| Literature DB >> 35682466 |
Kristen Pickles1, Tessa Copp1, Gideon Meyerowitz-Katz2,3, Rachael H Dodd1, Carissa Bonner1, Brooke Nickel1, Maryke S Steffens4, Holly Seale5, Erin Cvejic1, Melody Taba1, Brian Chau1, Kirsten J McCaffery1.
Abstract
Central to a successful population vaccination program is high uptake of vaccines. However, COVID-19 vaccine uptake may be impeded by beliefs based on misinformation. We sought to understand the prevalence and nature of misbeliefs about COVID-19 vaccines, and identify associated factors, shortly after commencement of Australia's national vaccine rollout. A cross-sectional survey was administered to unvaccinated young adults (n = 2050) in Australia aged 18-49 years (mean age 33 years), 13 July-21 August 2021. This sample was previously under-represented in COVID-19 research but shown to have less willingness to vaccinate. Two thirds of participants agreed with at least one misbelief item. Misperceptions about COVID-19 vaccines were found to be significantly associated with lower health literacy, less knowledge about vaccines, lower perceived personal risk of COVID-19, greater endorsement of conspiracy beliefs, and lower confidence and trust in government and scientific institutions. Misbeliefs were more common in participants with less educational attainment, in younger age groups, and in males, as per previous research. Understanding determinants and barriers to vaccination uptake, such as knowledge and beliefs based on misinformation, can help to shape effective public health communication and inform debunking efforts at this critical time and in the future.Entities:
Keywords: COVID-19; beliefs; misinformation; misperceptions; trust; vaccination; vaccination willingness; vaccine knowledge; vaccine uptake; vaccines
Mesh:
Substances:
Year: 2022 PMID: 35682466 PMCID: PMC9180736 DOI: 10.3390/ijerph19116883
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 4.614
Measures evaluated in this study.
| Item | Description and Reference (If Applicable) | Item Scoring and Analysis |
|---|---|---|
|
| ||
| | Mean value 10 items; scale: 1 = definitely false to 4 = definitely true; 5 = I don’t know enough to make a decision | |
| 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 | ||
|
| ||
| | 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 | ||
| | 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 | ||
|
| Two individual items, adapted from [ | |
| 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 | ||
|
| Mean of 4 items, adapted from [ | |
| 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 | ||
| I am concerned that government recommendations about | ||
|
| Mean of 3 items adapted from [ | |
| Scientists involved in developing and testing COVID-19 vaccines | ||
| Researchers involved in trialling COVID-19 vaccine safety and | ||
| Medical institutions (GPs, hospitals) involved in distributing COVID-19 vaccines | ||
|
| Mean of 2 items adapted from [ | |
| Federal government agencies responsible for managing the | ||
| State government agencies responsible for managing the | ||
|
| 4 items, scale range 1–4, adapted from [ | |
| Perceived importance of COVID-19 vaccine for health | ||
| Perceived protection to self and community from getting | ||
| Perceived safety of COVID-19 vaccine | ||
| Perceived concern about having a serious reaction to | ||
|
| ||
| 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 [ | |
|
| ||
| Apart from concerns about rare blood clots, have you seen or heard anything else bad about COVID-19 vaccines? —Yes | Content analysis, adapted from [ | |
| 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 | ||
* This item was excluded from regression analyses, as we note that this item could reasonably be interpreted as true (i.e., people vaccinated against COVID-19 can protect the health of others in the community).
Sample characteristics (N = 2050). Values are shown as n (%) unless otherwise indicated.
| 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, | 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% | |
* Higher scores indicate greater confidence and trust; # “non-binary” and “not given” had too few observations and were suppressed.
Trust in vaccine effectiveness and safety.
| 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) |
* Combined “very much” and “moderately” versus all other responses (“a little” and “not at all”).
Mean scores (SD) for misperceptions, knowledge, conspiracy.
| 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%) |
a Responses recoded from 1 (definitely false) to 5 (definitely true); 3 (uncertainty response). b Higher score indicating more agreement with conspiratorial beliefs. c Computed based on binary correct/incorrect responses.
Agreement with COVID-19 vaccine misbeliefs.
| 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%) |
* This item was excluded from regression analyses as we note that this item could reasonably be interpreted as true (i.e., people vaccinated against COVID-19 can protect the health of others in the community). We found roughly an equivalent % endorsement between the first and second most common misbeliefs (29% vs. 22% agreement)
Vaccine-related conspiracy beliefs.
| 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%) |
General vaccine knowledge—Shading indicates correct response.
| 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%) |
Multivariable truncated linear regression of the misbeliefs score. Higher values of the outcome indicate greater support for misbeliefs. Data are presented as estimated marginal mean differences (95% CIs). Statistical significance is indicated by * p < 0.05; ** p < 0.01; *** p < 0.001. N = 2050 complete cases.
| Main Effect | Base Model (Control Variables Only) | Main Effect | Estimated Marginal Mean Differences (Full Multivariable Model) | |
|---|---|---|---|---|
|
| ||||
| Age (/year) | 0.008 ** | 0.001 | ||
| Male gender (vs. female) a | 0.106 ** | −0.013 | ||
| Non-binary, transgender | −0.276 | |||
| Prefer not to say | 0.812 | |||
| Education (vs. high school or less) | <0.0001 | 0.01 | ||
| Cert I-IV | 0.018 | −0.018 | ||
| University education | −0.315 *** | −0.108 ** | ||
| State (vs. NSW) | 0.087 | −0.132 | 0.094 | |
| ACT | −0.120 | 0.063 | ||
| NT | −0.124 | 0.026 | ||
| VIC | 0.043 | 0.012 | ||
| QLD | −0.063 | 0.063 | ||
| WA | −0.099 | −0.049 | ||
| SA | −0.137 | −0.098 | ||
| TAS | 0.0759 | −0.039 | ||
| Vaccine knowledge | −0.779 *** | |||
| Health literacy | −0.128 *** | |||
| Confidence in government | −0.181 *** | |||
| Conspiratorial beliefs | 0.301 *** | |||
| Trust in institutions | −0.147 *** | |||
| Trust in governments | 0.016 | |||
| Perceived personal risk of COVID-19 | 0.033 * | |||
| Frequency checking social media for COVID-19 information or updates | −0.027 * |
a Marginal mean differences are not reported for gender reported as “not specified” or “other” due to small sample size, but these data were included in the regression model.
Content discouraging COVID-19 vaccination that participants had witnessed, with frequency of the themes and example quotes.
| 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” |