COVID-19 Vaccine Misperceptions in a Community Sample of Adults Aged 18–49 Years in Australia
Abstract
:1. Introduction
2. Methods
2.1. Study Design
2.2. Setting
2.3. Participants
2.4. Measures
2.5. Statistical Analysis
3. Results
Sample Characteristics
4. Confidence and Trust in Vaccines
5. Misperceptions, Conspiracy Beliefs, and Vaccine Knowledge
5.1. COVID-19 Vaccine Misperceptions
5.2. Vaccine-Related Conspiracy Beliefs
5.3. Vaccine Knowledge
5.4. Factors Associated with Greater Agreement with COVID-19 Vaccine Misbeliefs
5.5. Content Discouraging People from Having a COVID-19 Vaccine
- Negative vaccine side effects and vaccine risk (n = 384, 39.9%): Included responses pertaining to concerns about specific and general side effects of the COVID-19 vaccine as well as concerns about adverse events post-vaccination and overall safety of the vaccine. Specific side effects of concern included blood clots, fertility and reproductive concerns, motor, cognitive and neurological disorders, AstraZeneca-specific concerns, shaking, paralysis, pain, fever and fainting.
- Conspiracy theories (n = 133, 13.8%): Example conspiracy theories commonly raised included virus legitimacy scepticism, 5G, tracking, microchips, magnetism caused by the vaccine and vaccine causing COVID-19 or other disease.
- Antivax or hesitance towards vaccine (n = 115, 11.9%): Responses included general anti-vaccination sentiments (e.g., “strongly against vaccine for well-informed reasons” or “not liking vaccines”), reluctance to receive vaccinations and mentions of “Antivaxxers” as community.
6. Discussion
7. Limitations
8. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Item | Description and Reference (If Applicable) | Item Scoring and Analysis |
---|---|---|
Main outcome | ||
COVID-19 vaccine related misbeliefs [21,22,23] | Mean value 10 items; scale: 1 = definitely false to 4 = definitely true; 5 = I don’t know enough to make a decision (Responses recoded from 1 (definitely false) to 5 (definitely true); 3 (I don’t know) | |
Getting the COVID-19 vaccine gives you COVID-19 | ||
More people will die of a negative side effect to the COVID-19 vaccine than would actually die from the virus | ||
The flu shot provides immunity to COVID-19 | ||
Supplements are more effective than COVID-19 vaccines | ||
COVID vaccines cause immune damage | ||
People who have had a COVID-19 vaccine shed the virus to others | ||
COVID vaccinated people can affect non-vaccinated people’s health * | ||
COVID-19 vaccines have been linked to infertility | ||
COVID-19 vaccines contain tracking technology | ||
COVID-19 vaccines alter your DNA | ||
Explanatory variables | ||
General vaccine knowledge [24] | Mean value 8 items (0–1): scale: Agree, don’t agree, don’t know (Scored as % correct) | |
Vaccines are not needed because diseases can be treated (e.g., with antibiotics) | ||
Without broadly applied vaccine programs, smallpox would still exist | ||
The effectiveness of vaccines has been proven | ||
People would be more resistant to diseases if they were not given so many vaccines | ||
Conditions like autism, multiple sclerosis, and diabetes might be triggered through vaccinations | ||
The immune system is overloaded if we are given too many vaccinations | ||
The doses of chemicals used in vaccines are not dangerous for humans | ||
Vaccinations increase the occurrence of allergies | ||
Acceptance of vaccine conspiracies [25] | Mean value 7 items: scale 1 = strongly disagree to 5 = strongly agree | |
Data about vaccine safety is often fabricated (made up) | ||
People are deceived about the effectiveness of vaccines | ||
Immunising is harmful, and this fact is covered up | ||
Drug companies cover up the dangers of vaccines | ||
Data about vaccine effectiveness is often fabricated (made up) | ||
People are deceived about vaccine safety | ||
The government is trying to cover up the link between vaccines and autism | ||
Perceived risk of COVID-19 | Two individual items, adapted from [26] | |
Perceived public threat of COVID-19 (scale: 1 = no threat at all to 10 = very serious public health threat) | ||
Concern about getting COVID-19 (scale: 1 = not at all concerned to 4 = very concerned) | ||
Confidence in Government | Mean of 4 items, adapted from [27]; scale: 1 = strongly disagree to 7 = strongly agree | |
I am confident in information about COVID-19 vaccines provided by the government | ||
I am satisfied with the amount of information about COVID-19 vaccines provided by the government | ||
I will follow government advice on COVID-19 vaccination to help protect the wider community | ||
I am concerned that government recommendations about COVID-19 vaccines are not safe | ||
Trust in Institutions | Mean of 3 items adapted from [28], scale: 1 = strongly disagree to 7 = strongly agree | |
Scientists involved in developing and testing COVID-19 vaccines | ||
Researchers involved in trialling COVID-19 vaccine safety and efficacy | ||
Medical institutions (GPs, hospitals) involved in distributing COVID-19 vaccines | ||
Trust in Government | Mean of 2 items adapted from [28], scale: 1 = strongly disagree to 7 = strongly agree | |
Federal government agencies responsible for managing the control of COVID-19 | ||
State government agencies responsible for managing the control of COVID-19 | ||
Confidence in COVID-19 vaccine benefits | 4 items, scale range 1–4, adapted from [29] (reported descriptively) | |
Perceived importance of COVID-19 vaccine for health | ||
Perceived protection to self and community from getting COVID-19 vaccine | ||
Perceived safety of COVID-19 vaccine | ||
Perceived concern about having a serious reaction to COVID-19 vaccine | ||
Frequency checking COVID-19 information | ||
How often, if at all, do you check social media (such as Facebook or Twitter) for information or updates about COVID-19? | 1 item, scale: 1 = Once an hour or more to 5 = I don’t use social media, adapted from [30] | |
Exposure to negative information about COVID-19 vaccines | ||
Apart from concerns about rare blood clots, have you seen or heard anything else bad about COVID-19 vaccines? —Yes | Content analysis, adapted from [29] | |
In the last week, have you come across any content discouraging people from vaccinating (i.e., on your social media, from friends, at the workplace?) —Yes |
Characteristic | n (%) | |
---|---|---|
Age (years), mean (SD) | 33.13 (7.9) | |
Highest level of education | High school or less | 460 (22.4%) |
Certificate I-IV | 722 (35.2%) | |
University | 868 (42.3%) | |
Gender | Woman | 1028 (50.1%) |
Man | 1009 (49.2%) | |
Non-binary, transgender, or prefer not to say # | 11 (0.5%) | |
Residential state or territory | Australian Capital Territory | 30 (1.5%) |
Northern Territory | 17 (0.8%) | |
New South Wales | 619 (30.2%) | |
Victoria | 513 (25.0%) | |
Queensland | 439 (21.4%) | |
Western Australia | 214 (10.4%) | |
South Australia | 159 (7.8%) | |
Tasmania | 59 (2.9%) | |
Adequate health literacy | 1707 (83.3%) | |
Digital health literacy (1–5), mean (SD) | 3.8 (0.6) | |
Difficulty finding/understanding information online (1–10), mean (SD) | 4.9 (1.9) | |
How serious of a public health threat do you think COVID-19 is in Australia, (1–10), mean (SD) | 7.06 (2.52) | |
How concerned are you about getting COVID-19? | Not at all concerned | 290 (14.1%) |
A little concerned | 784 (38.2%) | |
Moderately concerned | 609 (29.7%) | |
Very concerned | 367 (17.9%) | |
Confidence in government (1–7), mean (SD) * | 4.52 (1.4) | |
Trust in institutions (1–7), mean (SD) * | 5.06 (1.5) | |
Trust in government (1–7), mean (SD) * | 4.36 (1.7) | |
Information source about COVID-19 vaccines, % | Official Government source | 53% |
Mainstream media | 46% | |
Social media | 45% |
How Much Do You Trust * | Effectiveness (n, %) | Safety (n, %) |
---|---|---|
Childhood vaccines | 1760 (85.8) | 1801 (87.9) |
Flu vaccine | 1537 (75.0) | 1624 (79.2) |
Travel vaccines | 1506 (73.5) | 1510 (73.7) |
Pfizer | 1363 (66.5) | 1329 (64.9) |
AstraZeneca | 867 (42.3) | 792 (38.6) |
Variable | n (%) |
---|---|
Vaccine misperceptions (1–5) a | 2.2 (0.9) |
Vaccine-related conspiracy beliefs (1–5) b | 2.6 (0.9) |
Vaccine knowledge (% correct) c | 49% (26%) |
True | False | Don’t Know Enough to Make a Decision | |
---|---|---|---|
COVID vaccinated people can affect non-vaccinated people’s health * | 602 (29.4%) | 1081 (52.7%) | 367 (17.9%) |
People who have had a COVID-19 vaccine shed the virus to others | 459 (22.4%) | 1185 (57.8%) | 406 (19.8%) |
COVID-19 vaccines cause immune damage | 386 (18.8%) | 1172 (57.2%) | 492 (24.0%) |
COVID-19 vaccines have been linked to infertility | 366 (17.9%) | 963 (47.0%) | 721 (35.2%) |
More people will die of a negative side effect to the COVID-19 vaccine than would actually die from the virus | 354 (17.3%) | 1431 (69.8%) | 265 (12.9%) |
COVID-19 vaccines alter your DNA | 324 (15.8%) | 1283 (62.6%) | 443 (21.6%) |
Getting the COVID-19 vaccine gives you COVID-19 | 308 (15.0%) | 1477 (72.1%) | 265 (12.9%) |
Supplements are more effective than COVID-19 vaccines | 285 (13.9%) | 1472 (71.8%) | 293 (14.3%) |
The flu shot provides immunity to COVID-19 | 268 (13.1%) | 1561 (76.1%) | 221 (10.8%) |
COVID-19 vaccines contain tracking technology | 253 (12.3%) | 1488 (72.6%) | 309 (15.1%) |
Agree | Disagree | Unsure | |
---|---|---|---|
People are deceived about the effectiveness of vaccines | 651 (31.8%) | 859 (41.9%) | 540 (26.3%) |
People are deceived about vaccine safety | 607 (29.6%) | 877 (42.8%) | 566 (27.6%) |
Drug companies cover up the dangers of vaccines | 571 (27.9%) | 848 (41.4%) | 631 (30.8%) |
Data about vaccine safety is often fabricated (made up) | 445 (21.7%) | 898 (43.8%) | 707 (34.5%) |
Data about vaccine effectiveness is often fabricated (made up) | 434 (21.2%) | 994 (48.5%) | 622 (30.3%) |
The government is trying to cover up the link between vaccines and autism | 308 (15.0%) | 1105 (53.9%) | 637 (31.1%) |
Immunising is harmful, and this fact is covered up | 280 (13.7%) | 1284 (62.6%) | 486 (23.7%) |
Agree | Disagree | Don’t Know | |
---|---|---|---|
The effectiveness of vaccines has been proven | 1629 (79.5%) | 212 (10.3%) | 209 (10.2%) |
Vaccines are not needed because diseases can be treated (e.g., with antibiotics) | 235 (11.5%) | 1619 (79.0%) | 196 (9.6%) |
Without broadly applied vaccine programs, smallpox would still exist | 1507 (73.5%) | 200 (9.8%) | 343 (16.7%) |
People would be more resistant to diseases if they were not given so many vaccines | 384 (18.7%) | 1113 (54.3%) | 553 (27.0%) |
Conditions like autism, multiple sclerosis, and diabetes might be triggered through vaccinations | 347 (16.9%) | 1015 (49.5%) | 688 (33.6%) |
The immune system is overloaded if we are given too many vaccinations | 473 (23.1%) | 904 (44.1%) | 673 (32.8%) |
The doses of chemicals used in vaccines are not dangerous for humans | 829 (40.4%) | 504 (24.6%) | 717 (35.0%) |
Vaccinations increase the occurrence of allergies | 351 (17.1%) | 753 (36.7%) | 946 (46.1%) |
Main Effect p-Value | Base Model (Control Variables Only) | Main Effect p-Value | Estimated Marginal Mean Differences (Full Multivariable Model) | |
---|---|---|---|---|
Control Variables | ||||
Age (/year) | 0.008 ** [0.003,0.013] | 0.001 [−0.002,0.004] | ||
Male gender (vs. female) a | 0.106 ** [0.029,0.183] | −0.013 [−0.066,0.041] | ||
Non-binary, transgender | −0.276 [−0.628,0.076] | |||
Prefer not to say | 0.812 [−0.344,1.968] | |||
Education (vs. high school or less) | <0.0001 | 0.01 | ||
Cert I-IV | 0.018 [−0.087,0.123] | −0.018 [−0.091,0.053] | ||
University education | −0.315 *** [−0.416,−0.214] | −0.108 ** [−0.178,−0.038] | ||
State (vs. NSW) | 0.087 | −0.132 [−0.452,0.188] | 0.094 | |
ACT | −0.120 [−0.444,0.204] | 0.063 [−0.157,0.282] | ||
NT | −0.124 [−0.556,0.309] | 0.026 [−0.268,0.320] | ||
VIC | 0.043 [−0.061,0.146] | 0.012 [−0.059,0.083] | ||
QLD | −0.063 [−0.045,0.171] | 0.063 [−0.012,0.138] | ||
WA | −0.099 [−0.237,0.037] | −0.049 [−0.145,0.046] | ||
SA | −0.137 [−0.290,0.016] | −0.098 [−0.204,0.008] | ||
TAS | 0.0759 [−0.159,0.311] | −0.039 [−0.200,0.120] | ||
Vaccine knowledge | −0.779 *** [−0.912,−0.646] | |||
Health literacy | −0.128 *** [−0.200,−0.056] | |||
Confidence in government | −0.181 *** [−0.241,−0.122] | |||
Conspiratorial beliefs | 0.301 *** [0.263,0.340] | |||
Trust in institutions | −0.147 *** [−0.176,−0.117] | |||
Trust in governments | 0.016 [−0.007,0.038] | |||
Perceived personal risk of COVID-19 | 0.033 * [0.0004,0.065] | |||
Frequency checking social media for COVID-19 information or updates | −0.027 * [−0.049,−0.005] |
Theme | n (%) | Example Free Text Response |
---|---|---|
Negative vaccine side effects and vaccine risk | 384 (39.9) | “I heard that getting vaccinated can cause rare blood clots and is dangerous so I choose not to, I don’t want to risk my life” |
Conspiracy theories | 133 (13.8) | “Tin foil hat people saying the vaccine is designed to make you more likely to catch a virus which will be released in 2025 as the world governments want to cull the population by 6.5 billion people” |
Antivax or hesitance towards vaccine | 115 (11.9) | “Many people within my community are strongly against the vaccine for many well informed and educated reasons” |
Concerns about lack of vaccine testing and contents | 75 (7.8) | “The immunization has been rushed way to quickly without adequate testing before it was released to the public” |
Distrust in government | 64 (6.6) | “Gov’t not reporting the cases of adverse effect and death due to COVID-19 vaccines” |
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Pickles, K.; Copp, T.; Meyerowitz-Katz, G.; Dodd, R.H.; Bonner, C.; Nickel, B.; Steffens, M.S.; Seale, H.; Cvejic, E.; Taba, M.; et al. COVID-19 Vaccine Misperceptions in a Community Sample of Adults Aged 18–49 Years in Australia. Int. J. Environ. Res. Public Health 2022, 19, 6883. https://doi.org/10.3390/ijerph19116883
Pickles K, Copp T, Meyerowitz-Katz G, Dodd RH, Bonner C, Nickel B, Steffens MS, Seale H, Cvejic E, Taba M, et al. COVID-19 Vaccine Misperceptions in a Community Sample of Adults Aged 18–49 Years in Australia. International Journal of Environmental Research and Public Health. 2022; 19(11):6883. https://doi.org/10.3390/ijerph19116883
Chicago/Turabian StylePickles, Kristen, Tessa Copp, Gideon Meyerowitz-Katz, Rachael H. Dodd, Carissa Bonner, Brooke Nickel, Maryke S. Steffens, Holly Seale, Erin Cvejic, Melody Taba, and et al. 2022. "COVID-19 Vaccine Misperceptions in a Community Sample of Adults Aged 18–49 Years in Australia" International Journal of Environmental Research and Public Health 19, no. 11: 6883. https://doi.org/10.3390/ijerph19116883
APA StylePickles, K., Copp, T., Meyerowitz-Katz, G., Dodd, R. H., Bonner, C., Nickel, B., Steffens, M. S., Seale, H., Cvejic, E., Taba, M., Chau, B., & McCaffery, K. J. (2022). COVID-19 Vaccine Misperceptions in a Community Sample of Adults Aged 18–49 Years in Australia. International Journal of Environmental Research and Public Health, 19(11), 6883. https://doi.org/10.3390/ijerph19116883