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COVID-19 and Psychological Outcomes 1
Running Head: IMPACT OF COVID-19 ON PSYCHOLOGICAL OUTCOMES
Psychological Outcomes Associated with Stay-at-Home Orders and the Perceived Impact of
COVID-19 on Daily Life
Matthew T. Tull*,1, Keith A. Edmonds1, Kayla M. Scamaldo1, Julia R. Richmond1, Jason P.
Rose1, and Kim L. Gratz1
1Department of Psychology, University of Toledo, Toledo, OH, USA
MANUSCRIPT IN PRESS AT PSYCHIATRY RESEARCH
Tull, M. T., Edmonds, K. A., Scamaldo, K. M., Richmond, J. R., Rose, J. P., & Gratz, K. L.
(2020). Psychological outcomes associated with stay-at-home orders and the perceived impact of
COVID-19 on daily life. Psychiatry Research, 113098.
*Correspondence concerning this article should be addressed to Matthew T. Tull, Ph.D.,
Department of Psychology, Mail Stop 948, University of Toledo, 2801 West Bancroft Street,
Toledo, OH 43606, USA; Phone: 419-530-4302; E-mail: email@example.com.
COVID-19 and Psychological Outcomes 2
The COVID-19 pandemic has resulted in the widespread implementation of extraordinary
physical distancing interventions (e.g., stay-at-home orders) to slow the spread of the virus.
Although vital, these interventions may be socially and economically disruptive, contributing to
adverse psychological outcomes. This study examined relations of both stay-at-home orders and
the perceived impact of COVID-19 on daily life to psychological outcomes (depression, health
anxiety, financial worry, social support, and loneliness) in a nationwide U.S. community adult
sample (N = 500; 47% women, mean age = 40). Participants completed questionnaires assessing
psychological outcomes, stay-at-home order status, and COVID-19’s impact on their daily life.
Being under a stay-at-home order was associated with greater health anxiety, financial worry,
and loneliness. Moreover, the perceived impact of COVID-19 on daily life was positively
associated with health anxiety, financial worry, and social support, but negatively associated
with loneliness. Findings highlight the importance of social connection to mitigate negative
psychological consequences of the COVID-19 pandemic.
Keywords: anxiety; coronavirus; COVID-19; loneliness, social support
COVID-19 and Psychological Outcomes 3
The World Health Organization (WHO) announced on January 30, 2020 that the severe
acute respiratory syndrome coronavirus (COVID-19) was a Public Health Emergency of
International Concern. Currently, COVID-19 has infected over 2 million people and resulted in
over 150,000 deaths across 210 countries (WHO, 2020). Currently, approximately 900,000
individuals in the U.S. have been infected with COVID-19 and over 50,000 have died due to the
virus (Centers for Disease Control and Prevention [CDC], 2020). Moreover, due to COVID-19’s
long incubation period, ease of transmission, high mortality rate (relative to the seasonal flu), and
lack of pharmacological interventions (Linton et al., 2020; Shereen et al., 2020), governments
have had to implement extraordinary physical distancing interventions to slow the spread of the
virus. Within the U.S., stay-at-home orders have been implemented in most states and the
District of Columbia (Mervosh et al., 2020).
From a public health perspective, there is strong justification for such interventions –
physically separating people is an effective strategy for preventing the spread of infectious
diseases (Ahmed et al., 2018; Jackson et al., 2014; Qualls et al., 2017), including COVID-19
(Flaxman et al., 2020; Thakkar et al., 2020). However, although stay-at-home orders are vital for
protecting physical health (CDC, 2020), such interventions can also be socially and economically
disruptive (Chen et al., 2011; Reger et al., 2020; Thunström et al., 2020). Indeed, recent reviews
have suggested that the negative social and economic consequences of current stay-at-home
orders and the COVID-19 pandemic itself (e.g., economic downturn, frequent exposure to
distressing media coverage) could contribute to adverse psychological outcomes, including
increased loneliness, reduced social support, depression, anxiety, and financial concerns
(Asmundson & Taylor, 2020; Courtet et al., 2020; Reger et al., 2020). Given the recent and
COVID-19 and Psychological Outcomes 4
sudden emergence of COVID-19, research in this area is understandably limited. However,
several studies from China during the initial COVID-19 outbreak revealed associations of
COVID-19 with increased anxiety, depression, and stress (Cao et al., 2020; Wang et al., 2020;
Zhang et al., 2020). Further, the overall impact of COVID-19 on the economy, daily life, and
social activity, greater social isolation, and the inability to work were associated with greater
psychological difficulties (Cao et al., 2020; Zhang et al., 2020). Although research on the
psychological outcomes associated with COVID-19 is limited, available findings are consistent
with those obtained in past studies on the psychological consequences of other pandemics. For
example, Hawryluck et al. (2004) found that quarantine during the 2003 SARS outbreak was
associated with high rates of depression (31.2%) and anxiety (28.9%). Likewise, elevated levels
of anxiety were observed during the 2009 H1N1 pandemic (Wheaton et al., 2012).
To extend this research to the psychological impact of COVID-19 in the U.S., the present
study examined associations of stay-at-home orders and the perceived impact of COVID-19 on
daily life to relevant psychological outcomes (i.e., depression, health anxiety, financial worry,
perceived social support, and loneliness). We predicted that both stay-at-home orders and the
perceived impact of COVID-19 on daily life would evidence significant positive associations
with all psychological difficulties and a significant negative association with social support when
controlling for relevant demographic variables. We also predicted a significant interaction of
stay-at-home orders and perceived impact of COVID-19 on the outcomes of interest, such that
the relation of stay-at-home order status to negative psychological outcomes would be stronger
for participants who perceived COVID-19 as having a greater impact on their daily life.
COVID-19 and Psychological Outcomes 5
Participants included a nationwide community sample of 500 adults from 45 states in the
U.S. who completed online measures through an internet-based platform (Amazon’s Mechanical
Turk; MTurk) from March 27, 2020, through April 5, 2020. The study was posted to MTurk via
CloudResearch (cloudresearch.com), an online crowdsourcing platform linked to MTurk that
provides additional data collection features (e.g., creating selection criteria). MTurk is an online
labor market that provides “workers” with the opportunity to complete different tasks in
exchange for monetary compensation, such as completing questionnaires for research. As such,
MTurk provided the opportunity to collect a large nationwide sample in a relatively short amount
of time, facilitating timely examination of the initial impact of the COVID-19 pandemic in the
U.S. Data provided by MTurk-recruited participants have been found to be as reliable as data
collected through more traditional methods (Buhrmester et al., 2011). MTurk samples also have
the advantage of being more diverse than other internet-recruited or college student samples
(Buhrmester et al., 2011). For the present study, inclusion criteria included (1) U.S. resident, (2)
at least a 95% approval rating as an MTurk worker, (3) completion of at least 5,000 previous
MTurk tasks (referred to as Human Intelligence Tasks [HITS]), and (4) valid responses on
questionnaires (i.e., assessed by accurate completion of multiple attention check items).
Participants (47% women; 51.8% men; 0.2% transgender; 0.6% non-binary; 0.4% other)
ranged in age from 20 to 74 years (Mage = 40.0 ± 11.6). All states in the U.S. were represented,
with the exception of Delaware, New Hampshire, North Dakota, Vermont, and West Virginia.
The states with the greatest representation in the sample were Florida (11.2%), California
(8.6%), Pennsylvania (6%), Texas (5.6%), New York (5.4%), North Carolina (4.6%), Michigan
COVID-19 and Psychological Outcomes 6
(4.4%), Ohio (4%), Illinois (3.4%), and Washington (3%). Most participants identified as White
(85%), followed by Black/African-American (8.4%), Asian/Asian-American (6.6%), Latinx
(1.9%), and Native American (1.6%). Regarding educational attainment, 11.8% had completed
high school or received a GED, 35.6% had attended some college or technical school, 43% had
graduated from college, and 9.6% had advanced graduate/professional degrees. Most participants
were employed full-time (69.2%), followed by employed part-time (16.2%) and unemployed
(14.6%). Annual household income varied, with 30.6% of participants reporting an income of <
$35,000, 33.6% reporting an income of $35,000 to $64,999, and 35.8% reporting an income of >
$65,000. Regarding household composition, 58.6% of participants reported living alone and the
remaining 41.4% reported living with at least one other person (ranging from 2-8 other
household members; mean = 3.2 ± 1.1). In addition, 44.1% of participants reported having at
least one child in their household (ranging from 1-3 children in the household; mean = 0.72 ±
0.94). Few participants reported having sought out testing for COVID-19 (1%) or having been
infected with COVID-19 (0.8%).
All procedures received approval from the university’s Institutional Review Board. To
ensure the study was not being completed by a bot (i.e., an automated computer program used to
complete simple tasks), participants first responded to a Completely Automatic Public Turing
test to Tell Computers and Humans Apart (CAPTCHA) prior to providing informed consent. On
the consent form, participants were also informed that “…we have put in place a number of
safeguards to ensure that participants provide valid and accurate data for this study. If we have
strong reason to believe your data are invalid, your responses will not be approved or paid and
your data will be discarded.” Data were collected in blocks of nine participants at a time and all
COVID-19 and Psychological Outcomes 7
data, including attention check items and geolocations, were examined by researchers before
compensation was provided. Attention check items included three explicit requests embedded
within the questionnaires (e.g., “If you are paying attention, choose ‘2’ for this question”), two
multiple-choice questions (e.g., “How many words are in this sentence?”), a math problem (e.g.,
“What is 4 plus 2”), and a free-response item (e.g., “Please briefly describe in a few sentences
what you did in this study”). Participants who failed one or more attention check items were
removed from the study (n = 53 of 553 completers). Workers who completed the study and
whose data were considered valid (based on attention check items and geolocations; N = 500)
were compensated $3.00 for their participation.
A demographic questionnaire assessed age, sex, annual income, household composition,
and racial/ethnic background.
COVID-19 related experiences and stressors were assessed via a 20-item measure
developed for this study. Participants were asked about a variety of relevant experiences
associated with the COVID-19 pandemic. Of interest to the present study were two questions
from this measure assessing: (1) stay-at-home order status (i.e., “Do you live in a state that has
instituted a stay-at-home order?” [0 = no; 1 = yes]); and (2) perceived impact of COVID-19 (i.e.,
“To what extent has the situation associated with COVID-19 affected the way you live your
life?”). Participants responded to the latter question using a 5-point Likert-type scale ranging
from 1 (no impact at all) to 5 (impacted my life a great deal).
Current depression symptoms were assessed using the depression subscale of the 21-item
version of the Depression Anxiety Stress Scales (DASS-21; Lovibond & Lovibond, 1995).
Participants are presented with a series of statements reflecting the experience of symptoms of
COVID-19 and Psychological Outcomes 8
depression (e.g., “I found it difficult to work up the initiative to do things,” “I felt that I had
nothing to look forward to”). Participants are instructed to rate each item on a 4-point Likert-type
scale indicating the extent to which the item applied to them in the past week (0 = “did not apply
to me at all”, 1 = “applied to me some of the time”, 2 = “applied to me a good part of the time”, 3
= “applied to me most of the time”). All items from the depression subscale were summed to
create one composite score (ranging from 0 – 21), with higher scores indicating greater
depression symptoms. This measure has demonstrated good reliability and validity (Lovibond &
Lovibond, 1995). Internal consistency of the depression subscale was acceptable ( = .90).
The Short Health Anxiety Inventory (SHAI; Abramowitz et al., 2007; Salkovskis et al.,
2002) is an 18-item self-report measure assessing health anxiety symptoms. For each item,
participants choose one response from a group of four statements of increasing severity (e.g., 1 =
“I do not worry about my health”, 2 = “I occasionally worry about my health”, 3 = “I spend
much of my time worrying about my health”, 4 = “I spend most of my time worrying about my
health”). The SHAI has demonstrated good reliability, internal consistency, and construct
validity (Salkovskis et al., 2002). All items were summed to create one composite score (ranging
from 18 – 72), with higher scores indicated greater health anxiety. Internal consistency in the
present sample was acceptable ( = .93).
Financial worry was assessed using three items from the Family Economic Strain Scale
(FESS; Hilton & Devall, 1997), which assesses concerns about the availability of finances in the
future (“I am afraid that my income will decrease;” “I worry about having money to celebrate
holidays and other special occasions;” and “I worry about financial matters”). Participants rate
items on a 5-point Likert-type scale ranging from 1 (never) to 5 (always). Previous research
using the full scale has provided evidence for its reliability and construct validity (Hilton &
COVID-19 and Psychological Outcomes 9
Devall, 1997). All items were summed to create one composite score (ranging from 3 – 15), with
higher scores indicting greater financial worry. Internal consistency of the items used in this
study were acceptance (α = 86).
The UCLA Loneliness Scale – Version 3 (ULS-3; Russell, 1996) is a 20-item self-report
measure of perceptions of loneliness and social isolation. Participants rate items (e.g., “No one
really knows me well;” “I lack companionship;” “There are people I feel close to [reverse
scored]”) based on how often they apply to themselves on a 4-point Likert-type scale ranging
from 1 (never) to 4 (often). Higher scores are indicative of greater loneliness. The ULS-3 has
demonstrated adequate test-retest reliability and good construct validity (Russell, 1996). All
items were summed to create one composite score (ranging from 20 – 80), with higher scores
indicating greater loneliness. Internal consistency in the present sample was acceptable (α = .94).
Perceived availability of social support was assessed using the Multidimensional Scale of
Perceived Social Support (MSPSS; Zimet et al., 1988). The MSPSS is a 12-item measure
designed to assess perceived availability of social support from three primary sources: family
(e.g., “ I can talk about my problems with my family”), friends (e.g., “I can count on my friends
when things go wrong”), and significant others/special persons (e.g., “There is a special person
who is around when I am in need”). Participants rate items on a 7-point Likert-type scale ranging
from 1 (very strongly disagree) to 7 (very strongly agree). The MSPSS has demonstrated good
test-retest reliability and discriminant and construct validity (Zimet et al., 1988). All items were
summed to create one composite score (ranging from 12 – 84), with higher scores indicating
greater social support. Internal consistency in the present sample was acceptable (α = 96).
COVID-19 and Psychological Outcomes 10
2.4. Analysis Plan
Descriptive statistics for the primary variables of interest (stay-at-home order status,
perceived impact of COVID-19, depression symptom severity, health anxiety, financial worry,
loneliness, and social support) were computed, as were point-biserial and Pearson product-
moment correlations to examine zero-order associations among variables. Next, a series of
hierarchical linear regression analyses were conducted to evaluate hypotheses. Demographic
variables (i.e., age, sex, racial/ethnic background [racial/ethnic minority vs. non-minority],
income level [< $50,000/year vs. < $50,000/year], and whether participants lived alone or with
others) relevant to the outcome variables were entered in the first step of each model. Stay-at-
home order status and perceived impact of COVID-19 (centered) were entered in the second step
of each model, followed by the product of these variables in the third step. Depression symptom
severity, health anxiety, financial worry, loneliness, and social support served as dependent
variables. Given that five regression models were conducted, p was set at .01. Unstandardized
betas are presented to allow evaluation of effect size. A power analysis demonstrated that a
sample size of 500 offered sufficient power (≥ .80) to detect a medium effect with an alpha level
of p = .01 (Faul et al., 2009).
3.1. Preliminary Analyses
At the time of data collection, 82.4% (n = 412) of participants were living in states with
active stay-at-home orders. Participants living in states with stay-at-home orders had been under
these orders for an average of 5.71 days (SD = 4.54). Descriptive data for and correlations among
the primary variables of interest are presented in Table 1. Of note, one participant did not
COVID-19 and Psychological Outcomes 11
complete the perceived impact of COVID-19 item and another did not complete the financial
3.2. Primary Analyses
Outcomes for all regression models evaluating hypotheses are presented in Table 2.
The overall model was significant, accounting for 7% of the variance in depression
symptom severity, F (8, 490) = 4.53, p < .001, f = .24. However, neither stay-at-home order
status nor perceived impact of COVID-19 accounted for a significant amount of unique variance
in depression symptom severity above and beyond the covariates, ΔR2 = .01, F (2, 491) = 2.16, p
= .116, f = .07, although both age and income level were uniquely negatively associated with
depression symptom severity in this step of the model. The addition of the interaction between
stay-at-home order status and perceived impact of COVID-19 did not significantly improve the
model, ΔR2 = .00, F (1, 490) = .02, p = .879, f = .00.
3.2.2. Health Anxiety
The overall model was significant, accounting for 8% of the variance in health anxiety, F
(8, 490) = 5.24, p < .001, f = .26. The addition of stay-at-home order status and perceived impact
of COVID-19 in the second step of the model accounted for significant variance in health
anxiety above and beyond covariates, ΔR2 = .05, F (2, 491) = 12.02, p < .001, f = .21, with both
stay-at-home order status and perceived impact of COVID-19 demonstrating significant unique
positive associations with health anxiety. Likewise, female sex was uniquely positively
associated with health anxiety and income level was uniquely negatively associated with health
anxiety in this step of the model. The addition of the interaction between stay-at-home order
status and perceived impact of COVID-19 did not significantly improve the model, ΔR2 = .00, F
COVID-19 and Psychological Outcomes 12
(1, 490) = 1.02, p = .312, f = .01.
3.2.3. Financial Worry
The overall model was significant, accounting for 14% of the variance in financial worry,
F (8, 489) = 9.60, p < .001, f = .37. Stay-at-home order status and perceived impact of COVID-
19 accounted for significant unique variance in financial worry above and beyond covariates,
ΔR2 = .04, F (2, 490) = 10.21, p < .001, f = .19, with both stay-at-home order status and
perceived impact of COVID-19 emerging as significant unique predictors. In addition, income
level was uniquely negatively associated with financial worry in this step of the model. The
addition of the interaction between stay-at-home order status and perceived impact of COVID-19
did not significantly improve the model, ΔR2 = .00, F (1, 489) = 0.27, p = .605, f = .00.
The overall model was significant, accounting for 10% of the variance in loneliness, F (8,
490) = 7.08, p < .001, f = .31. The addition of stay-at-home order status and perceived impact of
COVID-19 in the second step of the model accounted for significant variance in loneliness above
and beyond covariates, ΔR2 = .04, F (2, 491) = 9.64, p < .001, f = .19. However, whereas stay-at-
home order status was significantly positively associated with loneliness, the perceived impact of
COVID-19 was significantly negatively associated with loneliness. In addition, income level was
uniquely negatively associated with loneliness in this step of the model. The addition of the
interaction between stay-at-home order status and perceived impact of COVID-19 did not
significantly improve the model, ΔR2 = .00, F (1, 490) = 0.08, p = .783, f = .00.
3.2.5. Perceived Social Support
The overall model was significant, accounting for 12% of the variance in perceived social
support, F (8, 490) = 8.13, p < .001, f = .34. Stay-at-home order status and perceived impact of
COVID-19 and Psychological Outcomes 13
COVID-19 accounted for significant variance in perceived social support above and beyond the
covariates, ΔR2 = .03, F (2, 491) = 9.27, p < .001, f = .18. However, only perceived impact of
COVID-19 was uniquely associated with perceived social support, and this association was
positive (vs. negative as hypothesized). In addition, income level was uniquely positively
associated with perceived social support in this step of the model. The addition of the interaction
between stay-at-home order status and perceived impact of COVID-19 did not significantly
improve the model, ΔR2 = .00, F (1, 490) = 0.07, p = .792, f = .00.
3.3. Exploratory Analyses
Given evidence of robust age and sex differences in the outcomes of interest (Altemus,
2006; Borys & Perlman, 1985; Christensen et al., 1999; Luhman & Hawkley, 2016), as well as
evidence that the impact of COVID-19 may vary as a function of age and sex (Dowd et al., 2020;
Wenham et al., 2020), a series of hierarchical linear regression analyses were conducted to
explore whether age or sex moderated associations between (a) stay-at-home orders and
psychological outcomes (2-way interaction); (b) the perceived impact of COVID-19 and
psychological outcomes (2-way interaction); and (c) the interaction of stay-at-home order status
and the perceived impact of COVID-19 and psychological outcomes (3-way interaction). None
of the examined interactions significantly improved the models. Specifically, none of the 2-way
or 3-way interactions involving age accounted for significant variance in any of the
psychological outcomes (ΔR2s = .00 to .01, Fs < 1.80, ps > .148, fs < .07). Likewise, none of the
interactions involving sex accounted for significant unique variance in any psychological
outcomes (ΔR2s = .00 to .005, Fs < .95, ps > .332, fs = .00).
Finally, given that the presence of children in the household could exacerbate some of the
negative psychological outcomes associated with COVID-19 and related stay-at-home orders
COVID-19 and Psychological Outcomes 14
(e.g., health anxiety, financial worries), an exploratory hierarchical linear regression was
conducted to examine the main and interactive effects of having children in the home on
psychological outcomes. Given the overlap between variables representing whether participants
lived alone and whether participants had children in their home (χ2 = 78.91, p < .001), the former
variable was removed from this model. Results revealed no significant unique associations
between having children in the home and any of the psychological outcomes of interest (bs = -
.29 to .29, ps > .023). Likewise, none of the interactions of having children in the home with
stay-at-home order status or the perceived impact of COVID-19 were significant in any of the
models (ΔR2s = .00 to .008, Fs < 1.42, ps > .237, fs < .06). Notably, the same pattern of non-
significant associations for all main and interactive effects involving having children in the home
was found when using a continuous variable reflecting the number of children in the household
(vs. the dichotomous variable reflecting the presence or absence of children in the home).
The goal of the present study was to examine associations of stay-at-home orders and the
perceived impact of COVID-19 on daily life to relevant psychological outcomes (i.e., depression,
health anxiety, financial worry, perceived social support, and loneliness). Study hypotheses were
partially supported. Although the interaction of stay-at-home order status and the perceived
impact of COVID-19 on daily life did not account for significant variance in any of the
outcomes, each of these factors was independently associated with several psychological
outcomes. As predicted, being under a stay-at-home order was associated with greater health
anxiety, financial worry, and loneliness, consistent with the theorized unintended negative
consequences of such orders (Reger et al., 2020) and past research on the psychological
consequences of quarantine during a pandemic (Brooks et al., 2020). Moreover, consistent with
COVID-19 and Psychological Outcomes 15
research on the psychological consequences of COVID-19 in China (Cao et al., 2020; Wang et
al., 2020; Zhang et al., 2020) and past research on the psychological consequences of other
pandemics (Tausczik et al., 2012; Wheaton et al., 2012), the perceived impact of COVID-19 on
daily life was associated with greater health anxiety and financial worry. Contrary to predictions,
the perceived impact of COVID-19 was negatively associated with loneliness and positively
associated with social support.
Stay-at-home orders or experiencing changes to daily life habits due to COVID-19 may
increase perceptions of risk for harm to one’s physical, social, and financial health, resulting in
increased health anxiety and financial worry. Moreover, stay-at-home orders may result in
sudden changes to one’s social life. Reduced contact with once common social connections may
initially bring about increased feelings of loneliness and social isolation. However, findings also
suggest that one potential positive outcome of this pandemic may be an increase in social support
seeking or connectedness as individuals try to adjust to changes in daily life. Although being
under a stay-at-home order was associated with increased loneliness, the perception that COVID-
19 had a greater impact on one’s daily life was associated with increased social support and
reduced loneliness. These findings are consistent with suggestions that the wide-spread shared
experience of COVID-19 may increase closeness and social cohesion (Courtet et al., 2020),
similar to what has been observed in past mass tragedies (Calo-Blanco et al., 2017; Hawdon &
Notably, despite evidence that the impact of COVID-19 may vary as a function of age
and sex (Dowd et al., 2020; Wenham et al., 2020), results revealed few associations between age
or sex and the psychological outcomes of interest. Likewise, none of the examined associations
of stay-at-home order status or the perceived impact of COVID-19 on daily life with
COVID-19 and Psychological Outcomes 16
psychological outcomes varied as a function of age or sex. Together, these results suggest that
the associations of stay-at-home orders and the perceived impact of COVID-19 with
psychological outcomes – at least in the early stages of this pandemic and related public health
interventions – do not differ as a function of age or sex. However, whether these associations
will become stronger for individuals of a particular sex or age group as the pandemic persists
remains to be determined. Conversely, income level was uniquely inversely associated with
health anxiety, financial worry, and loneliness, and uniquely positively associated with perceived
social support. As such, these findings suggest that individuals with lower incomes may be
particularly at-risk for the negative psychological outcomes of COVID-19 and related social and
economic consequences. As this pandemic and related social distancing interventions persist
(even if to a lesser degree), widespread interventions focused on promoting mental health and
well-being (including a sense of connection) among less financially secure individuals are also
Study limitations warrant consideration. The use of cross-sectional data precludes
conclusions about the nature or direction of the associations examined. We also do not know the
extent with which these psychological symptoms existed prior to COVID-19 and the
implementation of stay-at-home orders. Likewise, self-report questionnaires may be influenced
by social desirability or recall difficulties that could affect the validity of provided data. Future
studies would benefit from incorporating structured clinical interviews and/or timeline follow-
back procedures to assess psychological symptoms and their temporal relation to physical
distancing or COVID-19-related stressors. Given our recruitment methods and sample (relatively
non-diverse self-selected MTurk workers), results may not generalize to the larger U.S.
population, other countries, or vulnerable populations (e.g., individuals with chronic medical
COVID-19 and Psychological Outcomes 17
conditions; health care workers; hospitalized patients). Replication of findings is needed within
other samples and populations.
In addition, results only speak to the early associations of stay-at-home orders and the
perceived impact of COVID-19 to psychological outcomes, and these variables accounted for
only a modest amount of the variance in the examined outcomes. Longer-term prospective
studies are needed to evaluate if the observed relations increase or decrease in magnitude as the
pandemic continues. Indeed, studies on the trajectory of psychological symptoms over the course
of past pandemics have found that, although initial reactions tend to be characterized by elevated
levels of anxiety and worry, these symptoms tend to decrease over the course of the pandemic
(Jones & Salathé, 2009; Tausczik et al., 2011). Given the relatively high mortality rate associated
with COVID-19, the lack of adequate testing in some countries, and the absence of effective
pharmaceutical interventions for COVID-19, it remains to be seen whether a similar trajectory
will occur with the current pandemic. Finally, it will be important for future research to examine
the relation of these psychological outcomes to future adaptive and maladaptive behaviors. For
example, individuals with elevated health anxiety may engage in greater help-seeking behavior
(e.g., visiting emergency rooms, visiting multiple doctors), taxing health care resources.
Alternatively, health anxiety may be associated with the avoidance of seeking out care due to
fears of contagion, potentially putting the individual’s physical health at risk if they are infected
with COVID-19 or suffering from another medical problem that requires attention (Asmundson
& Taylor, 2020). Likewise, loneliness may contribute to alcohol abuse (Åkerlind & Hörnquist,
1992) or increased suicide risk (Calati et al., 2019; Joiner et al., 2012).
Despite limitations, results of this study highlight associations between stay-at-home
orders, the perceived impact of COVID-19 on an individual’s life, and a variety of positive and
COVID-19 and Psychological Outcomes 18
negative psychological outcomes. In the absence of effective infection prevention efforts, wide-
spread testing and tracking, and/or pharmacological interventions (e.g., vaccines) for COVID-19,
large-scale public health interventions such as physical distancing or stay-at-home orders are
necessary to reduce the spread of the virus and infection-related mortality. However, in the
context of these necessary public health interventions, results of this study highlight the need for
concurrent psychological interventions aimed at mitigating the potential negative psychological
consequences of COVID-19 and related social distancing interventions, including interventions
aimed at increasing social connection and social support (Reger et al., 2020). In particular, as this
pandemic persists, it is imperative that evidence-based tele-mental health services are made
available and accessible to vulnerable individuals throughout the duration of stay-at-home orders
and other social distancing interventions (Reger et al., 2020).
COVID-19 and Psychological Outcomes 19
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COVID-19 and Psychological Outcomes 24
Table 1. Descriptive statistics for and correlations among primary variables of interest.
2. COVID-19 impact
3. Depression severity
4. Health anxiety
5. Financial worry
7. Social support
Note. p values are presented in parentheses below the correlation statistic. Stay-at-home = “Do
you live in a state that has instituted a stay-at-home order?” (0 = no; 1 = yes); COVID-19 impact
= “To what extent has the situation associated with COVID-19 affected the way you live your
COVID-19 and Psychological Outcomes 25
Table 2. Main and interactive associations of stay-at-home order status and perceived impact of COVID-19 to psychological outcomes (N =
Note. p values listed as .000 are p < .001. Race = Racial/ethnic background (0 = racial/ethnic minority, 1 = non-minority); Sex (0 = Male; 1 =
Female); Income = income level (0 = < $50,000/year; 1 = < $50,000/year); Live alone = Whether participants live alone or have other
individuals in their household (0 = live alone; 1 = live with others); Stay-at-home = “Do you live in a state that has instituted a stay-at-home
order?” (0 = no; 1 = yes); COVID-19 impact = “To what extent has the situation associated with COVID-19 affected the way you live your
life?;” Interaction = Stay-at-home status × Perceived impact of COVID-19.