A Comparison of Depression and Anxiety among University Students in Nine Countries during the COVID-19 Pandemic.

Journal of Clinical Medicine Article A Comparison of Depression and Anxiety among University Students in Nine Countries during the COVID-19 Pandemic Dominika Ochnik 1,* , Aleksandra M. Rogowska 2, Cezary Ku´snierz 3, Monika Jakubiak 4, Astrid Schütz 5, Marco J. Held 5, Ana Arzenšek 6, Joy Benatov 7, Rony Berger 8,9, Elena V. Korchagina 10 , Iuliia Pavlova 11 , Ivana Blažková12, Zdeˇnka Koneˇcná13, Imran Aslan 14 , Orhan Çınar 15,16, Yonni Angel Cuero-Acosta 17 and Magdalena Wierzbik-Stro´nska 1   Citation: Ochnik, D.; Rogowska, A.M.; Ku´snierz, C.; Jakubiak, M.; Schütz, A.; Held, M.J.; Arzenšek, A.; Benatov, J.; Berger, R.; Korchagina, E.V.; et al. A Comparison of Depression and Anxiety among University Students in Nine Countries during the COVID-19 Pandemic. J. Clin. Med. 2021,10, 2882. https://doi.org/10.3390/ jcm10132882 Academic Editor: Michele Roccella Received: 20 April 2021 Accepted: 27 June 2021 Published: 29 June 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). 1Faculty of Medicine, University of Technology, 40-555 Katowice, Poland; r[email protected] 2Institute of Psychology, University of Opole, 45-052 Opole, Poland; ar[email protected] 3Faculty of Physical Education and Physiotherapy, Opole University of Technology, 45-758 Opole, Poland; [email protected] 4Faculty of Economics, Maria Curie-Sklodowska University in Lublin, 20-031 Lublin, Poland; [email protected] 5Department of Psychology, University of Bamberg, 96047 Bamberg, Germany; [email protected] (A.S.); mar[email protected] (M.J.H.) 6Faculty of Management, University of Primorska, 6101 Koper, Slovenia; [email protected] 7Department of Special Education, University of Haifa, Haifa 3498838, Israel; [email protected] 8The Center for Compassionate Mindful Education, Tel Aviv 69106, Israel; bergerr[email protected] 9Bob Shapell School of Social Work, Tel-Aviv University, Tel Aviv 69978, Israel 10 Institute of Industrial Management, Economics and Trade, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia; elena.kor[email protected] 11 Department of Theory and Methods of Physical Culture, Lviv State University of Physical Culture, 79007 Lviv, Ukraine; [email protected] 12 Department of Regional and Business Economics, Mendel University in Brno, 613 00 Brno, Czech Republic; [email protected] 13 Faculty of Business and Management, Brno University of Technology, 612 00 Brno, Czech Republic; [email protected].cz 14 Health Management Department, Bingöl University, Bingöl 12000, Turkey; [email protected] 15 Faculty of Economics and Administrative Sciences, Ataturk University, Erzurum 25240, Turkey; [email protected] 16 Faculty of Economics and Administrative Sciences, A˘grı ˙ Ibrahim Çeçen University, A˘grı 04000, Turkey 17 School of Management, Universidad del Rosario, Bogotá111711, Colombia; [email protected] *Correspondence: [email protected] Abstract: The mental health of young adults, particularly students, is at high risk during the COVID-19 pandemic. Thepurposeofthisstudywastoexaminedifferencesinmentalhealthbetweenuniversitystudents in nine countries during the pandemic. The study encompassed 2349 university students (69% female) from Colombia, the Czech Republic (Czechia), Germany, Israel, Poland, Russia, Slovenia, Turkey, and Ukraine. Participants underwent the following tests: Patient Health Questionnaire (PHQ-8), Generalized Anxiety Disorder (GAD-7), Exposure to COVID-19 (EC-19), Perceived Impact of Coronavirus (PIC) on students’ well-being, Physical Activity (PA), and General Self-Reported Health (GSRH). The one-way ANOVA showed significant differences between countries. The highest depression and anxiety risk occurred in Turkey, the lowest depression in the Czech Republic and the lowest anxiety in Germany. The χ2 independence test showed that EC-19, PIC, and GSRH were associated with anxiety and depression in most of the countries, whereas PA was associated in less than half of the countries. Logistic regression showed distinct risk factors for each country. Gender and EC-19 were the most frequent predictors of depression and anxiety across the countries. The role of gender and PA for depression and anxiety is not universal and depends on cross-cultural differences. Students’ mental health should be addressed from a cross-cultural perspective. Keywords: mental health; anxiety; depression; students; COVID-19; general self-reported health; physical activity; gender; cross-national study J. Clin. Med. 2021,10, 2882. https://doi.org/10.3390/jcm10132882 https://www.mdpi.com/journal/jcm J. Clin. Med. 2021,10, 2882 2 of 22 1. Introduction The newly-emerged coronavirus is responsible for a highly viral and infectious disease resulting in a severe acute respiratory syndrome (SARS-Cov-2). The pandemic began in December 2019 and has subsequently spread rapidly worldwide [1]. The first wave of the coronavirus disease (COVID-19) pandemic entered a global stage in the spring of 2020 and prevailed until the summer [ 2 ]. The COVID-19 pandemic has forced the introduction of preventive restrictions. Due to the restrictions, social isolation was experienced on an unprecedented scale globally. This contributed to the deterioration of mental health [ 3 – 7 ]. The COVID-19 pandemic is also perceived as the deepest global economic recession in the past eight decades [ 8 ]. Considering increased levels of anxiety and depression during previous economic crises [ 9 ], the financial instability caused by the pandemic can become a crucial risk factor in relation to mental health deterioration. Research has also shown a linkage between lower social status and mental health issues [10,11] . Therefore, due to financial instability, the current pandemic can affect the mental health of individuals who are not at a serious risk of becoming infected with COVID-19. Recent cross-national studies revealed that mental health deterioration associated with the pandemic is not exclusively limited to individuals who have been infected but extends to the general population [12]. Young adults are highly vulnerable to mental health deterioration during the COVID-19 pandemic [ 13 – 15 ] even though they are the least susceptible to the COVID-19 infection [ 16 ]. Young age is one of the key risk factors as the prevalence of depressive symptoms in early adulthood is high and dynamic and mediated by several environmental and biological factors [ 17 ]. Mental health issues are common in the student population—more than onethird of students experienced some form of mental health problem in the pre-pandemic period [ 18 ]. Despite the fact that students are a socially privileged population, they have been at a higher depression risk compared to the general population, even in the prepandemic period [ 19 , 20 ]. Students’ physical health status is also relatively poor when compared to their non-studying working peers or the overall population [ 21 , 22 ]. Based on the meta-analysis of studies conducted between 1990 and 2010, the prevalence of depression among students amounted to 30.6% on average [ 19 ] compared to 12.9% in the global population based on data from 30 countries collected between 1994 and 2014 [ 20 ]. Financial difficulties constitute a risk factor for the increase of anxiety and depression levels. They can also lead to poor academic performance [ 23 ]. Financial concerns are not the only factor affecting students’ mental health issues. They can also be influenced by [ 24 ] academic pressure and demanding workloads [ 25 ], student mistreatment and abuse [ 26 ] and worries about health [ 27 ]. Students are particularly susceptible to affective disorders due to high social expectations as they are deemed to represent the future of a community [ 28 ]. Research showed that during the ongoing pandemic, student status (particularly being a student on the first-cycle of studies) is a relevant risk factor for mental health issues [ 29 – 32 ]. Social isolation during the COVID-19 pandemic revealed a higher experience of insecurity concerning housing and employment opportunities [ 33 ], smaller living space and lower levels of social interaction in young adults compared to adults [ 4 , 34 ]. Academic stress and virtual learning are also crucial risk factors [ 35 , 36 ]. According to the International Labor Organization [ 37 ], the education sector has been strongly affected by the COVID-19 pandemic. Therefore, the student population is at a high risk of mental health deterioration during the COVID-19 pandemic and special attention should be paid to research encompassing this cohort. There are several additional risk factors for mental health deterioration during the ongoing pandemic, such as female gender and lower income [ 12 , 31 , 32 , 38 – 41 ], place of residence [ 42 , 43 ], financial and learning-related concerns [ 44 , 45 ] or physical inactivity [ 39 ]. Concerns regarding loved ones, own health, or academic performance were pronounced during the pandemic [ 45 ] and contributed to an increase in anxiety and depression levels [ 44 ]. Students also shifted their main concerns from learning-related to financial and/or health-related matters [ 46 ]. Recent studies showed that exposure to COVID-19-related mat- J. Clin. Med. 2021,10, 2882 3 of 22 ters may increase the risk of anxiety symptoms in students (particularly among men) [ 47 ]. Physical activity constitutes the next key predictor of mental health problems. People who spent more time outside during mobility restrictions reported lower stress and higher positive mental health [ 48 ]. International research showed that social isolation during the COVID-19 pandemic was linked to lower PA intensity. Additionally, eating patterns were less healthy [ 49 ]. Students who were physically inactive (less than 150 min of activity a week) during the COVID-19 pandemic reported higher anxiety and depression compared to the physically active group [ 39 ]. Physical activity turned out to be a stronger predictor of depression than anxiety in students [ 39 ]. An additional issue related to reactions to the pandemic is mixed media coverage and rapid changes in official messages regarding protective behaviors. Misinformation is one of the crucial factors in anxiety response during the pandemic [ 50 ]. Regular searching for additional information concerning the coronavirus turned out to be a risk factor related to the fear of the coronavirus [51]. The number of research papers dedicated to the COVID-19 pandemic has already exceeded the number of studies dedicated to Ebola and H1N1. However, few studies were created via international collaboration [ 52 ]. Additionally, cross-national research regarding mental health during the COVID-19 pandemic frequently refers to the general population [ 12 , 29 – 31 , 53 – 57 ] rather than the student population [ 45 , 58 , 59 ]. Additionally, in articles related to students’ mental health, a binational, rather than cross-national perspective appears more frequently [ 45 , 58 , 59 ]. Cross-national studies concerning mental health during the COVID-19 pandemic indicate that mental health differentiates the general population at a country level [ 12 , 29 – 31 , 53 – 57 ]. Analyses from 78 countries showed a slightly higher depression in Poland compared to the overall mean and an even stronger effect in Turkey [ 30 ]. The Polish general population manifested the highest anxiety and depression rate during the COVID-19 pandemic compared to the sample from China, Spain, Iran, United States of America, Pakistan, and Vietnam [57]. The main aim of this study is to compare depression and anxiety levels among university students in nine countries: Colombia, the Czech Republic (Czechia), Germany, Israel, Poland, Russia, Slovenia, Turkey, and Ukraine during the first wave of the COVID-19 pandemic. Risk factors for depression and anxiety will also be examined separately in each country, including gender, place of residence, level of study, exposure to COVID-19, the perceived impact of COVID-19 on students’ well-being (including qualifications, economic status, and social relationships), physical activity and physical health. 2. Materials and Methods 2.1. Participants The required sample size for each country group was computed a priori by means of G*Power software (Düsseldorf, Germany) [ 60 ]. In order to obtain a medium effect size of Cohen’s W= 0.03 with given 95% power in a 2 × 2 χ2 contingency table, df = 1 (two groups in two categories each, two tailed), α = 0.05, G*Power suggests 145 participants are required in each country group (non-centrality parameter λ = 13.05, critical χ2 = 3.84, power = 0.95). Initially, the total sample consisted of 2453 respondents. However, 104 persons (4.24% of the initial total sample) declined participation (responded “No” to the informed consent). Therefore, the final total sample encompassed 2349 university students from nine countries: Colombia (n= 155), Czechia (n= 310), Germany (n= 270), Israel (n= 199), Poland (n= 301), Russia (n= 285), Slovenia (n= 209), Turkey (n= 310), and Ukraine (n= 310). The present number of university students in each country exceed the required sample size. This may lead to an increase in the power of 0.95 for the statistical analysis. All the respondents were eligible for the study and confirmed their student status. Additionally, respondents who decided not to reveal their gender were excluded from statistical analyses concerning gender (n= 6). Colombian students (n= 155) were recruited from Bogota universities: Del Rosario University (n= 142, 92%) and El Bosque University (n= 13, 8%). The total sample in Czechia was comprised of students recruited from Mendel University in Brno ( n= 310, 100% ), J. Clin. Med. 2021,10, 2882 4 of 22 and in Germany from the University of Bamberg (n= 270, 100% ). The Israeli sample represented the University of Haifa (n= 199, 100%). The Polish sample consisted of 301 students recruited from Maria Curie-Sklodowska University (UMCS) in eastern Poland (n= 149, 48% ) and from the University of Opole in the south of Poland (n= 152, 51%). Russian students were recruited from universities located in Sankt Petersburg: Peter the Great St. Petersburg Polytechnic University (n= 155, 54%), Higher School of Economics (HSE) University (n= 90, 31%), and St. Petersburg State University of Economics and Finance (n= 42, 15%). The total sample in Slovenia was comprised of students recruited from the University of Primorska in Koper (n= 209, 100%). Turkish students were from eleven Turkish universities mostly located in eastern Turkey: Bingol University, Bingöl ( n= 148, 48% ); Atatürk University, Erzurum (n= 110, 35%); Mu˘gla Sıtkı Koçman University, Mu˘gla (n= 35, 11%); A˘grı ˙ Ibrahim Çeçen University, A˘grı (n= 6, 2%); Fırat University, Elazı˘g (n= 3, 0.8%); Kırıkkale University, Kırıkkale (n= 1, 0.3%); Adnan Menderes University, Aydın (n= 1, 0.3%); Ba¸skent University, (n= 3, 1%); Bo˘gaziçi University (n= 1, 0.3%), Dicle University, Diyarbakır (n= 1, 0.3%), and Istanbul University (n= 1, 0.3%). Ukrainian students represented the Lviv State University of Physical Culture (n= 310, 100%). Female students constituted 69% of the sample (n= 1627). Over half of respondents lived in rural areas and small towns (n= 1248; 54%). First cycle studies (Bachelor) were represented by the highest number of students (n= 1843; 78%) compared to the second cycle or higher (n= 506; 22%). The majority of participants studied in the full-time mode (n= 2007; 85%). The mean age of participants was 23 (SD = 4.66). The mean values for depression and anxiety in the total sample were 7.16 (SD = 5.52) and 8.85 (SD = 6.05), respectively. Detailed descriptive statistics for each country are presented in Table S1. All questions included in the Google Forms questionnaire were designated as mandatory. Therefore, participants were unable to omit any response. However, hot-deck imputation was introduced to deal with a low number of missing data (n= 5, 0.02%) in the German sample (study conducted via SoSci Survey [61]). 2.2. Study Design The cross-national study was conducted during the first wave of the COVID-19 pandemic (May–July 2020). The sample consisted of 2349 university students from Colombia, Czechia, Germany, Israel, Poland, Russia, Slovenia, Turkey, and Ukraine. The survey study was conducted via Google Forms in all countries except Germany. This country exploited the SoSci Survey [ 61 ]. The invitation to participate in the survey was sent to students by researchers via a variety of means, e.g., Moodle e-learning platform, student offices, email, or social media. The average time of data collection was 23.26 min (SD = 44.03). No form of compensation was offered as an incentive to participate in eight countries. In Germany, students were offered a possibility to enter into a lottery for a € 20 Amazon gift card as an incentive to participate. In Israel, the participants were eligible to win NIS 300 gift cards. To minimize bias sources, the student sample was highly diversified as regards its key characteristics: the type of university, field of study and the cycle of study. Sampling was purposive. The selection criterion was university student status. Ethics Statement: The study protocol was approved by the ethics committee of the University Research Committee at the University of Opole, Poland, decision no. 1/2020. The study followed the ethical requirements of the anonymity and voluntariness of participation. Each person answered the informed consent question. Following the Helsinki Declaration, a written informed consent was obtained from each student before inclusion. 2.3. Measurements The Patient Health Questionnaire (PHQ-8) [ 62 ] was used to measure depression symptoms. The PHQ-8 consists of eight items, conforming with DSM-V diagnostic criteria [ 48 ]. The symptoms include depressed mood, loss of interest in most or all activities, loss of energy, or feeling of worthlessness [ 62 ]. Participants use a Likert-type response scale ranging from 0 = not at all, to 3 = nearly every day. The range of PHQ-8 scores is from 0 to 24 , J. Clin. Med. 2021,10, 2882 5 of 22 severe. A cut-off score of 10 or above is recommended to screen for major depressive disorder risk [ 62 ]. Due to the requirements of a further statistical analysis with the use of the χ2 independence test and logistic regression, the PHQ-8 was dichotomized as follows: 0 = No risk (PHQ-8 < 10), 1 = Risk (PHQ-8 ≥ 10). The internal consistency reliability of the original version measured by Cronbach’s α equals 0.86. The value of 0.88 for the total sample was recorded in this study. In order to measure anxiety risk, the 7-item Generalized Anxiety Disorder (GAD-7) scale [ 63 ] was exploited. GAD-7 is a self-reported measure designed to screen for symptoms following Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-V) criteria [ 64 ]. The Generalized Anxiety Disorder (GAD) is characterized by a persistent and excessive worry about various issues. It relates to anxiety as a state [ 63 ]. People rate how often they experienced anxiety symptoms in the course of two weeks preceding the study on a 4-point Likert scale (0 = not at all, 1 = several days, 2 = more than half the days, and 3 = nearly every day). The GAD-7 ranges from 0 to 21. Scores above 10 points indicate an anxiety disorder risk [ 63 ]. Due to the requirements of the χ2 independence test and logistic regression, GAD-7 was dichotomized as follows: 0 = No risk (GAD-7 < 10), 1 = Risk (GAD-7 ≥10). The Cronbach’s αfor the GAD-7 in this study was 0.92 in the total sample. Exposure to COVID-19 [ 39 ] was assessed based on eight questions regarding the coronavirus consequences: (1) Have you experienced symptoms that could indicate the coronavirus infection?; (2) Have you been tested for the coronavirus?; (3) Were you hospitalized for the coronavirus?; (4) Did you have to be in strict quarantine for at least 14 days , in isolation from loved ones because of the coronavirus infection?; (5) Has anyone in your family, among friends, or relatives been infected with the coronavirus?; (6) Have any of your relatives died of the coronavirus?; (7) Have you or a loved one lost their job because of the coronavirus?; and (8) Are you currently experiencing a worsening of your functioning or economic status due to the coronavirus pandemic’s effects? Individuals answered each of these questions (0 = No, 1 = Yes) The total score was a sum of eight items, where a higher score indicated stronger coronavirus exposure. The results were divided into two categories for the χ2 independence test and logistic regression: 0 = Low exposure (score 0), 1 = High exposure (scores 1–8). The Perceived Impact of Coronavirus (PIC) on students’ well-being [ 39 ] was measured using five statements Participants used a 5-item Likert scale (from 1 = I strongly disagree, to 5 = I definitely agree) to express how much they are afraid that the current situation associated with the coronavirus pandemic (COVID-19) may negatively affect their lives in each of the following five aspects: (1) Completing the semester and obtaining qualifications; (2) Finding a job and professional development; (3) Financial situation (e.g., subsistence during studies); (4) Relationships with loved ones, family, (5) Relations with colleagues, friends. Next, scores obtained from the five items were summarized to a total score of the perceived coronavirus impact on students’ well-being (PCI). The higher the scores, the more significant the coronavirus-related concerns were. We have used the median to dichotomize the total score of the PIC and its three subscales: Qualifications (Graduation), Economic Status, and Social Relationships. The total PIC was coded as follows (for the χ2 independence test and logistic regression): 0 = Lower (PIC ≤ 15), 1 = Higher (PIC ≥ 16). We added scores of items PIC1 and PIC2 for the Qualifications scale and then coded as 0 = Low (scores 2–6) , 1 = High (scores 7–10). Social Relationships scale consisted of items PIC4 and PIC5 coded as 0 = Low (scores 2–4), 1 = High (scores 5–10). Single item PIC3 concerning Economic Status scale was coded as 0 = Low (scores 1–3), 1 = High (scores 4–5). The Cronbach’s α (indicating the internal reliability of the scale) amounted to 0.71 in the present study (in the total sample). Physical activity (PA) during the coronavirus-related lockdown was assessed using the following question: “How many days a week did you exercise physically or pursued sports activities at home or away from home, at the university, in clubs, or at the gym, in the last month?” [ 39 ]. Participants answered this question on an eight-point scale (from 0 = Not one day to 7 = Seven days a week). Next, the students responded to the question: J. Clin. Med. 2021,10, 2882 6 of 22 “How many minutes a day (on average) did you practice?” indicating the average number of minutes of PA per day. The number of days was multiplied by the number of minutes per day to calculate the previous week’s PA level. We divided the total sample into two groups: 0 = Sufficient (PA ≥ 150 min weekly) and 1 = Insufficient (PA < 150 min weekly), in line with the WHO recommendation [65]. The General Self-Rated Health (GSRH) status was assessed using two single-item questions as a shorter alternative to the standard general physical health (PH) survey (SF-12V) [ 66 , 67 ]. The first question GSRH-1 concerns an overall physical health (GSRH) assessment (i.e., “In general, would you say your health is . . . ?”), while the second GSRH-2, compares self-health with other people (i.e., “Compared to others your age, would you say your health is . . . ?”) (GSRH Comparative). Both GSRH items are rated on a 5-point Likert scale (1 = Excellent, 2 = Very Good, 3 = Good, 4 = Fair, and 5 = Poor). Therefore, higher scores denote worse health status. Research indicates that poorly self-rated health in the single-item GSRH has a strong association with mortality [ 66 ]. We spilt the GSRH as follows (due to the χ2 independence test and logistic regression requirements): 0 = Better health (GSRH ≤ 3), 1 = Worse health (GSRH ≥ 4). In the present study, the Cronbach’s α for GSRH was 0.88 (N= 2349). Demographic data included questions regarding age (in years), gender (0 = Men, 1 = Women ), place of residence (Village, Town, City, Agglomeration/Metropolis), and the current level of study (Bachelor, Master, Postgraduate, Doctoral). We divided answers regarding the place of residence into two categories (for the χ2 independence test and logistic regression) coded as: 0 = village and town, 1 = city, agglomeration, or metropolis. Additionally, we have incorporated 4% of participants who studied at a doctoral or postgraduate level into the category Master. Therefore, for further analysis, the level of study is comprised of two categories: 0 = Bachelor and 1 = Master (for Master or higher). 2.4. Statistical Analysis The statistical analysis included descriptive statistics: mean (M), standard deviation (SD), 95% of confidence interval (CI) with lower limit (LL) and upper limit (UL). Subsequently, a one-way analysis of variance (ANOVA) was performed to test the differences in the mean scores of depression and anxiety between university students from the nine countries: Slovenia, Czechia, Germany, Poland, Ukraine, Russia, Turkey, Israel, and Colombia. The effect size for ANOVA was assessed using ηp2 (a value of ηp2 = 0.01 is considered to be a small effect size, 0.09 a medium effect, and 0.25 a large effect). Tukey’s honest significant difference (HSD) test was used to find means that are significantly different from each other. Furthermore, Pearson’s χ2independence test was conducted to examine relationships between depression and anxiety and other variables in each of the nine countries. A 2×2 contingency table was provided in each country separately, for depression and anxiety as independent variables, as well as such predictor variables as gender, place of residence, level of study, physical activity, exposure to the COVID-19 pandemic, the total impact of COVID-19 on students’ well-being, as well as impact in the domain of qualifications, economic status, and social relationships, self-rated physical health, and comparative self-rated physical health (Comparative PH). However, all Colombian students (100%) were assigned to the Town/City category, and 97% (n= 155) to the first cycle study. Therefore, place of residence and level of study were excluded from the statistical analysis in the Colombian sample. The effect size for Pearson’s χ2 independence test was assessed using ϕ statistic (a value of ϕ = 0.1 is considered to be a small effect, 0.3 a medium effect, and 0.5 a large effect). Next, multivariate logistic regression analysis was performed in each country separately to test the adjusted odds ratio (AOR), in order to assess potential risk factors (gender, place of residence, exposure to COVID-19, PIC, PA, PH, Comparative PH) as predictors of depression and anxiety in each country. All predictors were entered into the model simultaneously. The following statistics were calculated for estimation: coefficient estimates, 95% confidence intervals (CI) for the regression coefficient, standard errors of the regression coefficient, odds ratio, z-values, and their corresponding p-values. J. Clin. Med. 2021,10, 2882 7 of 22 The bias-corrected accelerated bootstrapping (BCa) method of estimating regression coefficient was also applied, with the number of replications set to 5000 (if the bias-corrected 95% confidence intervals (CI B ) did not include the null value, then a statistically significant effect was considered). Goodness of fit of the regression model was assessed using pseudo R 2 , including Cox and Snell R 2CS , McFadden R 2McF , and Nagelkerke R 2N . All analyses were performed using Statistica Version 13.1, StatSoft Polska (Cracow, Poland) [ 68 ] and the open-source statistical software JASP Version 014.1 [69]. 3. Results 3.1. Country Differences in Depression and Anxiety A one-way between subjects ANOVA was conducted to compare the effect of country on depression and anxiety (see Figures 1and 2, for more details). There was a significant effect of country on depression with a large effect size, F(8, 2340) = 31.02, p< 0.001 , ηp2 = 0.09. Post hoc comparisons using the Tukey HSD test indicated that the mean score of the PHQ-8 in Poland was significantly higher than in Slovenia (p< 0.01), Czechia (p< 0.001), Ukraine (p< 0.001), and Germany (p< 0.05), and was significantly lower than in Turkey (p< 0.001). In addition, Slovenia demonstrated higher depression than Czechia (p< 0.01), but lower than Turkey (p< 0.001) and Colombia (p< 0.05). Among all of the nine countries, the lowest scores in depression emerged in Czechia, where it was significantly lower than that of Russia (p< 0.001), Germany (p< 0.001), Turkey (p< 0.001), Israel (p< 0.001), and Colombia (p< 0.001). Depression in Ukraine was found as being significantly lower than in Russia (p< 0.05), Turkey (p< 0.001), and Colombia (p< 0.001). Turkey scored the highest in depression, when compared to other countries, including Russia (p< 0.001), Germany (p< 0.001), Israel (p< 0.001), and Colombia (p< 0.01). The mean scores for depression are shown in Figure 1. J. Clin. Med. 2021, 10, x FOR PEER REVIEW 8 of 22 Figure 1. Mean scores of depression (PHQ-8) among university students across the nine countries during the first wave of the COVID-19 pandemic. The dots in the figure represent outliers. Figure 2. Mean scores for anxiety (GAD-7) among university students across the nine countries during the first wave of the COVID-19 pandemic. The dots in the figure represent outliers. 3.2. Association of Depression and Anxiety with Other Variables A Pearson’s χ2 test of independence was performed separately for each country to examine 2 × 2 association between mental health indices, such as depression and anxiety, and such variables as gender, place of residence, level of study, exposure to COVID-19, the perceived impact of COVID-19 on students’ well-being (PIC), including qualifications (graduation), economic status, and relationships, physical activity, and physical health as rated independently and compared with people of the same age. As shown in Tables S1 and S2, numerous associations were found for the nine countries for depression and anxiety, respectively. The relationship between depression and gender was significant in Colombia (χ2(1) = 4.44, p < 0.05, ϕ = 0.17), Poland (χ2(1) = 7.28, p < 0.01, ϕ = 0.16), Russia (χ2(1) = 10.24, p < 0.01, ϕ = 0.19), Turkey (χ2(1) = 15.40, p < 0.001, ϕ = 0.22), and Ukraine (χ2(1) = 9.02, p < 0.01, ϕ = 0.17). Place of residence was not significantly associated with depression at all in any country. The level of study was significantly related to depression in Colombia (χ2(1) = 4.16, p < 0.05, ϕ = −0.16), Czechia (χ2(1) = 5.71, p < 0.05, ϕ = −0.13), and Slovenia (χ2(1) = 8.24, Figure 1. Mean scores of depression (PHQ-8) among university students across the nine countries during the first wave of the COVID-19 pandemic. The dots in the figure represent outliers. J. Clin. Med. 2021,10, 2882 8 of 22 J. Clin. Med. 2021, 10, x FOR PEER REVIEW 8 of 22 Figure 1. Mean scores of depression (PHQ-8) among university students across the nine countries during the first wave of the COVID-19 pandemic. The dots in the figure represent outliers. Figure 2. Mean scores for anxiety (GAD-7) among university students across the nine countries during the first wave of the COVID-19 pandemic. The dots in the figure represent outliers. 3.2. Association of Depression and Anxiety with Other Variables A Pearson’s χ2 test of independence was performed separately for each country to examine 2 × 2 association between mental health indices, such as depression and anxiety, and such variables as gender, place of residence, level of study, exposure to COVID-19, the perceived impact of COVID-19 on students’ well-being (PIC), including qualifications (graduation), economic status, and relationships, physical activity, and physical health as rated independently and compared with people of the same age. As shown in Tables S1 and S2, numerous associations were found for the nine countries for depression and anxiety, respectively. The relationship between depression and gender was significant in Colombia (χ2(1) = 4.44, p < 0.05, ϕ = 0.17), Poland (χ2(1) = 7.28, p < 0.01, ϕ = 0.16), Russia (χ2(1) = 10.24, p < 0.01, ϕ = 0.19), Turkey (χ2(1) = 15.40, p < 0.001, ϕ = 0.22), and Ukraine (χ2(1) = 9.02, p < 0.01, ϕ = 0.17). Place of residence was not significantly associated with depression at all in any country. The level of study was significantly related to depression in Colombia (χ2(1) = 4.16, p < 0.05, ϕ = −0.16), Czechia (χ2(1) = 5.71, p < 0.05, ϕ = −0.13), and Slovenia (χ2(1) = 8.24, Figure 2. Mean scores for anxiety (GAD-7) among university students across the nine countries during the first wave of the COVID-19 pandemic. The dots in the figure represent outliers. A significant effect of country on anxiety was also revealed, with a large effect size, F(8, 2340) = 57.78, p< 0.001, ηp2 = 0.15. As Tukey’s HSD test indicates, the mean score of the GAD-7 in Poland was significantly higher than in Slovenia (p< 0.01), Czechia (p< 0.001 ), Ukraine (p< 0.001), Russia (p< 0.01), and Germany (p< 0.001). Slovenia showed significantly higher scores in anxiety than Czechia (p< 0.001) and Germany ( p< 0.001 ), and lower than Turkey (p< 0.001). Czechia demonstrated significantly lower anxiety than Ukraine (p< 0.05), Russia (p< 0.001), Turkey (p< 0.001), Israel ( p< 0.001 ), and Colombia ( p< 0.001 ), and significantly higher anxiety than Germany ( p< 0.001 ). Anxiety level in Ukraine was found as being significantly lower than in Russia ( p< 0.05 ), Turkey (p< 0.001), Israel (p< 0.01), and Colombia (p< 0.001), and higher than in Germany (p< 0.01). As far as anxiety is concerned, Russia significantly differed from Germany ( p< 0.001 ) and Turkey (p< 0.01). Among the nine countries, Germany showed the lowest scores in anxiety, significantly lower than Turkey ( p< 0.001 ), Israel (p< 0.001), and Colombia (p< 0.001). In contrast, Turkey demonstrated the highest anxiety, significantly higher than Israel ( p< 0.001 ), and Colombia ( p< 0.01) . The mean scores of anxiety are shown in Figure 2. 3.2. Association of Depression and Anxiety with Other Variables A Pearson’s χ2 test of independence was performed separately for each country to examine 2 ×2 association between mental health indices, such as depression and anxiety, and such variables as gender, place of residence, level of study, exposure to COVID-19, the perceived impact of COVID-19 on students’ well-being (PIC), including qualifications (graduation), economic status, and relationships, physical activity, and physical health as rated independently and compared with people of the same age. As shown in Tables S1 and S2, numerous associations were found for the nine countries for depression and anxiety, respectively. The relationship between depression and gender was significant in Colombia ( χ2(1) = 4.44 ,p< 0.05, φ = 0.17), Poland ( χ2 (1) = 7.28, p< 0.01, φ = 0.16), Russia ( χ2 (1) = 10.24, p< 0.01 , φ = 0.19), Turkey ( χ2 (1) = 15.40, p< 0.001, φ = 0.22), and Ukraine ( χ2 (1) = 9.02, p< 0.01 , φ = 0.17). Place of residence was not significantly associated with depression at all in any country. The level of study was significantly related to depression in Colombia ( χ2 (1) = 4.16, J. Clin. Med. 2021,10, 2882 9 of 22 p< 0.05 , φ = − 0.16), Czechia ( χ2 (1) = 5.71, p< 0.05, φ = − 0.13), and Slovenia ( χ2 (1) = 8.24, p< 0.01 , φ = − 0.19), while it was of no importance in the other countries. The relationship between depression and exposure to COVID-19 was significant in most countries (except Turkey and Colombia), including Slovenia ( χ2 (1) = 0.23, p< 0.001, φ = 0.33), Czechia ( χ2 (1) = 11.44, p< 0.001 , φ = 0.19), Germany ( χ2 (1) = 4.16, p< 0.05, φ = 0.12), Poland, ( χ2 (1) = 7.60, p< 0.01, φ= 0.16 ), Ukraine ( χ2 (1) = 6.65, p< 0.01, φ = 0.15), Russia ( χ2 (1) = 10.39, p< 0.01, φ = 0.19), and Israel ( χ2 (1) = 15.99, p< 0.001, φ = 0.28). Except Colombia, the total PIC was linked to depression in the following: Slovenia ( χ2 (1) = 33.96, p< 0.001, φ = 0.40), Czechia ( χ2 (1) = 16.10, p< 0.001, φ= 0.23 ), Germany ( χ2 (1) = 39.80, p< 0.001, φ = 0.39), Poland, ( χ2 (1) = 20.85, p< 0.001 , φ = 0.26), Ukraine ( χ2 (1) = 13.00, p< 0.001, φ = 0.21), Russia ( χ2 (1) = 19.72, p< 0.001, φ= 0.26 ), Turkey ( χ2 (1) = 9.26, p< 0.01, φ = 0.17), and Israel ( χ2 (1) = 35.64, p< 0.001, φ = 0.42). Qualifications were insignificant in Czechia and Poland. However, they were of concern in Slovenia ( χ2(1) = 32.67 , p< 0.001 , φ = 0.40), Germany ( χ2 (1) = 16.95, p< 0.001, φ = 0.25), Ukraine ( χ2 (1) = 4.96, p< 0.05 , φ = 0.13), Russia ( χ2 (1) = 15.66, p< 0.001, φ = 0.23), Turkey χ2 (1) = 6.09, p< 0.05 , φ = 0.14), Israel ( χ2 (1) = 12.94, p< 0.001, φ = 0.26), and Colombia ( χ2 (1) = 3.93, p< 0.05 , φ = 0.16). Deterioration of economic status was a source of concern in most countries (except Poland): Slovenia ( χ2(1) = 10.10 ,p< 0.01, φ = 0.22), Czechia ( χ2 (1) = 8.46, p< 0.01, φ = 0.16), Germany ( χ2 (1) = 14.02, p< 0.001, φ = 0.23), Ukraine ( χ2 (1) = 4.65, p< 0.05, φ = 0.12), Russia ( χ2 (1) = 11.25, p< 0.001, φ = 0.20), Turkey χ2 (1) = 13.58, p< 0.001, φ = 0.21), Israel ( χ2(1) = 13.12 ,p < 0.001, φ = 0.26), and Colombia ( χ2 (1) = 5.06, p< 0.05, φ = 0.18). Relationships with friends and family members were a source of concern in most countries during the COVID-10 pandemic (except Colombia): Slovenia ( χ2 (1) = 13.70, p< 0.001, φ = 0.27), Czechia ( χ2 (1) = 11.06, p< 0.001, φ = 0.19), Germany ( χ2 (1) = 9.76, p< 0.01, φ = 0.19), Poland ( χ2 (1) = 24.57, p< 0.05, φ = 0.29), Ukraine ( χ2 (1) = 8.36, p< 0.01, φ = 0.16), Russia ( χ2 (1) = 24.16, p< 0.001, φ = 0.29), Turkey χ2 (1) = 4.26, p< 0.05, φ = 0.12), and Israel ( χ2 (1) = 14.38, p< 0.001, φ = 0.27). The relationship between high depression and insufficient physical activity (PA less than 150 min. per week) was revealed in Poland ( χ2 (1) = − 4.85, p< 0.05, φ = − 0.13), Ukraine ( χ2 (1) = − 11.77, p< 0.001, φ = − 0.20), Russia ( χ2 (1) = − 7.36, p< 0.01, φ = − 0.16), and Israel ( χ2 (1) = 3.89, p< 0.05, φ = − 0.14). An association between high depression and worse physical health was significant in most countries (except Czechia and Ukraine): Slovenia ( χ2 (1) = 15.16, p< 0.001, φ = 0.27), Germany ( χ2 (1) = 21.71, p< 0.001, φ = 0.29), Poland ( χ2 (1) = 13.14, p< 0.001, φ = 0.21), Russia ( χ2 (1) = 10.00, p< 0.01, φ = 0.19), Turkey χ2 (1) = 5.89, p< 0.05, φ = 0.14), Israel ( χ2 (1) = 4.89, p< 0.05, φ = 0.16), and Colombia ( χ2 (1) = 5.14, p< 0.05, φ = 0.18). When students compared self-rated physical health to other people of the same age, the association between depression and comparative health was noted in most countries (except Russia): Slovenia ( χ2 (1) = 20.88, p< 0.001 , φ = 0.32), Czechia ( χ2 (1) = 14.45, p< 0.001, φ = 0.22), Germany ( χ2 (1) = 7.09, p< 0.01, φ = 0.16), Poland ( χ2 (1) = 21.64, p< 0.001, φ = 0.27), Ukraine ( χ2 (1) = 6.96, p< 0.01, φ = 0.15), Turkey χ2 (1) = 10.73, p< 0.001, φ = 0.19), Israel ( χ2 (1) = 5.76, p< 0.05, φ = 0.17), and Colombia (χ2(1) = 6.83, p< 0.01, φ= 0.21). Anxiety was related to gender in Israel ( χ2 (1) = 4.87, p< 0.05, φ = 0.16), Russia ( χ2(1) = 4.15 ,p< 0.05, φ = 0.12), Turkey ( χ2 (1) = 9.15, p< 0.01, φ = 0.17) and Ukraine ( χ2(1) = 7.52 ,p< 0.01, φ = 0.16). An association between anxiety and place of residence was significant solely in Poland ( χ2 (1) = 7.67, p< 0.01, φ = 0.16). The relationship between the level of study and anxiety was observed in Czechia ( χ2 (1) = 6.80 p< 0.01, φ = − 0.15) and Slovenia ( χ2 (1) = 5.61, p< 0.05, φ = − 0.16). Exposure to COVID-19 was significantly associated with anxiety in all countries, Slovenia ( χ2 (1) = 13.25, p< 0.001, φ = 0.25), Czechia ( χ2 (1) = 10.34, p< 0.01, φ = 0.18), Germany ( χ2 (1) = 8.82, p< 0.01, φ = 0.18), Poland ( χ2(1) = 8.97 ,p< 0.01, φ = 0.17), Ukraine ( χ2 (1) = 10.03, p< 0.01, φ = 0.18), Russia ( χ2(1) = 6.95 ,p< 0.01, φ = 0.16), Turkey χ2 (1) = 7.90, p< 0.01, φ = 0.16), Israel ( χ2 (1) = 10.28, p< 0.01, φ = 0.23), and Colombia ( χ2 (1) = 4.40, p< 0.05, φ = 0.17). The total PIC was significantly related to anxiety in all countries: Slovenia ( χ2 (1) = 29.98, p< 0.001, φ= 0.38 ), Czechia ( χ2 (1) = 13.01, p< 0.001, φ = 0.20), Germany ( χ2 (1) = 9.36, p< 0.01, φ = 0.18), Poland ( χ2 (1) = 12.74, p< 0.001, φ = 0.21), Ukraine ( χ2 (1) = 17.48, p< 0.001, φ = 0.24), Russia ( χ2 (1) = 5.34, p< 0.05, φ= 0.14), Turkey χ2(1) = 11.92, p< 0.001, φ= 0.20), Israel (χ2(1) = 32.27, J. Clin. Med. 2021,10, 2882 16 of 22 motivation was competition, whereas in collectivistic cultures, like China, it was rather a social affiliation and wellness [77]. Living in a city or town/village turned out to be irrelevant for depression in the nine countries. This is in congruence with previous meta-analyses [ 20 , 78 , 79 ]. Students are quite a homogeneous group. Therefore, both groups living in rural and urban areas have common characteristics (i.e., young age) linked to depressive symptoms during the pandemic [ 13 – 15 ]. However, living in a small city or a village was associated with anxiety risk exclusively in Polish students. In all the remaining countries, it was an irrelevant factor. Previous research also showed inconsistent results. Living in an urban area was linked to lower anxiety in China [42] but higher anxiety in Bangladesh [43]. Our research showed that the association between gender and mental health risk is not clear when analyzed in different countries. Female students from Ukraine, Russia, and Turkey had a higher prevalence of anxiety and depression risk compared to male students in those countries. The highest rate of both depression and anxiety risk was revealed among Turkish female students. Furthermore, Polish and Israeli female students showed a higher prevalence of anxiety risk, whereas Colombian female students manifested the risk of depression. Previous research showed a gender effect on the prevalence of depression [ 20 , 70 , 79 , 80 ]. Additionally, a recent meta-analysis regarding students’ mental health during the COVID-19 pandemic has revealed that female students were found to have a higher prevalence of anxiety and depression [ 81 ]. However, we have found no gender association with mental health issues among Slovenian, Czech, and German students. Therefore, the cultural context should be incorporated when exploring gender association with mental health issues. 4.3. Predictors of Depression and Anxiety in the Nine Countries The multiple regression models are closer to actual psychological complexity, as they reveal risk factors in their simultaneous effect on mental health, compared to bivariate models where the particular factors predict mental health issues independently. The most frequent predictors of depression and anxiety in the nine countries were gender, exposure to COVID-19, and comparative physical health. The multiple logistic regression proved gender to be a significant predictor of anxiety but only among Israeli, Ukrainian, and Turkish students. Gender was a more frequent predictor of depression among Colombian, Polish, Russian, Turkish, and Ukrainian students, but a less significant predictor in Colombia. Previous cross-national research in 23 European countries showed that the largest gender differences in depression were noted in certain former Soviet Union countries, and the lowest in Western and Nordic countries [ 70 ]. The results in our study partially conform with the aforementioned report. However, in our research, gender was not a risk factor for mental health issues among students in Slovenia and Czechia (former Soviet Union countries). This inconsistency can be partially explained by gender inequalities denoted by the the Gender Inequality Index (GII) [ 82 ], which in Slovenia (0.07) and Czechia (0.14) is relatively lower compared to Ukraine (0.29) and Russia (0.25). Therefore, the gender role hypothesis seems to be a more appropriate explanation, particularly for female gender as a risk factor for depression in five out of the nine countries. The gender role hypothesis claims that the gender gap in the prevalence of mental health issues is due to specific differences in coping resources, stressors, or opportunities for expressing psychological distress distinctively for women and men [ 83 ]. Gender role (the concept of femininity and masculinity) affects major risk factors for internalizing and externalizing problems [ 84 ]. This hypothesis has found a partial confirmation as regards depression, but not anxiety [ 83 ]. Depression was revealed to be related to the changes in traditional female gender roles. Narrowing gender differences in depression was observed along with the declining gender role traditionality [ 83 ]. Our study also confirms the significance of gender as a predictor of depression in relation to the gender role hypothesis. J. Clin. Med. 2021,10, 2882 17 of 22 However, the results in Israel, Ukraine and Turkey also show the significance of gender in predicting anxiety in the student population during the COVID-19 pandemic. Multiple regression models showed the importance of exposure to the COVID-19 infection in five countries (Slovenia, Czechia, Israel Russia, and Ukraine) for depression, and in four countries (Czechia, Poland, Turkey, and Ukraine) for anxiety, even though the stringency of restrictions index (ranging from 0 to 100) in those countries varied from 41 in Slovenia to 82 in Ukraine. Therefore, exposure to the infection as a risk factor of depression or/and anxiety appeared in several countries independently of restrictions introduced by the governments. The perceived impact of COVID-19 on students’ well-being was a risk factor for depression in Israel and Germany, and additionally, for anxiety in Israel. In other countries, this variable was insignificant in multivariate models. However, its subscales showed different patterns depending on the country. Worries about graduation were considered as risk factors for depression in Slovenia and Russia, and for anxiety in Czechia and Russia. The perceived impact of COVID-19 on students’ economic status was significantly associated with depression and anxiety in the majority of the countries, as the above analysis showed. The deterioration of economic status as a risk factor for both depression and anxiety is in line with other studies [ 85 , 86 ]. However, when economic status was introduced in multiple models, it turned out to be a trivial predictor of depression, while being a significant predictor of anxiety only in one country (Czechia). Therefore, even though PIC Economic Status is relevant when analyzed as a singular risk factor for mental health, when combined with other risk factors for mental health, such as exposure to COVID-19 or female gender, it becomes insignificant. Concern about relationship quality was the strongest predictor in the multivariate models of depression and anxiety in Poland and Russia. Therefore, in the countries with stronger traditional family values, the perceived impact of the COVID-19 pandemic on students’ relationships with family was a significant risk factor for mental health issues. Insufficient physical activity in multivariate models was a risk factor for depression in Russia and Ukraine, and for anxiety in Czechia. Worse physical health played a different role than worse comparative physical health. General physical health was a strong predictor of depression in Germany and Russia and a weaker predictor of anxiety in Poland. Worse comparative health turned out to be a significant risk factor for depression in four countries (Czechia, Poland, Slovenia, and a weaker predictor in Turkey). For anxiety, this was true only for two countries. However, the results in Colombia and Czechia were not confirmed when the bias-corrected accelerated bootstrapping method was introduced. Therefore, comparative physical health was a more common predictor of depression than anxiety among students across the nine countries. Although introduced variables allowed for the creation of multivariate models of depression in each country, anxiety was not explained by proposed predictors in Slovenia, Germany, and Colombia. 4.4. Limitations There are several limitations to the present study. One is the cross-sectional character of the research. The longitudinal study could reveal the cause—effect relationship between the proposed indices and mental health issues. Direct comparisons among countries are also limited due to the different pace and extent of public health restrictions imposed by governments and due to the situation with COVID-19 related deaths in the observed period in each of the observed countries. Another limitation is a self-selected study sample and data collection via self-reported questionnaires. Therefore, the data can be subject to retrospective response bias. Previous research showed that more depressive symptoms can be elicited for milder forms of depression through self-reported measurements compared to clinician-rating methods (interview) [ 87 ]. More educated and younger people usually score higher on self-rated scales than on clinician-rating scales [ 88 ]. However, it should be noted that even though a milder form of depression may be elicited among young adults, J. Clin. Med. 2021,10, 2882 18 of 22 depressive symptoms have increased during the pandemic [ 89 , 90 ]. Finally, generalizing the results may be hindered by the lack of random sampling and representation of the student population being limited to specific regions in each country. Considering strengths and limitations of this study, future research ought to examine mental health using a longitudinal design from the cross-cultural perspective. 5. Conclusions Our study has shown risk factors for depression and anxiety and differences in mental health among university students in the nine countries during the first wave of the COVID19 pandemic. We have revealed that even so common a risk factor as gender does not predict anxiety or depression in all the countries. Moreover, physical inactivity as a risk factor strongly depends on the country, and in most of the nine countries was a significant predictor neither for anxiety nor depression. This research underlines the necessity of interpreting data within the cross-cultural context and argues that presenting mental health results during the COVID-19 pandemic only in one country can be challenging in terms of generalization. We demonstrated that, even though there are several risk factors associated with mental health issues in all of the nine countries (i.e., exposure to COVID-19, perceived impact of COVID-19 on students’ well-being, including graduation, economic status, and relationships quality, general and comparative health), the multivariate models differed drastically among the countries. Therefore, despite the globalization of a homogeneous student population, our study showed varied mental health predictors in relation to cultural, political and economic situation in a particular country. Planning and implementation of psychological intervention programs for students should include differentiation by country concerning mental health risk factors. Supplementary Materials: The following are available online at https://www.mdpi.com/article/10 .3390/jcm10132882/s1, Table S1: Association between depression risk and other variables among university students from Colombia, Czechia, Germany, Israel, Poland, Russia, Slovenia, Turkey, and Ukraine during the first wave of the COVID-19 pandemic. Table S2: Association between anxiety risk and other variables among university students from Colombia, Czechia, Germany, Israel, Poland, Russia, Slovenia, Turkey, and Ukraine during the first wave of the COVID-19 pandemic. Table S3: Logistic regression for depression symptoms among university students from Colombia during the first wave of the COVID-19 pandemic. Table S4 : Logistic regression for depression symptoms among university students from Czechia during the first wave of the COVID-19 pandemic. Table S5: Logistic regression for depression symptoms among university students from Germany during the first wave of the COVID-19 pandemic. Table S6: Logistic regression for depression symptoms among university students from Israel during the first wave of the COVID-19 pandemic. Table S7: Logistic regression for depression symptoms among university students from Poland during the first wave of the COVID-19 pandemic. Table S8: Logistic regression for depression symptoms among university students from Russia during the first wave of the COVID-19 pandemic. Table S9: Logistic regression for depression symptoms among university students from Slovenia during the first wave of the COVID-19 pandemic. Table S10: Logistic regression for depression symptoms among university students from Turkey during the first wave of the COVID-19 pandemic. Table S11: Logistic regression for depression symptoms among university students from Ukraine during the first wave of the COVID-19 pandemic. Table S12: Logistic regression for anxiety symptoms among university students from Colombia during the first wave of the COVID-19 pandemic. Table S13: Logistic regression for anxiety symptoms among university students from Czechia during the first wave of the COVID-19 pandemic. Table S14: Logistic regression for anxiety symptoms among university students from Germany during the first wave of the COVID-19 pandemic. Table S15: Logistic regression for anxiety symptoms among university students from Israel during the first wave of the COVID-19 pandemic. Table S16: Logistic regression for anxiety symptoms among university students from Poland during the first wave of the COVID-19 pandemic. Table S17: Logistic regression for anxiety symptoms among university students from Russia during the first wave of the COVID-19 pandemic. Table S18: Logistic regression for anxiety symptoms among university students from Slovenia during the first wave of the COVID-19 pandemic. Table S19: Logistic regression for anxiety symptoms among J. Clin. Med. 2021,10, 2882 19 of 22 university students from Turkey during the first wave of the COVID-19 pandemic. Table S20: Logistic regression for anxiety symptoms among university students from Ukraine during the first wave of the COVID-19 pandemic. Author Contributions: Conceptualization, D.O., A.M.R., C.K.; data curation, D.O.; formal analysis, A.M.R., investigation, D.O., A.M.R., C.K., M.J., A.S., M.J.H., A.A., J.B., R.B., E.V.K., I.P., I.B., Z.K., I.A., O.Ç., Y.A.C.-A.; methodology, A.M.R., D.O.; project administration, D.O.; resources D.O., A.M.R., C.K., M.J., A.S., M.J.H., A.A., J.B., R.B., E.V.K., I.P., I.B., Z.K., I.A., O.Ç., Y.A.C.-A., M.W.-S.; supervision, D.O., A.M.R.; visualization, A.M.R.; writing—original draft preparation, D.O., A.M.R.; writing— review and editing, D.O., A.M.R., C.K., M.J., A.S., M.J.H., A.A., J.B., R.B., E.V.K., I.P., I.B., Z.K., I.A., O.Ç., Y.A.C.-A., M.W.-S. All authors have read and agreed to the published version of the manuscript. 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