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COVID-19 PANDEMIC AND WELL-BEING
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Effect of the COVID-19 Pandemic and Big Five Personality on Subjective and
Psychological Well-Being
Jeromy Anglim, Sharon Horwood
1
Abstract
The current study assessed the effect of the COVID-19 (coronavirus)
pandemic on subjective well-being (SWB) and psychological well-being (PWB) and
whether the pandemic moderated the effect of personality on well-being. Measures of
Big Five personality, SWB (life satisfaction, positive affect, negative affect) and PWB
(positive relations, autonomy, environmental mastery, personal growth, purpose in
life, self-acceptance) were obtained from a sample of young adults in Melbourne,
Australia (n = 1132; 13 July to 11 August, 2020) during a second wave of viral
transmission and lockdown, and an identically recruited Pre-COVID sample (n = 547).
Well-being was lower in the COVID sample and differences were largest for positive
affect (d = -0.48) and negative affect (d = 0.70). While the effect of personality on
well-being was relatively robust, the effect of personality on well-being was slightly
reduced and the effect of extraversion on positive affect was particularly attenuated
during the pandemic.
Keywords: COVID-19, coronavirus, pandemic, personality, well-being
In 2020, the COVID-19 pandemic profoundly altered the way people live their
lives and experience the world. The combined effects of the virus and the strategies to
control its spread have caused increased social isolation, financial insecurity, and
uncertainty about the future (Van Bavel et al., 2020). Many commentators have
expressed concerns that the pandemic may induce elevated levels of depression,
loneliness, and suicide (Brooks et al., 2020; Courtet et al., 2020; Van Bavel et al.,
2020), and many cross-sectional surveys suggest that people are experiencing elevated
levels of distress (Sher, 2020; Xiong et al., 2020). However, initial longitudinal
studies conducted during early-stage lockdown suggest that well-being may have
remained relatively stable (Sibley et al., 2020) and that it is mostly viral spread rather
than lockdown that causes psychological distress (Foa et al., 2020). More broadly,
research on well-being shows that well-being (a) is relatively stable over time (Anglim
1
School of Psychology, Deakin University, Geelong, Australia
Please cite as (check for updated year, volume and page numbers):
Anglim, J. & Horwood, S. (2021) Effect of the COVID-19 Pandemic and Big
Five Personality on Subjective and Psychological Well-Being. Social Psychological
and Personality Science. https://doi.org/10.1177/1948550620983047
Original version 29th August 2020; Revised version submitted 26th November
2020. Published online in SPPS on January 12th 2021.
Data, analysis scripts, and study materials are available on the OSF at
https://osf.io/tpa3x . Correspondence concerning this article should be addressed to
Jeromy Anglim, School of Psychology, Deakin University, Locked Bag 20000,
Geelong, 3220 Australia. Email: jeromy.anglim@deakin.edu.au
COVID-19 PANDEMIC AND WELL-BEING
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et al., 2015; Fujita & Diener, 2005; Schimmack & Oishi, 2005), (b) has a hereditary
component (Røysamb et al., 2018; Weiss et al., 2008), (c) is influenced by
homeostatic processes (Cummins, 2015; Headey & Wearing, 1989; Headey &
Wearing, 1992), and (d) is driven substantially by broad personality traits such as
neuroticism, extraversion, and conscientiousness (Anglim et al., 2020; Steel et al.,
2019). Nonetheless, life events do influence well-being (Luhmann et al., 2012) and the
effect of a modern global pandemic on well-being is not yet well understood. It is
unclear whether the personality profile that thrives under normal circumstances also
thrives during a pandemic. As such it is particularly important to understand how the
COVID-19 pandemic is affecting well-being and what kinds of people are most
psychologically vulnerable to its negative effects (Van Bavel et al., 2020).
Despite an emerging literature on the effect of the COVID-19 pandemic on
well-being (for reviews, see Sher, 2020; Xiong et al., 2020), many gaps in
understanding remain. First, most studies examining the effect of COVID-19 on well-
being are cross-sectional surveys conducted during the pandemic that lack a
meaningful Pre-COVID comparison group. Second, of the current longitudinal studies
that overcome this issue (e.g., Foa et al., 2020; Sibley et al., 2020; Zacher & Rudolph,
2020), most concern the early stages of the pandemic. In particular, little is known
about the effects of sustained or second-wave lockdowns. Third, many of the large
panel studies that may ultimately examine changes in well-being employ abbreviated
measures of well-being, particularly in relation to more humanistic conceptions of
well-being related to meaning, purpose, and social connection (Ryff, 1989; Ryff &
Keyes, 1995). Fourth, although a few studies have looked at the relationship between
personality and well-being in the COVID-19 context, very little research has yet
compared the effect of personality on well-being before and after onset of the
pandemic. Understanding whether the COVID-19 pandemic moderates the effect of
personality on well-being has practical implications for knowing how to assist
different types of people during the pandemic. It also provides a powerful natural
experiment to assess theoretical expectations for how personality and the environment
interact.
Thus, the current study aimed to assess the effect of personality and the
COVID-19 pandemic on subjective well-being (SWB) and psychological well-being
(PWB). Specifically, it sought to assess the degree to which different aspects of well-
being were affected by the COVID-19 pandemic and whether the pandemic moderated
the effect of personality on well-being. While researchers have adopted a range of
different perspectives to well-being (for reviews, see Diener et al., 1999; Lucas &
Diener, 2008), we adopt the complementary perspectives of SWB and PWB, where
SWB is operationalized as high life satisfaction combined with high levels of positive
affect and low levels of negative affect (Deci & Ryan, 2008; Diener, 1984; Lucas et
al., 1996), and PWB is operationalized as positive relations, autonomy, environmental
mastery, personal growth, purpose in life, and self-acceptance (Ryan & Deci, 2001;
Ryff & Keyes, 1995). To achieve these aims, we compared data on Big Five
personality, SWB, and PWB from two samples of young adult university students
from Melbourne, Australia. Importantly, the measures used and the population that the
two samples were recruited from were identical in almost all respects. The Pre-
COVID sample was obtained in 2017 and the COVID sample was obtained in July
COVID-19 PANDEMIC AND WELL-BEING
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2020. Importantly, people in Melbourne had experienced two months of initial
lockdown, followed by a few weeks of re-opening, before increasing cases signaled
the onset of a second-wave of infections, which triggered a second lockdown. As
such, the Melbourne context provides an example of people experiencing sustained
social isolation without a clear sense of when the restrictions will end or whether they
will be effective.
The Effect of Pandemic on Well-Being
Several studies have assessed well-being during the COVID-19 pandemic
either cross-sectionally (e.g., Evans et al., 2020; Mazza et al., 2020; Qian & Yahara,
2020; Zhao et al., 2020) or longitudinally (e.g., Recchi et al., 2020; Wang et al., 2020).
While results are mixed, this research has often found relatively high levels of distress.
Nonetheless, these cross-sectional and longitudinal studies generally lack a pre-
COVID comparison group, which limits inferences about the causal effect of the
pandemic. The most insightful data arguably comes from longitudinal studies that
have measured well-being before and after the onset of COVID-19. For instance, Foa
et al. (2020) examined weekly mood data from Great Britain's mood tracker survey
before and during various phases of the pandemic. They found that positive mood
dropped when the virus began rapidly spreading in the community, but that mood
returned almost to pre-COVID levels once lockdown restrictions were put in place.
It seems that the greatest distress of the pandemic may be caused by
widespread viral transmission resulting in fear of sickness and death. Nonetheless,
lockdown and other social distancing restrictions involve a wide range of economic,
social, and psychological stressors and it is likely that the negative effects of
lockdown will escalate over time. In particular, returning to a second lockdown
presents additional challenges given that it is an admission that one lockdown is
insufficient. It is also clear that the effect of the COVID-19 pandemic varies
dramatically between people (Evans et al., 2020; Van Bavel et al., 2020). In addition
to the uneven distribution of objective economic and health impacts, people also vary
in how they experience and adapt to lockdown and the pandemic (Lades et al., 2020).
Some people may even thrive in lockdown, enjoying digital entertainment, online
delivery, online communication, reduced commute times, and more time with their
immediate family (Evans et al., 2020). Ultimately, how people respond to the
pandemic is likely due to a combination of both objective (e.g., health, finances,
duration and extent of deprivation of personally important activities) and subjective
effects related to the varying ways that people perceive and adapt to the pandemic.
Personality and Well-being under COVID
To understand these subjective factors that influence the effect of COVID-19
on well-being, it is helpful to review the broader personality literature. Research on
this relationship between personality and well-being has exploded in recent years (for
meta-analytic reviews, see Anglim et al., 2020; DeNeve & Cooper, 1998; Steel et al.,
2008). Recently, Anglim et al. (2020) conducted a meta-analysis showing how robust
the relationship is between Big Five personality (i.e., neuroticism, extraversion,
openness, agreeableness, and conscientiousness) and SWB and PWB (see meta-
analytic correlations in Table 1). They found that, in particular, neuroticism,
extraversion, and conscientious are strong correlates of well-being. This research also
consolidates evidence from primary studies (Anglim & Grant, 2016; Grant et al.,
COVID-19 PANDEMIC AND WELL-BEING
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2009; Meléndez et al., 2019; Sun et al., 2018) showing how certain pairs of
personality traits and well-being dimensions correlate more than would be expected
from their respective average correlations (e.g., see decomposition of cross-
correlations in Anglim and Grant (2016)). In particular, these include neuroticism with
negative affect, extraversion with positive affect and positive relations, openness with
personal growth, agreeableness with positive relations, and conscientiousness with
environmental mastery and purpose in life.
Table 1
Meta-Analytic Correlations of Big Five Personality with SWB and PWB from Anglim et al
(2020)
Trait
SWL
PA
NA
PR
AU
EM
PG
PL
SA
Neuroticism
-.39
-.34
.56
-.43
-.45
-.58
-.34
-.45
-.60
Extraversion
.32
.44
-.21
.47
.26
.38
.39
.39
.43
Openness
.08
.24
-.05
.20
.24
.11
.44
.21
.16
Agreeableness
.20
.19
-.25
.39
.10
.28
.31
.28
.28
Conscientiousness
.27
.35
-.25
.32
.30
.51
.32
.50
.44
Note. For SWB criteria studies = 120 to 224, n = 39,023 to 158,934. For PWB criteria, studies =
13 to 19, n = 5,281 to 6,840. SWL = satisfaction with life, PA = positive affect, NA = negative
affect, PR = positive relations, AU = autonomy, EM = environmental mastery, PG = personal
growth, PL = purpose in life, SA = self-acceptance.
While meta-analytic literature highlights the robustness of the relationship
between personality and well-being (Anglim et al., 2020), the environment may still
moderate this relationship. In particular, the effect of personality on well-being may
be influenced by person-environment fit (Edwards et al., 2006). So, for instance, by
definition, extraverts enjoy social interactions, agreeable people appreciate social
harmony, conscientious people enjoy working towards longer term goals, and open
people enjoy learning about creative ideas. Typically, people are able to influence
their environment in the short and long term. However, social distancing measures
induced by the pandemic have created a range of constraints on personal freedom,
particularly in relation to the ability to engage in social interactions. Many articles in
the popular press have suggested that extraverts will struggle more with the social
constraints of lockdown (e.g., Smillie & Haslam, 2020). If this is true, then the
normally positive relationship between extraversion and well-being will be attenuated.
Alternatively, the overall magnitude of the relationship between personality
and well-being may be altered by the pandemic. In particular, the pandemic is a
"strong situation". Casale and Flett (2020) argued that the last time such a strong
situation affected so many people was World War II. By definition, where the
environment is weak, people are more able to select and alter their environment and
choose how they behave. In the context of a pandemic, the enforcement of public
health measures mean that people's environments are more constrained. Choices about
social activities, work arrangements, and other lifestyle choices are all constrained by
emergency health guidelines. The pandemic also presents a substantial and persistent
external stressor that may exert relatively objective effects on well-being that are
highly variable across individuals. Collectively, these effects may attenuate the effect
of personality.
COVID-19 PANDEMIC AND WELL-BEING
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There is now also an emerging literature on the relationship between
personality and well-being during various phases of the COVID-19 pandemic (e.g.,
Jørgensen et al., 2020; Kroencke et al., 2020; Michinov & Michinov, 2020;
Modersitzki et al., 2020; Qian & Yahara, 2020; Russo et al., 2020; Zajenkowski et al.,
2020). However, the lack of a pre-COVID comparison group in this research makes it
unclear whether the relationship between personality and well-being is altered by the
pandemic. One exception is a longitudinal study by Folk et al. (2020) that examined
the ability of extraversion to predict lethargy and social connection before and during
the early-stages of the pandemic. They found some evidence of a reduced correlation
between extraversion and lethargy during the pandemic. Nonetheless, a few
limitations were present. In particular, a full set of Big Five measures is required to
determine whether declines in correlations are general or trait-specific. It is also
important to measure traits both pre- and post-COVID in order to rule out any general
decline in correlations due to a cross-lagged design. Finally, it seems likely that the
size of any moderating effect of personality will be related to the size of the effect of
the pandemic on well-being, and this effect is likely to be the larger after a sustained
period of lockdown and exposure to health risks.
Method
Data, analysis scripts, and study materials are available on the OSF at
https://osf.io/tpa3x/?view_only=c734d8cd874d414f8f1a84ad1a7c33e9
Participants and Procedure
Participants in both COVID and Pre-COVID groups were undergraduate
psychology students drawn from two units at a university based in Victoria, Australia,
with its main campus in Melbourne. As part of their studies, students had the option to
complete an online survey that consisted of personality measures and various criterion
measures. They also had the option to allow their data to be used for research
purposes. Students received their personality scores which informed an assessment
task. Because the survey was voluntary and students received feedback about their
personality, students were incentivized to answer the survey conscientiously.
Examination of survey completion times were almost universally consistent with
conscientious completion. The survey received ethics approval from the first author's
institutional Human Research Ethics Committee.
The COVID Sample completed the survey mostly in July 2020 (97% between
July 13th and July 31st; and 3% between August 1st and 11th). Further details about
the COVID-19 context in Melbourne is provided in the online supplement, but the
essential aspect is that Melbourne had experienced two months of lockdown. This was
followed by a brief relaxation of restrictions, a rapid resurgence of cases, and a return
to a second lockdown. Results for the COVID sample reported in this paper focus on
participants that resided in Greater Melbourne (n = 1132; 80.9% female, 18.1% male,
and 1.0% other with mean age of 24.5 (SD = 8.1, range: 18 to 86; 27% aged over 25).
This was drawn from an overall COVID sample (n = 1470) was 81.6% female, 17.5%
male, and 1.0% other with mean age of 25.5 (SD = 8.6, range: 18 to 86; 33% aged
over 25) with 77% residing within Greater Melbourne, 83% within 500km of
Melbourne and the remainder residing in other parts of Australia. Results for the
overall COIVD sample are reported in the online supplement. The final overall sample
was obtained after excluding 42 participants for one or more of the following reasons:
COVID-19 PANDEMIC AND WELL-BEING
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(a) not residing in Australia (n = 23), (b) less than 3 distinct response options on the
PWB measure (n = 5), the personality measure (n = 1), the PANAS (n = 17).
The Pre-COVID Sample was collected in 2017 (84% in July, 3% in August,
11% in November, and 2% in December). The Pre-COVID sample (n = 547) was
79.4% female and 20.6% male ("other" was not an option in this survey) with mean
age of 25.0 (SD = 7.68, range: 18 to 65; 26% aged over 25) and 81% residing within
Greater Melbourne, and 88% within 500km of Melbourne. Analyses of this Pre-
COVID sample were previously reported in Anglim et al. (2020). This final sample
was obtained after excluding 3 participants for one or more of the following reasons:
less than 3 distinct response options on the PWB measure (n = 3), the personality
measure (n = 0), the PANAS (n = 3).
The sample size was determined by the recruitment source. There was 96.9%
power to detect a small difference in well-being of d = 0.2, and a 99.99% power to
detect a difference of d = 0.3, and 80% power to detect a difference of d = .146 (two-
tailed, alpha = .05). There was 80% power to detect a change in population correlation
from .40 Pre-COVID to .27 during COVID. Confidence intervals are provided in the
results where appropriate, but are omitted from correlation matrices given that the
standard errors are small and would distract from extracting information from the
tables.
Materials
Big Five Personality
Big Five personality was measured using 50 items drawn from the IPIP NEO
(Goldberg, 1999; Goldberg et al., 2006). In the Pre-COVID sample items were rated
on a 5-point scale (1 = very inaccurate, 2 = moderately inaccurate, 3 = neither
inaccurate nor accurate, 4 = moderately accurate, 5 = very accurate). In the COVID
sample, items were rated on a scale from (1 = strongly disagree, 2 = disagree, 3 =
neither agree nor disagree, 4 = agree, 5 = strongly agree). Because the response
options were slightly different, personality scores were z-score standardized within
Pre-COVID and COVID samples. A comparison of COVID personality scores with
some other available normative data is presented in the online supplement, which
suggests that personality was relatively unchanged under the COVID pandemic.
Alphas Pre-COVID and COVID respectively were as follows: neuroticism (.87, .86),
extraversion (.81, .80), openness (.75, .73), agreeableness (.74, .74), and
conscientiousness (.80, .77).
Satisfaction with Life Scale
This well-established 5-item measure (Diener et al., 1985) provides a measure
of overall life satisfaction. Items were rated on a 7-point scale (1 = strongly disagree, 2
= disagree, 3 = slightly disagree, 4 = neither agree nor disagree, 5 = slightly agree, 6 =
agree, 7 = strongly agree). The scale score was the mean of items.
Positive and Negative Affect
Positive and negative affect was measured using the 20-item PANAS (Watson
et al., 1988). The PANAS consists of two scales that measure the frequency with
which positive and negative affect is experienced on a 5-point scale (1 = very slightly
or not at all, 2 = a little, 3 = moderately, 4 = quite a bit, 5 = extremely). Participants
were asked about how frequently they had experienced the emotions in "the past few
weeks" in the Pre-COVID sample and in "the past few months" in the COVID
COVID-19 PANDEMIC AND WELL-BEING
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Sample. The rationale for using months in the COVID sample was to capture the
experience of the COVID pandemic. Scales were scored as the mean of items.
Psychological Well-Being
The 42-item measure of Ryff's (1989) scales were used to measure the six
proposed dimensions of psychological well-being. Items were rated on a 6-point scale
(1 = strongly disagree, 2 = disagree somewhat, 3= disagree slightly, 4 = agree slightly,
5 = agree somewhat, 6 = strongly agree). Note that in the 42-item measure is a subset
of the 84-item measure and in the Pre-COVID sample, the 84-item measure was
administered. But to enable comparison, we scored both time points using only the 42-
item measure. Scale scores were the mean after item reversal.
COVID Comparisons
Five items were administered to the COVID sample assessing subjective
perceptions of changes to experience during the COVID-19 pandemic. Items assessed
perceived changes to stress, loneliness, boredom, fear, and optimism. A sample item
was "How much stress have you experienced during the Coronavirus pandemic?"
Response options were "Much less than usual", "less than usual", "same as usual,
"more than usual", and "much more than usual".
Results
Group Differences in Means
Table 2 presents the mean differences between the Pre-COVID and COVID
groups on well-being variables. There was a consistent pattern of the COVID sample
experiencing less well-being. The largest differences in well-being were observed for
the more time-constrained mood variables whereby COVID participants were
experiencing significantly more negative affect (d = 0.70, p < .001) and significantly
less positive affect (d = -0.48, p < .001). Effect sizes for positive relations, autonomy,
environmental mastery, and self-acceptance ranged from d = -0.25 to -0.32.
Differences for purpose in life and life satisfaction were smaller again, and finally
there was no significant difference for personal growth.
Table 2
Differences in Well-Being in Pre-COVID and COVID Samples
Pre-COVID
(n = 547)
COVID
(n = 1132)
Difference
Variable
a
M
SD
a
M
SD
t
sig.
d [95% CI]
Life Satisfaction
.85
4.74
1.34
.86
4.46
1.34
-4.06
***
-0.21 [-0.31, -0.11]
Positive Affect
.88
3.32
0.76
.88
2.95
0.75
-9.32
***
-0.48 [-0.59, -0.38]
Negative Affect
.87
2.05
0.74
.89
2.57
0.84
12.82
***
0.70 [0.59, 0.80]
Positive Relations
.78
4.76
0.85
.77
4.55
0.86
-4.74
***
-0.25 [-0.35, -0.15]
Autonomy
.76
4.13
0.83
.77
3.90
0.86
-5.30
***
-0.28 [-0.38, -0.18]
Environmental Mastery
.80
4.12
0.90
.82
3.83
0.93
-6.14
***
-0.32 [-0.43, -0.22]
Personal Growth
.78
4.96
0.75
.76
4.88
0.72
-1.87
-0.10 [-0.20, 0.00]
Purpose in Life
.77
4.59
0.86
.76
4.43
0.83
-3.55
***
-0.18 [-0.28, -0.08]
Self-Acceptance
.88
4.17
1.06
.88
3.88
1.07
-5.25
***
-0.27 [-0.38, -0.17]
* p < .05, ** p < .01, *** p < .001
In order to provide a more nuanced understanding of changes to affective
experience under COVID, an item-level comparison of the PANAS was performed.
COVID-19 PANDEMIC AND WELL-BEING
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Table 3 shows the percentage of participants who reported experiencing a given
emotion "quite a bit" or "extremely" in the Pre-COVID and the COVID samples.
While all positive emotions were less prevalent and all negative emotions were more
prevalent during the pandemic, there was also a distinct pattern to the magnitude of
these differences. With regards to positive emotions, emotions related to being happy
and engaged (i.e., excited, interested, enthusiastic) showed the biggest differences.
With regards to negative emotions, the differences were fairly generalized across
emotions related to anxiety and sadness.
Table 3
Differences in PANAS Mood Variables in Pre-COVID and COVID Samples
Emotion
Pre-COVID
(n = 547)
%
COVID
(n = 1132)
%
Difference
%
Positive Affect
Excited
55
27
-28***
Interested
66
41
-25***
Enthusiastic
51
30
-21***
Active
44
29
-15***
Determined
59
44
-14***
Proud
42
29
-13***
Attentive
48
36
-12***
Strong
40
29
-11***
Inspired
42
31
-11***
Alert
41
36
-5*
Negative Affect
Ashamed
6
12
6***
Guilty
11
18
7***
Hostile
5
13
7***
Scared
10
23
13***
Jittery
14
28
14***
Depressed
16
32
15***
Nervous
27
42
15***
Afraid
10
25
15***
Irritable
22
39
16***
Upset
18
39
21***
Note. Percentages are the percentages of people reporting that they have experienced the emotion
quite a bit or extremely (see online supplement for equivalent analysis using item means).
* p < .05, ** p < .01, *** p < .001
We also asked participants in the COVID sample about the extent to which
they had various experiences more or less than usual during the Coronavirus pandemic
(see Table 4). Over half the participants reported experiencing more stress, loneliness,
and boredom, and less optimism during the pandemic compared to their Pre-COVID
experience.
COVID-19 PANDEMIC AND WELL-BEING
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Table 4
Self-reported Differences in Experience during the COVID-19 Pandemic
Experience
Less than usual
%
Same as Usual
%
More than usual
%
More % - Less %
Stress
6
29
65
58
Loneliness
10
30
60
50
Boredom
8
25
68
60
Fear
10
41
49
39
Optimism
54
37
9
-45
Note. n = 1132. Responses indicate the degree to which participants report experiencing the
experience during the pandemic more or less than usual. "Less than usual" includes participants
who reported experiencing "much less than usual" or "less than usual". "More than usual"
includes participants who reported experiencing "much more than usual" or "more than usual".
Correlations
Table 5 presents the correlations between personality and well-being for the
Pre-COVID and COVID samples along with the significance tests of the differences
between these correlations. In general, the correlation matrices were significantly
different (p < .001) using cortest in the psych package (Revelle, 2018). The average
absolute correlation between personality and well-being was significantly larger in the
Pre-COVID sample (mean r = .35) than in the COVID sample (mean r = .30). The
95% bootstrap confidence interval of this difference was .011 to .088. Overall, 9 of the
45 correlation differences (COVID versus Pre-COVID) between personality and well-
being were significant at the .05 level, which is a lot more than would be expected by
chance if there were no underlying difference. Two of the most noteworthy
differences were (a) extraversion and positive affect (Pre-COVID r = .44; COVID r =
.31; difference p = .004), and (d) agreeableness and positive affect (Pre-COVID r =
.22; COVID r = .09; difference p = .007).
COVID-19 PANDEMIC AND WELL-BEING
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Table 5
Correlations between Big Five Personality and Well-Being in Pre-COVID and COVID Samples
SWL
PA
NA
PR
AU
EM
PG
PL
SA
Mean
abs r
Pre-COVID (n = 547)
Neuroticism
-.56
-.54
.70
-.48
-.43
-.72
-.48
-.45
-.72
.56
Extraversion
.33
.44
-.28
.51
.34
.40
.42
.29
.43
.38
Openness
.04
.25
-.05
.17
.31
.09
.42
.21
.18
.19
Agreeableness
.22
.22
-.27
.43
.02
.24
.30
.25
.26
.25
Conscientiousness
.28
.38
-.30
.28
.30
.49
.40
.58
.41
.38
Mean abs r
.29
.37
.32
.37
.28
.39
.40
.35
.40
.35
COVID (n = 1132)
Neuroticism
-.56
-.45
.65
-.46
-.38
-.68
-.41
-.41
-.72
.52
Extraversion
.33
.31
-.18
.44
.32
.37
.38
.28
.42
.34
Openness
-.01
.18
.02
.09
.27
-.01
.36
.13
.05
.12
Agreeableness
.22
.09
-.22
.36
-.06
.24
.22
.19
.22
.20
Conscientiousness
.32
.36
-.18
.22
.17
.48
.29
.50
.40
.32
Mean abs r
.29
.28
.25
.32
.24
.36
.33
.30
.36
.30
Difference
Neuroticism
-.01
.09*
-.05
.01
.05
.05
.07
.04
.00
.04
Extraversion
.01
-.13**
.10*
-.07
-.02
-.03
-.03
-.01
-.01
.05
Openness
-.05
-.07
.08
-.08
-.04
-.10
-.06
-.08
-.12*
.08
Agreeableness
.00
-.14**
.05
-.06
-.08
.00
-.08
-.06
-.04
.06
Conscientiousness
.04
-.02
.12*
-.06
-.12*
-.01
-.11*
-.08*
-.02
.06
Mean abs r
.02
.09
.08
.06
.06
.04
.07
.05
.04
.06
Note. Difference is COVID correlation minus Pre-COVID correlation. Absolute Pre-COVID
sample correlations greater than or equal to .09, .12, and .15 are significant at .05, .01, and .001
respectively. Absolute COVID sample correlations greater than or equal to .06, .08, and .10 are
significant at .05, .01, and .001 respectively. Significance of differences between correlations are
as follows: * p < .05, ** p <.01, ** p < .001. SWL = satisfaction with life, PA = positive affect,
NA = negative affect, PR = positive relations, AU = autonomy, EM = environmental mastery,
PG = personal growth, PL = purpose in life, SA = self-acceptance. The mean abs r are row and
column mean absolute correlations.
Regression Models
Regression models were estimated in order to provide an overall assessment of
the importance of demographics, personality, and the pandemic. Table 6 presents
regression models predicting each well-being dimension from demographics,
personality, COVID pandemic status, and COVID by personality interactions (see
online supplement for a comparison of regression models decomposing variance
explained by demographics, COVID, and personality). Age was coded as over 25 or
not because of the substantial skew in the data. Well-being was z-score standardized
to facilitate parameter interpretation. COVID was coded as 0 for Pre-COVID and 1 for
during COVID. Thus, the intercept reflects the expected well-being of a non-female
aged 25 or less, prior to COVID, and who has average scores on all Big Five traits.
COVID-19 PANDEMIC AND WELL-BEING
11
Table 6
Regression Models Predicting Well-Being from Demographics, Personality, the COVID-19
Pandemic, and Personality by COVID Interactions
Predictor
SWL
PA
NA
PR
AU
EM
PG
PL
SA
Coefficient
Intercept
-0.02
0.41***
-0.45***
0.01
0.21***
0.13**
-0.08
-0.03
0.06
Female
0.25***
-0.10
0.09*
0.18***
-0.13*
0.10*
0.11*
0.14**
0.17***
Age > 25
-0.15***
-0.07
-0.17***
0.07
0.25***
0.06
0.25***
0.19***
-0.04
Neuroticism
-0.50***
-0.32***
0.58***
-0.22***
-0.28***
-0.57***
-0.25***
-0.21***
-0.59***
Extraversion
0.08*
0.23***
0.01
0.34***
0.17***
0.13***
0.23***
0.11**
0.13***
Openness
-0.04
0.14***
0.06
0.05
0.18***
-0.05
0.29***
0.10**
0.06*
Agreeableness
0.04
0.05
-0.08*
0.28***
-0.14***
0.00
0.13***
0.06
0.03
Conscientiousness
0.08*
0.21***
-0.04
0.07
0.16***
0.26***
0.21***
0.45***
0.16***
COVID
-0.19***
-0.45***
0.60***
-0.25***
-0.25***
-0.31***
-0.09*
-0.17***
-0.25***
COVID by Neuroticism
0.02
0.00
0.07
-0.05
-0.03
0.04
0.03
-0.01
-0.02
COVID by Extraversion
0.08
-0.09*
0.03
-0.01
0.00
0.04
0.01
0.04
0.06
COVID by Openness
0.00
0.01
-0.01
-0.03
0.04
0.00
0.01
0.00
-0.05
COVID by Agreeableness
0.00
-0.12**
0.02
-0.03
-0.04
0.02
-0.03
-0.05
-0.04
COVID by Conscientiousness
0.04
0.05
0.08
-0.03
-0.06
0.02
-0.05
-0.05
0.02
95% CI
Intercept
-.13, .09
.30, .52
-.55, -.35
-.09, .12
.10, .33
.04, .22
-.19, .02
-.13, .08
-.03, .15
Female
.15, .35
-.20, .01
.00, .19
.08, .28
-.24, -.02
.01, .18
.01, .20
.04, .24
.09, .26
Age > 25
-.24, -.06
-.16, .02
-.25, -.09
-.02, .16
.15, .34
-.01, .13
.17, .34
.10, .28
-.12, .03
Neuroticism
-.59, -.42
-.40, -.24
.50, .65
-.30, -.14
-.37, -.19
-.63, -.50
-.33, -.17
-.29, -.13
-.66, -.52
Extraversion
.00, .16
.15, .30
-.06, .08
.27, .42
.09, .25
.06, .19
.16, .31
.03, .18
.07, .19
Openness
-.11, .03
.07, .21
.00, .12
-.01, .12
.11, .26
-.11, .01
.22, .35
.03, .17
.00, .12
Agreeableness
-.03, .11
-.02, .12
-.15, -.02
.21, .35
-.21, -.06
-.06, .06
.06, .20
-.01, .13
-.03, .08
Conscientiousness
.01, .16
.13, .28
-.11, .03
-.01, .14
.08, .24
.20, .32
.13, .28
.37, .52
.10, .22
COVID
-.27, -.11
-.53, -.37
.53, .67
-.33, -.17
-.34, -.17
-.37, -.24
-.17, -.01
-.25, -.09
-.32, -.19
COVID by Neuroticism
-.08, .12
-.10, .09
-.02, .15
-.15, .04
-.13, .07
-.04, .12
-.07, .12
-.10, .09
-.10, .06
COVID by Extraversion
-.01, .17
-.19, .00
-.05, .11
-.10, .08
-.09, .10
-.03, .12
-.08, .10
-.05, .13
-.01, .13
COVID by Openness
-.08, .09
-.07, .10
-.09, .06
-.11, .05
-.05, .13
-.07, .07
-.07, .09
-.08, .08
-.11, .02
COVID by Agreeableness
-.09, .08
-.20, -.03
-.06, .10
-.12, .05
-.13, .06
-.06, .09
-.11, .05
-.14, .03
-.11, .03
COVID by Conscientiousness
-.05, .13
-.04, .14
.00, .16
-.12, .05
-.15, .03
-.06, .09
-.14, .04
-.14, .04
-.06, .09
Adjusted R2
0.37
0.37
0.49
0.40
0.30
0.58
0.41
0.39
0.58
Note. Female is coded 1 = Female, 0 = Male or Other; Age is coded 1 = 26 or older, 0 = 18 to 25;
COVID is coded 0 = Pre-COVID (n = 547), 1 = COVID (n = 1132). Well-being variables are z-
score standardized. Personality variables are z-score standardized within COVID groups.
Interactions are the product of the 0–1 COVID variable and the standardized personality
variables. SWL = satisfaction with life, PA = positive affect, NA = negative affect, PR = positive
relations, AU = autonomy, EM = environmental mastery, PG = personal growth, PL = purpose in
life, SA = self-acceptance.
* p < .05, ** p < .01, *** p < .001
The coefficients for personality were largely as one would expect with many
large coefficients, especially for neuroticism, extraversion, and conscientiousness.
There was also the typical personality–well-being pairs where personality coefficients
were larger than average for the trait. For example, elevated pairs of predictors
included openness on personal growth, extraversion and agreeableness on positive
relations, and neuroticism on negative affect. The parameter for the COVID-19
pandemic corresponds to a z-score of the difference between COVID and Pre-COVID
controlling for personality and demographics. This parameter largely mirrors the
pattern of results of raw group differences in Table 2. With regards to interactions
COVID-19 PANDEMIC AND WELL-BEING
12
between COVID and personality, there were only two significant effects. First,
extraversion interacted with COVID status such that the effect of extraversion on
positive affect was reduced during COVID-19 (beta = 0.09, p = .045). Second,
agreeableness interacted with COVID status such that the effect of agreeableness on
positive affect was reduced during COVID-19 (beta = -0.12, p = .008). As a
robustness check, we examined the effect of not standardizing personality within
samples, and this reduced the estimated standardized effect of the pandemic by an
average 0.08 (see online supplement for details).
Discussion
The current study sought to assess the effect of the COVID-19 pandemic on
well-being and whether the effect of personality on well-being was moderated by the
pandemic. Several key findings emerged. First, it was clear that the young adults were
experiencing lower levels of well-being during the pandemic. This effect was
strongest for positive and negative affect. The effect on other well-being indicators
was smaller, but it still suggested some targeted and slightly larger effects for positive
relations, autonomy, and environmental mastery compared to purpose in life, life
satisfaction, and personal growth. Second, consistent with the theory of strong
situations, the effect of personality on well-being was slightly weaker during the
pandemic. Third, there was some evidence of COVID-19 moderating the effect of
personality on well-being. In particular, the benefits of extraversion on positive affect
were attenuated.
COVID 19 and Well-being
Overall, after four months of social restrictions, concerns about a second wave
of viral spread, and the arrival of a second lockdown, the well-being of young adults
in Melbourne, Australia was lower than it was pre-COVID. In particular, the
differences in negative affect (d = 0.70) and positive affect (d = -0.48) were quite
substantial. These findings differ from the study of early stages of lockdown in New
Zealand (Sibley et al., 2020) that found minimal changes in well-being, but share
some similarity with the United Kingdom experience (Foa et al., 2020) where positive
mood declined when the virus started spreading. Presumably, the effect of lockdown
and social distancing provisions vary over time and by environmental conditions. In
particular, lockdown likely involves both adjustment and fatigue processes. While
lockdown appears to result in improved well-being compared to uncontrolled viral
spread (Foa et al., 2020), over time, it likely becomes more draining both
economically and psychologically.
Positive and negative affect appeared to be most affected by the pandemic. In
particular, people reported much lower levels of interest, enthusiasm, and excitement
whereas the effect on negative affect was more generalized. Overall, this is consistent
with affect being a time-constrained appraisal more directly influenced by recent
events, whereas life satisfaction and PWB are broader appraisals of life that are less
impacted by negative events of relatively fixed duration. Nonetheless, there was some
evidence of reduced levels of PWB, particularly in relation to autonomy and positive
relations which is consistent with the reduced freedoms and scope for social
interaction during lockdown (Cantarero et al., 2020).
COVID-19 PANDEMIC AND WELL-BEING
13
Personality and Well-being under COVID 19
Overall, the relationship between personality and well-being was not
substantially altered by the pandemic, albeit some small theoretically important
differences were observed. Focusing first on the similarities, the results reiterate the
importance of personality to well-being. It shows that people's mood even in extreme
circumstances is driven more by personality than by the general experience of a
pandemic. It also suggests that the effect of personality and the pandemic are mostly
additive. In other words, if an individual has high neuroticism, low extraversion and
low conscientiousness, they are likely to have lower well-being, and irrespective of
personality, the COVID pandemic tends to result in reduced well-being.
Nonetheless, the average correlation between personality and well-being was
slightly lower during the pandemic. In particular, while everyone is exposed to the
pandemic, the social, economic, and health effects are not distributed evenly. While
some of these effects may be influenced by personality, many effects such as
unemployment, increased financial insecurity, and suffering from COVID-19 are
presumably relatively independent of personality. Thus, in addition to lockdown
reducing the capacity of personality to be expressed in the form of people selectively
entering into environments, the varied degree of negative effects of the pandemic may
attenuate the effect of personality on well-being.
There was also some evidence that the pandemic differentially moderated the
relationship between personality and well-being. Of the 45 correlations between
personality traits and well-being, 9 were significant at .05, which is more than would
be expected by chance. Given that positive and negative affect were the well-being
dimensions most influenced by the pandemic, these seem the most likely candidates
for moderator effects. In particular, the reduced effect of extraversion on positive
affect seems noteworthy. Theory suggests that extraverts seek out social interaction
and are energized by it. From this perspective, lockdown has the potential to deprive
extraverts of some of their sources of happiness. While most people enjoy social
contact (Jacques-Hamilton et al., 2019; Zelenski et al., 2012), theory and the current
results suggest that extraverts will feel more deprived by lockdown. Results provide
some support for theories of extraversion that emphasize the effect of instrumental
processes and situation selection in addition to the effects of temperament (for
discussion, see Lucas et al., 2008). Thus, while extraversion still promotes positive
affect under lockdown, results suggest that the normal beneficial effects of
extraversion on mood are attenuated.
Limitations
Several limitations should be noted. First, because the study used a between-
subjects design as opposed to a longitudinal design, it is possible that extraneous
factors may have influenced observed group differences. We dealt with this challenge
by obtaining data from the same population of undergraduate psychology students at
the same university. In general, demographic differences were very small, and our
main regression analyses controlled for age and gender. We also performed analyses,
available through the online scripts, where we examined the robustness of the results
(by, for example, excluding interstate participants or excluding people over age 25)
and the results were not materially altered. The online supplement also presents
archival and historical evidence of the stability of Australian society in the years prior
COVID-19 PANDEMIC AND WELL-BEING
14
to the pandemic (Wilkins et al., 2020). Second, there were a few minor differences in
test administration between the two contexts. But, the underlying context to complete
the survey in order to learn about their own personality was unchanged.
Conclusion
The current study makes several notable contributions. First, it contributes to
an understanding of the well-being effects of second-wave lockdowns during the
COVID-19 pandemic. The large sample sizes and the presence of a Pre-COVID
comparison group are also major strengths. Second, it provides one of the first
comprehensive assessments of a full spectrum of SWB and PWB measures during the
COVID-19 pandemic. Third, it provides the first, to our knowledge, comprehensive
assessment of whether the pandemic moderated the effect of personality on well-being
(although, see also Folk et al., 2020). In so doing, it contributes more generally to an
understanding of how personality interacts with pandemics and other major
population-level events to influence well-being. In particular, the finding that the well-
being benefits of extraversion are reduced during sustained lockdown is particularly
interesting and worthy of further research.
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COVID-19 PANDEMIC AND WELL-BEING
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Online Supplement
Context of COVID-19 in Melbourne
To provide context to the present results, we briefly discuss the experience of
the COVID-19 pandemic in Melbourne and Australia up to August 2020. Melbourne
is the second most populous city in Australia and is the capital city of the state of
Victoria. On March 10, the State premier warned Victorians to expect "extreme
measures" in order to deal with the COVID-19 pandemic. On March 19, international
borders were closed to non-residents and non-Australian citizens. From March 22,
social distancing restrictions were gradually introduced in Victoria. In April and May,
Melbourne operated largely under "Stage 3" restrictions which meant that there were
only four reasons to leave home: (1) work and study that could not be done from
home, (2) personal exercise, (3) essential shopping, and (4) caring responsibilities.
While there was some community transmission of coronavirus, most of Australia's
cases were returned travelers who were placed into hotel quarantine arrangements. As
a result of moving early to introduce restrictions, Australia almost reduced community
transmission to zero, and in some states and territories it appeared to do so, although
there were a few small isolated outbreaks in Melbourne.
At the beginning of June, there was a general easing of restrictions in
Melbourne (e.g., hotels, restaurants, galleries, and community centers were open with
some restrictions, and small social gatherings were permitted) with plans for further
easing of restrictions by June 22. However, as June progressed, there were gradual
increases in the number of people in Melbourne testing positive to COVID-19. This
second wave of infections was believed to have been seeded by ineffective hotel
quarantine arrangements and compounded by a range of factors including inadequate
contact tracing. Cases grew in various lower socio-economic-status suburbs in
Melbourne and these suburbs were placed back into Stage 3 lockdown on June 30.
When this failed to contain the spread of the virus, all of Melbourne was again placed
into Stage 3 lockdown on July 7. As case counts continued to rise, it became clear that
social distancing measures would need to be amplified relative to the first wave of the
virus. Compulsory mask wearing outside the home was announced on July 19. Stage 4
restrictions were introduced on August 2. Stage 4 restrictions involved all but essential
retail shops being closed, an 8pm to 5am curfew, a one hour limit on private exercise,
and people being forbidden to travel more than 5km from home unless for a permitted
purpose. It was in this context that the survey was administered in the second half of
July 2020. Thus, while the rest of Australia had very little community transmission
and was experiencing a semblance of normality, people in Melbourne were preparing
to go into a second lockdown with an unknown end-point and unclear potential for
lasting success.
Alternative Analysis of PANAS Items
In the main text, we report differences in item responses to the PANAS in
terms of percentage endorsement. Table S1 provides the equivalent analysis using
means and standard deviations on the original 5-point scale.
COVID-19 PANDEMIC AND WELL-BEING
18
Table S1
Comparison of Means and Standard Deviations of PANAS Items
Pre-COVID
(n = 547)
COVID
(n = 1132)
Emotion
M
SD
M
SD
d
Excited
3.46
1.07
2.79
1.06
-0.63
Interested
3.72
1.00
3.16
1.02
-0.56
Enthusiastic
3.38
1.06
2.88
1.06
-0.47
Active
3.18
1.19
2.80
1.16
-0.32
Determined
3.58
1.04
3.24
1.11
-0.33
Proud
3.16
1.18
2.79
1.14
-0.31
Attentive
3.33
1.00
3.07
0.98
-0.26
Strong
3.12
1.15
2.87
1.10
-0.22
Inspired
3.15
1.14
2.86
1.14
-0.25
Alert
3.15
1.06
3.06
1.07
-0.08
Ashamed
1.56
0.95
1.96
1.14
0.42
Guilty
1.92
1.09
2.21
1.20
0.27
Hostile
1.65
0.94
2.08
1.09
0.46
Scared
1.82
1.06
2.46
1.22
0.60
Jittery
1.99
1.13
2.61
1.24
0.55
Depressed
2.20
1.15
2.71
1.31
0.44
Nervous
2.65
1.19
3.08
1.22
0.36
Afraid
1.81
1.07
2.52
1.24
0.66
Irritable
2.51
1.13
3.03
1.11
0.46
Upset
2.42
1.09
3.04
1.16
0.57
Note. Cohen's d uses Pre-COVID standard deviation.
Regression Model Comparison
To further quantify the relative importance of personality and the COVID
pandemic, regression models predicting well-being outcomes were estimated for
various predictor sets: (1) only the demographics of age and gender as coded earlier,
(2) demographics and Big 5 personality, (3) demographics and the COVID pandemic,
(4) demographics, Big 5 personality, and the COVID pandemic. The results in Table
S2 clearly show that personality is a much stronger predictor of well-being than the
pandemic. That said, the size of difference varies across the well-being indicators.
Specifically, the pandemic is a strong predictor over and above demographics of
positive affect and negative affect, although even for these variables, personality is a
much stronger predictor.
Table S2
Adjusted R-squared for Regression Models Predicting Well-being from Sets of Predictors
Predictors
k
SWL
PA
NA
PR
AU
EM
PG
PL
SA
Mean
1. Demog
2
.001
.005
.032
.008
.045
.010
.037
.031
.004
.019
2. Demog + Big 5
7
.361
.321
.415
.389
.286
.557
.409
.382
.568
.410
3. Demog + COVID
3
.009
.050
.113
.020
.058
.032
.038
.038
.018
.042
4. Demog + COVID + Big 5
8
.369
.364
.493
.402
.300
.577
.410
.388
.581
.431
Note. Predictors in regression models are indicated as follows: Demog = Female and Aged over
25, Big 5 = the big 5 personality scores, COVID = The dummy coded variable indicating
COVID-19 PANDEMIC AND WELL-BEING
19
COVID. SWL = satisfaction with life, PA = positive affect, NA = negative affect, PR = positive
relations, AU = autonomy, EM = environmental mastery, PG = personal growth, PL = purpose in
life, SA = self-acceptance. Mean is the mean adjusted r-squared value for the set of predictors
averaged over the 9 well-being outcomes.
Comparison of Melbourne versus Non-Melbourne COVID Sample
All participants in the sample resided in Australia. Most resided in Melbourne
(capital of Victoria). But some resided elsewhere in Victoria or elsewhere in Australia.
We initially thought it would be best to retain all participants for the primary analyses
presented in the manuscript. First, we wished to maximize comparability with the Pre-
COVID sample. Second, we wanted to maximize statistical power. Third, we wanted
to avoid making arbitrary exclusion decisions. Finally, all participants in Australia had
experienced the first wave of lockdown and were living under at least modest social
distancing restrictions as well as the threat of a second wave. Furthermore, many of
these "non-Melbourne" participants resided in the state of Victoria, of which
Melbourne is the capital. In particular, many of the regional cities in Victoria (e.g.,
Geelong, Bendigo, Ballarat, etc.) are very connected to Melbourne, and in general,
regional Victoria was experiencing a milder form of a second wave of viral
transmission with plans for a milder form of lockdown.
However, we were persuaded by reviewer feedback which suggested that it
would be better to focus on the Melbourne sample in the manuscript and present the
full sample in the online supplement. The Melbourne sample had a more homogenous
experience of the COVID pandemic. The experience of the Melbourne sample
experienced a greater threat in terms of public health. They also experienced more
severe and longer-term consequences of lockdown. In particular, at the time of testing,
it was unclear when the Melbourne sample would come out of second-wave lockdown
and whether the efforts to control the virus would be effective.
Ultimately, the general pattern of results are consistent regardless of whether
the Melbourne or Overall sample is examined. The main difference is that the
estimated reduction in well-being in the COVID sample is slightly elevated when
analyzing the Melbourne sample.
We first present here a supplementary analysis examining whether the
participants in Greater Melbourne were experiencing lower levels of well-being than
other participants (see Table S1). Greater Melbourne residents were exposed to a
second lockdown and a second wave of viral transmission. Thus, we examined
whether this led to reduced well-being relative to other people in Victoria and
Australia.
Results generally show limited differences in personality with the exception
that non-Melbourne participants were slightly more conscientiousness, and a general
pattern of Melbourne participants having lower levels of well-being.
COVID-19 PANDEMIC AND WELL-BEING
20
Table S3
Comparison of Greater Melbourne and Other Participants in the COVID
Sample
Other
(n = 338)
Melbourne
(n = 1132)
M
SD
M
SD
t
sig
d
Female
0.84
0.37
0.81
0.39
1.18
-0.07
Age
28.98
9.27
24.50
8.05
7.95
***
-0.48
Neuroticism
2.88
0.74
2.96
0.72
-1.75
0.11
Extraversion
3.27
0.71
3.31
0.70
-0.76
0.05
Openness
3.86
0.53
3.83
0.52
0.81
-0.05
Agreeableness
3.82
0.50
3.78
0.49
1.27
-0.08
Conscientiousness
3.57
0.59
3.43
0.59
3.71
***
-0.23
Life Satisfaction
4.71
1.25
4.46
1.34
3.20
***
-0.20
Positive Affect
3.18
0.77
2.95
0.75
4.83
***
-0.30
Negative Affect
2.39
0.83
2.57
0.84
-3.44
***
0.21
Positive Relations
4.59
0.86
4.55
0.86
0.80
-0.05
Autonomy
4.03
0.82
3.90
0.86
2.62
**
-0.16
Environmental Mastery
4.03
0.91
3.83
0.93
3.47
***
-0.22
Personal Growth
5.07
0.69
4.88
0.72
4.35
***
-0.27
Purpose in Life
4.63
0.84
4.43
0.83
3.87
***
-0.24
Self-Acceptance
4.07
1.04
3.88
1.07
3.06
***
-0.19
Analyses of the Overall Dataset including Non-Melbourne Participants
We also reproduce the main analyses reported in the primary manuscript using
the larger overall COVID sample which includes additional cases where participants
reside in Victoria (but outside Greater Melbourne) or in other states of Australia (see
Table S4, Table S5, Table S6, and Table S7). The general observation is that this
makes very little difference to the results except that the difference between the pre-
COVID and COVID samples is slightly reduced.
Table S4
Differences in Well-Being in Pre-COVID and Overall COVID Samples
Pre-COVID
(n = 547)
Overall COVID
(n = 1470)
Difference
Variable
a
M
SD
a
M
SD
t
sig.
d [95% CI]
Life Satisfaction
.85
4.74
1.34
.86
4.52
1.33
-3.37
***
-0.17 [-0.27, -0.07]
Positive Affect
.88
3.32
0.76
.89
3.01
0.76
-8.26
***
-0.41 [-0.51, -0.32]
Negative Affect
.87
2.05
0.74
.89
2.53
0.84
12.36
***
0.64 [0.54, 0.74]
Positive Relations
.78
4.76
0.85
.76
4.56
0.86
-4.71
***
-0.24 [-0.34, -0.14]
Autonomy
.76
4.13
0.83
.76
3.93
0.85
-4.79
***
-0.24 [-0.34, -0.14]
Environmental Mastery
.80
4.12
0.90
.81
3.88
0.93
-5.40
***
-0.27 [-0.37, -0.17]
Personal Growth
.78
4.96
0.75
.77
4.93
0.72
-0.78
-0.04 [-0.14, 0.06]
Purpose in Life
.77
4.59
0.86
.77
4.48
0.83
-2.60
**
-0.13 [-0.23, -0.03]
Self-Acceptance
.88
4.17
1.06
.88
3.92
1.07
-4.61
***
-0.23 [-0.33, -0.13]
* p < .05, ** p < .01, *** p < .001
COVID-19 PANDEMIC AND WELL-BEING
21
Table S5
Differences in PANAS Mood Variables in Pre-COVID and Overall COVID Samples
Emotion
Pre-COVID
(n = 547)
%
Overall
COVID
(n = 1470)
%
Difference
%
Positive Affect
Excited
55
29
-26***
Interested
66
43
-23***
Enthusiastic
51
32
-19***
Active
44
31
-13***
Determined
59
47
-11***
Proud
42
31
-11***
Attentive
48
38
-10***
Strong
40
31
-9***
Inspired
42
33
-9***
Alert
41
38
-4
Negative Affect
Ashamed
6
12
5***
Guilty
11
18
6***
Hostile
5
12
7***
Scared
10
22
12***
Depressed
16
29
13***
Jittery
14
27
14***
Nervous
27
41
14***
Afraid
10
24
14***
Irritable
22
37
15***
Upset
18
38
19***
Note. Percentages are the percentages of people reporting that they have experienced the emotion
quite a bit or extremely.
* p < .05, ** p < .01, *** p < .001
COVID-19 PANDEMIC AND WELL-BEING
22
Table S6
Correlations between Big Five Personality and Well-Being in Pre-COVID and Overall COVID
Samples
SWL
PA
NA
PR
AU
EM
PG
PL
SA
Pre-COVID
Neuroticism
-.56
-.54
.70
-.48
-.43
-.72
-.48
-.45
-.72
Extraversion
.33
.44
-.28
.51
.34
.40
.42
.29
.43
Openness
.04
.25
-.05
.17
.31
.09
.42
.21
.18
Agreeableness
.22
.22
-.27
.43
.02
.24
.30
.25
.26
Conscientiousness
.28
.38
-.30
.28
.30
.49
.40
.58
.41
Overall COVID
Neuroticism
-.55
-.45
.65
-.46
-.38
-.68
-.41
-.42
-.71
Extraversion
.31
.30
-.15
.43
.32
.34
.38
.27
.40
Openness
.01
.18
.02
.10
.28
-.01
.36
.10
.07
Agreeableness
.23
.10
-.22
.37
-.06
.25
.23
.17
.22
Conscientiousness
.31
.37
-.20
.22
.19
.48
.28
.50
.40
Difference
Neuroticism
.01
.09*
-.05
.01
.04
.04
.07
.03
.01
Extraversion
-.01
-.14**
.13**
-.08*
-.02
-.06
-.04
-.02
-.03
Openness
-.04
-.06
.07
-.07
-.03
-.10*
-.06
-.11*
-.11*
Agreeableness
.01
-.13**
.05
-.05
-.08
.01
-.07
-.07
-.04
Conscientiousness
.03
-.01
.10*
-.07
-.11*
-.01
-.12**
-.08*
-.01
Note. Difference is COVID correlation minus Pre-COVID correlation. Absolute Pre-COVID
sample correlations greater than or equal to .09, .12, and .15 are significant at .05, .01, and .001
respectively. Absolute COVID sample correlations greater than or equal to .06, .07, and .09 are
significant at .05, .01, and .001 respectively. Significance of differences between correlations are
as follows: * p < .05, ** p <.01, ** p < .001.
Table S7
Regression Models Predicting Well-Being from Demographics, Personality, the COVID-19
Pandemic, and Personality by COVID Interactions (Overall COVID Sample)
Predictor
SWL
PA
NA
PR
AU
EM
PG
PL
SA
Intercept
-0.07
0.35***
-0.41***
-0.01
0.18***
0.10*
-0.14**
-0.07
0.01
Female
0.28***
-0.07
0.05
0.21***
-0.11*
0.11**
0.12**
0.15**
0.20***
Age > 25
-0.12**
-0.01
-0.20***
0.07
0.23***
0.09**
0.27***
0.17***
-0.02
Neuroticism
-0.51***
-0.32***
0.58***
-0.22***
-0.28***
-0.57***
-0.25***
-0.21***
-0.60***
Extraversion
0.08*
0.23***
0.01
0.34***
0.17***
0.13***
0.24***
0.11**
0.13***
Openness
-0.04
0.13***
0.06
0.05
0.19***
-0.05
0.29***
0.10**
0.06*
Agreeableness
0.04
0.05
-0.08*
0.28***
-0.14***
0.00
0.13***
0.06
0.02
Conscientiousness
0.08*
0.20***
-0.03
0.06
0.16***
0.26***
0.21***
0.45***
0.15***
COVID
-0.16***
-0.40***
0.58***
-0.25***
-0.24***
-0.29***
-0.06
-0.15***
-0.23***
COVID by Neuroticism
0.04
0.00
0.06
-0.05
-0.03
0.03
0.03
-0.02
-0.01
COVID by Extraversion
0.06
-0.10*
0.05
-0.02
0.01
0.02
0.00
0.04
0.05
COVID by Openness
0.01
0.02
-0.01
-0.03
0.04
-0.01
0.00
-0.03
-0.04
COVID by Agreeableness
0.01
-0.11**
0.04
-0.03
-0.05
0.02
-0.02
-0.06
-0.04
COVID by Conscientiousness
0.04
0.07
0.05
-0.04
-0.05
0.01
-0.06
-0.06
0.02
Adjusted R2
0.36
0.35
0.48
0.40
0.30
0.57
0.40
0.38
0.58
Note. Female is coded 1 = Female, 0 = Male or Other; Age is coded 1 = 26 or older, 0 = 18 to 25;
COVID is coded 0 = Pre-COVID, 1 = COVID. Well-being variables are z-score standardized.
COVID-19 PANDEMIC AND WELL-BEING
23
Personality variables are z-score standardized within COVID groups. Interactions are the product
of the 0–1 COVID variable and the standardized personality variables.
* p < .05, ** p < .01, *** p < .001
Analyses Examining Personality Differences
Table S8 shows the descriptive statistics for the personality variables in the
Pre-COVID and COVID sample using unstandardized variables. In general, the
standard deviations in the Pre-COVID sample were slightly larger. This was caused by
the use of slightly different response scales in the two surveys. In particular, the
response scale in the Pre-COVID sample encouraged slightly more responding to 1
and 5 than 2 and 4 compared to the response scale used for the COVID sample. This
was the principal reason why we decided to z-score standardize the personality
measures. In general, the differences were small, although the COVID sample was
slightly higher on neuroticism.
Table S8
Means and Standard Deviations for Big Five Personality Pre-COVID and
COVID
Pre-COVID
(n = 547)
COVID
(n = 1132)
M
SD
M
SD
d
Neuroticism
2.75
0.81
2.96
0.72
0.28
Extraversion
3.26
0.71
3.23
0.63
-0.05
Openness
3.76
0.65
3.84
0.53
0.14
Agreeableness
3.76
0.58
3.68
0.53
-0.15
Conscientiousness
3.54
0.63
3.46
0.54
-0.15
To further investigate whether personality in the COVID sample (2020) was
different in some way, we also compared Big Five personality to data collected in
2018 and 2019. The 2018 and 2019 samples were recruited from the same university
undergraduate psychology unit in the same way as the 2017 Pre-COVID sample and
the 2020 COVID sample. However, they contained no well-being measurement. Big
Five personality was also measured using a slightly different subset of 50 items in
2018 and 2019. The 2020 data collection included the superset of items that enabled
comparison with both 2017 and 2018/2019. In all three years, the same response scale
was used. Table S9 mostly shows that scores are very similar, although openness is
slightly higher. Importantly, this suggest that the COVID-19 pandemic was not having
a major effect on responses to the personality test.
COVID-19 PANDEMIC AND WELL-BEING
24
Table S9
Means and Standard Deviations for Big Five Personality
2018
(n = 701)
2019
(n = 1412)
COVID
(n = 1132)
M
SD
M
SD
M
SD
d 2019
d 2018
Neuroticism
2.92
0.75
2.91
0.73
2.96
0.72
0.08
0.06
Extraversion
3.27
0.69
3.26
0.68
3.31
0.70
0.07
0.06
Openness
3.70
0.57
3.78
0.52
3.83
0.52
0.11
0.26
Agreeableness
3.74
0.51
3.74
0.49
3.78
0.49
0.08
0.09
Conscientiousness
3.40
0.61
3.46
0.60
3.43
0.59
-0.04
0.05
Note. d 2019 is the Cohen's d effect size of the COVID sample compared to
the 2019 sample using the 2019 sample standard deviation. d 2018 is the Cohen's d
effect size of the COVID sample compared to the 2018 sample using the 2019 sample
standard deviation.
Effect of Standardizing Personality within Groups
To further examine the decision to standardize personality within groups, we
report the analyses where personality was not standardized within groups (See Table
S10). The effect of standardization was negligible for main effects of personality,
main effects of demographics, and personality by covid interactions (i.e., max absolute
change in coefficient was 0.02). The intercept was changed in a few cases (e.g.,
satisfaction with life, negative affect and environmental mastery, and self-acceptance)
where they were around .10 lower (or higher in the case of negative affect). Similarly,
the COVID coefficient was reduced in magnitude (see comparison in Table S11). This
is all presumably driven by the fact that neuroticism was slightly higher in the COVID
sample and neuroticism correlates highly with well-being and negative affect in
particular. When controlling for personality, the COVID effects are still quite
substantial for positive affect (-0.40) and negative affect (0.40). With regards to the
well-being indicators, positive relations (-0.20) and autonomy (-0.23) stand out
relative to the remaining well-being scales.
COVID-19 PANDEMIC AND WELL-BEING
25
Table S10
Regression Models Predicting Well-Being from Demographics, Personality, the COVID-19
Pandemic, and Personality by COVID Interactions where Personality was not Standardized
within Groups
Predictor
SWL
PA
NA
PR
AU
EM
PG
PL
SA
Intercept
-0.12
0.37
-0.34
-0.02
0.19
0.02
-0.08
-0.07
-0.04
Female
0.25
-0.10
0.10
0.18
-0.13
0.09
0.10
0.14
0.17
Age > 25
-0.15
-0.07
-0.17
0.07
0.25
0.06
0.26
0.19
-0.04
Neuroticism
-0.50
-0.32
0.57
-0.21
-0.28
-0.55
-0.24
-0.20
-0.58
Extraversion
0.08
0.23
0.01
0.35
0.17
0.13
0.23
0.11
0.13
Openness
-0.04
0.13
0.06
0.05
0.18
-0.05
0.28
0.10
0.06
Agreeableness
0.04
0.05
-0.09
0.29
-0.13
0.01
0.13
0.06
0.03
Conscientiousness
0.09
0.20
-0.05
0.07
0.15
0.26
0.20
0.43
0.15
COVID
-0.06
-0.40
0.45
-0.20
-0.23
-0.15
-0.11
-0.13
-0.12
COVID by Neuroticism
0.01
-0.01
0.08
-0.06
-0.03
0.03
0.02
-0.01
-0.03
COVID by Extraversion
0.08
-0.09
0.04
-0.01
0.01
0.04
0.01
0.04
0.06
COVID by Openness
0.00
0.02
-0.01
-0.03
0.05
-0.01
0.03
0.00
-0.05
COVID by Agreeableness
-0.01
-0.12
0.03
-0.04
-0.03
0.01
-0.03
-0.05
-0.04
COVID by Conscientiousness
0.04
0.07
0.08
-0.04
-0.05
0.03
-0.04
-0.03
0.02
Adjusted R2
0.37
0.37
0.49
0.40
0.30
0.58
0.41
0.39
0.58
Note. Female is coded 1 = Female, 0 = Male or Other; Age is coded 1 = 26 or older, 0 = 18 to 25;
COVID is coded 0 = Pre-COVID (n = 547), 1 = COVID (n = 1132). Well-being variables are z-
score standardized. Personality variables are z-score standardized within COVID groups.
Interactions are the product of the 0–1 COVID variable and the standardized personality
variables.
Table S11
Changes in the COVID Regression Coefficient based on whether Personality
was or was not Standardized within Groups
Outcome
Personality
Standardized
within Groups
COVID
Coefficient
Personality
Not
Standardized
with Groups
COVID
Coefficient
Difference
% Reduction
Life Satisfaction
-0.19
-0.06
0.13
0.68
Positive Affect
-0.45
-0.40
0.05
0.11
Negative Affect
0.60
0.45
0.15
0.25
Positive Relations
-0.25
-0.20
0.05
0.20
Autonomy
-0.25
-0.23
0.02
0.08
Environmental Mastery
-0.31
-0.15
0.16
0.52
Personal Growth
-0.09
-0.11
-0.02
-0.22
Purpose in Life
-0.17
-0.13
0.04
0.24
Self-Acceptance
-0.25
-0.12
0.13
0.52
Mean
-0.15
-0.11
0.08
0.26
Discussion of Group Differences
It is worth considering whether other factors might explain the observed
COVID-19 PANDEMIC AND WELL-BEING
26
differences in reported well-being besides the COVID pandemic, especially
considering that the Pre-COVID sample was obtained in mid to late 2017. As is
described below, Australian society has been very stable for many years prior to the
COVID-19 pandemic. There have been no major economic or political changes, and
the best available data on life satisfaction supports this claim.
Economy: Prior to the COVID-19 pandemic, the last time that Australia had
experienced an economic recession was 30 years earlier (1990-1991).
Government: There have been no changes to either state or federal
government in the time between pre- and post-COVID assessments. The state
government at the time of the pandemic had been in office since 2014. The federal
government had been in office since 2013.
Other Estimates of Well-being: Participants from the largest nationally
representative panel survey (HILDA) in Australia illustrates how mean levels of life
satisfaction has been both high and very stable over the 18 waves that have so far been
reported (2001 to 2018). In each wave, participants rated their life satisfaction on a
single life satisfaction item on a scale from 0 to 10. The standard deviation of life
satisfaction in these samples is approximately 1.5. Since 2010, mean life satisfaction
has ranged from 7.87 and 7.93. I.e., the Cohen's d movement from a mid-point of 7.9
has been no more than plus or minus 0.02. While equivalent data is not yet available
for 2019 and 2020, the data does illustrate how stable well-being has been in
Australian society prior to the onset of the COVID-19 pandemic. See Figure S1 and
Figure S2.
Figure S1
Mean Life Satisfaction for All Persons and By Sex based on the Australian Household Income
and Labour Dynamics Survey
Note. The above figure is from (Wilkins, Botha, & Vera-Toscano, 2020) and
licenced Creative Commons CC-BY Attribution 3.0 Australia. Data is based on
COVID-19 PANDEMIC AND WELL-BEING
27
between 12,408 and 13,834 interviews per wave.
Figure S2
Mean Life Satisfaction by Age Group based on the Australian Household Income and Labour
Dynamics Survey
Note. The above figure is from (Wilkins et al., 2020) and licenced Creative
Commons CC-BY Attribution 3.0 Australia.
It also interesting to consider whether there is other corroborating evidence
that the COVID-19 pandemic is impacting well-being in Australia. In general, this
evidence is only just beginning to emerge. For instance, Terry, Parsons-Smith, and
Terry (2020) compared mood profiles to pre-COVID norms and obtained Cohen's d
values of .28 for tension, 0.66 for depression, 0.58 for anger, 0.54 for vigor, 0.62 for
fatigue, and 0.70 for confusion.
Some other external evidence also points to the idea that the COVID pandemic
and the associated lockdown has been particularly unpleasant for young people. For
instance, a report released in November 2020 by the Victorian Agency for Health
Information found an increase in emergency presentations for self-harm and suicidal
ideation in those aged under-18 [compared to 2019] and calls to the counselling line
Beyond Blue were elevated when new restrictions were announced (Houston & Butt,
2020).
Houston, C., & Butt, C. (2020). Experts warn of deepening mental health crisis as youth bear brunt of COVID-19 lockdown. The
Age. Retrieved from https://www.theage.com.au/national/victoria/experts-warn-of-deepening-mental-health-crisis-as-
youth-bear-brunt-of-covid-19-lockdown-20201113-p56e9d.html
Terry, P. C., Parsons-Smith, R. L., & Terry, V. R. (2020). Mood Responses Associated with COVID–19 Restrictions. Frontiers
in Psychology, 11, 3090.
COVID-19 PANDEMIC AND WELL-BEING
28
Wilkins, R., Botha, F., & Vera-Toscano, E. (2020). The Household, Income and Labour Dynamics in Australia Survey: Selected
Findings from Waves 1 to 18. Retrieved from
