ORIGINAL RESEARCH article

Front. Psychiatry, 25 April 2022

Sec. Public Mental Health

Volume 13 - 2022 | https://doi.org/10.3389/fpsyt.2022.860683

Psychological Distress, Fear and Coping Strategies During the Second and Third Waves of the COVID-19 Pandemic in Southern Germany

  • 1. Department of Psychiatry and Psychotherapy III, University of Ulm, Ulm, Germany

  • 2. Geriatric Center Ulm (GZU), Ulm, Germany

  • 3. Faculty of Medicine, Cairo University, Cairo, Egypt

  • 4. Faculty of Medicine, Benha University, Benha, Egypt

  • 5. Department of Neurology, RWTH Aachen University, Aachen, Germany

  • 6. Division of Nephrology, University of Heidelberg, Heidelberg, Germany

  • 7. Center of Psychiatry (ZfP), Biberach, Germany

  • 8. Agaplesion Bethesda Clinic, Geriatric Research Unit Ulm University, Ulm, Germany

  • 9. School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia

  • 10. School of Health, Federation University Australia, Berwick, VIC, Australia

  • 11. Faculty of Public Health, Universitas Airlangga, Surabaya, Indonesia

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Abstract

Background:

The COVID-19 pandemic has imposed enormous psychological discomfort and fear across the globe, including Germany.

Objectives:

To assess the levels of COVID-19 associated psychological distress and fear amongst Southern German population, and to identify their coping strategies.

Methods:

A cross-sectional survey using an online questionnaire was conducted in healthcare and community settings in the region of Ulm, Southern Germany. Assessment inventories were the Kessler Psychological Distress Scale (K-10), the Brief Resilient Coping Scale (BRCS), and the Fear of COVID-19 Scale (FCV-19S), which were valid and reliable tools.

Results:

A total of 474 Individuals participated in the study. The mean age was 33.6 years, and 327 (69%) were females. Most participants (n = 381, 80.4%) had high levels of psychological distress, whereas only 5.1% had high levels of fear, and two-thirds of participants showed higher levels of coping. Moderate to very high levels of psychological distress were associated with being female, living alone, distress due to employment changes, experiencing financial impact, having multiple co-morbidities, being a smoker, increased alcohol use over the previous 6 months, contact with COVID-19 cases and healthcare providers for COVID-19-related stress. Individuals who were ≥60 years, lived with non-family members, had co-morbidities and visited a healthcare provider had higher levels of fear. Higher levels of education and income showed better coping amongst participants.

Conclusion:

Psychological distress was very high during the COVID-19 pandemic in Germany and associated with low levels of coping. This study identified vulnerable groups of people, who should be given priorities for addressing their health and wellbeing in future crisis periods.

Introduction

The coronavirus disease (COVID-19) has spread into 222 countries and territories worldwide and the World Health Organization (WHO) declared a global public health emergency on 30 January 2020 (1). As of 23 November 2021, Germany reported more than five million confirmed cases and almost 100,000 deaths from COVID-19 (2). This led to enact public health measures by the Government such as physical distancing, canceling large gatherings, imposing travel restrictions and lockdown in large cities, ensuring obligatory quarantine for positive cases, primary close contacts, along with closing of educational institutions. The lockdown also resulted in the closure of many small businesses, and the unemployment rate increased to 4.1% in summer 2020 compared to 3.1% just before the pandemic (3). Ongoing restrictions also impacted on the physical and mental health of the population, especially older adults with multiple comorbidities (4). Ongoing social isolation and uncertainty of further COVID-19 pandemic waves could potentially trigger long-term mental disorders (5).

Furthermore, Unemployment and social isolation were associated with risky behaviors such as increased tobacco and alcohol consumption (6). Lockdown measures and social distancing restrictions caused a shift to telehealth facilities (7). Previous studies showed that healthcare workers engaged in the diagnosis and management of COVID-19 patients were more prone to psychological distress and various mental disorders, such as depression, anxiety, anger, fear of spreading the infection to their relatives, friends, or colleagues (8, 9).

Studies from several countries around the world including Germany found that the pandemic caused higher psychological distress, anxiety, and depression amongst a large proportion of community members (10–16). Studies also showed that depression, stress, and anxiety during the pandemic triggered sleep disorders and increased consumption of tobacco and alcohol (17). However, with increased vaccination rates and easing of restrictions, impacts may change during the current pandemic waves. Although there are previously published studies that assessed anxiety, fear and distress amongst community members and healthcare workers in Germany during the COVID-19 pandemic, the existing evidence lacks a full understanding of the impacts of the pandemic on mental health and coping strategies amongst the public in Germany and identification of the relevant predictors. Therefore, this study aimed to assess the levels of psychological distress, fear of the COVID-19 disease, and coping strategies among a wide range of population in Germany; it also aimed to identify critical factors associated with those outcomes. The population subgroups who were at higher risk of developing poor mental health outcomes would be identified in this study, which would enable the policymakers to optimize psychosocial interventions targeted to those vulnerable groups of population and guide resource planning to avoid long-term mental health impacts.

Materials and Methods

Study Design and Setting

A cross-sectional study was conducted according to The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement Checklist (18). This study was a part of a large study involving 17 countries and was led by the last author (10). Participants were informed about the study using social media and received the link of the questionnaire through social media or by emails. In addition, Quick Response (QR) codes were used on professional posters in outpatient clinics to inform patients about the study and invite participation. Data were collected from healthcare settings, including General Practices, hospitals, allied health professionals, and community settings, using a structured self-administered online questionnaire (10, 13, 14, 19).

Study Population

Adult participants who were ≥18 years old with the capacity to respond to an online questionnaire in German language were included in three main groups: (a) patients who attended a healthcare setting, either for face-to-face or telehealth consultation in the last 4 weeks irrespective of respiratory/COVID-19 symptoms, (b) healthcare workers (full time, part-time or casual) who have been in contact with patients in the last 4 weeks in a healthcare setting (doctor, nurses, allied health professionals, technicians, patient service attendants, receptionists, etc.) irrespective of caring for respiratory/COVID-19 patients, and (c) community members who did not consult any healthcare provider in the last 4 weeks.

Data Collection

An online link to the web-based questionnaire was developed using Google forms to collect data from February to April 2021 during the second and third waves of the COVID-19 pandemic. According to Robert Koch Institute, the second German wave began in October 2020 (https://www.shorturl.at/shortener.php), while the third wave started in March 2021 (https://www.shorturl.at/loqHP). Initially, there was a screening question related to age to confirm eligibility; subsequently data were collected on: (a) socio-demographics as age, gender, location of residence, marital status, living conditions (alone or with families), the highest level of education, country of birth; (b) profession as a primary occupation, the impact of COVID-19 on occupation, identification as a frontline healthcare worker; (c) self-reported comorbidities as hypertension, cardiovascular diseases, chronic respiratory diseases, diabetes, cancer; (d) behavioral risk factors as current smoking, alcohol intake; (e) health service utilization (in the last 4 weeks) as consultation with a healthcare provider for any symptom, admission to the hospital including reasons for admission; (f) exposure and contact history of COVID-19, test and diagnosis of COVID-19, close contact, isolation and quarantine status; (g) psychological impact measured by the Kessler Depression Scale (K-10) (20), and fear measured by the Fear of COVID-19 Scale (FCV) (21); (h) coping strategies measured by the Brief Resilient Coping Scale (BRCS) (22); and (j) access to mental health resources (in the last four weeks) (see Appendix 1).

Study Tools

Kessler Psychological Distress Scale (K10)

The K10 scale is a 10-item self-rated questionnaire that measures distress based on depressive and anxiety symptoms. Each item has five possible answers (none of the time = 1, a little of the time = 2, some of the time = 3, most of the time = 4, all of the time = 5) allowing for a total score of 50. A score of 10–15 is likely to be well, 16–29 is medium risk for anxiety or depression and 30–50 is high risk for anxiety or depressive symptoms (20). Cronbach's alpha for this tool was 0.902, which was satisfactory.

Fear of COVID-19 Scale (FCV-19S)

The FCV-19S is a seven-item scale that assesses fear of COVID-19 among the general population. Each item has five possible answers (strongly disagree = 1 disagree = 2 neutral = 3 agree = 4 strongly agree = 5) allowing for a maximum score of 35, a score of 7-22 is considered low fear and 23–35 is considered high fear of COVID-19 (21). Cronbach's alpha for this tool was 0.82, which was satisfactory.

Brief Resilient Coping Scale (BRCS)

The BRCS is a 4-item scale that measures a psychological well-being construct: resilience. Each item is a 5-point response (does not describe me at all = 1, does not describe me = 2, neutral = 3, describes me = 4, describes me very well = 5). The maximum possible score is 20, and it is categorized into low resilience (score 4–13), medium resilience (score 14–16) and high resilience (Score 17–20) (22). Cronbach's alpha for this tool was 0.758, which was satisfactory.

Sample Size Calculation

All participants fulfilling the inclusion criteria were invited to participate. Considering Germany's population of 84 million according to World Population Prospects (23), the prevalence of lifetime mental health issues amongst Germans was 31.1% (24), at 95% confidence intervals, margin of error (5%), and 80% power, the required sample size was 329. The sample size was calculated using Open Epi Info software version 7.2. Convenient sampling was used to recruit the study participants by following snowball sampling.

Ethics

Ethical approval was obtained from the Research Ethical Committee (REC) of the Ulm University (Ethical Approval Number 448/20 – FSt/Sta).

Statistical Analysis

International Business Machines Corporation (IBM) Statistical Package for the Social Sciences (SPSS) statistics software version 25 was used for data analysis. Descriptive analyses were conducted and followed by inferential analyses. Continuous variables were presented as mean ± standard deviation (SD), while categorical variables were presented as numbers and percentages. Internal consistency of the instruments was calculated using Cronbach's alpha. The study outcomes were categorized into binary variables as follows: K-10 score was categorized into low (score 10–15) and moderate to very high (score 16–50), FCV-19S score was categorized into low (score 7–21) and high (score 22–35) and BRCS score was defined into low (score 4–13) and medium to high (score 14–20) resilient copers. Univariate and multivariate logistic regression (adjusted for age, gender, born in Germany, living status, employment status, level of education) were performed to explore the association between population characteristics and the study's outcomes. Odds ratios (ORs), adjusted odds ratios (AORs) and 95% confidence intervals (95% CIs) were obtained. Firth logistic regression with penalized maximum likelihood was used for fear of COVID-19 outcome as the number of events was relatively low for the number of adjusted variables. To measure the association between distress, fear and coping, partial rank correlation was conducted on the overall score as a continuous variable for each scale. This was done after controlling for potential confounding factors (age, gender, born in Germany, living status, employment status and level of education). P values less than 0.05 were considered statistically significant.

Results

Population Characteristics

A total of 474 people participated in the study. The mean age of the participants was 33.6 (13.3) years, and 327 (69%) were females. Most of them were born in Germany (89.9%, n=426), and around half lived with family members (48.5%, n = 230). Two-thirds (62.4%, n = 296) of the participants had a source of income during the pandemic, and only 2.1% (n = 10) had their jobs affected by the pandemic. Half of the participants (57%, n = 270) reported change in the employment situation, and half of them (49.4%, n = 196) had higher perceived distress due to that change. About half participants (47.3%, n = 224) self-identified as essential service workers and 54.6% (n = 259) reported being healthcare workers. Only 7.4% (n = 35) participants reported having psychiatric or mental health issues, although a quarter of the participants (24.1%, n = 114) perceived their mental health status as poor to fair. Table 1 shows the characteristics of included participants, and Tables 2–4 shows multivariate analyses of psychological distress, fear, and coping.

Table 1

CharacteristicNo.%
Age474
Mean (± SD)33.6 ± 13.32
Age groups474
18–2923248.9
30–5922046.4
>60224.6
Gender474
Female32769.0
Born in Germany474
Yes42689.9
Living status474
Live with family members23048.5
Live with non-family members14530.6
Live alone9920.9
Highest educational/vocational qualification474
Secondary/Higher Secondary/Grade 7 to 1218839.7
Certificate/Diploma/Trade qualifications8317.5
Bachelor/Masters/PhD20342.8
Current employment condition474
Unemployed/Housewife/Homemaker/Home duties (No source of income)16835.4
Jobs affected by COVID-19 (lost job/working hours reduced/afraid of job loss)102.1
Have an income source (employed/Government benefits)29662.4
Perceived distress due to change of employment status397
A little to none20150.6
Moderate to a great deal19649.4
Improved working situation due to change of employment status406
A little to none35286.7
Moderate to a great deal5413.3
Self-identification as frontline or essential service worker474
Yes22447.3
Self-identification as a healthcare worker474
Yes, doctor6413.5
Yes, nurse183.8
Yes, another healthcare worker17737.3
COVID-19 impacted the financial situation474
Yes, impacted positively439.1
Yes, impacted negatively6714.1
Affected by the change in a financial situation474
Not at all19841.8
Unsure5311.2
Somewhat13027.4
A great extent398.2
Co-morbidities474
Psychiatric/Mental health problem357.4
Other co-morbidities*10221.5
Co-morbidities474
Single co-morbidity9820.7
Multiple co-morbidities439.1
Perceived status of own mental health474
Good to Excellent36075.9
Poor to Fair11424.1
Smoking474
Ever smoker (Daily/Nondaily/Ex)5912.4
Increased smoking over the last 6 months59
Yes2441.7
Current alcohol drinking (last 4 weeks)474
Yes20042.2
Increased alcohol drinking over the last 6 months200
Yes4623
Contact with known/suspected case of COVID-19474
Unsure5110.8
Yes, I had indirect contact7816.5
Yes, provided direct care10522.2
Experience related to COVID-19 pandemic474
No known exposure to COVID-1933470.5
Treated in hospital / Ordered to quarantine/ Tested positive / Lived with someone who had COVID-1912325.9
Traveled overseas and had to quarantine173.6
Self-identification as a patient (visited a healthcare provider in the last 6 months)474
Yes22447.3
If yes, which type of healthcare did you use? (Multiple responses)268
Visit a primary care physician or health care professional18468.7
Telehealth consultation (online or by phone) with a general practitioner, specialist, or health professional103.7
I was tested for COVID-19 at a special test site4215.7
Hospital emergency room83.0
I was in a hospital for other reasons249.0
Healthcare service used to overcome COVID-19 related stress in the last 6 months474
Yes255.3
If yes, which type of healthcare did you receive? (Multiple responses)61
Consulted a primary care physician2642.6
Consulted a psychologist1727.9
Consulted a psychiatrist46.6
Used specialty mental health services (hospital, community mental health services, inpatient mental health services)23.3
Used mental health resources (pamphlets, brochures, leaflets, and books provided by mental health staff and distributed at hospital)34.9
Mental health resources used and available through media (methods and techniques of psychological support provided by psychologists through online media, television news, or various online and social networking platforms)58.2
Mental health support services used (including mental health program)46.6

Baseline demographic characteristics of the participants (N = 474).

Data are presented as the mean and standard deviation (SD) or number (n) and percentage (%).

COVID-19, Coronavirus Disease 19; K-10, Kessler Depression Scale; FCV, Fear of Coronavirus-19 Scale; BRCS, Brief Resilient Coping Scale.

*

Cardiac diseases/ Stroke/ Hypertension/ Hyperlipidaemia/ Diabetes/ Cancer/ Chronic respiratory illness.

Table 2

CharacteristicsLow distressHigh distressUnadjusted analysisAdjusted analysis*
n%n%pORs95% CIspAORs95% CIs
Age groups93381
18–29239.920990.1RefRef
30–595826.416273.6<0.0010.310.180.520.0290.410.180.91
>601254.51045.5<0.0010.090.040.240.0000.100.030.33
Gender93381
Male5134.79665.3RefRef
Female4212.828587.2<0.0013.612.265.760.0004.042.416.77
Born in the same country of residence93381
No714.64185.4RefRef
Yes8620.234079.80.3571.480.643.420.0550.410.161.02
Living status93381
Live with family members6327.416772.6RefRef
Live with non-family members1611.012989.0<0.0013.041.685.510.5301.320.553.17
Live alone1414.18585.90.0112.291.214.320.0412.051.034.01
Highest educational/vocational qualification93381
Secondary/Higher Secondary/Grade 7 to 122111.216788.8RefRef
Certificate/Diploma/Trade qualifications2327.76072.30.0010.330.170.640.0940.490.211.13
Bachelor/Masters/PhD4924.115475.90.0010.400.230.690.3170.680.321.44
Current employment condition93381
Unemployed/Housewife/Home maker/Home duties (No source of income)2213.114686.9RefRef
Jobs affected by COVID-19 (lost job/working hours reduced/afraid of job loss)110.0990.00.7781.360.1611.230.2723.560.3734.23
Have an income source (employed/Government benefits)7023.622676.40.0070.490.290.820.5221.270.612.63
Perceived distress due to change of employment status68329
A little to none4723.415476.6RefRef
Moderate to a great deal2110.717589.30.0012.541.454.440.0012.851.545.27
Improved working situation due to change of employment status72334
A little to none6518.528781.5RefRef
Moderate to a great deal713.04787.00.3271.520.663.520.7351.170.482.85
Self-identification as a frontline or essential service worker93381
No4417.620682.4RefRef
Yes4921.917578.10.2430.760.481.200.6561.150.632.08
Self-identification as a healthcare worker93381
No3717.217882.8RefRef
Yes, doctor1625.04875.00.1660.620.321.220.1991.800.734.42
Yes, nurse211.11688.90.511.660.377.540.3852.080.4010.79
Yes, other healthcare worker3821.513978.50.2870.760.461.260.5380.820.431.55
COVID-19 impacted financial situation93381
No impact8022.028478.0RefRef
Yes, impacted positively614.03786.00.2281.740.714.260.2861.740.634.78
Yes, impacted negatively710.46089.60.0352.411.065.490.0063.611.459.00
Affected by the change in financial situation79341
Not at all5527.814372.2RefRef
Unsure611.34788.70.0173.011.227.450.0462.781.027.61
Somewhat1612.311487.70.0012.741.495.040.0013.341.676.68
A great extent25.13794.90.0087.121.6630.350.0097.511.6633.94
Co-morbidities93381
No6619.627180.4RefRef
Psychiatric/Mental health problem38.63291.40.1232.600.778.740.0952.970.8310.64
Other co-morbidities*2423.57876.50.3880.790.471.350.6220.860.481.56
Co-morbidities93381
No6419.226980.8RefRef
Single co-morbidity2424.57475.50.2560.730.431.250.4000.770.421.42
Multiple co-morbidities511.63888.40.2321.810.684.780.0423.121.049.33
Perceived status of own mental health93381
Good to Excellent9325.826774.2Ref
Poor to Fair00.0114100.00.00280.044.931,300.40No. is too low to estimate
Smoking93381
Never smoker8821.232778.8RefRef
Ever smoker (Daily/Nondaily/ Ex)58.55491.50.0272.911.137.490.0074.131.4811.58
Increased smoking over the last 6 months554
No514.33085.7Ref
Yes00.024100.00.148.830.46167.700.1126.690.70886.78
Current alcohol drinking (last 4 weeks)93381
No5118.622381.4RefRef
Yes4221.015879.00.5180.860.551.360.9581.100.611.70
Increased alcohol drinking over the last 6 months42158
No3925.311574.7RefRef
Yes36.54393.50.0114.861.4316.550.0194.771.2917.61
Contact with known/suspected case of COVID-1993381
No5824.218275.8Ref
Unsure1019.64180.40.4861.310.622.770.5421.300.563.02
Yes, had indirect contact1012.86887.20.0372.171.054.480.0432.261.034.98
Yes, provided direct care1514.39085.70.0411.911.033.560.0172.331.174.68
Experience related to COVID-19 pandemic93381
No known exposure to COVID-198024.025476.0RefRef
Treated in hospital / Ordered to quarantine/ Tested positive / Lived with someone who had Covid-19118.911291.10.0013.211.646.260.0092.591.265.30
Traveled overseas and had to quarantine211.81588.20.2602.360.5310.550.4281.890.399.06
Self-identification as a patient (visited a healthcare provider in the last 6 months)93381
No5421.619678.4RefRef
Yes3917.418582.60.2521.310.832.070.2711.340.802.26
Level of fear of COVID-19 (FCV- 19S categories)93381
Low (score 7–21)9120.235979.8RefRef
High (score 22–35)28.32291.70.1702.790.6412.080.1423.260.6715.74
Level of coping (BRCS categories)93381
Low resilient coping (score 4– 13)2415.213484.8RefRef
Medium to high resilient coping (score 14–20)6921.824778.20.0870.640.391.070.0970.610.341.09
Healthcare services used to overcome COVID-19 related stress in the last 6 months93381
No9320.735679.3RefRef
Yes00.025100.00.00413.371.841,702.700.00613.581.771,752.73

Factors associated with high psychological distress among the study population (based on K10 scoring).

Data are presented as number (n) and percentage (%). P ≤ 0.05 were considered statistically significant.

ORs, Odds Ratio; AOR, Adjusted Odds Ratio; CI, Confidence Interval; Ref, Reference category; COVID-19, Coronavirus Disease 19; K-10, Kessler Depression Scale; FCV, Fear of Coronavirus-19 Scale; BRCS, Brief Resilient Coping Scale.

*

Adjusted for Age, Gender, born in Germany, living status, employment status and level of education.

Bold indicated statistical significance.

Psychological Distress

After adjusting for potential confounders, multivariate analyses showed that being a female, living alone, those with distress due to employment change, worsened financial situation, having multiple co-morbidities, smoking, increased alcohol consumption over the last 6 months, contact with COVID-19 case whether direct or indirect, direct experience of COVID-19 and healthcare use to overcome pandemic stress in the last 6 months were associated with moderate to very high levels of psychological distress (Table 2).

Fear of COVID-19

Multivariate logistic regression showed that being over 60, living with non-family members, those having a diploma or a trade qualification, those with single or multiple comorbidities, perceived mental health status as poor to fair, direct experience of COVID-19, visiting a health care provider in the past 6 months and using healthcare service to overcome pandemic related stress in the last 6 months were associated with higher levels of fear of COVID-19 (Table 3).

Table 3

CharacteristicsLow levels of fearHigh levels of fearUnadjusted analysesAdjusted analysis
n%n%pORs95% CIspAORs95% CIs
Age groups45024
18–2922396.193.9RefRef
30–5920995.0115.00.5641.300.533.210.0913.400.8417.49
> ≥601881.8418.20.0095.511.5419.650.00213.932.6684.21
Gender45024
Male14498.032.0RefRef
Female30693.6216.40.0573.290.9711.220.0572.740.9710.44
Born in the same country of residence45024
No4797.912.1RefRef
Yes40394.6235.40.3402.680.3520.320.6511.460.3413.62
Living status45024
Live with family members22196.193.9RefRef
Live with non-family members13693.896.20.3161.630.634.200.0414.121.0617.39
Live alone9393.96.13.90.3951.580.554.580.1642.190.716.35
Highest educational/vocational qualification45024
Secondary/Higher Secondary/Grade 7 to 1217894.7105.3RefRef
Certificate/Diploma/Trade qualifications7792.867.20.5401.390.493.950.0347.751.1940.49
Bachelor/Masters/PhD19596.183.90.5170.730.281.890.7561.210.374.08
Current employment condition45024
Unemployed/Housewife/Home maker/Home duties (No source of income)1619.875.1RefRef
Jobs affected by COVID-19 (lost job/working hours reduced/afraid of job loss)880.0220.00.0475.751.0332.250.9780.980.293.23
Have an income source (employed/Government benefits)28194.9155.10.6611.230.493.070.4510.650.212.01
Perceived distress due to change of employment status37522
A little to none18994.0126.0RefRef
Moderate to a great deal18694.9105.10.7060.850.362.010.6160.790.311.96
Improved working situation due to change of employment status38422
A little to none33294.3205.7RefRef
Moderate to a great deal5296.323.70.5530.640.152.810.9321.060.213.64
Self-identification as a frontline or essential service worker45024
No23794.8135.2RefRef
Yes21395.1114.90.8860.940.412.150.9821.010.372.93
Self-identification as a healthcare worker45024
No20193.5146.5RefRef
Yes, doctor6398.411.60.1570.230.031.770.3450.420.042.41
Yes, nurse1583.3316.70.1262.870.7411.110.4531.870.349.02
Yes, other healthcare worker17196.663.40.1690.500.191.340.1210.410.131.27
COVID-19 impacted financial situation45024
No impact34995.9154.1RefRef
Yes, impacted positively4093.037.00.3951.750.486.290.1842.480.617.85
Yes, impacted negatively6191.069.00.0992.290.866.130.1632.300.706.66
Affected by the change in financial situation45024
Not at all18894.9105.1RefRef
Unsure5196.223.80.7000.740.163.470.9400.940.163.76
Somewhat12495.464.60.8580.910.322.570.8960.930.312.63
A great extent3692.337.70.5111.570.415.980.3401.940.466.64
Co-morbidities45024
No32095.0175.0RefRef
Psychiatric/Mental health problem3394.325.70.8641.140.255.160.4291.840.346.72
Other co-morbidities*9795.154.90.9540.970.352.700.5901.330.443.55
Co-morbidities45024
No32697.972.1RefRef
Single co-morbidity8990.899.20.0034.711.7113.000.0015.762.0117.44
Multiple co-morbidities3581.4818.6<0.00110.653.6431.12<0.0019.482.8932.19
Perceived status of own mental health45024
Good to Excellent35097.2102.8RefRef
Poor to Fair10087.71412.3<0.0014.902.1111.37<0.0015.832.4115.02
Smoking45024
Never smoker39294.5235.5RefRef
Ever smoker (Daily/Nondaily/ Ex)5898.311.70.2350.290.042.220.1670.350.041.46
Increased smoking over the last 6 months581
No35100.000.0RefRef
Yes2395.814.20.3614.530.18116.040.3343.480.27276.80
Current alcohol drinking (last 4 weeks)45024
No25894.2165.8RefRef
Yes19296.084.00.3700.670.281.600.3770.680.271.59
Increased alcohol drinking over the last 6 months1928
No14795.574.5RefRef
Yes4597.812.20.4810.470.063.900.9280.920.104.72
Contact with known/suspected case of COVID-1945024
No23095.8104.2RefRef
Unsure5098.012.00.4640.460.063.680.9420.940.104.36
Yes, had indirect contact7089.7810.30.0502.631.006.920.0572.640.977.07
Yes, provided direct care10095.254.80.8031.150.383.450.5131.470.444.46
Experience related to COVID-19 pandemic45024
No known exposure to COVID-1932296.4123.6RefRef
Treated in hospital / Ordered to quarantine/ Tested positive / Lived with someone who had Covid11291.1118.90.0252.641.136.140.0213.091.198.12
Traveled overseas and had to quarantine1694.115.90.6301.680.2113.710.1494.950.4926.65
Self-identification as a patient (visited a healthcare provider in the last 6 months)45024
No24497.662.4RefRef
Yes20692.0188.00.0083.551.399.120.0242.811.147.77
Level of psychological distress (K10 categories)45024
Low (score 10–15)9197.822.2Ref
Moderate to Very High (score 16–50)35994.2225.80.1702.790.6412.080.1622.610.7114.59
Level of coping (BRCS categories)45024
Low resilient coping (score 4–13)14793.0117.0Ref
Medium to high resilient coping (score 14–20)30395.9134.10.1870.570.251.310.1900.560.231.35
Healthcare services used to overcome COVID-19 related stress in the last 6 months45024
No43396.4163.6Ref
Yes1768.0832.0<0.00112.744.7933.84<0.00115.264.8848.84

Factors associated with high levels of fear of COVID-19 among the study population (based on FCV-19S scoring).

Data are presented as number (n) and percentage (%). P-values ≤ of 0.05 were considered statistically significant.

ORs, Odds Ratio; AOR, Adjusted Odds Ratio; CI, Confidence Interval; Ref, Reference category; COVID-19, Coronavirus Disease 19; K-10, Kessler Depression Scale; FCV, Fear of Coronavirus-19 Scale; BRCS, Brief Resilient Coping Scale.

*

Adjusted for Age, Gender, born in Germany, living status, employment status and level of education.

Bold indicated statistical significance.

Coping Strategies

Multivariate analyses revealed that having an income source and being a healthcare worker were associated with higher levels of coping. Conversely, higher levels of education, distress due to change in employment, worsened financial situation due to the pandemic, and perceived status of mental health as poor to fair were the factors that predicted lower levels of coping amongst the study participants (Table 4).

Table 4

CharacteristicsLow levels of copingHigh levels of copingUnadjusted analysisAdjusted analysis
n%n%pORs95% CIspAORs95% CIs
Age groups158316
18–298134.915165.1RefRef
30–597132.314967.70.5531.130.761.660.8300.940.521.69
>60627.31672.70.4721.430.543.800.6871.250.433.66
Gender158316
Male4530.610269.4RefRef
Female11334.621465.40.4000.840.551.270.5470.870.561.36
Born in the same country of residence158316
No1837.53062.5RefRef
Yes14032.928667.10.5191.230.662.280.7881.090.572.11
Living status158316
Live with family members6930.016170.0RefRef
Live with non-family members4833.19766.90.5280.870.551.350.7531.110.592.06
Live alone4141.45858.60.0450.610.370.990.0630.610.361.03
Highest educational/vocational qualification158316
Secondary/Higher Secondary/Grade 7 to 126132.412767.6RefRef
Certificate/Diploma/Trade qualifications3339.85060.20.2450.730.431.240.0130.430.220.83
Bachelor/Masters/PhD6431.513968.50.8461.040.681.600.0340.530.290.95
Current employment condition158316
Unemployed/Housewife/Home maker/Home duties (No source of income)7343.59556.5RefRef
Jobs affected by COVID-19 (lost job/working hours reduced/afraid of job loss)440.0660.00.8311.150.314.240.5251.560.406.08
Have an income source (employed/Government benefits)8127.421572.6<0.0012.041.373.04<0.0013.331.905.87
Perceived distress due to change of employment status116236
A little to none5326.414873.6RefRef
Moderate to a great deal8141.311558.70.0020.510.330.780.0030.510.330.80
Improved working situation due to change of employment status140266
A little to none11633.023667.0RefRef
Moderate to a great deal2444.43055.60.10.610.341.100.1890.670.361.22
Self-identification as a frontline or essential service worker158316
No9738.815361.2RefRef
Yes6127.216372.80.0081.691.152.500.3701.260.762.08
Self-identification as a healthcare worker158316
No9041.912558.1RefRef
Yes, doctor2437.54062.50.5341.200.682.130.4820.760.361.63
Yes, nurse527.81372.20.2491.870.645.440.5341.450.454.64
Yes, other healthcare worker3922.013878.0<0.0012.551.633.980.0161.911.133.24
COVID-19 impacted financial situation158316
No impact11431.325068.7RefRef
Yes, impacted positively1432.62967.40.8690.950.481.860.6690.860.431.73
Yes, impacted negatively3044.83755.20.0330.560.330.960.0230.510.290.91
Affected by the change in financial situation145275
Not at all6130.813769.2RefRef
Unsure2343.43056.60.0870.580.311.080.0910.570.291.10
Somewhat3728.59371.50.6501.120.691.820.8431.050.631.75
A great extent2461.51538.5<0.0010.280.140.57<0.0010.230.110.47
Co-morbidities158316
No11132.922667.1RefRef
Psychiatric/Mental health problem1748.61851.40.0670.520.261.050.0610.490.241.03
Other co-morbidities*3029.47270.60.5041.180.731.910.9540.990.601.63
Co-morbidities158316
No10230.623169.4RefRef
Single co-morbidity3838.86061.20.1310.700.441.110.1100.660.401.10
Multiple co-morbidities1841.92558.10.1400.610.321.170.1440.590.291.20
Perceived status of own mental health158316
Good to Excellent8724.227375.8RefRef
Poor to Fair7162.34337.7<0.0010.190.120.30<0.0010.200.130.33
Smoking158316
Never smoker13332.028268.0RefRef
Ever smoker (Daily/Nondaily/ Ex)2542.43457.60.1170.640.371.120.1100.620.341.12
Increased smoking over the last 6 months2534
No1645.71954.3RefRef
Yes937.51562.50.5311.400.494.050.3491.990.478.38
Current alcohol drinking (last 4 weeks)158316
No8932.518567.5RefRef
Yes6934.513165.50.6450.910.621.340.3750.830.551.25
Increased alcohol drinking over the last 6 months69131
No5233.810266.2RefRef
Yes1737.02963.00.6900.870.441.730.4230.740.351.55
Contact with known/suspected case of COVID-19158316
No8535.415564.6RefRef
Unsure2447.12752.90.1210.620.341.140.1530.640.341.18
Yes, had indirect contact1924.45975.60.0721.700.953.040.0771.700.953.06
Yes, provided direct care3028.67571.40.2151.370.832.260.2901.320.792.20
Experience related to COVID-19 pandemic158316
No known exposure to COVID- 1911634.721865.3RefRef
Treated in hospital / Ordered to quarantine/ Tested positive / Lived with someone who had Covid-193830.98569.10.4421.190.761.860.3781.230.781.93
Traveled overseas and had to quarantine423.51376.50.3481.730.555.420.2781.920.596.20
Self-identification as a patient (visited a healthcare provider in the last 6 months)158316
No7931.617168.4RefRef
Yes7935.314564.70.3980.850.581.240.4460.860.581.27
Level of fear of COVID-19 (FCV- 19S categories)158316
Low (score 7–21)14732.730367.3RefRef
High (score 22–35)1145.81354.20.1870.570.251.310.2010.550.221.38
Level of distress K-10 Score categories)158316
Low (score 10–15)2425.86974.2RefRef
Moderate to Very High (score 16–50)13435.224764.80.0870.640.391.070.1300.640.361.14
Healthcare services used to overcome COVID-19 related stress in the last 6 months158316
No14632.530367.5RefRef
Yes1248.01352.00.1150.520.231.170.1840.550.231.33

Factors associated with coping among the study population (based on BRCS scoring).

Data are presented as number (n) and percentage (%). P ≤ of 0.05 were considered statistically significant.

ORs, Odds Ratio; AOR, Adjusted Odds Ratio; CI, Confidence Interval; Ref, Reference category; COVID-19, Coronavirus Disease 19; K-10, Kessler Depression Scale; FCV, Fear of Coronavirus-19 Scale; BRCS, Brief Resilient Coping Scale.

*

Adjusted for Age, Gender, Born in Germany, living status, employment status and level of education.

Bold indicated statistical significance.

Association Between Psychological Distress, Coping and Fear of COVID-19

The K-10 distress score correlated significantly with the FCV-19S score (spearman's r = 0.331, p < 0.001), the BRCS score showed an inverse relationship with the distress and fear scores (spearman's r = −0.276 and – 0.173, p < 0.001). People with higher distress had higher levels of fear of COVID-19 and lower coping. On the other hand, people with better coping had lower distress and fear of COVID-19 (Table 5).

Table 5

VariablesDistressFear of COVIDCoping
Distress10.331*−0.276*
Fear of COVID1−0.173*
Coping1

Association between psychological distress, coping and fear of COVID-19 using spearman's partial rank correlation.

Controlling for Age, Gender, born in Germany, living status, employment status and level of education.

*

Significant at p < 0.001 level.

Discussion

Moderate to very high levels of psychological distress were associated with being a female, living alone, suffering employment change or worsening the financial situation, and poor mental health, smoking and alcohol consumption. Higher levels of fear of COVID-19 were markable in people of ≥60 years, or those with comorbidities or poor mental health. Having an income source and being a healthcare worker was associated with higher levels of coping.

During the COVID-19 pandemic, the course of psychological disturbances which were associated with psychological distress, fear, and coping strategies among the community members including healthcare workers across the world were well-studied (25). Our study can be seen as a supplement to a global cross-sectional study involving 17 countries (10). The same online instruments were used like the prior global study led by the last author (MAR), but the current study adapted German language. In this study, more females participated than males, which was in line with other similar German studies (16, 26–28) in the first wave of the pandemic, and also supports an Australian (10), Egyptian (15), Bangladeshi (14), Malaysian (13), and global study (10). A possible explanation might be that women were more inclined to share their experiences by participating in the study or women were more impacted due to the pandemic, lockdown or financially that prompted them to participate in the study. The mean age (33.6 years) showed that the study participants of this study were younger than those who were included in similar German studies (16, 26, 27).

For the issue of psychological distress in this study, there were more participants with moderate to very high distress, which was in line with the results of previous studies conducted in Germany (27), Australia (10), Malaysia (13), Bangladesh (14), Hong Kong (19) and globally (10), as well as other studies (28–31). Furthermore, similar to this study, previous studies (10, 13, 14, 27) also reported that females and younger respondents had higher psychological distress compared to the reference group. A previous study showed that women seemed to be more impacted by the pandemic in terms of wellbeing than men (32). According to the findings of this study, the common factors associated with moderate to very high levels of psychological distress were being females, those with change in the employment status, and worsening the financial situation, which was supported by earlier evidence (10, 13, 14). Similarly, Hetkamp and Schweda (33) found that respondents reported reduced sleep quality and moderate generalized anxiety and psychological burdens. A possible explanation could be that participants might experience crucial interference with their everyday lives, which was likely to increase psychological distress while the accessibility of conventional mental health care was limited (25). It could also be assumed that uncertainties about the novel coronavirus, its progression, and variable nature of pandemic, and availability and access to the varied range of evidence also could contribute to the report of various country-wise reports of moderate to a high level of psychological stress. There was also a higher correlation between potential contact with COVID-19 cases, whether direct or indirect, experience with the pandemic, and healthcare use to overcome pandemic stress.

Regarding the issue of fear in this study, there were more participants with low fear, which supports studies conducted in Bangladesh (14), Australia (10), Malaysia (13), and globally (10). That indicated habituation to the threatening situation of the pandemic. However, generalized anxiety could remain elevated over time due to the ongoing nature of pandemic (33). Similarly, a largescale German study among 3,500 randomly selected participants reported mental health (anxiety, depression) impact shortly after the lockdown came into effect (34). This study identified the factors associated with higher fear of COVID-19, which were similar as reported in the earlier studies: being female, and middle-aged, or over 60 (10, 13, 14). Being born in the same country of residence, and having at least a trade/certificate/diploma or bachelor degree were associated with higher levels of fear in this study, which were similar to the study conducted in Bangladesh (14).

Regarding the issue of coping in this study, there were more participants with high levels of coping, which is supported by the previous Malaysian (13) and the global study (10). High resilience coping could be explained by the long period of pandemic in Germany. Having an income source and being a healthcare worker were associated with higher levels of coping, findings of which were different compared to the previous studies (10, 13, 14). Finally, results showed that the COVID-19 pandemic and subsequent lockdown measures in early 2020 might slow the spread of the virus. However, those restrictions forced a sudden and dramatic change to the daily routines of community people, although not all individuals were impacted in the similar way. Some situational factors such as occupation, family status, financial and health impact, personality traits could influence individuals' experience during the ongoing COVID crisis in Germany (35).

This study had few limitations. The participants were included from the Ulm region in Southern Germany, which limits the generalizability across the whole German territory. Furthermore, it wasn't possible to exclude more responses from distressed individuals than non-distressed individuals, potentially resulting in selection bias. Finally, the study findings were limited to individuals who could access to online platforms in order to participate; therefore, there was limited generalizability due to the focus to internet-literate people. However, due to the lockdown measures applied during data collection, an online survey was the only available option to perform this study. One of the most crucial points in our study was collecting the targeted sample size during the pandemic lockdown period. Lastly, this study was the only German study that assessed the factors associated with psychological distress, fear, and coping strategies during the second and third waves of the COVID-19 pandemic. The data collection period coincided with the transition between the second and third waves in Germany, therefore, it was also not unlikely to have increased prevalence of psychological distress amongst the participants who participated in this study.

Conclusions

This study identified levels of psychological distress, fear and coping amongst the community members during the COVID-19 pandemic in the Ulm region in Southern Germany. In addition, several factors and risk groups that were associated with those outcomes, were identified. The identified higher risk groups should be prioritized for receiving mental health support from the relevant healthcare providers such as family physicians and psychiatrists, and automated follow-up reminders could be sent through text messages which would prevent further deterioration of mental health conditions.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Statements

Data availability statement

The original contributions generated for this study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author/s.

Ethics statement

The studies involving human participants were reviewed and approved by the Research Ethical Committee (REC) of the Ulm University (Ethical Approval Number 448/20 – FSt/Sta). The patients/participants provided their written informed consent to participate in this study.

Author contributions

ME had substantial contribution to the conception or design of the study, data collection, and scientific writing of the manuscript. CS-L contributed to the conception and revised the manuscript critically. XW coordinated data collection. KD performed the statistical analysis. MK took part in scientific writing. ER, RA, MD, MG, and BC revised the manuscript critically for important intellectual content. SA, BB, and WC provided critical feedback on the narrative structure and methods and results. MAR conceptualized the study, coordinated data collection, provided critical feedback, and revised the manuscript. All authors contributed to the article and approved the submitted version.

Acknowledgments

We would like to acknowledge the support of the study participants, who donated their valuable time to respond to our survey.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyt.2022.860683/full#supplementary-material

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Summary

Keywords

COVID-19, psychological distress, fear, cross-sectional survey, coping, mental health, Germany

Citation

Elsayed M, Schönfeldt-Lecuona C, Welte XA, Dardeer KT, Kamal MA, Abdelnaby R, Rudek MA, Riedel E, Denkinger M, Gahr M, Connemann BJ, Alif SM, Banik B, Cross W and Rahman MA (2022) Psychological Distress, Fear and Coping Strategies During the Second and Third Waves of the COVID-19 Pandemic in Southern Germany. Front. Psychiatry 13:860683. doi: 10.3389/fpsyt.2022.860683

Received

23 January 2022

Accepted

22 March 2022

Published

25 April 2022

Volume

13 - 2022

Edited by

Mohammadreza Shalbafan, Iran University of Medical Sciences, Iran

Reviewed by

Nabi Nazari, Lorestan University, Iran; Abdorreza Naser Moghadasi, Tehran University of Medical Sciences, Iran

Updates

Copyright

*Correspondence: Mohamed Elsayed Muhammad Aziz Rahman ;

†These authors have contributed equally to this work

This article was submitted to Public Mental Health, a section of the journal Frontiers in Psychiatry

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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