Psychological correlates of COVID-19 pandemic in the Austrian population

doi:10.21203/rs.3.rs-23337/v1

Background: COVID-19 poses the greatest challenge for the entire world since the Second World War. Governments are forced to define strict measures to avoid the spreading of the virus, which may further impose psychological burden for the majority of the population. The aim of this study was to evaluate the psychological distress in Austria during the initial stage of the COVID-19 outbreak.

Methods: From 25 March to 3 April 2020, an anonymous online survey was conducted. Target group included all members of the Austrian population older than 15 years. The survey addressed the following areas (1) and sociodemographic data, (2) physical and mental health; (3) knowledge and concerns about COVID-19; (4) contact with infected people; (5) prevention efforts; (6) need for further information. The Impact of Event Scale-Revised (IES-R) and the Depression, Anxiety and Stress Scale (DASS-21) were used to assess mental health. Analyses were based on 4,126 individuals (74% female, age: M = 38.68, SD = 13.36).

Results: 43.3% rated the psychological impact as moderate (5.6%) or severe (37.7%). 26.5% reported moderate (13.3%) to severe (13.2%) depression; 20.3% moderate (8.9%) to severe (11.4%) anxiety and 21.2% reported to suffer from moderate (10.5%) or severe stress (10.7%). Being female, higher age, lower levels of education, concern about family members, internet as main source of information, student or pupil status, poor self-rated health, and the attitude that “there is too much unnecessary worry” were signiﬁcantly associated with higher psychological burden. Protective factors were the possibility to work in home office, frequent (indirect) contact with family or friends, the availability of virus-specific information, confidence in the diagnosis capability, and physical activity during the crisis.

Conclusion: This study is among the first in Europe on the psychological correlates of the COVID-19 pandemic. 37.7% of the Austrian study population reported a severe psychological impact on the event and 1 in 10 is considered to suffer from severe depression, anxiety or stress. The present findings inform about the identification of protective factors, psychologically vulnerable groups and may guide the development of psychological interventions.

Infectious Diseases

Health Economics & Outcomes Research

Health Policy

COVID-19 pandemic

stress

anxiety

depression

psychological status

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified first on January 20 in Wuhan, China. This virus triggers the COVID-19 pandemic, which was classified by the WHO on January 30, 2020, as a health emergency of international scope. In the meantime, the whole world has been affected by this virus with unforeseeable economic, personnel and psychological consequences.

COVID-19 virus is a highly contagious disease. The main symptoms of this virus infection include high fever, cough and severe difficulties to breathe, while the older population is more likely to get infected, with worse outcomes (1). The fundamental challenge of such a pandemic is that not every person shows the same symptoms. It is supposed that people can be infected with this virus without showing any typical symptoms, making a reliable estimate about its prevalence difficult. The finding that the reproductive number of the COVID-19 virus has been estimated at 4.08 – meaning that on average, every case of COVID-19 will create up to 4 new cases – stresses the need for the implementation of strict policies (2). Similar to other virus epidemics like, for example, SARS, people in the surroundings can be infected through sneezing and coughing or even merely through speaking (3). According to the European Union (https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-cases), there were 786,459 confirmed COVID-19 cases worldwide, including 9,634 in Austria, and 37,831 deaths worldwide, and 108 deaths in Austria by March 30, 2020.

Based on these data, many governments worldwide defined strict restrictions to reduce the risk of new infections within the population and to protect the health care system from excessive demands. Experiences from previous virus epidemics showed that the uncontrolled spread of a virus can only be prevented by instituting widespread and strict quarantine policies with large personal restrictions (4). On February 25, Austrian authorities reported the first COVID-19 in Austria and on March 11 the first death due to this virus infection. Since that time, numbers of infections and deaths have increased exponentially in Austria and all over the world. Northern Italy, in particular, was severely affected by the COVID-19 pandemic and reported hundreds of deaths a day. Due to its proximity to Italy, the Austrian province of Tyrolia has been declared a quarantine zone on March 13. 14 days after that, the Austrian authorities imposed measures with strict personal recommendations against the spreading of the COVID-19 virus, which included a complete shutdown of the industry (except industries necessary for the immediate supply of the population, like pharmacies, hospitals and groceries) and strict personnel restrictions. Apart from preventive hygiene measures like washing the hands or sneezing in the elbow, the Austrian government imposed a complete curfew with some exceptions: (a) shopping for food or medication, (b) helping other people, (c) go to work or (d) to take a walk or do sports. Individuals are encouraged to keep a distance of 2 meters to other people. It was generally forbidden to meet other people who do not live in the same household. The whole country of Austria has been in a historical state of emergency. The Austrian government and politicians speak of circumstances that have not existed since the Second World War. Figure 1 shows the development of the COVID-19 outbreak, the measures taken to control the spread of the virus and the recruitment period of the participants.

Although these measures were successful in terminating the outbreak in all areas of the country, there is evidence that quarantine policies create psychological, emotional, and financial problems for the majority of the population (4). Little is known about the psychological consequences of extensive personnel restrictions related to a virus epidemic. It can be assumed, that such measures pose a burden on individuals, thus challenging mental health and resilience (5).

Based on the study of Wang et al. (2020), the present study is the first nationwide large-scale survey of the psychological correlates and mental health in Austria during the initial state of COVID-19 pandemic. Results may inform about the psychological needs of the population and could provide a basis for tailored mental health interventions in order to support the population in this exceptional situation. Therefore, the main focus of the study was on the evaluation of the extent of psychological distress of the Austrian population and to contribute to international comparisons regarding the mental health correlates of the COVID-19 pandemic.

2.1. Participants

A cross-sectional study design was implemented to assess the potential psychological distress during the COVID-19 pandemic in the Austrian population within the first two weeks after implementation of strict personnel restrictions, by using an anonymous online survey (LimeSurvey GmbH, Hamburg, Deutschland). Target group included all members of the public exceeding the age of 15 years. The online survey was distributed in social and print media with a request to pass it on to others. A total of 4,618 people answered the questionnaire. 492 individuals had to be excluded due to incorrect completion (e.g., not fully completed). Analysis was based on 4,126 individuals (women: N = 3042, men: N = 1073; age: M = 38.68, SD = 13.36).

2.2. Procedure

Data collection took place over 10 days (25 March – 3 April 2020), after the Austrian government imposed measures with strict personal recommendations against the spreading of the COVID-19 virus. These measures were implemented 14 days after the first COVID-19 infection in Austria were detected (see Figure 1).

2.3. Survey Development

Based on the methodological approach of Wang et al. (2020), several instruments were used to address the following areas, in addition to sociodemographic data: (1) physical health status (currently, and over the past 14 days); (2) basic knowledge and concerns about COVID-19; (3) contact with COVID-19 infected people in the past 14 days; (4) prevention measures against COVID-19 in the past 14 days; (5) additional information required with respect to COVID-19; and (6) the psychological correlates of the COVID-19 outbreak.

A number of sociodemographic data were gathered (age, sex, relationship status, number and age of children or other individuals living in the same the household, pets, educational level, current employment status, professional group). Furthermore, individuals were asked about their current work situation, for example, if they lost their job because of the COVID-19 pandemic or how they organized their everyday work at home, how many hours they spent at home on average and how often they had contact with people outside the household.

Specific questions concerning health status were also evaluated and were always related to the past 14 days. Physical symptoms including fever, headache and muscle pain, coughing shortness of breath, dizziness and sore throat were assessed. Individuals were asked whether they received medical treatment, were hospitalized or had been tested for the COVID-19 virus in the last 14 days. Furthermore, individuals were asked to rate their current physical health status and give additional information about existing chronic illnesses. Self-rated physical health status was measured on a 5-point Likert scale (1 = very poor to 5 = very good). Contact history variables included direct or indirect contact with confirmed COVID-19 individuals as well as contact with materials or individuals with suspected COVID-19.

Furthermore, knowledge about COVID-19 was assessed. The following variables were used: knowledge about transmission pathways (queried via a knowledge test), level of confidence in the current diagnostic options, satisfaction with health information about COVID-19 and information about the development of new infections and deaths. Individuals were asked about their sources from which they obtained the information. Respondents were also asked to what extend they were afraid that they themselves or a family member could become infected with COVID-19. Finally, they were asked about their use of precautionary measures (washing hands, wearing masks, etc.) against COVID-19 infection and how high they rated the chances of surviving a COVID-19 infection. 5-point Likert scales were used to measure participant's attitudes, opinions and perceptions (e.g., 1 = very unlikely to 5 = very likely). Participants were also requested to indicate whether they were in need of further information regarding treatment, distribution opportunities, local outbreaks, etc.

The Impact of Event Scale-Revised (IES-R; Maercker & Schützwohl, 1998) was used to evaluate the psychological correlates of COVID-19. It aims to measure the subjective response to a specific traumatic event (7). The IES-R is a short and easy self-administered questionnaire with 22 items and three subscales. The main focus of this questionnaire is to measure the mean avoidance, intrusion, and hyperarousal (8). Furthermore, a total subjective stress IES-R score can be calculated. Referred to Creamer et al. (2003), the sum score can be divided into 0-23 (normal), 24-32(mild psychological impact), 33-36 (moderate psychological impact), and >37 (severe psychological impact). Originally, this test has been developed for American students, but it has also been used across diverse populations (including different national groups), whereby the factor structure has remained robust (10). In the present study, reliability for this scale (Cronbach´s alpha = .93) was very good. For analysis the sum score was calculated.

In order to examine the mental health status, the short form of the depression, anxiety and stress-scale (DASS-21, Nilges & Essau, 2015) was used. This inventory has been applied in research related to virus-epidemics (12). DASS-21 is a well-established instrument to measure the core symptoms of depression, anxiety and stress (13). The calculation of scores were related to a previous study. All subscales consisted of 7 items and the scores of the subscales (depression, anxiety, and stress) were divided into categories from normal to extremely severe. In more detail, for depression: mild depression (10–12), moderate depression (13–20), severe depression (21–27), and extremely severe depression (28–42); for anxiety: normal (0–6), mild anxiety (7–9), moderate anxiety (10–14), severe anxiety (15–19), and extremely severe anxiety (20–42), and for stress: normal (0–10), mild stress (11–18), moderate stress (19–26), severe stress (27–34), and extremely severe stress (35–42). In the present study, reliabilities for the subscales depression (Cronbach´s alpha = .91), stress (Cronbach´s alpha = .88) and anxiety (Cronbach´s alpha = .91) were very good. For analysis, the sum scores of the three subscales stress, anxiety and depression were calculated.

Stress resilience was measured with the German version of the Resilience Scale (RS-11; Schumacher et al., 2005; Wagnild & Young, 1993). The RS-11 comprises 11 items, ranging from 1-7. Answers are summed up indexing trait resilience. Higher scores reflect greater trait resilience. In the present sample, reliability for this scale (Cronbach´s alpha = .90) was very good. For analysis, the total score was calculated. (Results will be published separately in a further publication).

2.4. Statistical Analysis

Statistical analyses were conducted using the software IBM SPSS statistics version 24 (IBM Corp., NY, USA). The general level of significance was fixed at p < .05 (two tailed). Descriptive statistics were calculated for all variables and presented as mean (M) and standard deviation (SD) for continuous variables, median and percentages or response for categorical and nominal variables. Linear regression was used to analyze univariate association between predictor variables and the sum scores of the DASS-21 subscales and the IES-R. In order to ensure comparability with the results of Wang et al. (2020), reference categories for the linear regression analyses were based on Wang´s methodology. Ordinal data from Likert scales were treated as continuous variables (e.g., frequency of precautionary measures). Chi-Square tests of independence were used to determine if there were significant differences between nominal variables. Bonferroni-Holm procedure was utilized to adjust for multiple comparisons.

3.1. Survey respondents

Psychological symptoms during of COVID-19 were measured using the DASS-21 (11) and the IES-R (6). The sample mean score for the DASS-21 scale was M = 24.87 (SD = 26.97). Sample mean scores for the DASS-21 subscales were 8.88 (SD = 10.26) for depression, 5.42 (SD = 8.38) for anxiety and 10.58 (SD = 10.85) for stress.

According to the cut-off scores proposed by Wang et al. (2020), 2,652 (64.3%) participants showed a low score on the depression subscale (score: 0–9), 383 (9.3%) were considered to suﬀer from mild depression (score: 10–12), 547 (13.3%) from moderate depression (score: 13–20), and 544 (13.2%) from severe or extremely severe depression (score: 21–42). N = 3,069 (74.4%) participants showed a low score on the anxiety subscale (score: 0–6), 216 (5.2%) were considered to suﬀer from mild anxiety (score: 7–9), 369 (8.9%) from moderate anxiety (score: 10–14), and 472 (11.4%) from severe or extremely severe anxiety (score: 15–42). N = 2,546 (61.7%) participants showed a low score on the stress subscale (score: 0–10), 703 (17%) were considered to suﬀer from mild stress (score: 11–18), 435 (10.5%) from moderate stress (score: 19–26), and 442 (10.7%) from severe or extremely severe stress (score: 27–42).

Cut-off scores from the German version of the DASS-21 (11) revealed 544 (13.2%) clinically relevant cases of depression, 574 (13.9%) clinically relevant cases of anxiety and 769 (18.6%) clinically relevant cases of stress.

The sample mean score of the IES-R was 32.36 (SD = 24.02). According to the cut-of scores proposed by Creamer et al. (2003), 1,771 (42.9%) participants rated the psychological impact as minimal (score<23), 570 (13.8%) as mild (score: 24–32), 231 (5.6%) as moderate, and 1554 (37.7%) as severe (score: >33).

In direct comparison with the results of Wang et al. (2020), significantly less Austrian individuals rated the psychological impact of the COIVD-19 outbreak as moderate or severe (Wang et al., 2020: 53.8% vs 43.3%; X² (2, N = 5,336) = 142.67, p < .001. In contrast, significantly more participants of the Austrian sample reported severe depression (Wang et al., 2020: 4.3% vs 13.2%; X² (3, N = 5,336) = 89.61, p < .001), severe anxiety (Wang et al., 2020: 8.4% vs 11.4%; X² (3, N = 5,336) = 138.02, p < .001) and severe stress (Wang et al., 2020: 2.6% vs 10.7%; X² (3, N = 5,336) = 126.79, p < .001).

3.2. Associations with sociodemographic variables

Men reported significantly lower stress (B = -4.68, 95% CI = -5.42, -3.94, p < .001), anxiety (B = -2.59, 95% CI = -3.17, -2.01, p < .001), depression (B = -2.74, 95% CI = -3.45, -2.03, p < .001), and less psychological impact of the current event (B = -11.41, 95% CI = -13.04, -9.78, p < .001) than women. Higher age was significantly associated with less stress (B = -0.11, 95% CI = -0.13, -0.09, p < .001), anxiety (B = -0.05, 95% CI = -0.08, -0.03, p < .001), and depression (B = -0.11, 95% CI = -0.13, -0.09, p < .001). Participants living together with children showed significantly higher stress (B = 0.82, 95% CI = -1.83, -0.51, p < .001), but lower scores in depression (B = -1.17, 95% CI = -1.83, -0.51, p < .001). Lower levels of education were significantly associated with higher scores of stress, anxiety, depression and psychological impact of COVID-19. For example, lower secondary education was significantly associated with more anxiety (B = 2.20, 95% CI = 0.63, 3.77, p = .006), depression (B = 4.33, 95% CI = 2.41, 6.25, p < .001) and more psychological impact (B = 7.59, 95% CI = 3.08, 12.10, p < .001) compared to doctorate/PhD (for further details, see Table 1). Unemployed status was significantly associated with higher stress (B = 3.19, 95% CI = 1.61, 4.71, p < .001), anxiety (B = 2.73, 95% CI = 1.55, 3.91, p < .001), depression (B = 4.60, 95% CI = 3.17, 6.03, p < .001) and greater impact of the event (B = 4.71, 95% CI = 1.32, 8.1, p = .006) as compared to respondents who were employed. Student, respectively pupil status was significantly associated with higher stress (Student: B = 1.83, 95% CI = 0.86, 2.80, p < .001) and depression (Student: B = 3.52, 95% CI = 2.61, p < .001, 4.43; Pupil: B = 5.17, 95% CI = 3.26, 7.08, p < .001) as compared to employed participants. Individuals working from home showed significantly lower anxiety (B = -1.31, 95% CI = -1.88, -0.74, p < .001), depression (B = -2.28, 95% CI = -2.98, -1.58, p < .001), and IES-R scores (B = -2.34, 95% CI = -3.99, -0.69, p = .005) as compared to those working under normal conditions. Participants on sick leave scored significantly higher in stress (B = 3.96, 95% CI = 1.51, 6.41, p = .002), anxiety (B = 4.80, 95% CI = 2.91, 6.69, p < .001), depression (B = 4.17, 95% CI = 1.86, 6.48, p < .001), and IES-R (B = 8.93, 95% CI = 3.5, 14.36, p = .001) as compared to those working under normal conditions. Further analyses revealed that an increase of hours per day spent at home was significantly associated with higher stress (B = 0.19, 95% CI = 0.11, 0.27, p < .001), anxiety (B = 0.10, 95% CI = 0.04, 0.16, p = .002) and depression (B = 0.18, 95% CI = 0.11, 0.25, p < .001), while a higher number of social contacts with friends and/or family members was significantly associated with lower scores in anxiety and depression. For example, contacting family or friends every few days was significantly associated with lower anxiety (B = ‑3.51, 95% CI = -5.66, -1.36, p = .001) and depression (B = -3.69, 95% CI = - .33, -1.05, p = .006) as compared to no contact. For further details, see Table 1.

Table 1. Linear regression results of demographic variables associated with the psychological impact of the 2020 COVID-19 outbreak measured with DASS-Subscales and the IES-R.

*Variables*	*N (%) M (SD)*	Stress			Anxiety			Depression			Impact of Event
*Variables*	*N (%) M (SD)*	R²	B (95% CI)	p	R²	B (95% CI)	p	R²	B (95% CI)	p	R²	B (95% CI)	p
Gender
Male	1073 (26)	0.036	4.68±0.74	<.001	0.018	-2.59±0.58	<.001	0.014	-2.74±0.71	<.001	0.043	-11.41±1.63	<.001
Female (Ref.)	3042 (74)		-	-		-	-		-	-		-	-
Age (Continuous)	38.68 (13.36)	0.018	0.11±0.02	<.001	0.006	-0.05±0.02	<.001	0.022	-0.11±0.02	<.001	0.000	-0.02±0.05	.48
Marital status
Single	1057 (25.6)		3.37±3.19	.039		-0.71±2.47	.58		3.19±3.01	.038		4.61±7.09	.20
Married/Partnership	2838 (68.8)	0.002	2.92±3.15	.07	0.001	-1.29±2.44	.30	0.014	0.37±2.97	.80	0.000	4.67±7.00	.19
Divorced	185 (4.5)		1.23±3.49	.49		-1.83±2.71	.19		0.38±3.29	.82		5.54±7.76	.16
Widowed (Ref.)	46 (1.1)		-	-		-	-		-	-		-	-
Household size (Continuous)	2.39 (2.21)	0.000	0.03±0.15	.67	0.000	-0.01±0.12	.86	0.000	-0.10±0.14	.16	0.000	0.04±0.33	.80
Children in household
Yes	1448 (35.1)	0.001	0.82±0.69	.020	0.000	0.09±0.54	.75	0.003	-1.17±0.66	<.001	0.000	1.25±1.54	.11
No (Ref.)	2678 (64.9)		-	-		-	-		-	-		-	-
Education Level
No formal education	31 (0.8)		2.40±4.07	.25	0.007	2.07±3.14	.20	0.013	4.19±3.84	.033	0.003	4.31 ± 9.02	.35
Lower secondary education	216 (5.2)		2.60±2.03	.012		2.20±1.57	.006*		4.33±1.92	<.001*		7.59 ± 4.51	<.001*
Vocational education	694 (16.8)		0.79±1.64	.35		1.83±1.27	.005*		1.71±1.55	.031		5.21 ± 3.64	.005*
High School Certificate	1286 (31.2)	0.003	1.66±1.55	.036		1.43±1.20	.002		2.53±1.46	<.001*		3.58 ± 3.44	.041
Bachelor Degree	584 (14.2)		1.33±1.68	.12		0.87±1.30	.19		1.70±1.58	.036		2.87 ± 3.73	.13
Master Degree	1096 (26.6)		0.91±1.57	.26		0.11±1.21	.86		0.25±1.48	.74		2.20 ± 3.48	.22
Doctorate/PhD (Ref.)	219 (5.3)		-	-		-	-		-	-		-	-

*Variables*	*N (%) M (SD)*	Stress			Anxiety			Depression			Impact of Event
*Variables*	*N (%) M (SD)*	R²	B (95% CI)	p	R²	B (95% CI)	p	R²	B (95% CI)	p	R²	B (95% CI)	p
Employment status		0.010			0.007			0.027			0.003
Unemployed	208 (5)		3.19±1.52	<.001*		2.73±1.18	<.001*		4.60±1.43	<.001*		4.71±3.39		.006*
Retired	343 (8.3)		-1.40±1.21	<.05		0.46±0.94	.34		0.14±1.14	.81		2.62±2.70		.06
Student	586 (14.2)		1.83±0.97	<.001*		0.91±0.75	.018		3.52±0.91	<.001*		-0.04±2.15		.97
Pupil	113 (2.7)		1.98±2.03	.06		1.49±1.58	.06		5.17±1.91	<.001*		1.39±4.52		.55
Self-Employed	287 (7)		-0.74±1.31	.27		-0.51±1.02	.33		-0.63±1.23	.32		-1.86±2.93		.21
Employed (Ref.)	2589 (62.7)		-	-		-	-		-	-		-		-
Daily working routine only (Self-)Employed (N=2876)
Home Office	1438 (50)		-0.71±0.74	.06		-1.31±0.57	<.001*		-2.28±0.70	<.001*		-2.34±1.65		.005*
Holiday	153 (5.3)		0.12±1.78	.89		-0.32±0.77	.63		-1.09±1.68	.20		-2.03±3.95		.31
Sick Leave	78 (2.7)	0.004	3.96±2.45	.002*	0.012	4.80±1.89	<.001*	0.015	4.17±2.31	<.001*	0.005	8.93±5.43		.001*
Others	588 (20.4)		-0.08±1.00	.87		-0.32±0.77	.41		-1.41±0.94	.003*		0.10±2.22		.93
Normal (Ref.)	619 (21.5)		-	-		-	-		-	-		-		-
Hours per day spent at home (Continuous)	21.22(4.17)	0.005	0.19±0.08	<.001	0.002	0.10±0.06	.002	0.005	0.18±0.07	<.001	0.001	0.13±0.18		.14
Contact to family/friends outside
Several times a day	2270 (55)		-1.21±2.71	.38		-2.52±2.10	.018*		-3.23±2.57	.014*		-1.30±6.01		.67
Daily	888 (21.5)		-1.47±2.77	.30		-2.87±2.14	.009*		-3.23±2.62	.016*		-2.50±6.13		.42
Every few days	762 (18.5)	0.002	-2.29±2.78	.11	0.004	-3.51±2.15	.001*	0.003	-3.69±2.64	.006*	0.003	-4.58±6.17		.15
Once in a Week	143 (3.5)		-1.54±3.21	.35		-1.64±2.48	.20		-2.87±3.04	.06		-1.87±7.11		.61
Never (Ref.)	63 (1.5)		-	-		-	-		-	-		-		-
Notes. Descriptive statistics are presented as mean and standard deviations in parentheses for continuous predictor variables or n (%) for categorical predictor variables. * = significant after Bonferroni Holm adjustment for multiple comparisons.

3.3. Associations with health status

Higher scores in self-rated health were significantly associated with lower scores in stress (B = -4.83, 95% CI = -4.39, -5.27, p < .001), anxiety (B = -3.76, 95% CI = -3.42, -4.10, p < .001), depression (B = -4.83, 95% CI = -4.39, -5.27, p < .001), and IES-R (B = -7.68, 95% CI = -6.67, -8.69, p < .001). Several participants reported a range of physical symptoms, most frequently headache (46.7%), coryza (31.7%), sore throat (23.5%), myalgia (22.7%), cough (21.5%), dizziness (15.3%), respiratory problems (5.4%), chills (3.6%), and fever (1.8%). Linear regression analyses showed that physical health concerns were significantly associated with higher scores in stress, anxiety, depression and the IES-R scores. For example, having a pre-existing health condition was significantly associated with more stress (B = 1.83, 95% CI = 0.99, 2.67, p < .001), anxiety (B = 2.10, 95% CI = 1.45, 2.75, p < .001), depression (B = 1.67, 95% CI = 0.88, 2.46, p < .001) and higher scores in the IES-R (B = 4.26, 95% CI = 2.40, 6.12, p < .001). For further details, see Table 2.

In the last two weeks, 8.3% of the participants reported to have received medical treatment, 2.6% reported direct and 7.3% indirect contact with individuals with confirmed COVID-19 infection. Moreover, 13.2% reported contact with individuals with suspected COVID-19 infection, 35.7% contact with infected materials, and 0.4% had been admitted to the hospital. Only 1.5% had been tested for COVID-19 and 4.3% reported being under quarantine by a health authority. Medical treatment within the last 14 days was significantly associated with higher stress (B = 3.68, 95% CI = 2.49, 4.87, p < .001), anxiety (B = 2.98, 95% CI = 2.06, 3.90, p < .001), depression (B = 3.21, 95% CI = 2.08, 4.34, p < .001) and higher scores in the IES-R (B = 5.59, 95% CI = 2.94, 8.24, p < .001). Indirect contact with individuals with a confirmed COVID-19 infection and contact with an individual with suspected infection was significantly associated with higher stress (indirect contact: B = 2.25, 95% CI = 0.98, 3.52, p < .001; suspected contact: B = 2.02, 95% CI = 1.05, 2.99, p < .001), anxiety (indirect contact: B = 1.74, 95% CI = 0.76, 2.72, p < .001; suspected contact: B = 1.60, 95% CI = 0.85, 3.35, p < .001), depression (indirect contact: B = 2.05, 95% CI = 0.85, 3.25, p < .001; suspected contact: B = 1.31, 95% CI = 0.38, 2.23; p = .005) and higher scores in the IES-R (indirect contact: B = 3.71, 95% CI = 0.90, 6.52, p = .010; suspected contact: B = 4.11, 95% CI = 1.95, 6.27, p < .001). In contrast, direct contact with an individual with confirmed infection was significantly associated with anxiety (B = 2.36, 95% CI = 0.75, 3.97, p = .004), but not with stress, depression or the IES-R. Contact with potentially infectious material was significantly positively associated with stress (B = 0.79, 95% CI = 0.10, 1.48, p = .025), anxiety (B = 0.88, 95% CI = 0.35, 1.41, p < .001) and depression (B = 0.85, 95% CI = 0.20, 1.50, p = .011). Having been tested for COVID-19 was significantly associated with stress (B = 4.49, 95% CI = 1.78, 7.20, p = .001), anxiety (B = 2.20, 95% CI = 0.10, 4.30, p = .041) and depression (B = 3.86, 95% CI = 1.29, 6.43, p = .003). Being under quarantine within the last 14 days was significantly associated with more stress (B = 2.80, 95% CI = 1.57, 4.43, p < .001), anxiety (B = 3.04, 95% CI = 1.78, 4.10, p < .001), depression (B = 2.82, 95% CI = 1.28, 4.36, p < .001) and higher scores in the IES-R (B = 6.69, 95% CI = 3.07, 10.3, p < .001).

Table 2. Linear regression results of physical health variables associated with the psychological impact of the 2020 COVID-19 outbreak measured with DASS-Subscales and the IES-R.

*Variables*	*N (%)* *M (SD)*	Stress			Anxiety			Depression			Impact of Event
*Variables*	*N (%)* *M (SD)*	R²	B (95% CI)	p	R²	B (95% CI)	p	R²	B (95% CI)	p	R²	B (95% CI)	p
Subjective health status
5-point Likert scale	4.24 (0.71)	0.100	-4.83±0.44	<.001	0.100	-3.76±0.34	<.001	0.095	-4.46±0.42	<.001	0.051	-7.68±1.01	<.001
(Continuous)			-	-		-	-		-	-		-	-
Pre-existing condition
Yes	794 (19.2)	0.004	1.83±0.84	<.001	0.020	2.10±0.65	<.001	0.004	1.67±0.79	<.001	0.005	4.26±1.86	<.001
No (Ref.)	3332 (80.8)		-	-		-	-		-	-		-	-
Fever
Yes	75 (1.8)	0.001	2.70±2.47	.032	0.003	3.17±1.91	.001	0.001	2.40±2.34	.045	0.002	7.24±5.48	.010
No (Ref.)	4051 (80.8)		-	-		-	-		-	-		-	-
Chills
Yes	149 (3.6)	0.018	7.77±1.76	<.001	0.026	7.30±1.35	<.001	0.014	6.40±1.67	<.001	0.011	13.36±3.91	<.001
No (Ref.)	3977 (96.4)		-	-		-	-		-	-		-	-
Headache
Yes	1925 (46.7)	0.056	5.15±0.64	<.001	0.034	3.09±0.50	<.001	0.042	4.24±0.61	<.001	0.017	6.27±1.46	<.001
No (Ref.)	2201 (53.3)		-	-		-	-		-	-		-	-
Myalgia
Yes	936 (22.7)	0.020	3.62±0.78	<.001	0.022	2.97±0.60	<.001	0.018	3.27±0.74	<.001	0.006	4.42±1.75	<.001
No (Ref.)	3190 (77.3)		-	-		-	-		-	-		-	-
Cough
Yes	886 (21.5)	0.006	1.97±0.80	<.001	0.008	1.87±0.62	<.001	0.002	1.23±0.76	.002	0.003	3.19±1.78	<.001
No (Ref.)	3240 (78.5)		-	-		-	-		-	-			-
Respiratory problems
Yes	222 (5.4) 3904 (94.6) (5.4)	0.016	1.97±0.80	<.001	0.050	8.32±1.11	<.001	0.013	5.22±1.38	<.001	0.008	9.64±3.24	<.001
No (Ref.)	3940 (94.6)		-	-		-	-		-	-		-	-
Dizziness
Yes	631 (15.3)	0.053	6.90±0.89	<.001	0.070	6.14±0.69	<.001	0.047	6.19±0.85	<.001	0.025	10.54±2.01	<.001
No (Ref.)	3495 (84.7)		-	-		-	-		-	-		-	-
Coryza
Yes	1307 (31.7)	0.007	1.89±0.71	<.001	0.006	1.41±0.55	<.001	0.002	1.05±0.67	.002	0.000	1.15±1.58	.15
No (Ref.)	2819 (68.3)		-	-		--	-		-	-		-	-

*Variables*	*N (%)*	Stress			Anxiety			Depression			Impact of Event
		R²	B (95% CI)	p	R²	B (95% CI)	p	R²	B (95% CI)	p	R²	B (95% CI)	p
Sore throat
Yes	968 (23.5)	0.019	3.53±0.77	<.001	0.021	2.85±0.60	<.001	0.008	2.11±0.74	<.001	0.007	4.66±1.72	<.001
No (Ref.)	3158 (76.5)		-	-		-	-		-	-		-	-
Medical treatment in the past 14 days
Yes	342 (8.3)	0.009	3.68±1.19	<.001	0.010	2.98±0.92	<.001	0.007	3.21±1.13	<.001	0.004	5.59±2.65	.010
No (Ref.)	3784 (91.7)		-	-		-	-		-	-		-	-
Direct contact with individual in the past 14 days
with confirmed infection
Yes	107 (2.6)	0.000	1.41±2.08	.19	0.002	2.36±1.61	.004	0.001	1.90±1.97	.06	0.000	3.61±4.61	.12
No (Ref.)	4019 (97.4)		-	-		-	-		-	-		-	-
Indirect contact with individual in the past 14 days
with confirmed infection
Yes	202 (7.3)	0.003	2.25±1.27	<.001	0.003	1.74±0.98	<.001	0.003	2.05±1.20	<.001	0.002	3.71±2.81	<.01
No (Ref.)	3824 (92.7)		-	-		-	-		-	-		-	-
Contact with individual
with suspected infection
Yes	544 (13.2)	0.004	2.02±0.97	<.001	0.004	1.60±0.75	<.001	0.002	1.31±0.92	<.001	0.003	4.11±2.16	<.001
No (Ref.)	3582 (86.8)		-	-		-	-		-	-		-	-
Contact with infectious materials individual
Yes	1472 (35.7)	0.001	0.79±0.69	.024	0.003	0.88±0.53	.001	0.001	0.85±0.65	.011	0.000	0.80±1.53	.31
No (Ref.)	2654 (64.3)		-	-		-	-		-	-		-	-
Hospitalization in the past 14 days
Yes	17 (0.4)	0.001	3.91±5.16	.14	0.000	2.59±3.99	.20	0.001	4.20±4.89	.09	0.000	6.55±11.44	.26
No (Ref.)	4109 (99.6)		-	-		-	-		-	-		-	-
Testing for COVID-19 in the past 14 days
Yes	62 (1.5)	0.003	4.49±2.71	<.01	0.001	2.20±2.10	.041	0.002	3.86±2.57	.003	0.000	3.48±6.03	.26
No (Ref.)	4064 (98.5)		-	-		-	-		-	-		-	-
Quarantine in the past 14 days
Yes	177 (4.3)	0.003	2.80±1.63	<.001	0.005	3.04±1.26	<.001	0.003	2.82±1.54	<.001	0.003	6.69±3.61	<.001
No (Ref.)	3949 (95.7)		-	-		-	-		-	-		-	-
Notes. Descriptive statistics are presented as mean and standard deviations in parentheses for continuous predictor variables or n (%) for categorical predictor variables.

3.4. Associations with virus-specific knowledge and concerns

The majority of the participants were aware of the increase of the number of infected individuals (99.7%), the number of deaths (99.1%) and the number of recovered individuals (87.7%). The knowledge about the increase in the number of recovered individuals and infections was significantly associated with lower stress (recovered: B = -1.71, 95% CI = -2.72, -0.70, p < .001; infected: B = -6.30, 95% CI = -11.98, -0.62, p < .001), anxiety (recovered: B = -1.73, 95% CI = ‑2.51, ‑0.95, p < .001; infected: B = -7.89, 95% CI = -12.28, -3.50, p < .001), depression (recovered: B = ‑2.04, 95% CI = -2.99, -1.09, p < .001; infected: B = -7.58 , 95% CI = -12.96, -2.20, p < .001) and lower scores in the IES-R (recovered: B = -4.36, 95% CI = -6.59, -2.13, p < .001; infected: B = -12.76, 95% CI = -25.36, -0.16, p < .001). Further, the belief that COVID-19 cannot be transmitted via air, was significantly associated with lower stress (B = -2.17, 95% CI = -2.94, -1.4, p < .001), anxiety (B = -1.45, 95% CI = ‑2.05, -0.85, p < .001), depression (B = ‑1.80, 95% CI = -2.53; -1.07, p < .001) and lower scores in the IES-R (B = ‑3.74, 95% CI = ‑5.46, ‑2.02, p < .001).

The most prominent source of health information about COVID-19 was the internet (56.3%), followed by TV (30.3%) and radio (7.3). Internet as preferred source of information was significantly associated with higher stress (B = 1.37, 95% CI = ‑0.89, 3.63) and depression (B 1.04, 95% CI = -0.82, 2.90) as compared to the reference category “TV”. Most of the respondents (84.9%) were highly satisfied or somewhat satisfied with the available health information. Satisfaction with the health information was significantly associated with lower anxiety (B = -2.44, 95% CI = -4.21, -0.67, p = .007), while dissatisfaction with the provided information was associated with higher stress (B = 4.26, 95% CI = 0.93, 7.59, p = .012).

Most of the participants stated that they are very confident (20.8%) or confident (58.6%) regarding the diagnostic capabilities of the health system, while 18.5%, respectively, 2.1% were rather not confident or not confident at all. Less confidence in the doctor’s ability to diagnose COVID-19 was significantly related to higher stress (B = -2.72, 95% CI = -3.19, -2.25, p < .001), anxiety (B = ‑1.99, 95% CI = -2.36, -1.62, p < .001), depression (B = -2.70, 95% CI = ‑3.15, -2.25, p < .001) and a higher IES-R score (B = -4.77, 95% CI = -5.82, -3.72, p < .001). 71.5% were very worried or somewhat worried about other family members getting COVID-19, while 41.6% of the respondents were very worried or somewhat worried about their children getting infected. High levels of concern about other family members or children were significantly associated with higher stress (family members: B = 5.39, 95% CI = 3.43, 7.35, p < .001; children: B = 5.21, 95% CI = 3.85, 6.57, p < .001), anxiety (family members: B = 4.16, 95% CI = 2.64, 5.68, p < .001; children: B = 4.48, 95% CI = 3.43, 5.53, p < .001), depression (family members: B = 2.97, 95% CI = 1.09, 4.85, p = .002; children: B = 4.48, 95% CI = 3.43, 5.53, p < .001), and more psychological impact of the outbreak (family members: B = 10.47, 95% CI = 6.12, 14.82, p < .001; children: B = 12.10, 95% CI = 9.09, 15.11, p < .001).

Almost half of the participants (49.8%) thought that an own infection was likely or very likely, but the majority (92.2%) believed that it was very likely or somewhat likely to survive a COVID-19 infection. Higher perceived likelihood of being infected with COVID-19 was significantly associated with higher stress (B = 2.94, 95% CI = 1.49, 4.39, p < .001) and depression (B = 2.40, 95% CI = 1.02, 3.78, p < .001), while a higher perceived likelihood of surviving COVID-19 infection was significantly associated with less stress (B = ‑4.71, 95% CI = -6.26, -3.16, p < .001), anxiety (B = ‑5.04, 95% CI = -6.59, -4.21, p < .001), depression (B = -4.18, 95% CI = -5.65, 2.71, p < .001) and impact of event (B = -14.35, 95% CI = -17.76, -10.94, p < .001). For details, see Table 3.

Table 3. Linear regression results of variables related to concerns and knowledge associated with the psychological impact of the 2020 COVID-19 outbreak measured with DASS-Subscales and the IES-R.

*Variables*	*N (%)*	Stress			Anxiety			Depression			Impact of Event
*Variables*	*N (%)*	R²	B (95% CI)	p	R²	B (95% CI)	p	R²	B (95% CI)	p	R²	B (95% CI)	p
Transmission via droplets
Yes	4077 (98.8)		2.41±3.60	.98		-0.03±2.79	.98		-0.92±3.41	.60		6.85±7.99	.09
No	14 (0.3)	0.000	6.26±6.71	.06	0.000	5.00±5.20	.06	0.001	4.51±6.36	.16	0.000	15.53±14.89	<.05
Unsure (Ref.)	35 (0.8)		-	-		-	-		-	-		-	-
Transmission via
contaminated objects
Yes	2767 (67.1)		0.67±0.75	.08		0.57±0.58	.06		0.60±0.71	.10		0.11±1.67	.90
No	236 (5.7)	0.001	-1.09±1.52	.16	0.002	-1.05±1.18	.08	0.001	-0.97±1.44	.19	0.000	-3.16±3.37	.07
Unsure (Ref.)	1123 (27.2)		-	-		-	-		-	-		-	-
Transmission via air
Yes	978 (23.7)		0.27±0.91	.55		0.60±0.70	.10		0.21±0.86	.64		0.70±2.01	.49
No	1929 (46.8)	0.004	-2.17±0.77	<.001*	0.006	-1.45±0.60	<.001*	0.003	-1.80±0.73	<.001*	0.003	-3.74±1.72	<.001*
Unsure (Ref.)	1219 (29.5)		-	-		-	-		-	-		-	-
Knowledge about
increasing infections
Yes	4112 (99.7)	0.001	-6.30±5.68	.030	0.003	-7.89±4.39	<.001	0.002	-7.58±5.38	.006	0.001	-12.76*±12.60 12.60	.047
No (Ref.)	14 (0.3)		-	-		-	-		-	-		-	-
Knowledge about
increasing deaths
Yes	4088 (99.1)	0.000	-1.86±3.46	.29	0.000	-1.54±2.68	.26	0.000	-2.36±3.28	.16	0.000	-0.09±7.67	.98
No (Ref.)	38 (0.9)		-	-		-	-		-	-			-
Knowledge about
increasing recoveries
Yes	3619 (87.7)	0.003	-1.71±1.01	<.001	0.005	-1.73±0.78	<.001	0.004	-2.04±0.95	<.001	0.004	-4.36±2.23	<.001
No (Ref.)	507 (12.3)		-	-		-	-		-	-		-	-
Main source of information
Internet	2324 (56.3)		1.37±-2.26	<.001*		0.30±-0.73	.30		1.04±-1.86	<.001*		-0.21±1.65	.80
Radio	303 (7.3)		0.03±-0.01	.97		0.58±-0.50	.28		0.12±-0.07	.85		0.99±3.01	.52
Family/Friends	78 (1.9)	0.005	0.91±0.19	.47	0.003	1.23±-0.03	.21	0.004	1.28±0.21	.28	0.001	1.41±5.49	.61
Others (e.g. newspapers)	169 (4.1)		-1.93±0.25	.029		-1.75±0.80	.011*		-1.40±0.27	.10		-4.15±3.86	.035
TV (Ref.)	1252 (30.3)		-	-		-	-		-	-		-	-

*Variables*	*N (%)* *M (SD)*	Stress			Anxiety			Depression			Impact of Event
*Variables*	*N (%)* *M (SD)*	R²	B (95% CI)	p	R²	B (95% CI)	p	R²	B (95% CI)	p	R²	B (95% CI)	p
Satisfaction with information
Very satisfied	1696 (41.1)		-1.92±2.28	.10		-2.44±1.77	.007*		-2.56±2.16	.020		-3.84±5.08	.14
Somewhat satisfied	1974 (47.8)		0.26±2.27	.82		-1.28±1.76	.16		-0.70±2.15	.53		-1.53±5.06	.55
Not very satisfied	294 (7.1)	0.012	2.00±2.54	.12	0.011	0.18±1.97	.86	0.015	1.19±2.41	.33	0.005	2.07±5.66	.47
Not satisfied at all	72 (1.7)		4.26±3.33	.012*		1.17±2.59	.38		2.34±3.16	.15		1.96±7.43	.61
Do not know (Ref.)	90 (2.2)		-	-		-	-		-	-		-	-
Confidence in diagnosis capability
4-point Likert scale	2.98 (0.70)	0.030	-2.72±0.47	<.001	0.027	-1.99±0.37	<.001	0.033	-2.70±0.45	<.001	0.019	-4.77±1.05	<.001
(Continuous)			-	-		-	-		-	-		-	-
Likelihood of own infection
Very likely	467 (11.3)		2.94±1.45	<.001*		1.24±1.12	.030		2.40±1.38	.001*		2.29±3.23	.16
Somewhat likely	1587 (38.5)<

Psychological correlates of COVID-19 pandemic in the Austrian population

Status:

Journal Publication

Version 1

Abstract

Figures

1. Background

2. Methods

3. Results