Vives, M. V. & Slater, M. From presence to consciousness through virtual reality. Nat. Rev. Neurosci. 6, 332–339 (2005).

    CAS  Article  Google Scholar 

  18. Makransky, G. & Petersen, G. B. The cognitive affective model of immersive learning (CAMIL): A theoretical research-based model of learning in immersive virtual reality. Educ. Psychol. Rev. 33, 1–22 (2021).

    Article  Google Scholar 

  19. Makransky, G., Andreasen, N. K., Baceviciute, S. & Mayer, R. E. Immersive virtual reality increases liking but not learning with a science simulation and generative learning strategies promote learning in immersive virtual reality. J. Educ. Psychol. (2020).

  20. Wu, B., Yu, X. & Gu, X. Effectiveness of immersive virtual reality using head-mounted displays on learning performance: A meta-analysis. Brit. J. Educ. Technol. 51, 1991–2005 (2020).

    Article  Google Scholar 

  21. Nowak, G. J. et al. Using immersive virtual reality to improve the beliefs and intentions of influenza vaccine avoidant 18-to-49-year-olds: Considerations, effects, and lessons learned. Vaccine 38, 1225–1233 (2020).

    Article  Google Scholar 

  22. Mottelson, A. et al. A self-administered virtual reality intervention increases COVID-19 vaccination intention. Vaccine 39, 6746–6753 (2021).

    CAS  Article  Google Scholar 

  23. Bai, S., Hew, K. F. & Huang, B. Does gamification improve student learning outcome? Evidence from a meta-analysis and synthesis of qualitative data in educational contexts. Educ. Res. Rev. 30, 100322 (2020).

    Article  Google Scholar 

  24. US Centers for Disease Control and Prevention. Vaccines & Immunizations-Glossary. Accessed 30 May 2020; https://www.cdc.gov/vaccines/terms/glossary.html.

  25. Petersen, G. B., Klingenberg, S., Mayer, R. E. & Makransky, G. The virtual field trip: Investigating how to optimize immersive virtual learning in climate change education. Brit. J. Educ. Technol. 51, 2099–2115 (2020).

    Article  Google Scholar 

  26. Parong, J. & Mayer, R. E. Learning science in immersive virtual reality. J. Educ. Psychol. 110, 785 (2018).

    Article  Google Scholar 

  27. Petersen, G. B., Petkakis, G. & Makransky, G. A study of how immersion and interactivity drive VR learning. Comput. Educ. 179, 104429 (2022).

    Article  Google Scholar 

  28. Martingano, A. J., Hererra, F. & Konrath, S. Virtual reality improves emotional but not cognitive empathy: A meta-analysis. Technol. Mind Behav. 2, 15 (2021).

    Google Scholar 

  29. Nicholls, L. A. B. et al. Older adults’ vaccine hesitancy: Psychosocial factors associated with influenza, pneumococcal, and shingles vaccine uptake. Vaccine 39, 3520–3527 (2021).

    Article  Google Scholar 

  30. European Centre for Disease Prevention and Control. COVID-19 Vaccine Tracker. Accessed 13 January 2022; https://vaccinetracker.ecdc.europa.eu/public/extensions/COVID-19/vaccine-tracker.html%5C#age-group-tab.

  31. Kaiser Family Foundation. Does The Public Want To Get A COVID-19 Vaccine? When? Accessed 13 January 2022; https://www.kff.org/coronavirus-covid-19/dashboard/kff-covid-19-vaccine-monitor-dashboard/.

  32. Betsch, C., Böhm, R. & Chapman, G. B. Using behavioral insights to increase vaccination policy effectiveness. Policy Insights Behav. Brain Sci. 2, 61–73 (2015).

    Article  Google Scholar 

  33. Dubé, E. et al. Vaccine hesitancy: An overview. Hum. Vaccines Immunother. 9, 1763–1773 (2013).

    Article  Google Scholar 

Download references

Acknowledgements

This research was funded by the European Institute of Innovation and Technology (EIT Health, Grant No. 210836). Registered at Open Science Foundation, https://doi.org/10.17605/OSF.IO/WUFXK.

Funding

The funder of the study (EIT Health) had no role in study design, data collection, data analysis, data interpretation, or writing of the report.

Author information

Authors and Affiliations

Authors

Contributions

All authors were involved in conceiving the study idea and design. C.V. led the study design and implementation, processed and analyzed data, and drafted the paper. T.L. created the Virtual Reality application and processed data. M.A., A.M., G.M. and R.B. were involved in study implementation. C.V., T.L., M.A., A.M., C.H., G.M. and R.B. revised the paper.

Corresponding author

Correspondence to Clara Vandeweerdt.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Vandeweerdt, C., Luong, T., Atchapero, M. et al. Virtual reality reduces COVID-19 vaccine hesitancy in the wild: a randomized trial. Sci Rep 12, 4593 (2022). https://doi.org/10.1038/s41598-022-08120-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41598-022-08120-4

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing