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Planning for a COVID-19 vaccination campaign in New Zealand: trust, affective and cognitive attitudes, and COVID-19 vaccine intention

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Abstract

Building public trust and willingness to vaccinate against COVID-19 is as important as developing a safe and effective vaccine to contain the pandemic. Based on the theory of planned behaviour and trust heuristic, this study tests factors associated with COVID-19 vaccination intentions using a national sample survey of the New Zealand public (N = 1040). Results show that while trust in health experts, Prime Minister Jacinda Ardern, and mass media are significantly associated with COVID-19 vaccine intention, affective attitude, and cognitive attitude partly mediate this relationship. Findings can help inform theory and practice of health campaigns to increase COVID-19 vaccine uptake. Trusted sources communicating information that addresses prevailing vaccine concerns are likely to increase public enthusiasm for COVID-19 vaccination.
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Communication Research and Practice
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Planning for a COVID-19 vaccination campaign
in New Zealand: trust, affective and cognitive
attitudes, and COVID-19 vaccine intention
Jagadish Thaker & Christopher Cook
To cite this article: Jagadish Thaker & Christopher Cook (2022): Planning for a COVID-19
vaccination campaign in New Zealand: trust, affective and cognitive attitudes, and COVID-19
vaccine intention, Communication Research and Practice, DOI: 10.1080/22041451.2021.2022325
To link to this article: https://doi.org/10.1080/22041451.2021.2022325
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Published online: 27 Jan 2022.
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Planning for a COVID-19 vaccination campaign in New
Zealand: trust, aective and cognitive attitudes, and
COVID-19 vaccine intention
Jagadish Thaker
a
and Christopher Cook
b
a
School of Communication, Journalism & Marketing, Massey University, Wellington, New Zealand;
b
Independent Health Communication Researcher
ABSTRACT
Building public trust and willingness to vaccinate against COVID-19 is
as important as developing a safe and eective vaccine to contain the
pandemic. Based on the theory of planned behaviour and trust heur-
istic, this study tests factors associated with COVID-19 vaccination
intentions using a national sample survey of the New Zealand public
(N = 1040). Results show that while trust in health experts, Prime
Minister Jacinda Ardern, and mass media are signicantly associated
with COVID-19 vaccine intention, aective attitude, and cognitive atti-
tude partly mediate this relationship. Findings can help inform theory
and practice of health campaigns to increase COVID-19 vaccine uptake.
Trusted sources communicating information that addresses prevailing
vaccine concerns are likely to increase public enthusiasm for COVID-19
vaccination.
KEYWORDS
COVID-19; vaccination
intentions; vaccine attitudes;
trust; health campaign;
SARS-CoV-2
The coronavirus disease 2019 (COVID-19) has resulted in over 5.5 million deaths and
198 million cases worldwide (https://covid19.who.int). Several countries have reported
repeated surges in infection rates and return of lockdowns, such as Australia, Germany,
and France, among others. With 51 deaths, New Zealand has been one of the few
countries that have been largely successful in containing the COVID-19 spread so far,
due to tough border controls and effective health communication (Roy, 2020; World
Health Organization, 2020).
Just as important as developing a COVID-19 vaccine is to develop public enthusiasm
for vaccination. Public health experts originally estimated that at least 75% of the
population needed to be vaccinated against COVID-19 for ‘herd immunity’ (Bartsch
et al., 2020), with higher rates of vaccination for new COVID-19 variants. However,
initially, public opinion surveys indicated a significant proportion of the population,
about 20–30% in the early stages of the pandemic, did not intend to get a COVID-19
vaccine (Ipsos, 2020; O’Keefe, 2020). In New Zealand, according to the Ministry of
Health surveys, about a quarter of the public (24%) was hesitant and another 16% said
CONTACT Jagadish Thaker jthaker@auckland.ac.nz
Supplemental data for this article can be accessed here.
COMMUNICATION RESEARCH AND PRACTICE
https://doi.org/10.1080/22041451.2021.2022325
© 2022 Australian and New Zealand Communication Association
they would not take a ‘well-tested and approved’ COVID-19 vaccine (Ministry of Health,
2021). Other studies show similar rates of vaccine hesitancy and scepticism in New
Zealand (Thaker, 2021).
Despite much improved vaccination rates there is still an urgent need to understand
factors that shape public intentions to take a COVID-19 vaccine so that public health
officials and other stakeholders can provide information that addresses and assuages
public concerns. Given the changing nature of the disease and the uncertainty related to
vaccine development and administration in the face of the Omicron variant, this study
seeks to evaluate an integrative framework by aligning attitudes and trust heuristic with
vaccine intentions, adding to the theory of planned behaviour in examining the relation-
ship between trust, attitudes, intentions (Larson et al., 2018; Yaqub, Castle-Clarke,
Sevdalis, & Chataway, 2014).
Attitudes are a key construct to understand individuals’ intentions to perform
a behaviour, according to several social cognition theories of behaviour change
(Ajzen, 1991; Hagger & Hamilton, 2021). For example, according to the theory of
planned behaviour (Ajzen, 1991), attitude, subjective norms, and perceived beha-
vioural control lead to behavioural intentions, which in turn, serve as a proximal
predictor of behaviours. We choose to focus on attitude as it is often the strongest
correlation of behavioural intentions (Hagger & Hamilton, 2021), as studies in vaccine
intentions (Xiao & Wong, 2020) and COVID-19 prevention or mitigation intentions
(Fischer & Karl, 2021) also attest. Attitude is also a key mediator among different
constructs of the theory of the planned behaviour, such as attitudes mediating the
association between norms and intentions (Stout, Christy, Winger, Vadaparampil, &
Mosher, 2020).
Trust likely plays an important role in shaping public attitudes (e.g. Earle, 2010;
Larson et al., 2018; Liu & Yang, 2020). When faced with a new policy or an
unfamiliar technology, individuals use information from their trusted sources to
form their own opinions. Messages from trusted sources help individuals to process
complex information quickly and efficiently, thereby affecting public attitudes, beliefs,
and behaviours.
Given the novelty of the pandemic and equally novel vaccines, an integrative approach
is likely to help identify important factors that drive vaccination intentions as
‘Vaccination represents a set of behavio(u)rs in an applied setting and thus is not the
domain of any single psychological theory’ (Brewer, Chapman, Rothman, Leask, &
Kempe, 2017, p. 187). New Zealand has been relatively successful in controlling the
community transmission of COVID-19. The next challenge is to vaccinate a substantial
proportion of its public as soon as possible to reach ‘herd immunity’. Multiple opinion
surveys show a quarter of the New Zealand public is hesitant, and a small but substantive
majority is sceptical (Thaker, 2021; Ministry of Health, 2021). Understanding the factors
associated with COVID-19 vaccination intentions will help health officials and advocacy
groups develop communication campaigns to ensure high vaccination uptake.
This study addresses a number of limitations in previous research, including
student samples and a limited number of studies outside the US and European
context (see Larson et al., 2016 for review). It seeks to add to our knowledge about
how trust and attitudes align with COVID-19 vaccine intentions, thereby contributing
2J. THAKER AND C. COOK
to the theory of planned behaviour. This study explores how both the affective and
cognitive dimensions of attitudes align with behavioural intentions to get a COVID-
19 vaccine, controlling for a number of measures.
Literature review
Attitudes towards vaccines
Vaccination attitudes can be defined as an expression of support or hesitancy across
different vaccines (e.g. Yaqub et al., 2014). Attitudes towards vaccines are comprised of
both affective (e.g. getting vaccine is desirable) and cognitive (e.g. getting vaccine is
effective) dimensions (e.g. Xiao, 2019). Attitudes in response to emotions, such as positive
or negative feelings, are ‘affective attitude’ while rational evaluations, such as effective or
ineffectiveness about vaccines, are termed as ‘cognitive attitude’ (e.g. Xiao, 2019).
A number of studies show that favourable attitudes are associated with vaccination
intentions (Brewer et al., 2017; Krishna, 2018; Xiao, 2019). Zhou et al. (2018) found that
attitudes were a leading factor of behavioural intentions. Internal factors such as percep-
tions about quality, accessibility, safety of vaccination services, and external factors such
as vaccination promotion campaigns together influence attitudes, which in turn, are a key
determinant of parents’ intention to get their child a vaccine. They argued that consistent
with the theory of planned behaviour, attitude was an intermediary variable in the model
between influencing factors and behaviours. Indeed, Stout et al. (2020) found that
attitudes were a key mediator between social norms and vaccine intentions, such that
perceiving greater parental and doctor support for HPV vaccination was related to more
favourable attitudes towards the vaccine, which, in turn, were related to increased vaccine
intentions. However, they did not find attitudes mediating direct and significant associa-
tion between friend norms and intentions. However, Stout et al. (2020) do not distinguish
between affective and cognitive attitudes.
Hypothesis H1: Affective attitude towards vaccines will be positively associated with
COVID-19 vaccine intention.
Hypothesis H2: Cognitive attitude towards vaccines will be positively associated with
COVID-19 vaccine intention.
Trust in informational sources
A large and substantial body of research elucidates that for individuals, information from
a trusted source helps reduce cognitive effort and provides a short-cut to make judge-
ments about an issue (e.g. (Slovic, 1993)).
A number of studies show that trust in health experts, government, mass media are
important determinants of vaccination intentions and behaviour (Cadeddu,
Daugbjerg, Ricciardi, & Rosano, 2020; de Figueiredo, Simas, Karafillakis, Paterson,
& Larson, 2020). Liu and Yang (2020) found that trust was positively associated with
vaccination intention and was one of the strongest associated factors with intention
for a domestic vaccine (compared to imported vaccine, where trust was not
COMMUNICATION RESEARCH AND PRACTICE 3
significantly associated). However, their study only tested trust in government.
Krishna (2018) found that trust in Centers for Disease Control and trust in healthcare
professionals was associated with less negative attitudes towards vaccines and was
positively associated with intention to vaccinate. However, trust in government and in
pharmaceutical companies was not associated with attitudes about vaccines. Further,
a key limitation of these studies is lack of measurement of trust in different agencies,
particularly trust in mass media (Freimuth, Jamison, An, Hancock, & Quinn, 2017;
Larson et al., 2018), trust in family and friends (de Figueiredo et al., 2020). For
example, de Figueiredo et al. (2020) found that trusting health-care workers more
than family, friends, or other non-medical sources for medical and health advice was
most consistently associated with improved vaccination uptake.
Particularly, media as trust intermediary between health experts and public
deserves our attention as the public primarily learns about scientific breakthroughs
through media. Trust in media and trust in health experts is likely to be different
and it is important to test their relative importance. Trust in mass media refers to
trust in mainstream press such as newspapers, radio and television, which are
leading sources of information to the public about science and health issues
(Nisbet & Markowitz, 2016; Reuters Institute for the Study of Journalism, 2021).
Global surveys also show that the public use of and trust in traditional media
channels, particularly TV news, has increased following COVID-19. At the same
time, trust in news from social media or Internet search has remained relatively
stable at 25% (Digital News Report, 2021).
Further, this study tests trust in particular members of the government, such as Jacinda
Ardern, the Prime Minister of New Zealand, who was globally acknowledged as leading
a successful plan to contain COVID-19 community transmission (Roy, 2020).
H3: Trust in mass media will be positively associated with COVID-19 vaccine intention.
H4: Trust in family and friends will be negatively associated with COVID-19 vaccine
intention.
H5: Trust in Prime Minister Jacinda Ardern will be positively associated with COVID-19
vaccine intention.
H6: Trust in health experts will be positively associated with COVID-19 vaccine
intention.
The role of trust on attitudes and intentions
A unique aspect of this paper is to explore how trusted sources affect people’s attitudes
towards vaccine, adding to the theory of planned behaviour framework is examining the
relationship between trust, attitudes, intentions (Larson et al., 2018; Yaqub et al., 2014).
Information from trusted sources makes it easy for individuals to form attitudes,
particularly about unfamiliar objects such as new vaccines.
4J. THAKER AND C. COOK
One of the pathways through which trust can be associated with behavioural intention
is through attitudes, particularly affective attitudes. While previous studies show that
both affective and cognitive attitudinal components are distinct and predict intention
and behaviour, it is not clear if one dimension is more predictive than other. In a meta-
analysis of 14 health-promotion behaviours, affective attitude was a significantly more
powerful predictor of behaviour than cognitive attitude (Lawton, Conner, & McEachan,
2009). For risky behaviours such as speeding, binge drinking, affective attitude was
a stronger predictor of intentions and behaviours than cognitive attitude. Contrarily,
for directed healthy behaviours, such as regular exercise, cognitive attitude may be more
important than affective attitude in shaping intentions
Vaccination can be termed proactive prevention behaviour; therefore, cognitive
attitudes may play a more important role in motivating behaviour than affective
attitudes. Indeed, Xiao (2019) found that cognitive attitude was significantly
associated with HPV vaccine intentions, whereas affective attitude was not.
However, previous research has shown that perceptions about risk, fear of needles,
perceived vaccination experiences, also affect vaccine intentions (see Yaqub et al.,
2014). As a result, both affective and cognitive dimensions are important to
explore (Lee, Carvallo, Lee, Chung, & Shin, 2019). It is important to replicate
the findings and explore how trust is associated with the affective attitude and
cognitive attitude and COVID-19 vaccine intentions.
RQ1: Do affective and cognitive attitudes mediate the association between trust (mass
media, family and friends, Prime Minister Ardern, health experts) and COVID-19
vaccine intention?
Apart from attitudes, previous vaccination behaviour has also been found to shape
future vaccine intention. For example, Liu and Yang (2020) found that previous vaccina-
tion was the strongest factors associated with vaccination intention compared with other
factors considered in their study.
H6: Previous vaccination behaviour will be positively associated with COVID-19 vaccine
intention.
Method
A nationally representative sample survey (N = 1040) of the New Zealand adults was
conducted in July 2020, after the country was briefly at the Alert Level 1, with fewer
restrictions on social gatherings and recommended precautions of physical distancing,
mask wearing, and contact tracing. The web-based survey was fielded by Qualtrics, using
their representative online panel. Qualtrics maintains an active online panel that is
representative of the target population (Qualtrics Panel, n.d). The panellists receive an
incentive such as a flat fee or discount gift card for participation. The average time to
complete the survey was 22 minutes. Ethics approval was filed at the human research
review board at (anonymised for peer review) university and the study was determined to
be exempt from a full review. Participants provided informed consent after reading brief
aims of the survey. The data was weighted based on age, sex, education, and ethnicity, post-
survey, to account for slight difference between the sample and the census estimates. The
Table 1 provides the descriptive statistics of the sample along with the Census estimates.
COMMUNICATION RESEARCH AND PRACTICE 5
Measures
COVID-19 vaccination intentions
Following previous studies (e.g. Liu & Yang, 2020) and recent surveys (O’Keefe, 2020;
Reiter, Pennell, & Katz, 2020), COVID-19 vaccination intention was measured using three
items. The three questions started with a prompt, ‘How much do you agree or disagree with
the following statements’, and was measured on a 5-point scale from ‘strongly agree’, to
strongly disagree’, with neither agree nor disagreeas the mid-point of the scale. The scales
were reverse coded so that higher scores indicate more willingness to get a COVID-19
vaccine. The three measures were: (1) ‘I intend to get vaccinated against the coronavirus’,
(M = 3.84, SD = 1.24) (2) ‘I will get vaccinated against the coronavirus even if I must pay for
the vaccine’, (M = 3.45, SD = 1.37) and (3) ‘I am willing to put my name on the list to get
vaccinated against the coronavirus’ (M = 3.59, SD = 1.33). The mean of the three measures
was used as an indicator of vaccine intentions (Cronbach’s α = .92, M = 3.63, SD = 1.22).
The measure about willingness to pay for a vaccine was adopted from previous studies (e.g.
Lin et al., 2020) as an additional indicator for vaccination intention and because it is possible
that vaccination against COVID-19 may become annual affair to fight new variants (Miller &
Burger, 2021). The mean of the three items were used as compute intention to vaccinate
against COVID-19 scale (M = 3.63, SD = 1.21). The three items were strongly correlated with
each other (r’s ranged from 0.77 to .83, p <. 001). Regression models were run on each of the
Table 1. Demographic characteristics of the sample.
N (unweighted) % (unweighted) % (weighted) % Census Estimate
Total 1040 100 100 100
Female 609 58.6 51 50.6
Male 431 41.4 49 49.3
Age
18–25 189 18.2 14 14
26–35 220 21.2 18 18
36–45 175 16.8 16 16
46–55 163 15.7 18 18
56–65 127 12.2 15 15
66 and above 166 16 19 19
Education
No qualification 96 9.2 19 18.19
Level 1 to Level 6 diploma 577 55.5 54 51.10
Bachelor’s degree or higher 367 35.3 27 24.82*
Ethnicity
European New Zealander 648 62.3 61.5 64
Māori 139 13.4 16.3 17
Pasifika 50 4.8 7.7 8
Asian or other 203 19.5 14.4 15.1
Annual personal income
Less than $19,999 280 26.9 27.5
$20,000 to $39,999 254 24.4 26.2
$40,000 to $59,999 182 17.5 18
$60,000 to $79,999 138 13.3 12.5
$80,000 to $99,999 68 6.5 5.6
$100,000 to $119,999 64 6.2 5.3
$120,000 or above 50 4.8 4.4
N = 1040. The census estimates according to 2018 census (https://www.stats.govt.nz/2018-census/). * Percentages do not
add to 100% as some responses were unidentifiable or not stated in the Census.
6J. THAKER AND C. COOK
ittabems as well as the index of the items. As the results were similar across the items, results
using the COVID-19 vaccination intention scale are presented below. Supplementary Table 1
provides multiple regression results of individual vaccination intention measures.
Attitudes towards vaccines
Attitudes towards vaccines were assessed using measures adapted from previous studies,
including both affective and cognitive dimensions (e.g. Xiao, 2019). Respondents rated,
‘Generally speaking, how do you feel about vaccines?’ on a scale consisting of 1–7
semantic differential items (bad/good, unpleasant/pleasant, undesirable/desirable) as
a measure of affective attitude (Cronbach’s α = .87, M = 5.05, SD = 1.75). Similarly,
cognitive attitude was measured on a semantic differential scale (useless/useful, worth-
less/valuable, ineffective/effective) (Cronbach’s α = .96, M = 5.65, SD = 1.71). Higher
scores indicate more favourable attitudes towards vaccines.
Previous vaccination refusal
Based on a five-point scale, from strongly disagree’, to strongly agree’, participants were
asked to respond to (1) ‘I have previously refused vaccination’ (M = 1.97, SD = 1.33) and
“I have previously refused to get my child vaccinated (M = 1.84, SD = 1.18). The two
items were strongly correlated (r = .73, p < .001) and their average was used as a measure
of previous vaccination refusal (M = 1.90, SD = 1.17). Higher scores indicate a high
degree of previous vaccination refusal.
Trust in informational sources
Trust in mass media was measured using five items on a five-point scale, strongly distrust
to strongly trust: (1) national newspapers such as New Zealand Herald (M = 3.39,
SD = 1.17), (2) online news such as Stu.co.nz (a popular national news website in
New Zealand) (M = 3.31, SD = 1.20), (3) radio such as RNZ (Radio New Zealand,
a national radio similar to BBC) (M = 3.54, SD = 1.05), (4) international newspapers
such as The Guardian and New York Times (M = 3.06, SD = 1.18), and (5) TV news (M
= 3.66, SD = 1.17). The five items were added to create an index of trust in mass media
(Cronbach’s α = .84, M = 3.39, SD = 0.91).
Trust in family and friends as a source of accurate information was measured using
a single item on a 5-point scale, strongly distrust to strongly trust (M = 3.82, SD = 0.91).
Similarly, trust in the Prime Minister Jacinda Ardern was measured using a single item
on a 5-point scale (M = 3.97, SD = 1.23).
Using a 5-point response scale, with strongly distrust to strongly trust, respon-
dents were asked how much they trust in (1) scientists (M = 3.99, SD = 1.09), (2)
medical experts (M = 4.14, SD = 1.02), (3) infectious disease experts (M = 4.11,
SD = 1.02), and (4) your doctor or GP (general practitioner) (M = 4.16, SD = .94).
Higher scores indicate more trust in health experts. The four items were added to
compute an index of trust in health experts (r’s ranged from .47 to .75, p < .001;
α = .87, Kaiser-Meyer-Olkin measure = .82, Bartlett’s test of sphericity (χ2
(6) = 2151.39, p < .001)).
COMMUNICATION RESEARCH AND PRACTICE 7
Covariates
A range of demographic variables were tested in the model, including gender (Female,
51%, Male, 49%), age (M = 3.59, SD = 1.69), education (no formal certification (19%),
post-school certification (54%), and graduate degree and above (27%), M = 2.07,
SD = .67), income (M = 2.76, SD = 1.69), parental status (1, 60%), currently employed
(1, 49%), and marital status (1, married or currently in some form of civil or legal
partnership, 56%). Ethnicity was measured using the New Zealand Census and was
dummy coded comparing Asians with other ethnicities.
Economic impact due to COVID-19 (M = 0.23, SD = .30) was measured as an average
of four items, following a prompt, ‘In the last 60 days, have you or a member of your
household experienced any of the following because of the spread of the coronavirus or
not?’ The measures were, ‘Lost income from a job or business’ (32.5% stating Yes), ‘Had
your work hours reduced’ (33.2%, Yes), ‘Lost a job’ (13.5%, Yes), and ‘Filed for unem-
ployment benefits’ (14.4%, Yes). Psychological impact (M = 0.28, SD = .32) was assessed
following the same prompt and as an average of the following measures: ‘Had trouble
sleeping’ (42.6%) and ‘Felt depressed’ (58.6%).
Analysis
Analysis proceeded in a stepwise fashion, starting with checking individual vari-
ables, testing scales, and correlations between important constructs. Very few
missing values were found in the data, the highest for vaccine attitudes (n = 10).
Because of such a small number of missing values, missing value imputation was
not performed. Instead, missing values were dropped from the analysis.
Hierarchical regression models were used, first with demographic variables only,
and then adding key constructs in model 2 to check if trust and attitudes can
explain unique and significant variation in vaccine intention above and beyond
demographic variables. Evaluation of standardised residuals, through histogram,
P-P plot, and scatter plots, indicated that the regression assumptions were met.
The Variance Inflation Factor (VIF) values ranged from 1.08 to 3.12 and the
tolerance statistics were all above 0.2 (range 0.32 to 0.92), indicating no collinear-
ity within the data. Mediation analyses was conducted using Hayes’ bootstrapping
procedures (5000 resamples) in SPSS (version 27; IBM Corp, Armonk, NY) macro,
model 6 (Hayes, 2017). Alternative models of mediation such as trust mediating
the attitude-intention relationship were also tested.
Results
Correlation between key variables is presented in Table 2. Table 3 presents the results of
a hierarchical multiple regression model, with demographic and COVID-19 impact
variables entered in the first block, followed by trust in information sources, attitudes
towards vaccines, and previous vaccination behaviour variables entered in the second
block.
Among the demographic variables, education (β = .12, p < .001) and income (β = .12,
p < .01) were significantly associated with COVID-19 vaccination intentions. Māori
(β = −.11, p < .05) (compared to Asians) and those with children (β = −.08, p < .05)
8J. THAKER AND C. COOK
(compared to those without children) were less likely to vaccinate against COVID-19.
Other demographic variables tested in this study were not significantly associated with
COVID-19 vaccination intentions, including economic and psychological impact due to
COVID-19. Demographic variables explained only 5% of variance in COVID-19 vaccine
intentions.
Table 2. Correlations between COVID-19 vaccination intentions and key variables.
1 2 3 4 5 6 7 8 9 10
1 COVID-19 vaccine
intention
1
2 COVID-19 Economic
impact
−0.03 1
3 COVID-19 Psychological
impact
−0.04 .50** 1
4 Trust mass media .27** 0.02 0.02 1
5 Trust family & friends 0.03 0.01 0.01 .26** 1
6 Trust Jacinda Ardern .26** −.08* −0.01 .39** .16** 1
7 Trust health experts .40** −.06* −0.04 .42** .20** .52** 1
8 Affective attitude .57** −0.06 −0.05 .23** 0.01 .20** .37** 1
9 Cognitive attitude .53** −.07* −0.05 .20** 0.01 .13** .37** .80** 1
10 Previous vaccination
behaviour
−.26** .15** .13** −0.04 −0.03 −.08** −.29** −.45** −.49** 1
n = 1015, list-wise deletion of missing values. *** p < .001 ** p < .01, * p < .05
Table 3. Results of hierarchical regression analysis predicting COVID-19 vaccine intentions.
B SE β B SE β
(Constant) 3.02 0.22 0.16 0.27
Gender (Female) −0.07 0.08 −0.03 −0.12 0.06 −0.04
Age 0.05 0.03 0.07 −0.02 0.02 −0.03
Education 0.21 0.06 0.12*** 0.04 0.05 0.02
Annual income 0.08 0.03 0.12** 0.07 0.02 0.10***
Currently employed −0.05 0.09 −0.02 −0.01 0.07 0.00
Parental status −0.20 0.08 −0.08* −0.12 0.07 −0.05
European New Zealander −0.16 0.12 −0.06 −0.03 0.09 −0.01
Māori −0.36 0.14 −0.11** −0.17 0.11 −0.04
Pasifika −0.23 0.17 −0.05 −0.15 0.13 −0.03
Ideology 0.04 0.04 0.03 −0.02 0.03 −0.01
COVID-19 Economic impact −0.12 0.15 −0.03 0.02 0.12 0.00
COVID-19 Psychological impact 0.01 0.14 0.01 −0.03 0.11 −0.01
Trust mass media 0.09 0.04 0.07*
Trust family & friends −0.03 0.03 −0.03
Trust Jacinda Ardern 0.10 0.03 0.09**
Trust health experts 0.22 0.05 0.16***
Affective attitude 0.22 0.03 0.31***
Cognitive attitude 0.15 0.03 0.20***
Previous vaccination refusal 0.03 0.03 0.03
ΔR
2
0.05*** 0.40***
n = 1012. Female (1) compared to male (1). Current employed (1) compared to others (retired, student, 0). Parental status
(with children, 1) compared to others (0). Ethnicity was dummy coded comparing Asians to other categories.
B = unstandardised coefficient, SE = standard error, β = standardised coefficient. *** p < .001, ** p < .01, * p < .05.
COMMUNICATION RESEARCH AND PRACTICE 9
However, when accounting for other theory-based key variables tested in this study, only
income (β = .10, p < .001) was significantly associated with intentions to vaccinate against
COVID-19. Affective attitude (β = .31, p < .001) was significantly associated with vaccine
intention, supporting H1. Cognitive attitude (β = .20, p < .001) was also significantly and
positively associated with COVID-19 vaccination intention, supporting H2.
The data supported hypothesis H3: Trust in mass media was associated with inten-
tions to vaccinate against COVID-19 (β = .07, p < .05). There was no significant
association between trust in family and friends and COVID-19 vaccine intention
(β = −.03, p = .28); H4 was not supported. There was a positive association between
trust in Prime Minister Jacinda Ardern and COVID-19 vaccine intentions, supporting
H5 (β = .09, p < .01). Data also supported H6, there was significant positive association
between trust in health experts and COVID-19 vaccination intentions (β = .16, p < .001).
While previous vaccination refusal was negatively associated with COVID-19 vaccination
intention in univariate analysis (r = −.26, p < .001), when accounting for other measures, it
was not significantly associated with COVID-19 vaccine intention (β = .03, p = .31). The final
model accounted for 40% of variance in COVID-19 vaccination intentions.
A series of parallel mediation models were explored to understand the association
between trust, attitudes, and COIVD-19 vaccine intention. First, some of the association
between trust in mass media and COVID-19 vaccine intentions are indirect, through
attitudes (indirect effect 0.16; 99% CI: .11–.22). Much of the indirect association between
trust in mass media and intention was accounted through affective attitude pathway
(indirect effect 0.11; 99% CI:.07–0.15). The indirect effect was also significant through
cognitive attitude pathway (indirect effect .04; 99% CI: .02–.08).
Second, there was no significant indirect effect between trust in family and friends and
intention through attitudes as the effect includes zero (indirect effect 0.005; 99% CI: -
.035–.046).
Third, there was a significant indirect effect between trust in Prime Minister Jacinda
Ardern and intention through attitudes (indirect effect 0.11; 99% CI: .07–.15). Much of this
indirect effect was accounted through affective attitude (indirect effect .07; 99% CI: .05–.12)
but the pathway through cognitive attitude (indirect effect .03; 99% CI: .01–.06) was also
significantly different from zero. In other words, the association between trust in Prime
Minister and intention was partly mediated by both affective and cognitive attitudes.
Fourth, there was a significant indirect effect between trust in health experts and
intention through attitudes (indirect effect 0.24; 99% CI: .18–.29). Much of this indirect
effect was accounted through affective attitude (indirect effect .17; 99% CI: .12–.23) but
the pathway through cognitive attitude (indirect effect .07; 99% CI: .02–.12) was also
significantly different from zero. Please see Supplementary Figures 1 through 4.
To summarise, three of the four mediation models between trust and intention via
affective and cognitive attitudes were significant, and it appears that the indirect effect
between trust and intention is primarily through affective attitudes (see Hayes, 2017,
p. 166). Alternative relationships, with trust as a mediator between attitudes and inten-
tion were also significant (not reported here) and implications are highlighted below.
10 J. THAKER AND C. COOK
Discussion
Findings from this study indicate that trust in informational sources such as mass media
(mainstream print and online newspapers, radio, and TV), the Prime Minister Jacinda
Ardern, and health experts is associated with affective attitude and cognitive attitude,
which, in turn, align with intentions to vaccinate against COVID-19. It is important to
note that while this study highlights attitudes as a mediator between trust and intention,
other pathways such as trust mediating the attitude–behaviour relationship or behaviour as
a causal predictor of both trust and attitudes, are all equally plausible and should be
explored in future through experiments and longitudinal analysis.
First, consistent with the theory of planned behaviour (Ajzen, 1991) and empirical
evidence (Stout et al., 2020; Zhou et al., 2018), favourable attitudes towards vaccines were
most strongly associated with vaccine intention, among the factors tested in this study. This
finding is similar to other studies (Krishna, 2018; Larson et al., 2016) and indicates that
vaccine attitudes are important in forming behavioural intentions, a proximal predictor of
behaviours. In particular, both affective attitude and cognitive attitude were strongly asso-
ciated with COVID-19 vaccine intentions, highlighting that attitudes consist of two dimen-
sions (Lawton et al., 2009; Lee et al., 2019; Xiao, 2019). Public attitudes to specific vaccines,
including COVID-19 vaccine, are likely shaped by a general attitude towards vaccines.
Second, findings of this study align with the assertion that trust is important in public
health campaigns as individuals pay attention to, and are more likely to follow advice
from, trusted sources of information (Cadeddu et al., 2020; de Figueiredo et al., 2020).
Trust in mass media, Prime Minister Jacinda Ardern, and health experts was positively
associated with COVID-19 vaccination intentions, in part, via attitudes. This line of
reasoning aligns with the premise presented above that trust acts as a heuristic for
information processing, particularly when individuals have to understand complex
scientific information, such as a rapid testing and approval of a novel vaccine against
COVID-19. Across three sources of trust – mainstream mass media, Prime Minister
Jacinda Ardern, and health experts – affective attitude and cognitive attitude partly
mediated the association between trust and intention.
Previous studies have largely focussed on media use and trust in mass media, as the
public is likely to come to know about health and scientific topics through mass media.
Similar to previous studies, trust in traditional news sources, such as printed and online
newspapers, TV news, radio news, was positively associated with intentions, indicating the
role of mass media to increase COVID-19 vaccine uptake. Empirical evidence, for example,
indicates that every additional news headline about influence, such as in the USA Today
newspaper, is associated with a significant uptake of the influenza vaccine among elderly
(Chen & Stoecker, 2020; Yoo, Holland, Bhattacharya, Phelps, & Szilagyi, 2010). One of the
pathways that trust in mainstream press may motivate vaccine intentions is by improving
both affective and cognitive attitudes towards vaccination, but the pathway is stronger via
affective attitudes. These findings imply that trust in mass media facilitates favourable
vaccine attitudes, which in turn, improves the public mood for vaccine uptake.
In a novel finding, trust in specific political leaders, the Prime Minister Jacinda Ardern
in this case, was positively associated with COVID-19 vaccination intention. Previous
studies measured trust in government rather than individual political leaders and found
mixed evidence (Krishna, 2018; Liu & Yang, 2020). This finding highlights that
COMMUNICATION RESEARCH AND PRACTICE 11
competency of political leaders – as much as public institutions – plays an important role
in how the public responds to a global public health crisis. In contrast to political leaders
in other countries, Prime Minister Ardern has been hailed globally as leading the country
to contain COVID-19 community transmission through formal press conferences as well
as regular social media appearances that likely made her a trustworthy leader (Roy, 2020).
Some of the association between trust in the Prime Minister and vaccine intention is
explained by attitudes – a large proportion of this mediation can be attributed to affective
attitude even though mediation via cognitive attitude remains significant.
Family and friends as a source of trusted information had no significant association
with either vaccine attitudes or with COVID-19 vaccination intentions, in contrast to our
expectations. Communication with trusted family and friends is frequent, accessible,
spatially and emotionally immediate, thereby more impactful in the vaccination decision-
making process, compared to more distant trusted sources such media sources, scientists,
or government (Yaqub et al., 2014). Therefore, it is only expected – and previous research
demonstrates – that family and friends are important sources to engage for any effective
health campaign to promote vaccination uptake (Chan, Jamieson, & Albarracin, 2020).
One possibility is that trust in information from family and friends probably relies on
other factors such as perceived expertise about new risks such as COVID-19, previous
vaccination behaviour, and other social norms (de Figueiredo et al., 2020; Justwan,
Baumgaertner, Carlisle, Carson, & Kizer, 2019; Larson et al., 2018). For example, Stout
et al. (2020) found that support from friends was less influential than doctors or parents
in shaping HPV vaccination intentions. Future research can attend to these other factors
in understanding how trusted friends and family members shape attitudes and vaccine
intentions.
Trust in health experts was associated with both affective and cognitive attitude, which
in turn, were associated with vaccine intentions. Previous research shows that health
experts are among the most trusted source of influence for vaccine uptake (Cadeddu
et al., 2020; Larson et al., 2018) and the findings highlight the role of health experts in
increasing vaccine uptake. Together, these findings highlight that on uncertain issues,
people have higher trust in relatively unfamiliar health experts than more familiar and
socially congruent groups such as their family and friends. Nevertheless, future research
should replicate and extend these findings between trust in different sources, attitudes,
and intentions.
As expected, individuals who had previously refused a vaccine were more likely to
decline getting a COVID-19 vaccine in univariate analysis. But after accounting for other
variables, including vaccine attitudes, it was not significantly associated with vaccine
intentions. At the same time, vaccine attitudes and previous vaccination refusal were
strongly and negatively associated (r = −.51, p < .001) and it is possible that the
association between previous behaviour towards vaccine and intentions for a future
COVID-19 vaccine are partly or completely mediated through other socio-cognitive
factors such as attitudes, norms, and behavioural control (Hagger & Hamilton, 2021).
Future research can explore these implications.
The central implication of this study is that a key public health investment to reduce
public vaccine hesitancy about COVID-19 vaccines is for trusted voices to speak more
often as that can boost favourable attitudes towards vaccination, which in turn can
improve vaccine uptake. According to the World Health Organisation (WHO) (2019)
12 J. THAKER AND C. COOK
(https://www.who.int/news-room/spotlight/ten-threats-to-global-health-in-2019), vac-
cine hesitancy is one of the ten most important health threats to the world. Vaccine
attitudes play a central role in vaccination intentions is a key learning of the paper that
may help attenuate the declining vaccination rates across the world.
Among the demographic variables, only income was consistently associated with
intention to vaccinate against COVID-19, whereas other indicators such as gender,
ethnicity, education, parental status, and age were just short of significance. The full
model, with vaccine attitudes and trust, explained 40% of variance in vaccine intentions,
indicating that these variables can largely account for differences in intentions and play
a more important role in how individuals make sense of a health issue and decide about
preventive behaviours such as vaccination (de Figueiredo et al., 2020; Hagger &
Hamilton, 2021; Larson et al., 2016).
Limitations
The findings of this cross-section survey need to be replicated in other countries as well
as tested longitudinally to identify how changing information about a potential
COVID-19 vaccine and its efficacy against new COVID-19 variants, shapes public
behavioural intention to get a vaccine. While this study tested trust in mass media,
future research should also explore trust in social media in influencing vaccine inten-
tions (Liu & Yang, 2020). In particular, this study explored the association between
trust and attitude and found that while trust and attitude mutually influence beha-
vioural intentions, the mediation effect was mostly explained by the association
between trust and affective attitude to intentions. Future research should explore the
role of trust along with the three constructs of attitude, social norms, and behavioural
control as per theory of planned behaviour. It is possible that trusted family and friends
have a stronger association with social norms, which in turn, affect intention. Another
limitation is the single measure of trust in family and friends in the study and future
researchers should use multiple measures to better assess its association with vaccine
attitudes and intentions. Understanding how trust contributes to the theory of planned
behaviour variables can better account of how public makes decisions about vaccina-
tion intentions.
Conclusion
Vaccination is our best defence against COVID-19 so far. Some scientists fear that new
variants of COVID-19 like Omicron, may make vaccination an annual affair (Miller &
Burger, 2021), further highlighting the need to track public attitudes and behaviours.
This study shows that general attitudes towards vaccines and trust in informational
sources are important correlates of intentions to vaccinate against COVID-19. For an
effective health campaign, both the messages and the messengers play an important role.
Disclosure statement
The authors have no known conflict of interest to disclose.
COMMUNICATION RESEARCH AND PRACTICE 13
Funding
Funding for the data collection was sponsored by Massey University.
Notes on contributors
Dr. Jagadish Thaker (JT) is currently working as a Senior Lecturer in Communication at the
University of Auckland. His research interests are in the fields of health, science, and climate
change communication.
Dr. Christopher Cook (PhD., Massey University) is an independent researcher working in the area
of digital health technologies.
ORCID
Jagadish Thaker http://orcid.org/0000-0003-4589-7512
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Introduction Given the continuing coronavirus disease 2019 (COVID-19) pandemic and much of the U.S. implementing social distancing owing to the lack of alternatives, there has been a push to develop a vaccine to eliminate the need for social distancing. Methods In 2020, the team developed a computational model of the U.S. simulating the spread of COVID-19 coronavirus and vaccination. Results Simulation experiments revealed that to prevent an epidemic (reduce the peak by >99%), the vaccine efficacy has to be at least 60% when vaccination coverage is 100% (reproduction number [R0]=2.5–3.5). This vaccine efficacy threshold rises to 70% when coverage drops to 75% and up to 80% when coverage drops to 60% when R0 is 2.5, rising to 80% when coverage drops to 75% when R0 is 3.5. To extinguish an ongoing epidemic, the vaccine efficacy has to be at least 60% when coverage is 100% and at least 80% when coverage drops to 75% to reduce the peak by 85%–86%, 61%–62%, and 32% when vaccination occurs after 5%, 15%, and 30% of the population have already been exposed to COVID-19 coronavirus. A vaccine with an efficacy between 60% and 80% could still obviate the need for other measures under certain circumstances such as much higher, and in some cases, potentially unachievable, vaccination coverages. Conclusions This study found that the vaccine has to have an efficacy of at least 70% to prevent an epidemic and of at least 80% to largely extinguish an epidemic without any other measures (e.g., social distancing).
Article
Objectives The World Health Organization recognizes that vaccine hesitancy is a top threat to the public health. To address vaccine hesitancy, much research guided by behavioral theories attempted to examine factors that contribute to vaccination intentions. The current study synthesizes the summary effects of attitude, norms and perceived behavioral control on vaccination intentions. Methods We searched five databases with relevant keyword combinations without time constraints. A sample of 5149 participants was included for final analysis. Results Attitude, norms and perceived behavioral control were significant predictors of vaccination intentions with attitude being the strongest. Type of recipient significantly moderated the PBC-intention relationship, while norm-intention correlations were significantly moderated by type of norm measures. Formative belief elicitation research had no moderating influences. Conclusion Our findings demonstrate clear support for the utility of theory of planned behavior in explaining vaccine hesitancy. Research is needed on how interventions can change these constructs to motivate vaccination.