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Big Five Personality Traits and Vaccination: A Systematic Review
and Meta-Analysis
Wiebke Bleidorn, Alexander G. Stahlmann, and Christopher J. Hopwood
Department of Psychology, University of Zurich
Objective: Despite the proven benefits of vaccination, people differ in their willingness to get vaccinated.
These differences are the result of multiple factors, including social, cultural, and psychological variables.
This meta-analysis estimated the effects of people’s Big Five personality traits on their vaccination attitudes,
intentions, and behaviors and examined the role of theoretically and empirically derived moderator vari-
ables. Method: We meta-analyzed data from 28 studies that sampled over 48,000 individuals to estimate
the effects of Big Five personality traits on vaccination attitudes, intentions, and behaviors. In addition,
we tested the moderating effects of age, gender, sample region, sample type (representative vs. convenience),
vaccination measure (attitude, intention, behavior, compound), vaccination type (COVID-19, Influenza, or
other), and reliability of the Big Five measure on the links between personality traits and vaccination.
Results: People with high levels in agreeableness and extraversion, and low levels in neuroticism reported
more positive attitudes toward vaccination, whereas open people reported stronger intentions to get vacci-
nated. Open and agreeable people were also more positive about novel COVID-19 vaccines, whereas extra-
verted people were more positive about influenza vaccines. There were no effects for conscientiousness.
Overall, effect sizes were small but generalized across age. Other moderator effects suggested a more
nuanced picture across cultural regions, sample types, and gender. Conclusions: The findings provide a
compelling picture of significant, albeit small, effects of personality traits on vaccination. Questions remain
about the processes through which personality traits may affect vaccination attitudes, intentions, and poten-
tially also behavior.
Public Significance Statement
Here, we integrated the data from 28 studies that sampled over 48,000 individuals to estimate the effects
of personality differences on people’s vaccination attitudes, intentions, and behaviors. The results sug-
gest that people who are agreeable, extraverted, and emotionally stable are more likely to have positive
attitudes toward vaccination. Additionally, people who are open to experiences have more favorable atti-
tudes toward novel COVID-19vaccines. These findings enhance our understanding of the psychological
factors influencing vaccination decisions and can inform targeted health care campaigns to address vac-
cination hesitancy.
Keywords: personality, Big Five, vaccination, attitudes, COVID-19s
People differ in their willingness to get vaccinated against poten-
tial illnesses such as measles, influenza, or COVID-19. Despite the
proven benefits of vaccination, disparities in vaccination rates per-
sist, driven in part by a complex interplay of psychological, social,
and cultural factors (Halstead et al., 2022;Podlesek et al., 2011).
Among these factors, personality traits have emerged as promising
candidates for understanding the heterogeneous attitudes, intentions,
and behaviors related to vaccination (Webster et al., 2023).
The literature on personality and vaccination is a new and rapidly
growing area of research, recently fueled by the public discourse
This article was published Online First September 19, 2024.
Anna Catriona Whittaker served as action editor.
Wiebke Bleidorn https://orcid.org/0000-0003-3795-8143
This study has been supported by a research grant from the Swiss National
Science Foundation awarded to Wiebke Bleidorn (Grant 205026: https://p3
.snf.ch/project-205026). We have no known conflicts of interest to disclose.
All data are made available on the Open Science Framework and can be
accessed at https://doi.org/10.17605/OSF.IO/MQ2N5 (Bleidorn et al., 2024).
This work is licensed under a Creative Commons Attribution-Non
Commercial-No Derivatives 4.0 International License (CC BY-NC-ND 4.0;
https://creativecommons.org/licenses/by-nc-nd/4.0). This license permits copy-
ing and redistributing the work in any medium or format for noncommercial use
provided the original authors and source are credited and a link to the license is
included in attribution. No derivative works are permitted under this license.
Wiebke Bleidorn served as lead for conceptualization, funding acquisition,
resources, supervision, and writing–original draft. Alexander G. Stahlmann
served as lead for formal analysis and contributed equally to visualization.
Christopher J. Hopwood served in a supporting role for conceptualization.
Wiebke Bleidorn and Alexander G. Stahlmann contributed equally to data
curation and methodology. Alexander G. Stahlmann and Christopher
J. Hopwood contributed equally to writing–review and editing.
Correspondence concerning this article should be addressed to Wiebke
Bleidorn, Department of Psychology, University of Zurich, Binzmühlestrasse
14, Box 7, CH-8050 Zurich, Switzerland. Email: wiebkebleidorn@gmail.com
Health Psychology
© 2024 The Author(s) 2025, Vol. 44, No. 1, 44–56
ISSN: 0278-6133 https://doi.org/10.1037/hea0001398
44
about vaccination in the course of the COVID-19 pandemic. Existing
studies provided mixed evidence about the links between personality
traits and vaccination, with some reporting negative correlations (e.g.,
with extraversion; Adamus et al., 2022), some suggesting positive cor-
relations (e.g., with agreeableness; Salerno et al., 2021), and others
finding no relations between personality traits and vaccination attitudes
or behaviors (Podlesek et al., 2011).
By integrating the results of a diverse range of studies, this meta-
analysis aims to provide a clearer understanding of the effects of per-
sonality traits on vaccination attitudes, intentions, and behaviors. In
addition to determining the main effects of personality traits on vacci-
nation outcomes, we examine the role of individual-level, vaccination-
related, and contextual moderators in shaping the personality-
vaccination link.
Mixed Results for Links Between Personality Traits and
Vaccination
Personality traits—relatively stable patterns of thoughts, feelings,
and behaviors—predict people’s attitudes and decisions in virtually
all life domains, including health (Friedman & Kern, 2014;Jokela et
al., 2014). Extensive research has demonstrated the role of the Big
Five personality traits—neuroticism, extraversion, openness, agree-
ableness, and conscientiousness—in predicting health-related out-
comes and behaviors, such as adherence to medical regimens,
engagement in risky health behaviors, and adoption of preventive
health measures (Bogg & Roberts, 2004;Kroencke et al., 2021;
Willroth et al., 2023;Wright et al., 2022).
Theory and some research suggest that certain Big Five personality
traits also predict vaccination attitudes, intentions, and behavior
(Howard, 2022;Webster et al., 2023). High levels of agreeableness
and conscientiousness, and, to a lesser degree, low levels in neuroti-
cism, have been theorized to predict favorable vaccination attitudes,
because people with high levels in these traits are more likely to adhere
to social norms and engage in preventive health care measures more
generally (Friedman & Kern, 2014;Willroth et al., 2023).
Specifically, agreeable people’s compassion for others may lead to
enhanced compliancewith vaccine recommendations, whereas people
low in agreeableness, may be less willing to get vaccinated in order to
slow down disease spread and protect others. Similarly, conscientious
people’s dutifulness may lead them to conform with vaccination reg-
imens, whereas people low in this trait may experience less need to
adhere to societal or medical mandates (Willroth et al., 2021).
Neurotic people have been theorized to be more concerned about
the potential side effects of vaccines, which should reduce their will-
ingness to get vaccinated (Branchflower & Blais, 2022).
There is less theoretical agreement about the roles of openness and
extraversion. Some have theorized that high openness is linked to
intellectual curiosity and a higher likelihood to adopt especially
new vaccination regimens (Mo et al., 2021;Webster et al., 2023),
because open people tend may be more willing and better able to
process novel health-related information, whereas others have
argued that highly open people may be more drawn to complemen-
tary and alternative medicine over standard medical care and thus be
less likely to endorse vaccination (Browne et al., 2015). Finally,
while some scholars suggested that extraverted people hold more
positive expectations about vaccination benefits (Howard, 2022),
others predicted negative or no links between extraversion and vac-
cination outcomes (Pereira Gonçalves et al., 2022).
Overall, the evidence for these hypotheses is inconsistent. However,
findings were consistently positive for agreeableness and extraversion
when significant. Conscientiousness showed similar trends, albeit with
sporadic negative correlations. Existing evidence is more mixed for
openness and neuroticism (Reagu et al., 2023;Yanto et al., 2021).
There are several possible reasons for this mixed body of
evidence. First, existing studies differ in their conceptualization of vac-
cination outcomes, with some measuring vaccination behavior or status,
often using dichotomous yes/no questions, and others assessing people’s
vaccination intentions or attitudes, typically with Likert-style response
scales, similar to those in personality trait measures. Intention and atti-
tude measures are not only conceptually and methodologically more
similar to personality trait measures, but they have been also theorized
to mediate the links between broad traits and behavior (Ajzen et al.,
2018;Hopwood et al., 2024). As such, we expected to find stronger cor-
relations between traits with measures of vaccination attitudes and inten-
tions than with people’s actual vaccination status or behaviors (Bleidorn
et al., 2021).
Second, different traits may be linked to different vaccination out-
comes. For example, agreeable people may be more likely to adhere
to general vaccination recommendations, especially when they are
aware of the societal value of, for example, influenza or COVID-19 vac-
cination (Bloom et al., 2021). New vaccines, like the recently introduced
COVID-19 vaccinations, may raise more concerns about side effects
among neurotic people. As mentioned above, highly open people may
also be more hesitant toward these vaccines to the degree that they
endorse unconventional, antiauthoritarian worldviews that favor alterna-
tive approaches to personal health (Browne et al., 2015). A contrasting
view is that open people are more likely to accept innovation including
new vaccines compared to people low in this trait (Mo et al., 2021).
Third, sociodemographic and cultural differences across studies
might also have contributed to the mixed state of evidence. For
example, personality trait effects on vaccination attitudes may wax
and wane across the lifespan. Lifespan theories of aging suggest
that the generative aspect of vaccination to protect others may be per-
ceived as more relevant among older compared to younger adults
(Erikson, 1959;Freund & Baltes, 2002;McAdams, 2001), suggest-
ing stronger links between agreeableness and vaccination among
older age groups. Gender may also play a role, as it has been linked
to both personality differences and vaccination, with men reporting
higher vaccination intentions and lower neuroticism than women
(Weisberg et al., 2011).
Fourth, the sample sizes vary substantially across existing studies.
Given that the links between personality traits and vaccination out-
comestendtobesmall(r.05–.10), large sample sizes are needed
to estimate these effects with sufficient power (Schönbrodt &
Perugini, 2013). Notably, small effects are common in the health
domain and do not necessarily imply diminished practical implications
(Funder & Ozer, 2019). For example, correlations between daily step
count and systolic blood pressure fall in a similar range as the reported
correlations between personality traits and vaccination outcomes (e.g.,
Crowley et al., 2021) but are still considered highly relevant in the con-
text of heart disease prevention (Banach et al., 2023). Understanding
that certain personality traits have small associations with vaccination
outcomes might guide the development of tailored interventions or edu-
cational campaigns to reach specific groups.
In summary, a systematic integration of the literature is needed to
provide a more precise picture of the effects of personality traits on vac-
cination attitudes, intentions, and behaviors. In addition to estimating
BIG FIVE PERSONALITY TRAITS AND VACCINATION 45
the overall effects of traits on vaccination, an integrative perspective is
needed to identify potential moderators that shape the personality-
vaccination links.
The Present Study
The purpose of this preregistered study was to integrate the literature
on the links between personality traits and vaccination in a systematic
review and meta-analysis. Expecting small effects, we predicted that
vaccination attitudes and behaviors are negatively correlated with neu-
roticism and positively with agreeableness and conscientiousness; we
had no directional hypotheses for the main effects of openness and
extraversion.
We further tested the moderating roles of vaccination measureand
sample age. Specifically, we predicted stronger personality effects
on attitude and intention measures than behavioral indicators and
stronger effects of agreeableness on vaccination outcomes in older
samples. Finally, we explored the moderating effects of gender, sam-
ple region, sample type (representative vs. convenience), vaccination
type (COVID-19, Influenza, or other), and length of the Big Five
measure on the links between personality traits and vaccination.
Method
Systematic Review
We used data from a broader systematic review on personality and
civic engagement preregistered at https://osf.io/x3yv7. We preregis-
tered the present study after conducting the systematic review, effect
size coding, and data retrieval, but before undertaking the meta-
analysis (https://osf.io/s5uh8). All the data, scripts, and additional
online materials are available at the Open Science Framework (OSF)
project website (https://osf.io/mq2n5/). This study was exempt from
ethical review according to local institutional guidelines.
Identification of Studies
Figure 1 displays a PRISMA flow chart illustrating our systematic
review process, which resulted in 46 eligible samples from 28 studies
for meta-analysis. At the identification stage, the search process involved
targeted searches in Scopus (the primary database) and BASE (for grey
literature), examining article titles, abstracts, and indexed keywords. We
used the following search terms for the links between personality traits
and vaccination outcomes: (personality OR “Big Five”OR “five factor
model”OR HEXACO OR extraver* OR introver* OR surgency OR
agreeable* OR conscientious* OR openness OR “open to experience”
OR “open to experiences”OR intellect OR neurotic* OR “emotional
stability”OR “emotionally stable”OR emotionality OR honesty OR
humility)AND vaccin*. We conducted three searches: the initial on
February 25, 2022, and two follow-ups on March 1, 2023, and
January 31, 2024
1
to include recent publications. Automated search
results were obtained from Scopus using Christopher Belter’s Scopus
Search API (https://github.com/christopherBelter/scopusAPI), while
BASE results were manually collected. The R script for study retrieval
is available at https://osf.io/x9pzh.
Each of the remaining studies was independently screened by
Alexander G. Stahlmann and one of four graduate students. Screening
relied primarily on titles, keywords, and abstracts, resorting to full
texts only when uncertainties arose. At the selection stage, Alexander
G. Stahlmann, along with two graduate students, independently assessed
the full texts of the positively screened studies. Each study was reviewed
by all three raters. During this process, an additional number of studies
were excluded for reasons such as being based on specialized popula-
tions likely to score highly on vaccination outcomes (e.g., samples con-
sisting solely of individuals who have already been vaccinated) or for
reusing a sample from another included study.
Coding of Studies
Alexander G. Stahlmann and two graduate students coded the stud-
ies using a standardized manual, accessible via OSF (https://osf.io/
4hrz7). Variables and statistics that were relevant to this meta-analysis
encompassed (a) sample size, (b) effect size, (c) the specifictypeof
effect size statistic employed, (d) the number of items used for person-
ality measurement, (e) the scope of the vaccination measure (attitude,
intention, behavior, or a compound of these), (f) the specificvaccine
investigated (Influenza, COVID-19, or undetermined), (g) information
about the sampling type (representative or nonrepresentative), (h) the
average age of the study participants, (i) the proportion of women,
and ( j) the sampling region. All variables and statistics were subse-
quently cross-verified among the coders and any discrepancies encoun-
tered were resolved through discussion until consensus was achieved.
Handling of Missing Effect Size Data
Of 34 initially selected studies, 18 (52.94%) did not report raw
effect size data suitable for meta-analysis. To address this, effect
sizes were directly obtained from the authors in four cases and cal-
culated from available data in seven cases, using the R package
esc (Lüdecke, 2019). In three studies, only partial effect sizes were
available; consequently, only these available data were incorporated
into the meta-analysis (Godfrey et al., 2024;KalebicMaglica &
Šincek, 2022;Ryu et al., 2023). Details about the calculation of
effect sizes based on available data are presented in the additional
online materials (https://osf.io/p2rn9); the R script for these calcula-
tions is available on OSF (https://osf.io/cbmau). Unfortunately,
effect sizes for the four remaining studies could not be procured,
resulting in a preliminary data set of 30 studies for the meta-analysis.
Among these 30 studies, two utilized the HEXACO model
(Branchflower & Blais, 2022;Ngo et al., 2023) whereas the remaining
studies employed Big Five measures. Given that HEXACO-derived
factors often share only moderate overlap with their Big Five counter-
parts, and in accordance with contemporary meta-analytical practices,
we chose not to combine HEXACO and Big Five data (e.g., Anglim et
al., 2020;Soutter et al., 2020). Consequently, we excluded the study
featuringHEXACOtraits,leaving28studiesincluding41samples
as the final data set for the meta-analysis focused solely on Big Five
personality traits. The final data set, complete with study codes, vari-
ables, and effect sizes, is available on OSF (https://osf.io/mq2n5/).
Meta-Analytic Procedure
All effect sizes were initially converted into Pearson’s correlations
and then transformed into Fisher’szscores (Borenstein et al., 2021;
Fisher, 1921). Consistent with state-of-the-art meta-analytic practice,
we estimated multilevel random-effects models that integrate effects
across samples and studies (see Assink & Wibbelink, 2016;Cheung,
1
The third search was requested during the review process for this journal.
BLEIDORN, STAHLMANN, AND HOPWOOD
46
2014), using the R package metafor and employing restricted maxi-
mum likelihood estimation in conjunction with Hartung–Knapp–
Sidik–Jonkman adjustment for statistical estimation (Borenstein
et al., 2021;Knapp & Hartung, 2003;R Core Team, 2022;Sidik &
Jonkman, 2002;Viechtbauer, 2023). We first calculated separate meta-
analytic models for each of the Big Five personality domains.
Subsequently, we conducted a series of univariate moderator analyses
for each domain. Finally, we converted the model statistics, including
point estimates, 95% confidence intervals (CIs), and 95% prediction
intervals back into Pearson’s correlations for interpretation.
We inspected forest plots, calculated various statistics to test for the
presence of influential studies, and examined contour-enhanced funnel
plots with Egger’s regression tests for each Big Five personality trait
(Egger et al., 1997;Peters et al., 2008). None of these analyses yielded
evidence that results were unduly influenced by outliers, small-study
effects, or publication bias (see the additional online materials for
results [https://osf.io/p2rn9]andRscript[https://osf.io/cbmau]). To
illustrate, Figure 2 displays the contour-enhanced funnel plot for neurot-
icism, where few studies show significant results and those that do
exhibit a balanced distribution of negative and positive effects. This pat-
tern of findings was congruent across all Big Five personality traits.
Adjustments to Preregistered Analyses
Initially, we had preregistered multivariate moderator analyses and
additional moderator variables (see https://osf.io/s5uh8). However, upon
Figure 1
PRISMA Flow Chart Illustrating the Systematic Review Process
Identification of studies via databases and registers
Records identified from:
•Scopus (n=4,859)
•BASE (n=1,343)
Identification
Records removed before screening:
•Ineligible records removed
(n=619)
•Duplicate records removed
(n=827)
Screening
Records screened (titles, keywords,
abstracts; full-text when in doubt):
•(n=4,756)
Records excluded:
•Did not measure civic engagement
(n=3,900)
•Did not measure the Big
Five/HEXACO traits (n=617)
Reports sought for retrieval:
•(n= 239)
Reports not retrieved:
•Record inaccessible (n=3)
•Record unavailable in English or
German (n=12)
•More duplicate records removed
(n=87)
Reports assessed for eligibility:
•(n= 137)
Reports excluded:
•Used a ‘restricted’ sample (e.g.,
volunteers; n=15)
•Reused a sample that was already
included (n=9)
Selection
Samplesincludedinreports:
•(k= 131)
Reports of included samples:
•(n= 113)
Vaccination-specific samples:
•(k=41)
Vaccination-specific reports:
•(n=28)
Reports excluded:
•Didnotpertaintovaccination
outcomes (n=83)
•Effect sizes could not be procured
(n=4)
BIG FIVE PERSONALITY TRAITS AND VACCINATION 47
data inspection, we learned that certain moderator combinations were too
rare to estimate robustness effects. We thus revised our approach to focus
on univariate moderator analyses. Additionally, we substituted the origi-
nal indicators of reliability, Cronbach’sαand test–retest reliability, with
the number of items used in personality measurement (i.e., the length
of the measure). This change was necessary because some studies did
not report reliability and because some measured traits with one or two
items and thus Cronbach’sαcould not be calculated.
Results
Description of Studies
Overall, the 28 studies included data from an estimated N=
48,712 participants and 182 effect sizes. Participants in this data
set had a mean age of 38.19 years (SD ≈9.55, Mdn ≈38.70 years,
range ≈17.00–54.75 years, with 39.29% data missing). Gender dis-
tribution averaged 58.84% female (SD ≈9.43, Mdn ≈58.20%,
range ≈48.00%–80.86%, with 14.29% data missing).
Table 1 presents relevant variables, statistics, and associations
between vaccination variables and Big Five traits for the 21 studies
included in the meta-analysis. All studies were published in peer-
reviewed journals, predominantly in the fields of medicine, public
health, and vaccination research. The mean publication year skews
recent, with an average year of 2021 and a median year of 2022.
Only two studies were published before 2020 (Browne et al.,
2015;Podlesek et al., 2011).
The geographical distribution of these studies was diverse, with no
single country contributing more than two studies except the United
States. The majority originated from Western cultures (19), but there
were also contributions from Mainland China (Mo et al., 2021;
Zhang et al., 2022), India (Khurana et al., 2022), Indonesia (Yanto
et al., 2021), Peru (Hervias-Guerra et al., 2023), Qatar (Reagu et al.,
2023), South Korea (Ryu et al., 2023), and Taiwan (Dutta, 2023;
Lee et al., 2022). Most studies utilized convenience or random samples
(21), with a smaller proportion using representative samples (Dutta,
2023;Halstead et al., 2022;Lin & Wang, 2020;Mo et al., 2021;
Murphy et al., 2021;Stahlmann et al., 2024); one was unspecified
(Patzina & Dietrich, 2022).
There was considerable variation in the vaccination measures used,
with seven studies focusing on attitudes, six on intentions, three on
vaccination status, four using compound measures, and eight using
multiple vaccination measures. Most studies focused on COVID-19
vaccinations (17), with fewer addressing influenza (three) or unspeci-
fied vaccines (five), and some includingmultiple vaccine types (three).
Meta-Analytic Correlations
Main Effects
Figure 3 visualizes the meta-analytic correlations between the Big
Five personality traits and vaccination (see main effects). The point esti-
mates and 95% CIs are presented in Table 2. Across traits, the average
meta-analytic correlation was .02, 95% CI [−.01, .05]. Main effects
were statistically significant for extraversion (r=.02, 95% CI [.00,
.04]) and agreeableness (r=.06, 95% CI [.02, .09]), but not for neurot-
icism (r=−.01, 95% CI [−.04, .02]), openness (r=.03, 95% CI
[−.01, .06]), or conscientiousness (r=.00, 95% CI [−.03, .03]).
Categorical Moderators
The rows following the main effects in Figure 3 illustrate meta-
analytic correlations accounting for different categorical moderator
effects. Consistent with our hypotheses, effect sizes for neuroticism,
openness, and agreeableness were significantly larger when related
to positive vaccination attitudes and intentions rather than vaccina-
tion status or composite measures. This pattern did not hold for extra-
version and conscientiousness.
We further found several significant moderating effects of vacci-
nation type, sample type, and region. Specifically, consistent with
views that emphasize the potential impacts of openness to new
ideas and health regimens, openness had a stronger positive effect
on COVID-19 vaccines than on influenza or other vaccines. In con-
trast, extraversion was more positively correlated with influenza vac-
cines, whereas agreeableness was positively correlated with all types
of vaccines. Sample type and region moderated the links between
extraversion and agreeableness with vaccination. Specifically, in
representative samples, we found stronger links between extraver-
sion and vaccination. Extraversion was also more strongly linked
with vaccination in non-Western samples, whereas agreeableness
was more strongly linked with vaccination in Western samples.
Continuous Moderators
Figure 4 illustrates the variations in meta-analytic correlations
based on the number of items used for personality trait measurement,
the percentage of women in the sample, and average participant age.
The point estimates and 95% CIs are presented in Table 3. In contrast
to our predictions, we found no significant age effect on the link
between agreeableness and vaccination. Instead, we found stronger
effects of agreeableness and conscientiousness on vaccination in
samples with more men than women. The number of items used
for measuring personality traits did not exhibit significant influence
on the magnitude of the effect sizes.
Figure 2
Meta-Analytic Personality–Vaccination Correlations and 95% CIs
Note. Bold effects have CIs not containing zero. CIs =confidence intervals.
BLEIDORN, STAHLMANN, AND HOPWOOD
48
Heterogeneity
Table 4 provides a summary of the sample size, the number of
effect sizes, and the number of studies involved in each specific
model, along with the within-study and between-study
heterogeneity for each Big Five trait. Higher levels of
between-study variability were observed for openness, agreeable-
ness, and conscientiousness, as compared to lower levels for extra-
version and the smallest for neuroticism. When comparing across
moderator models, the primary contributors to within-study hetero-
geneity appear to be the scope of measure used and the specific
vaccine under investigation, as evidenced bya significant reduction
in within-study heterogeneity in these models. Another notable
observation is the almost complete lack of within-study heterogene-
ity in the case of agreeableness, indicating that this particular trait is
highly robust, or insensitive, to variations in study design and mod-
erating factors.
Discussion
Vaccination is one of the most effective tools for safeguarding public
health, preventing outbreaks, and promoting overall well-being (https://
Table 1
Summary of Studies Identified in the Systematic Review That Pertain to Vaccination Outcomes
No. Study NNEOAC
#
items
Type of
measure Vaccine Sampling type
Age
M
Women
% Region
1Podlesek et al. (2011) 1,383 0 0 0 0 0 2 Status Influenza Nonrepresentative 37.07 74.00 Western
1Podlesek et al. (2011) 1,383 0 0 0 0 0 2 Status Influenza Nonrepresentative 37.07 74.00 Western
2Browne et al., (2015) 1,256 ? ? −? ? 3 Compound Undetermined Nonrepresentative ? 49.68 Western
3Lin and Wang (2020) 3,276 −00++ 2 Attitude Undetermined Representative 46.90 49.00 Western
4Murphy et al. (2021) 1,041 0 0 0 +0 10 Attitude COVID-19 Representative ? 51.50 Western
4Murphy et al. (2021) 2,025 −00++ 10 Attitude COVID-19 Representative ? 51.70 Western
5Salerno et al. (2021) 2,639 0 +0+0 2 Intention COVID-19 Nonrepresentative ? ? Western
5Salerno et al. (2021) 2,341 −00+0 2 Intention COVID-19 Nonrepresentative ? ? Western
6Yanto et al. (2021) 190 +00+0 2 Intention COVID-19 Nonrepresentative 44.84 54.20 Non-Western
7Howard (2022) 258 0 0 0 0 0 4 Intention COVID-19 Nonrepresentative 38.35 48.00 Western
7Howard (2022) 258 0 0 0 0 0 4 Intention Influenza Nonrepresentative 38.35 48.00 Western
7Howard (2022) 258 0 0 0 0 0 4 Status COVID-19 Nonrepresentative 38.35 48.00 Western
7Howard (2022) 258 0 0 0 0 0 4 Status Influenza Nonrepresentative 38.35 48.00 Western
7Howard (2022) 258 0 0 0 0 0 4 Status Undetermined Nonrepresentative 38.35 48.00 Western
8Mo et al. (2021) 6,922 M M +M M 2 Intention COVID-19 Representative 19.40 63.60 Non-Western
9Zhang et al. (2022) 1,200 ? ? ? ? ? 2 Compound COVID-19 Nonrepresentative ? 58.42 Non-Western
10 Patzina and Dietrich
(2022)
4,079 ? ? ? ? ? ? Intention COVID-19 ? 17.00 65.00 Western
11 Adamus et al. (2022) 500 −000+6 Status Influenza Nonrepresentative 44.32 50.00 Western
11 Adamus et al. (2022) 500 0 −0 0 0 6 Attitude Undetermined Nonrepresentative 44.32 50.00 Western
12 Khurana et al. (2022) 760 −+ 0+0 ? Attitude Undetermined Nonrepresentative ? 60.20 Non-Western
13 Shook et al. (2023) 475 0 0 0 0 0 6 Status Influenza Nonrepresentative 41.40 53.90 Western
14 Pereira Gonçalves et al.
(2022)
595 0 0 ++ 0 6 Compound COVID-19 Nonrepresentative 35.86 67.70 Western
15 Asri et al. (2022) 807 0 0 −0 0 2 Intention COVID-19 Nonrepresentative ? ? Western
16 Halstead et al. (2022) 9,667 −0+0 0 3 Attitude COVID-19 Representative 54.75 58.20 Western
17 KalebicMaglica and
Šincek (2022)
1,769 +MMM−8 Compound Undetermined Nonrepresentative 36.06 76.30 Western
18 Lee et al. (2022) 1,773 ? ? +? ? 2 Intention COVID-19 Nonrepresentative ? 67.75 Non-Western
19 Di Nuovo et al. (2022) 108 0 0 0 0 0 2 Attitude Undetermined Nonrepresentative ? 51.85 Western
20 Kaliterna Lipovc
an et al.
(2022)
721 0 0 +0 0 3 Status COVID-19 Nonrepresentative 43.00 80.86 Western
21 Reagu et al. (2023) 4,296 +−+−− 2 Intention COVID-19 Nonrepresentative ? ? Non-Western
21 Reagu et al. (2023) 3,946 −0+−− 2 Status Influenza Nonrepresentative ? ? Non-Western
22 Hervias-Guerra et al.
(2023)
459 −M M M M 6 Attitude COVID-19 Nonrepresentative 28.51 61.00 Non-Western
23 Stahlmann et al. (2024) 1,593 0 0 0 +0 20 Status Influenza Representative 42.92 49.22 Western
24 Dutta (2023) 390 M M −M M 3 Intention COVID-19 Representative ? 48.61 Non-Western
24 Dutta (2023) 390 M M −M M 3 Status COVID-19 Representative ? 48.61 Non-Western
25 Kleitman et al. (2023) 582 ? ? ? ? ? 4 Attitude COVID-19 Nonrepresentative 34.68 58.20 Western
25 Kleitman et al. (2023) 582 ? ? ? ? ? 4 Intention COVID-19 Nonrepresentative 34.68 58.20 Western
25 Kleitman et al. (2023) 582 ? ? ? ? ? 4 Status COVID-19 Nonrepresentative 34.68 58.20 Western
26 Kimbler et al. (2023) 44 0 0 0 +0 9 Intention COVID-19 Nonrepresentative 38.70 63.64 Western
26 Kimbler et al. (2023) 274 0 0 +++ 9 Status COVID-19 Nonrepresentative 19.99 81.00 Western
27 Ryu et al. (2023) 1,500 −+ 0++ 2 Attitude COVID-19 Nonrepresentative ? ? Non-Western
28 Godfrey et al. (2024) 500 0 0 +0−9 Status COVID-19 Nonrepresentative 45.50 51.40 Western
Note. “#items”indicates the average number of items that were used per Big Five personality traits. “NEOAC”indicates the reported effects for Big Five personality
traits, if any were identified: “N”stands for neuroticism (or negative emotionality vs. emotional stability), “E”for extraversion (or surgency), “O”stands for openness to
experience (or culture/intellect), “A”for agreeableness, and “C”for conscientiousness. Symbols (+), (−), and (0) indicate a reported positive, negative, or no link,
respectively. (?) means the information or zero-order correlations were unreported, and (M) signifies the relevant traits were not measured.
BIG FIVE PERSONALITY TRAITS AND VACCINATION 49
www.who.int/health-topics/vaccines-and-immunization). Despite the
established societal and individual benefits of vaccination, there
are pronounced differences in people’s attitudes toward vaccina-
tion, vaccination intentions, and actual vaccination behaviors.
These differences in vaccination rates are the result of multiple fac-
tors, including social, cultural, and personal variables that shape an
individual’s willingness to get vaccinated (Halstead et al., 2022;
Podlesek et al., 2011). Here, we integrated the literature on the
effects of Big Five personality traits on vaccination outcomes to
(a) provide robust estimates of the links between broad traits and
vaccination outcomes and (b) examine the effects of several
theoretically and empirically derived moderator variables. Six find-
ings stand out.
First, we found support for the hypothesis that agreeableness is a rel-
evant predictor in people’s vaccination decisions, particularly for their
general attitudes toward vaccination, the COVID-19 vaccination, and
common or seasonal vaccinations like the influenza vaccine. We also
found significant, albeit smaller, effects of extraversion on positive vac-
cination attitudes, whereas neuroticism had a negative effect. The only
trait associated with vaccination intentions was openness. Together,
this pattern of effects suggests that people who have more positive vac-
cination attitudes and intentions tend to care about others, are socially
Figure 3
Contour-Enhanced Funnel Plot for Neuroticism
−.2 −.1 0 .1 .2 −.2 −.1 0 .1 .2 −.2 −.1 0 .1 .2 −.2 −.1 0 .1 .2 −.2 −.1 0 .1 .2
Main effect
Scope of measure
Vaccine
Sampling type
Sampling region
Attitude
Intention
Status
Compound measure
COVID−19
Influenza
Undetermined
Representative
Not representative
Non−Western
Western
Neuroticism Extraversion Openness Agreeableness Conscientiousness
BLEIDORN, STAHLMANN, AND HOPWOOD50
oriented and optimistic, emotionally stable and confident, and
interested in new ideas and potentially complex health information.
These effects, albeit small, are consistent with recent findings about
personality–attitude links in other domains of prosocial behavior like
volunteering, charitable giving, or proenvironmental engagement
(Hopwood et al., 2024;Stahlmann et al., 2024;Zhao et al., 2017).
Especially the links with agreeableness and openness contribute to
an emerging picture of a personality profile that predisposes people
to invest in prosocial behaviors despite the fact that there may be tangi-
ble costs or risks (Hopwood et al., 2024;Reistetal.,2023;Smillie et al.,
2019).
Second, we found no effects for conscientiousness. These null
effects contrast our hypotheses and the literature that associated
this trait with a broad range of health-related behaviors and out-
comes (e.g., Jokela et al., 2014;Willroth et al., 2023). One expla-
nation for these null effects may have to do with the nature of
vaccination as preventative health care measure. In contrast to
health care regimens that require people to set goals and adhere
to routines, like healthy eating, physical exercise, or regular phys-
ical check-ups, vaccination is less associated with demands for
conscientiousness-related behaviors. Another possible explanation
is that the interaction between neuroticism and conscientiousness
may be a better predictor of vaccination than the individual main
effects of these variables. This idea of a “healthy neuroticism”sug-
gests that high levels of neuroticism can lead to increased vigilance
and concern about germs, symptoms, and treatments, when paired
with high levels of conscientiousness, potentially increasing the
likelihood that people invest in preventative health care regimens
like vaccination (e.g., Weston & Jackson, 2015). The healthy neu-
roticism effect has been demonstrated for some health behaviors,
like physical activity or smoking, but has yet to be tested for vacci-
nation outcomes.
Third, significant personality effects were more pronounced for
vaccination attitudes and intentions and unrelated to people’s actual
vaccination status. This finding is consistent with previous research
and theories that highlight the mediating functions of attitudes in
links between traits and behavior (Ajzen et al., 2018;Sheeran &
Webb, 2016). However, longitudinal or experimental research
would be needed to test such mediation effects. The stronger links
between traits and attitudes may also reflect a greater similarity in
the measures used to assess these constructs (i.e., self-report
Likert-type scales) than vaccination behavior (i.e., dichotomous sta-
tus measure).
Fourth, we found several moderator effects, particularly affecting
the links between extraversion, openness, and vaccination outcomes.
Perhaps most interesting in view of recent discussions of the psycho-
logical predictors of the COVID-19 vaccine acceptance, we found
that people higher versus lower in openness were more likely to
accept these new vaccines. This finding is consistent with theories
that emphasize that open people are more interested in new medical
innovations, more likely to accept novel vaccination regimes, and
better able to process vaccine-related information (Webster et al.,
2023). It is possible that the theorized links between openness and
alternative or complementary medicines are nonlinear and perhaps
only relevant for very high levels of this trait (Browne et al., 2015).
Fifth, in contrast to our predictions, we found no significant mod-
erating effects of age, suggesting similar associations between traits
and vaccination outcomes across the lifespan. Part of the reason
may be that peopledo not tend to consider vaccination as a generative
behavior but rather as a self-protective preventative measure (Freund
& Baltes, 2002). If correct, we would not expect an increased expres-
sion of older adults’generative personality through vaccination atti-
tudes. It is also possible that the relatively smaller number of older
adults in our samples limited our statistical power to detect such
effects.
Finally, we found several other significant moderator effects of
gender, sampling type, and sample region. Given that we did not pre-
dict these effects, we refrain from further discussions but would
encourage future research to replicate and further investigate these
effects. Particularly, the differential effects of extraversion and
Table 2
Meta-Analytic Personality–Vaccination Correlations
Main effect and moderators
Neuroticism Extraversion Openness Agreeableness Conscientiousness
r95% CI r95% CI r95% CI r95% CI r95% CI
Main effect −.01 [−.04, .02] .02 [.00, .04] .03 [−.01, .06] .06 [.02, .09] .00 [−.03, .03]
Scope of measure
Attitude −.07 [−−−−−.12, −−−−−.03] .01 [−.03, .05] .03 [−.03, .09] .08 [.02, .14] .04 [−.02, .09]
Intention .03 [−.02, .07] .03 [−.00, .07] .06 [.01, .10] .05 [−.00, .10] −.03 [−.07, .02]
Status −.01 [−.05, .04] .03 [−.01, .06] −.00 [−.05, .05] .04 [−.01, .09] −.01 [−.06, .03]
Compound measure .01 [−.09, .11] .02 [−.06, .10] .02 [−.09, .14] .08 [−.05, .20] .01 [−.08, .13]
Vaccine
COVID-19 −.02 [−.05, .02] .02 [−.01, .04] .05 [.00, .09] .05 [.01, .09] −.01 [−.05, .02]
Influenza .01 [−.05, .07] .05 [.01, .08] .01 [−.05, .06] .06 [.01, .11] .02 [−.03, .07]
Undetermined −.03 [−.10, .04] .02 [−.04, .07] −.03 [−.10, .04] .09 [.01, .16] .03 [−.04, .09]
Sampling type
Representative −.01 [−.04, .03] .03 [.01, .05] .03 [−.01, .08] .05 [.00, .09] −.02 [−.05, .02]
Nonrepresentative −.05 [−.12, .02] .01 [−.03, .05] .01 [−.06, .09] .10 [.02, .18] .06 [−.01, .13]
Sampling region
Non-Western −.03 [−.09, .03] .04 [.00, .08] .02 [−.05, .09] .07 [−.00, .14] .02 [−.04, .09]
Western −.01 [−.04, .03] .02 [−.01, .04] .03 [−.02, .08] .05 [.01, .10] .01 [−.05, .03]
Note. Each indented row set following the main effect represents a univariate moderator model. Bold values have CIs not containing zero. Openness to
experience also stands for culture and intellect, extraversion also stands for surgency, and neuroticism also stands for negative emotionality versus
emotional stability. CI =confidence interval.
BIG FIVE PERSONALITY TRAITS AND VACCINATION 51
agreeableness in non-Western versus Western samples have both
potential theoretical and practical implications about the ways in
which personality differences predict people’s vaccination decisions
in different cultures.
Limitations
The present study integrated data from 28 studies that sampled more
than 48,000 individuals to estimate the effects of personality traits on
Figure 4
Variations in Meta-Analytic Correlations Based on Continuous Moderators
Number of items per Big Five personality trait
Estimated Pearson correlation
012345678910
−0.2
−0.1
0.0
0.1
0.2
Average age
Estimated Pearson correlation
20 25 30 35 40 45 50 55
−0.2
−0.1
0.0
0.1
0.2
Percentage of women
Estimated Pearson correlation
45 50 55 60 65 70 75 80
−0.2
−0.1
0.0
0.1
0.2
Table 3
Effects of Continuous Moderators on Personality–Vaccination Correlations
Moderators
Neuroticism Extraversion Openness Agreeableness Conscientiousness
β95% CI pβ95% CI pβ95% CI pβ95% CI pβ95% CI p
# items −.003 [−.005, .010] .44 .001 [−.004, .005] .82 .000 [−.010, .010] .98 .004 [−.005, .013] .34 −.003 [−.011, .005] .45
M
age
−.000 [−.005, .004] .85 .001 [−.002, .003] .78 .002 [−.002, .006] .34 .004 [−.002, .010] .18 .003 [−.002, .008] .21
Women % .001 [−.002, .005] .43 −.001 [−.003, .002] .52 .001 [−.004, .005] .74 −−−−−.004 [−−−−−.008, −−−−−.001] .02 −−−−−.004 [−−−−−.007, −−−−−.001] .01
Note. Each row represents a univariate moderator model. Bold values have CIs not containing zero and ps,.05. Openness to experience also stands for culture
and intellect, extraversion also stands for surgency, and neuroticism also stands for negative emotionality versus emotional stability. “# items”indicates the
average number of items that were used per Big Five personality traits. CI =confidence interval.
BLEIDORN, STAHLMANN, AND HOPWOOD
52
vaccination. However, our approach was not without limitations. Most
importantly, the literature on personalityand vaccination, while growing,
is still relatively small. As such, some of the moderator tests may have
been underpowered to the degree that data was sparse. This limitation
is particularly relevant for the type of personality measures used. As
mentioned above, only two studies utilized a HEXACO measure,
which we then excluded given that HEXACO-derived factors often
share only moderate overlap with their Big Five counterparts (Anglim
et al., 2020;Soutter et al., 2020). Moreover, the majority of existing stud-
ies focused on the broad Big Five traits, with few studies focusing on
narrower facet traits that capture more specific trait content at lower lev-
els of the personality hierarchy (but see, Stahlmann et al., 2024). Theory
and some initial research suggest that the use of lower order trait mea-
sures may help explain some of the inconsistent findings. For example,
the dutifulness and orderliness facets of conscientiousness may be more
strongly linked to vaccination behavior than the competence or self-
discipline facets of this trait. Finally, more data would be needed to esti-
mate all moderators in one model as we had initially preregistered. Such
models could account for the fact that some of the moderators may be
correlated and thus share variance in explaining the links between per-
sonality traits and vaccination.
Conclusion
The results of the present meta-analysis integrate the rapidly grow-
ing body of research on personality and vaccination outcomes.
Together, the findings provide a compelling picture of significant,
albeit small, effects of personality traits on vaccination. Providing
further evidence for a prosocial personality profile, we found that
people who are high in agreeableness and extraversion, and low in
neuroticism are more likely to have positive attitudes toward vaccina-
tion. We further found that open people tend to be more inclined to
get vaccinated and to be more positive about novel COVID-19 vac-
cines, in particular. These effects appear to generalize across age.
Several other moderator effects suggest a more nuanced picture
across cultural regions and gender. Together, these findings add to
our growing understanding of the psychological factors that shape
vaccination decisions. Knowledge about the specific personality
traits that predict vaccination behavior can be used to target certain
populations, identify psychological factors that sour spur vaccination
hesitancy, and aid in developing effective health care campaigns that
are tuned to the personality profiles of those that may be otherwise
less likely to get vaccinated. For example, if low levels of openness
are linked with reduced vaccination intentions, effective vaccination
campaigns may focus on communicating the benefits of vaccination
in a way that highlights the long tradition and established routines of
vaccination rather than theirnoveltyand innovative nature.Questions
remain about the processes through which personality traits may
affect vaccination attitudes and potentially also behavior. A crucial
next step for personality theory and research will be to document
how such effects may unfold over time to result in actual vaccination
decisions.
Resumen
Objetivo: A pesar de los beneficios comprobados de la vacunación, las
personas difieren en su disposición a vacunarse. Estas diferencias son
el resultado de múltiples factores, incluyendo variables sociales, cultur-
ales y psicológicas. Este metaanálisis estimó los efectos de los Cinco
Grandes rasgos de personalidad de las personas en sus actitudes, inten-
ciones y comportamientos en materia de vacunación y examinó el
papel de las variables moderadoras derivadas teórica y empíricamente.
Métodos: Meta analizamos datos de 28 estudios que tomaron muestras
de más de 48,000 personas para estimar los efectos de los rasgos de per-
sonalidad de los Cinco Grandes en las actitudes, intenciones y compor-
tamientos de vacunación. Además, probamos los efectos moderadores de
la edad, el género, la región de la muestra, el tipo de muestra (represen-
tativa vs. conveniencia), la medida de vacunación (actitud, intención,
comportamiento, compuesto), el tipo de vacunación (COVID-19, influ-
enza u otra), y confiabilidad de la medida de los Cinco Grandes sobre los
vínculos entre los rasgos de personalidad y la vacunación. Resultados:
Las personas con niveles altos de afabilidad y extraversión, y niveles
bajos de neuroticismo informaron actitudes más positivas hacia la
vacunación, mientras que las personas abiertas informaron intenciones
más fuertes de vacunarse. Las personas abiertas y afables también se
mostraron más positivas con respecto a las nuevas vacunas contra el
COVID-19, mientras que las personas extrovertidas fueron más positivas
con respecto a las vacunas contra la influenza. No hubo efectos para la
escrupulosidad. En general, los tamaños del efecto fueron pequeños
pero generalizados en todas las edades. Otros efectos moderadores sugir-
ieron una imagen más matizada según las regiones culturales, los tipos de
Table 4
Meta-Analytic Summary Statistics and Heterogeneity Across Various Moderator Models
Main effect and
moderators
Neuroticism Extraversion Openness Agreeableness Conscientiousness
nkI
ws
2
I
bs
2
nkI
ws
2
I
bs
2
nkI
ws
2
I
bs
2
nkI
ws
2
I
bs
2
nkI
ws
2
I
bs
2
Main effect 52,526 25 60.93 26.59 50,298 23 28.66 35.40 59,256 26 8.50 82.96 50,298 23 ,1 87.42 52,067 24 10.77 76.88
No. of items 47,687 23 56.80 29.99 45,459 21 23.82 29.84 54,417 24 7.59 84.66 45,459 21 ,1 87.17 47,228 22 9.38 79.23
Type measure 52,526 25 46.72 38.4 50,298 23 32.88 35.94 59,256 26 ,1 91.38 50,298 23 ,1 86.90 52,067 24 32.16 52.88
Vaccine 52,526 25 87.55 ,1 50,298 23 9.40 57.52 59,256 26 2.71 89.30 50,298 23 ,1 86.26 52,067 24 6.99 81.13
Sampling type 48,447 24 52.54 34.90 46,219 22 29.27 35.51 55,177 25 8.02 83.79 46,219 22 ,1 86.93 47,988 23 11.12 74.64
Age 30,444 16 ,1 87.73 28,216 14 ,1 44.71 35,138 15 ,1 84.91 28,216 14 ,1 90.17 29,985 15 ,1 89.25
Women % 37,351 21 2.05 85.01 35,123 19 35.16 29.06 44,081 22 ,1 91.55 35,123 19 ,1 81.24 36,892 20 17.25 66.02
Sampling region 52,526 25 49.87 38.37 50,298 23 23.06 43.20 59,256 26 8.21 83.62 50,298 23 ,1 88.31 52,067 24 9.90 78.31
Note. Each row following the main effect represents a univariate moderator model. Openness to experience also stands for culture and intellect, extraversion
also stands for surgency, and neuroticism also stands for negative emotionality versus emotional stability. “n”and “k”refer to sample size and the number of
studies utilized in the specific model, respectively. “I
ws
2
”and “I
bs
2
”serve as multilevel equivalents for meta-analytic heterogeneity, quantifying the percentage of
within-study and between-study variance that is due to heterogeneity rather than chance (Higgins & Thompson, 2002;Konstantopoulos, 2011).
BIG FIVE PERSONALITY TRAITS AND VACCINATION 53
muestras y el género. Conclusiones: Los hallazgos proporcionan una
imagen convincente de los efectos significativos, aunque pequeños, de
los rasgos de personalidad en la vacunación. Quedan dudas sobre los
procesos a través de los cuales los rasgos de personalidad pueden afectar
las actitudes, las intenciones y potencialmente también el comporta-
miento en materia de vacunación.
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Received November 24, 2023
Revision received February 16, 2024
Accepted March 28, 2024 ▪
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