Erica W Austin1, Bruce W Austin2, Porismita Borah3, Shawn Domgaard3, Sterling M McPherson4. 1. Edward R. Murrow Center for Media & Health Promotion Research, Edward R. Murrow College of Communication, 6760Washington State University, Pullman, WA, USA. 2. Department of Kinesiology and Educational Psychology, Washington State University, Pullman, WA, USA. 3. Edward R. Murrow College of Communication, Washington State University, Pullman, WA, USA. 4. Elson S. Floyd College of Medicine, Spokane, WA, USA.
Abstract
PURPOSE: To assess how previous experiences and new information contributed to COVID-19 vaccine intentions. DESIGN: Online survey (N = 1264) with quality checks. SETTING: Cross-sectional U.S. survey fielded June 22-July 18, 2020. SAMPLE: U.S. residents 18+; quotas reflecting U.S. Census, limited to English speakers participating in internet panels. MEASURES: Media literacy for news content and sources, COVID-19 knowledge; perceived usefulness of health experts; if received flu vaccine in past 12 months; vaccine willingness scale; demographics. ANALYSIS: Structural equation modelling. RESULTS: Perceived usefulness of health experts (b = .422, P < .001) and media literacy (b = .162, P < .003) predicted most variance in vaccine intentions (R-squared=31.5%). A significant interaction (b = .163, P < .001) between knowledge (b = -.132, P = .052) and getting flu shot (b = .185, P < .001) predicted additional 3.5% of the variance in future vaccine intentions. An increase in knowledge of COVID-19 associated with a decrease in vaccine intention among those declining the flu shot. CONCLUSION: The interaction result suggests COVID-19 knowledge had a positive association with vaccine intention for flu shot recipients but a counter-productive association for those declining it. Media literacy and trust in health experts provided strong counterbalancing influences. Survey-based findings are correlational; thus, predictions are based on theory. Future research should study these relationships with panel data or experimental designs.
PURPOSE: To assess how previous experiences and new information contributed to COVID-19 vaccine intentions. DESIGN: Online survey (N = 1264) with quality checks. SETTING: Cross-sectional U.S. survey fielded June 22-July 18, 2020. SAMPLE: U.S. residents 18+; quotas reflecting U.S. Census, limited to English speakers participating in internet panels. MEASURES: Media literacy for news content and sources, COVID-19 knowledge; perceived usefulness of health experts; if received flu vaccine in past 12 months; vaccine willingness scale; demographics. ANALYSIS: Structural equation modelling. RESULTS: Perceived usefulness of health experts (b = .422, P < .001) and media literacy (b = .162, P < .003) predicted most variance in vaccine intentions (R-squared=31.5%). A significant interaction (b = .163, P < .001) between knowledge (b = -.132, P = .052) and getting flu shot (b = .185, P < .001) predicted additional 3.5% of the variance in future vaccine intentions. An increase in knowledge of COVID-19 associated with a decrease in vaccine intention among those declining the flu shot. CONCLUSION: The interaction result suggests COVID-19 knowledge had a positive association with vaccine intention for flu shot recipients but a counter-productive association for those declining it. Media literacy and trust in health experts provided strong counterbalancing influences. Survey-based findings are correlational; thus, predictions are based on theory. Future research should study these relationships with panel data or experimental designs.
Entities:
Keywords:
COVID-19; Indexing Keywords; behavior change; communication; critical thinking; disinformation; environmental and occupational health; flu; general medicine; health (social science); infectious diseases; intention; knowledge; media literacy; media technology; medicine (miscellaneous); misinformation; news; public health; vaccine
U.S. COVID-19 deaths exceeded 154 000 by July 2020, whereas only 24 000-62,000 people
died of flu over the entire 2019-20 season.[1] The flu vaccine was broadly
accepted, particularly in the U.S., which ranked among the top 10 nations for
influenza vaccine adoption.[2] Because COVID-19 clearly was not just a flu, it would be
essential to anticipate how to gain the confidence of enough individuals to create
herd immunity when newly developed and tested vaccines became available.[3] The purpose of
this study was to assess how people used their previous experiences with flu
vaccines along with new information acquired through the media environment to
develop intentions about receiving the COVID-19 vaccine when it became
available.Past behaviors should predict future behavior, but this is an imperfect
relationship[4] and anti-vaxxers were busily promoting unlikely scenarios
and falsehoods about COVID-19 vaccine risks. Moreover, despite the flu shot’s
relative popularity in the U.S. compared to other countries worldwide, under half of
U.S. residents got a flu vaccine in 2019-20.[5] Indeed, research
suggests[6] that previous influenza vaccination behavior contributed only
slightly to COVID-19 vaccination intentions when general COVID-19 vaccination
beliefs and attitudes were considered along with perceptions of potential adverse
effects and novelty. Intentions also associated with greater perceived information
sufficiency.People’s trust of scientific experts also matters for vaccine acceptance. Yet,
according to Gallup research polls, trust in elite institutions and in science has
plummeted.[7] This has direct ramifications for following public health
recommendations for vaccines.[8] Some mistrust is
understandable, however, given actual historical instances of forced vaccination
programs targeted minorities and other situations that have compromised
institutional credibility.[9]Knowledge about COVID-19 also is important because beliefs about the impact of
performing a behavior will inform people’s decisions to adopt or reject it. Indeed,
lack of knowledge has associated with distrust in the COVID-19 vaccine.[10] Yet,
overcoming emotional or social barriers of vaccines can be difficult, so presenting
new information to increase knowledge alone has not been enough.[11]According to social cognitive theory, as people make health decisions, they
incorporate new information along with past experiences in a triadic process of
reciprocal causation involving intrapersonal, behavioral, and environmental
influences.[12] Because information must be interpreted in the social
milieu, information-seeking behaviors and media literacy skills can affect the
message interpretation process.[13]We therefore constructed a model to predict flu shot intention that represents past
behavior as it interacts with knowledge (intrapersonal) and then incorporates
generalized trust of health experts (environmental) and media literacy skills
(behavioral) for acquiring additional information. This model demonstrates how
people would filter previous experiences and knowledge through a toxic information
environment to decide whether they would accept the COVID-19 vaccine when it became
available. It assesses the extent to which media literacy, recent use of the
influenza vaccine, perceived usefulness of expert health information sources, and
knowledge about COVID-19 together contributed to U.S. residents’ intentions in 2020
to receive the COVID-19 vaccine. We explain the steps of the model as follows.Providing a new vaccine to the public is a multi-step process, including the
development of the vaccine, trials and testing, approval from the U.S. Food and Drug
Administration (FDA), manufacturing, and distribution of the vaccine, and
encouraging adoption.[14] The COVID-19 vaccine likewise navigated three phases of
rigorous clinical trials to ensure safety, aided by past research on existing
vaccines for SARS and MERS.[14] The result has produced a strong safety record.[15] Yet
vaccination producers have had a challenging credibility problem despite this strong
safety record.Perceptions drive behavior, and misinformation vied with expert information to drive
perceptions about the COVID-19 vaccine development.[16] Due to the rapid development
of the COVID-19 vaccine, for example, some people had concerns that a rushed process
would compromise safety.[17] As the information environment constantly evolved amidst
the public health crisis, people navigated uncertainty and unfamiliar sources to
make important decisions for themselves and their families. We therefore
hypothesized that this situation made media literacy a crucial element in decision
making because individuals had to make sense of previous experience, sources, and
information content that may or may not be accurate, complete or unbiased.Media literacy skills are manifested through a two-step process that includes first
becoming aware that it is important to assess a message source and then by
establishing if the message requires fact checking.[18] A variety of studies, both
survey-based and experimentally based, have verified that critical thinking about
sources motivates critical thinking about message content and that these skills can
be learned.[13,19,20] When seeking
vaccine information for instance, people often turn to the internet for guidance,
which can provide a variety of credible and non-credible sites with health
information.[21] Research has also shown that forewarning about a source’s
credibility or persuasive intent can inspire critical thinking about sources,
helping to reduce the influence of affect on decision making.[20] The skills in
media literacy applied to a source can then motivate critical thinking about the
message content.[22-24] Determining
whether a source is credible, and then critically thinking about the message
content, is a necessary skill to make evidence-based decision making in
health.[25] Media literacy therefore influences beliefs, attitudes, and
behaviors.[26]Decision making about vaccines, therefore, should begin with media literacy about
sources for news. Forewarning about a source’s credibility or persuasive intent can
inspire critical thinking about sources, helping to reduce affect’s influence on
decision making.[20] This is important because disinformation campaigns make use of
principles of persuasion, including emotional appeals, to encourage sharing of
social media posts without fact checking.[27] In the case of the COVID-19
pandemic, the World Health Organization[16] declared an infodemic due to
the extent of disinformation circulating the globe.Greater media literacy for sources of news predicts greater media literacy
for content of news.Greater media literacy for content of news predicts a greater intention for
obtaining a COVID-19 vaccine.People also rely on their previous experiences with information sources to
build networks or communities of sources they admire or believe they can
trust generally or for certain topics. This might include experts in a
relevant field,[28] medium,[29] or
personality.[30] This trust can help
shape intentions to get vaccinated[31] or can mislead when
misplaced.[32] For example, people often turn to familiar experts
in a field somewhat related to that information.[28] Those with more
science literacy are better able to adapt to changes made based on
scientific evidence and more likely to follow proper health guidelines in
the future.[33] Unfortunately, Gallup found that 10% of Americans
believe vaccines cause autism, up 4% from 2014, and 46% said they were
unsure if it does or not.[8] A lack of trust in
health experts therefore can heighten vulnerability to misinformation about
science and potential mistrust in a new vaccine. Those with better media
literacy skills for discerning this have been shown to make more appropriate
health decisions in prevention and diagnosis.[34]Conversely, misplaced trust in the wrong experts also creates problems.
Consider that when some people seek information online, they may have mixed
success finding credible sources, such as a credible academic article or
newspaper. This can be successful when the perceived expert has relevant
expertise and can help them make viable health decisions, such as for being
vaccinated.[31] When this perception is inaccurate, however,
message quality is warped by purposeful disinformation or misinformation due
to a source’s lack of relevant expertise. The author of the information may
be an expert in one field but may not have expertise in topics of health
despite writing about it. Thus, an otherwise credible source can
accidentally perpetuate misinformation by speaking on matters on which they
are not an expert. Health decision-making can be misled.[32]An increased belief in the usefulness of health experts predicts a greater
intention for obtaining a COVID-19 vaccine.In addition to including critical thinking skills for evaluating media
sources and content, an individual’s decision making requires skills for
considering why and how content matters for their behavioral
choices.[18] Social Cognitive Theory holds that intentions for
health decisions will incorporate new information in the context of past
experiences, interpreted while being influenced by the environmental and
social environment. Critical thinking about a message’s health content
therefore can lead to skeptical use of information when building health
beliefs and intentions, but past experience also can lead to motivated
reasoning instead of entirely logical reasoning.[35] Thus, we hypothesize
that flu vaccine status may moderate how knowledge is associated with
COVID-19 vaccine intention. Specifically, a willingness to be vaccinated for
flu, along with a better understanding of COVID-19, could positively
associate with COVID-19 vaccine intention, when compared with those who have
COVID-19 knowledge but do not have a history of flu vaccination.Having previously received a flu shot moderates the impact of knowledge of
COVID-19 on future COVID-19 vaccine intentionIn sum, although health theories show that people make health decisions based
on intentions that incorporate beliefs, skills and barriers, these theories
do not explain how people go about filtering through the information
environment to interpret new information in the context of past experiences
to accomplish this. This model newly hypothesizes that while people
anticipated the upcoming life-critical health decision of the new COVID-19
vaccine, they incorporated updated information along with past experiences
in the social milieu in which health experts existed amongst a variety of
sometimes toxic information sources. This required media literacy to sort
through which sources to believe and what information to internalize.
Individuals then incorporated past behavior with their new knowledge amidst
the ongoing information flow to create their intentions about whether to
receive the COVID-19 vaccine when it would become available.
Methods
Design
An online survey (N = 1264, 18 + years) declared exempt by the University’s
Institutional Review Board, protocol #18213, June 11, 2020 was fielded between
June 22 and July 18, 2020. Participants provided informed consent by clicking on
a radio button that followed information about the study and contact information
for further information. A debrief statement at the end of the survey provided
links to more public health information about COVID-19.
Sample
A Qualtrics opt-in panel included an over-sample of Washington state residents
for a different study (N = 416) and used zip codes to achieve demographic and
regional quotas based on the 2019 U.S. Census. Panel-based sampling with quality
checks can produce high quality data[36] and random-digit-dialing
survey response rates can be 4-6%.[37] Prior to analysis,
post-stratified sample weights adjusted for the Washington state oversample to
ensure that regional samples reflected 2019 census estimates.[38] The
survey had 76.4% of the participants in urban zip codes, reflective of the U.S.
Census.[39]
Procedure
Qualtrics recruits broadly, such as from websites, social media, and gaming,
providing survey invitations with a link and validating identities through
third-party verification measures. An algorithm deployed by Qualtrics eliminates
duplicates, illogical patterns, speeders (survey completions in less than a
third of median of the overall survey duration), incompletes and other
poor-quality responses before providing the data for analysis. Additional review
eliminated 5 speeders and 4 who wrote gibberish and answered in patterns.
Measures
The full list of measures and background sources for this study can be found in
the Supplemental File Table 1, Measures Comprising the Constructs in
the Structural Model. Descriptive statistics are available in Supplemental Table 2, Descriptive statistics for demographics
and constructs. Respondents were asked media literacy questions regarding their
sources of news (eg, about checking identity, purpose, other sources, techniques
used; Cronbach’s alpha = .90) and about the content of their news (eg, about
checking accuracy, currency, completeness; alpha = .88), their knowledge about
COVID-19 (alpha = .76), their recent flu shot behavior, and how useful they
found different health experts (CDC, WHO, National Institute of Infectious
Diseases, Local Health Departments; alpha = .84), adapted from sources using
similar scales, and the knowledge scales were built using information from the
World Health Organization, The Centers for Disease Control and Prevention and
another contemporary survey.
Analysis
A structural equation model (SEM) tested the hypotheses with vaccine intention as
the primary outcome, a latent variable. Predictors included self-reported recent
flu shot and latent-variable constructs for knowledge of COVID-19, usefulness of
health experts, media literacy for content of news (MLCN), and media literacy
for sources of news (MLSN). An interaction term for the moderating effect of
knowledge of COVID-19 on vaccine intention also was estimated.Control variables included gender, age, education (1-no formal education to
9-doctorate degree), income (1-$0 to 8-$150,000 and greater), political
orientation (1-very liberal to 5-very conservative). Analyses were performed
using Mplus 8.1. Variance explained for endogenous terms helped judge model
fit.
Results
Figure 1 reports the
standardized estimates for the structural model, providing support for hypotheses 1
through 3: MLSN significantly predicts MLCN (H1: b = .818,
P < .001), MLCN significantly predicts vaccine intention
(H2: b = .162, P = .003); usefulness of health
experts significantly predicts vaccine intention (H3: b=.422,
P<.001). Standardized coefficients also can be found in the Supplemental File Table 3, Standardized Coefficients for the
Structural Model.
Figure 1.
The structural model with standardized coefficients. **
P < .01. *** P < .001.
The structural model with standardized coefficients. **
P < .01. *** P < .001.The interaction effect of COVID-19 knowledge and recent flu shot was statistically
significant (b = .163, P < .001) supporting
hypothesis H4. Calculations of interaction effects, as shown in Figure 2, require the use of both the main
effects for flu shot and knowledge, regardless of their p-values,
as well the interaction effect. Figure 2 shows that vaccine intention was, on average, .185 standard
deviations higher for the flu-shot group than the no-flu-shot group, although
non-significant (P = .052). For very low levels of Knowledge
(between −2 and −1 in Figure
2) the vaccine intention of the no-flu-shot group appears to be slightly
higher than the flu-shot group although not statistically significant
(P > .05). Figure 2 shows that as knowledge of COVID-19 increases, vaccine
intention gradually increases for those who have received a flu shot (slope = .031)
with the opposite occurring for those declining a flu shot (slope = −.132). Thus, an
increase in knowledge of COVID-19 corresponds to a decrease in vaccine intention for
respondents declining a flu shot. Lastly, only one control variable—income—was
significant, and it was positively related to vaccine intention (b
= .081, P = .028).
Figure 2.
Interaction between knowledge of COVID-19 and having received a flu shot.
Note: the difference in vaccine intention for those
individuals in both groups with knowledge levels less than −1 standard
deviations was not statistically significant.
Interaction between knowledge of COVID-19 and having received a flu shot.
Note: the difference in vaccine intention for those
individuals in both groups with knowledge levels less than −1 standard
deviations was not statistically significant.Variance explained for the endogenous variables was used to judge the fit of the SEM
model. The variance explained (R-squared) was 35% for vaccine intention and 67% for
media literacy for content of news. The R-squared value of 67% for ML for content of
news is an excellent value that aligns with expectations and results from other
studies of the close relationship between the two media literacy constructs
(r = .81). The variance explained of 35% for our primary
outcome of vaccine intent is moderate for a self-report instrument but is also an
indication that additional explanatory variables will likely contribute to the
model.
Discussion
This study assessed how media literacy for news sources and for news content, a
recent flu vaccine, usefulness of health experts, and knowledge about COVID-19
contributed to U.S. residents’ intentions to receive the COVID-19 vaccine when it
became available. Knowledge is often insufficient to predict behavior and previous
behavior could provide a helpful clue. Nevertheless, pervasive misinformation
created a major potential barrier to vaccine acceptance. We investigated how useful
media literacy skills might be alongside these other influences.The combined associations of media literacy and usefulness of expert health sources
with vaccine intentions were greater than the associations of knowledge and previous
flu shot behavior with intentions, suggesting that the ability to manage the current
information environment may play a greater role in individuals’ decision-making than
their past behavior and knowledge base. Perceived usefulness of health experts,
measured as government and health organizations, scientists and medical
professionals, and local health departments, demonstrated the single strongest
association with vaccine intentions.The results highlight the importance of individuals’ attempts to verify the
information obtained from information sources in addition to the value of their
having trust in health experts. After perceived usefulness of health experts,
self-reported media literacy for news content had the strongest association with
vaccine intention. Critical thinking about information sources predicted critical
thinking about content, showing its importance because information can be obtained
through news, entertainment, or persuasive messages. It also is a skill that can be
taught through education and interventions.[19]Interestingly, a counter-productive association was revealed in the association of
knowledge with intention for individuals who did not recently receive a flu shot.
Those with more knowledge who had not received a recent flu shot were less likely to
express the intention to receive a COVID-19 vaccine in the future, whereas those who
recently had received a flu shot were more likely to express the intention to
receive the COVID-19 vaccine in the future. People who have rejected a vaccine in
the past and possess some knowledge about COVID-19 may perceive a threat to their
freedom from promotions to receive the new vaccine, increasing reactance and thereby
creating a backlash against anticipated advocacy for it. Similarly, previous studies
have found that repetition of evidence can be counterproductive due to motivated
reasoning.[35] This illustrates that anti-vaccine sentiments can be
difficult to change, whether based on accurate knowledge or on misinformation.Our findings are from a cross sectional survey, which means the relationships are
correlational not causal. Future research should study these relationships with
panel data or with experimental designs. Additional predictors could boost model fit
for the structural model, but the variance explained is consistent with media
literacy interventions generally.[26] An important finding is how
an increase in knowledge about COVID-19 can associate with a reduction in vaccine
intention. The significant income control variable could suggest not just that
lower-income individuals are more vaccine hesitant, but also that they may be more
vulnerable to misinformation. Also, when knowledge of COVID-19 is high among certain
vaccine-hesitant individuals, their exposure to misinformation can be strong enough
emotionally to counter factual information about the disease. Political orientation
was nonsignificant although it bordered on significance towards the conservative end
of the spectrum, perhaps foreshadowing the increasing role it played as the pandemic
progressed.The relationships found in this study, while significant, were not large: but the
pandemic was in its early stages, the vaccine was not yet developed, and the
findings may have foreshadowed how attitudes were developing. Misinformation can be
difficult to combat because it is attention-getting, has emotional appeal, and can
be difficult to correct once it has taken hold. Events have shown how hardened
attitudes have become since the summer of 2020, with a good portion of the U.S.
population still unwilling to receive a COVID-19 vaccine despite the vaccine’s wide
availability and ongoing promotional information campaign efforts.This study’s results help to explain why public health advocates cannot depend on
previous behaviors and on knowledge to support public health promotional efforts in
an environment of pervasive misinformation, disinformation, public suspicion, and
motivated reasoning. Public health campaigns need to respect the freedom of the
individual to decide for themselves, while also helping them to decide based on
evidence-based information. This study suggests that media literacy campaigns
promoting how to discern credible sources of accurate health information may provide
a crucial tool for future vaccination promotion and could support other behavior
change campaigns.
So What?
What is Already Known on this Topic?
A person’s future acceptance of a vaccine is only partially predicted
by their previous vaccine behavior, trust in experts, and knowledge
of vaccines. Both knowledge and misinformation may deepen
pre-existing resistance.
What Does this Article Add?
This structural model-based analysis of survey data assessed how
COVID-19 vaccine intentions of U.S. residents in 2020 incorporated
recent flu shot behavior, expert source usefulness, COVID-19
knowledge, and media literacy. Knowledgeable respondents who
recently had declined a flu shot reported lower intentions to
receive a future COVID-19 vaccine compared to those with less
knowledge. The largest positive predictors of vaccine intention were
expert source usefulness and media literacy.
What Are the Implications for Health Promotion Practice or
Research?
The results highlight the importance of individuals’ attempts to
verify information obtained from information sources in addition to
the value of cultivating their trust in health experts. Public
health campaigns that respect individuals’ freedom to make decisions
for themselves must help them to do so based on accurate information
from credible sources. Thus, tools to coach how to identify
trustworthy sources of reliable health information may provide
crucial strategies to support future vaccination promotion and other
behavior change campaigns.Click here for additional data file.Supplemental Material for How Media Literacy, Trust of Experts and Flu Vaccine
Behaviors Associated with COVID-19 Vaccine Intentions by Erica W. Austin, Bruce
W. Austin, Porismita Borah, Shawn Domgaard, and Sterling M. McPherson in
American Journal of Health Promotion
Authors: Jay J Van Bavel; Katherine Baicker; Paulo S Boggio; Valerio Capraro; Aleksandra Cichocka; Mina Cikara; Molly J Crockett; Alia J Crum; Karen M Douglas; James N Druckman; John Drury; Oeindrila Dube; Naomi Ellemers; Eli J Finkel; James H Fowler; Michele Gelfand; Shihui Han; S Alexander Haslam; Jolanda Jetten; Shinobu Kitayama; Dean Mobbs; Lucy E Napper; Dominic J Packer; Gordon Pennycook; Ellen Peters; Richard E Petty; David G Rand; Stephen D Reicher; Simone Schnall; Azim Shariff; Linda J Skitka; Sandra Susan Smith; Cass R Sunstein; Nassim Tabri; Joshua A Tucker; Sander van der Linden; Paul van Lange; Kim A Weeden; Michael J A Wohl; Jamil Zaki; Sean R Zion; Robb Willer Journal: Nat Hum Behav Date: 2020-04-30
Authors: Susan M Sherman; Louise E Smith; Julius Sim; Richard Amlôt; Megan Cutts; Hannah Dasch; G James Rubin; Nick Sevdalis Journal: Hum Vaccin Immunother Date: 2020-11-26 Impact factor: 3.452