War, Researchers, and Anxiety: Evidence from Ukraine

War, Researchers, and Anxiety: Evidence from Ukraine | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article War, Researchers, and Anxiety: Evidence from Ukraine Natalia Tsybuliak, Uliana Kolomiiets, Hanna Lopatina, Anastasia Popova, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4603070/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 07 Nov, 2024 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract The ongoing war in Ukraine has significantly impacted the mental health of academic researchers, with anxiety emerging as a predominant issue. This study assessed the prevalence and severity of generalized anxiety disorder (GAD) among Ukrainian researchers during conflict, considering factors such as gender, age, migration status, scientific degree, and job title. The findings revealed that 44.3% of participants experienced moderately severe to severe anxiety, with migration due to the full-scale war being a significant predictor of higher anxiety levels. Notably, male researchers exhibit higher anxiety levels than their female counterparts, contrary to typical peacetime trends, suggesting that wartime responsibilities and societal expectations may play a crucial role. The data underscore the need for targeted mental health support, particularly for displaced researchers, and highlight the importance of developing gender-specific interventions. These insights are vital for informing policies and support programs to enhance researchers' mental health and productivity in conflict zones, ensuring the continuity and quality of scientific research during and after the war. Introduction The mental health of academic communities is a crucial aspect of their well-being and productivity. Modern research indicates an increase in mental health issues among researchers due to the challenges posed by the academic and social environment. These issues can negatively impact their efficiency, education quality, and research activities [ 1 ]. In 2022, the World Health Organization (WHO) declared mental health a “growing crisis”, highlighting the exacerbation of mental disorders due to the COVID-19 pandemic [ 2 ], which also had a significant impact on the academic environment [ 3 ]. Anxiety is one of the most common mental health issues among researchers [ 1 ], constituting one of the most severe mental health conditions and ranking among the top 25 causes of disease burden worldwide [ 4 ]. According to the WHO, anxiety disorders are characterized by excessive fear, worry, and related behavioural disturbances [ 5 ]. Anxiety is an emotion accompanied by a sense of danger and physical symptoms of tension when a person anticipates a potential threat, disaster, or failure. This anticipatory state mobilizes the body for action: muscle tension, breathing quickens, and heart rate accelerates. Anxiety is characterized as a future-oriented and persistent response to an unclear, diffuse threat [ 6 ]. Symptoms of anxiety can be severe enough to cause significant distress or substantial impairment in functioning [ 6 ]. High levels of anxiety among researchers are often caused by psychological stress changes. These changes include a lack of control and emotional exhaustion, resulting from overload, multitasking, demanding evaluation systems, the complexity of the academic path, and lack of recognition [ 8 , 9 , 10 , 11 , 12 ], including limited autonomy, insufficient resources, poor support, numerous conflicting types of work, and personal duties, as well as an imbalance between work and personal life [ 13 ]. Specific factors of anxiety in academic communities are associated with operating within a progressive discourse of competition, productivity pressure, accountability, and the commercialization of education [ 14 ], the absence of guarantees for contract renewal, and the constant fear that employment may depend on funding outcomes or grant awards [ 15 , 16 ], as well as the developing digital world, which causes 'technostress' among members of academic communities [ 17 ]. This creates a constant feeling of tension, anxiety, and uncertainty, negatively impacting the productivity and well-being of researchers, reducing their effectiveness, and worsening their health, including physical and psychological symptoms, even in peaceful and calm times [ 15 , 16 , 18 , 19 ]. Another factor exacerbating anxiety and affecting the mental health of researchers is military conflicts. Studies have shown that direct exposure to military actions significantly increases the risk of developing generalized anxiety disorder (GAD) and post-traumatic stress disorder (PTSD), especially among people who are directly in conflict zones, who are experiencing physical violence, or who are witnessing severe human suffering [ 7 ]. The impact of war also includes socioeconomic stresses and disruptions in social connections, which can cause mental health to deteriorate further in the long term [ 20 ]. In Ukraine, where the full-scale war has been ongoing for more than two years, the mental health of the academic community faces significant challenges. In the context of general research on the impact of war on mental health, a study by Yurtsenyuk and Sumariuk (2023) revealed a high prevalence of mental disorders, including depression, anxiety, and PTSD, among Ukrainians, reflecting a global trend identified by the WHO, where one in five participants in armed conflicts experience mental disorders, equivalent to approximately 9.6 million Ukrainians who potentially may have mental health issues such as depression, anxiety disorders, and stress disorders, including PTSD [ 21 ]. The impact of war varies depending on gender, age, and living conditions, with higher levels of anxiety, depression, and stress among those directly affected by military actions and increased levels of traumatic symptoms among women and young people [ 22 , 23 ]. However, there is limited specific information on the mental health of Ukrainian researchers. Existing studies are fragmented, indicating gaps in research on the impact of war on their mental health. Prolonged military conflicts significantly increase the level of burnout, especially among women [ 24 ], increase the use of psychoactive substances, and contribute to the emergence of symptoms of depression, fatigue, loneliness, and worsening mental health [ 22 ]. These data confirm a significant increase in post-traumatic symptoms among the researchers and their negative impact on research and educational institutions, particularly due to war-related factors such as migration, university displacement, loss of homes, social isolation, and constant life-threatening danger. Additionally, instability in critical infrastructure operations, including issues with electricity, communication, and internet access, exacerbates these challenges [ 25 , 26 ]. This underscores the need for the development of specialized support programs to mitigate the impact on mental health [ 24 , 27 ]. The absence of systematic studies analysing the prevalence and severity of anxiety among researchers during wartime underscores the need to enhance scientific efforts in this direction to develop effective support strategies. These strategies impact the productivity, mental health and well-being of researchers, as well as the country's academic potential and economic resilience. The primary aim of this study was to assess the prevalence and severity of anxiety among Ukrainian researchers during the war. Although the war in Ukraine began in 2014 in some regions, our study focuses on the impact of the full-scale war that has continued since 2022. This full-scale war means there is no safe place, and people in every part of the country are experiencing the effects of the war. Specifically, this study seeks to identify the researchers' sociodemographic factors that significantly influence anxiety levels in academia, focusing on differences by gender, migration status, age, scientific degree, job title, and university relocation due to occupation of Ukrainian territories by Russian troops. Results The study included a total of 429 Ukrainian researchers, representing a diverse cross-section of individuals affected by the full-scale war in Ukraine. The data in Table 1 reveal the prevalence and severity of GAD. Table 1 Generalized anxiety disorders among Ukrainian researchers in wartime. Level of GAD GAD values Distribution, N Distribution, % GAD, median (25–75 percentile) GAD, mean (standard deviation) Mild anxiety 0–4 80 18.6 3 (2–4) 2.44 (1.35) Moderate anxiety 5–9 159 37.1 7 (6–8) 6.97 (1.28) Moderately severe anxiety 10–14 103 24 12 (11–13) 11.84 (1.42) Severe anxiety 15–21 87 20.3 18 (16–21) 18.08 (2.37) Total 429 100 9.55 (5.52) Note: 1. GAD values – the cut-off points used for differentiating respondents’ anxiety levels. 2. N – number of respondents. 3. 25–75 percentile – shows the median GAD score for each of the four anxiety levels. Over 80% of respondents had moderate to severe anxiety disorders, with the largest group in the moderate range (37.1% with a median score of 7 and a mean of 6.97). The second largest group, comprising nearly one-fourth of respondents, was in the moderately severe range (24.0%, median score 12, mean 11.84). One fifth of respondents (20.1%, median score 18, mean 18.08) had severe anxiety. The smallest group had no anxiety or mild anxiety (18.6%, median score 3, mean 2.44). The overall mean score of 9.55 suggested that the majority of participants exhibited moderate anxiety levels on average. At the same time, using the GAD-7 scoring system by Spitzer et al. [ 28 ], where a score of 10 or greater indicates a probable case of GAD, this analysis showed that nearly 44.3% of participants fall into the categories of moderately severe or severe anxiety, meeting the cut-off score for a probable GAD diagnosis. This finding underscores the significant mental health challenges faced by researchers. To better understand the relationship between GAD and various sociodemographic factors among Ukrainian researchers, Table 2 presents the distribution of GAD across different variables using statistical analyses. Table 2 Distribution of generalized anxiety disorders across sociodemographic variables among Ukrainian researchers. Variable Subcategory GAD, mean [st.d.] Level of GAD, % (N) Tests Name Distribution, % (N) Mean [st.d.] Mild Anxiety Moderate Anxiety Moderately Severe Anxiety Severe Anxiety Pearson Chi 2 [Pr] ANOVA [Pr > Chi 2 ] Age Under 35 17% (73) 2.39 [0.87] 9.46 [5.2] 16.4% (12) 42.5% (31) 24.7% (18) 16.4% (12) 3.54 [0.94] 1.39 [0.71] 35–45 years 35.4% (153) 9.69 [5.47] 18.4% (28) 36.8% (56) 21.7% (33) 23.1% (35) 46–60 years 38.9% (167) 9.43 [5.62] 19.2% (32) 36.5% (61) 24.5% (41) 19.8% (33) 61 older 8.7% (37) 9.64 [6.11] 21.7% (8) 29.7% (11) 29.7% (11) 18.9% (7) Gender Male 25.4% (109) 0.75 [0.43] 10.49 [6.45] 19.1% (61) 38.1% (122) 25.0% (80) 17.8% (57) 4.79 [0.18] 8.69 [0.003]*** Female 74.6% (320) 9.22 [5.15] 17.5% (19) 33.9% (37) 21.1% (23) 27.5% (30) Scientific Degree PhD Students 19.4% (83) 2.83 [0.88] 9.06 [5.14] 21.7% (18) 39.8% (33) 25.3% (21) 13.3% (11) 9.95 [0.36] 1.61 [0.65] PhD Degree 63.6% (273) 9.58 [5.48] 19.0% (52) 37.0% (101) 23.1% (63) 20.9% (57) Doctor of Science 17% (73) 10.6 [5.94] 13.7% (10) 34.2% (25) 26.0% (19) 26.0% (19) Job Title Assistant 9.6% (41) 2.8 [0.82] 9.58 [5.04] 17.1% (7) 41.5% (17) 22.0% (9) 19.5% (8) 5.37 [0.8] 1.39 [0.7] Senior Lecturer 16.5% (71) 9 [5.63] 21.1% (15) 33.8% (24) 26.8% (19) 18.3% (13) Associate Professor 57.4% (246) 9.38 [5.45] 20.3% (50) 37.4% (92) 23.2% (57) 19.1% (47) Professor 16.5% (71) 10.66 [5.91] 11.3% (8) 36.6% (26) 25.4% (18) 26.8% (19) Change in permanent personal residence Internal Migrants 30.1% (129) 1.59 [0.73] 10.45 [5.8] 16.3% (21) 33.3% (43) 24.0% (31) 26.4% (34) Grouped yes-no 9.13 [0.03]** Grouped yes-no 1.76 [0.18] External Migrants 14.4% (62) 10.34 [5.69] 16.2% (10) 30.6% (19) 27.4% (17) 25.8% (16) Remained in Place 55.5% (238) 8.85 [5.25] 20.6% (49) 40.8% (97) 23.1% (55) 15.5% (37) University Relocation Remained Permanent 62.9% (270) 1.43 [0.6] 9.51 [5.67] 19.6% (53) 37.0% (100) 23.4% (63) 20.0% (54) 0.54 [0.91] 0.93 [0.33] Relocated 37.1% (159) 9.6 [5.29] 17.1% (27) 37.1% (59) 25.2% (40) 19.6% (31) Note: 1. (N) – number of respondents, indicated in parentheses. 2. [st.d] – standard deviation, indicated in square brackets. 3. Pearson Chi 2 [Pr] – results of the calculations of Chi-squared value, and the Pearson r coefficient [Pr] which is the two tailed significance level calculated using contingency tables in STATA. We are using 0.1 or below as our cutoff point for the significance level. 4. ANOVA [Pr > Chi 2 ] presents the results from Bartlett's test for equal variances, calculated in STATA using a one-way analysis of variance. As before, the cutoff point for Pr > Chi2 is 0.1statistically insignificant results. 5. Grouped yes-no – For the variable “change of permanent resident,” the tests are applied for two groups instead of the three presented in the table. Thus, the first group, “yes,” includes respondents who have experienced a change of permanent residence due to war, and “no,” includes those who do not have such experience. 6. *** and ** – mean pr < 0.01 and pr < 0.05, respectively. Age and anxiety. The prevalence of anxiety disorders appears relatively consistent across age groups. However, younger participants under 35 years of age had the highest percentages of moderate anxiety (42.5%) and moderately severe anxiety (24.7%). The lowest percentage of participants with severe anxiety (16.4%) was also observed in this group. Among those aged 35–45 years, 18.4% had mild anxiety, 36.8% had moderate anxiety, 21.7% had moderate severe anxiety, and 23.1% had severe anxiety. Among the 46–60 age groups, 19.2% had mild anxiety, 36.5% had moderate anxiety, 24.5% had moderate severe anxiety, and 19.8% had severe anxiety. For those aged 61 and older, the distribution shifted slightly: mild anxiety was reported by 21.7%, moderate anxiety by 29.7%, moderately severe anxiety by 29.7%, and severe anxiety by 18.9%. The data indicate that moderate anxiety is the most prevalent level across all age groups. However, younger respondents (under 35 years) tended to have higher levels of moderate anxiety, while older respondents (61 + years) had the highest prevalence of moderately severe anxiety. Severe anxiety is most pronounced in the 35–45 age group. Despite these variations, the statistical analysis indicated that there was no significant relationship between age and GAD (Pearson chi2: 3.54, Pr = 0.94; ANOVA: 1.39, Pr = 0.71). This suggests that while anxiety levels vary across age groups, age alone does not have a statistically significant influence on anxiety levels during wartime. Gender and anxiety. The data indicate some gender differences in the prevalence of anxiety disorders. Mild anxiety affected a similar proportion of females (19.1%) and males (17.5%). However, moderate anxiety is more prevalent among women, affecting 38.1% compared to 33.9% of men. The gap widened slightly with moderately severe anxiety, affecting 25% of females and 21.1% of males. Notably, severe anxiety showed a marked difference, affecting a greater percentage of men (27.5%) than women (17.8%). Overall, the data reveal notable differences between men and women. Men have a greater prevalence of severe anxiety (27.5%), while women are more commonly found in the moderate and moderately severe anxiety categories (38.1% and 25.0%, respectively). Overall, the mean GAD score wass greater among men (10.49, SD: 6.45) than women (9.22, SD: 5.15). The Pearson Chi2 test (4.79, Pr = 0.18) was not statistically significant, but the ANOVA result (Pr > Chi2 = 0.003) indicated that gender had a significant relationship with GAD. Scientific degree and anxiety. Among PhD students, moderate anxiety is the most prevalent (39.8%), and severe anxiety is the least common (13.3%). Those with a PhD showed a relatively even distribution across the four anxiety levels, while participants with a Doctor of Science degree exhibited the highest proportion of severe anxiety (26.0%) and a higher mean score (10.6, SD: 5.94). Despite these patterns, the Pearson chi2 (9.95, Pr = 0.36) and ANOVA tests (1.61, Pr = 0.65) indicated that the scientific degree had no significant relationship with GAD. Job title and anxiety. The assistants had the highest prevalence of moderate anxiety (41.5%) and a relatively balanced distribution across other anxiety levels. Senior Lecturers showed similar proportions across the four levels, while Associate Professors had the highest prevalence of moderate anxiety (37.4%). Professors had the highest prevalence of severe anxiety (26.8%). This suggests that as researchers progress to higher job positions, they may experience increased stress and mental health challenges. Despite this trend, statistical analysis revealed no significant relationship between job title and GAD (Pearson chi2: 5.37, Pr = 0.8; ANOVA: 1.39, Pr = 0.7). Change in permanent personal residence and anxiety. Internal migrants had the highest prevalence of severe anxiety (26.4%) and moderately severe anxiety (24.0%), with a mean GAD score of 10.45 (SD: 5.8). The external migrants also exhibited a high prevalence of severe anxiety (25.8%) and moderately severe anxiety (27.4%). Those who remained in place had a relatively low prevalence of severe anxiety (15.5%) and the highest prevalence of moderate anxiety (40.8%). Overall, internal and external migrants tend to have higher proportions of severe anxiety than those who stay in permanent locations. The elevated levels of severe anxiety among migrants highlight the psychological toll of personal forced displacement due to the full-scale war. The "grouped yes-no" analysis simplifies the categories into those who did or did not change residence due to the war, revealing a significant relationship between change of residence and GAD (Pearson Chi2: 9.13, Pr = 0.03). University relocation and anxiety. The distribution of anxiety levels was similar in both groups. Among those who worked at a university, which is a permanent location, mild anxiety affected 19.6% of participants, while moderate anxiety was most prevalent, impacting 37.0%. Moderately severe anxiety affects 23.4%, and severe anxiety impacts 20.0%. Among researchers who temporarily relocated universities to Ukraine-controlled territories, mild anxiety was reported by 17.1% of participants, and moderate anxiety remained the most common at 37.1%. Moderately severe anxiety affects 25.2%, while severe anxiety is present in 19.6%. Overall, the data indicate that moderate anxiety is the most prevalent level across both groups. The proportion of severe anxiety remains comparable between those who have worked at a university based on permanent campus location and those who have worked at a relocated university (20.0% and 19.6%, respectively). However, researchers from relocated universities have a slightly higher prevalence of moderately severe anxiety. These trends suggest that university relocation may have introduced additional stress factors that were not significant factors during the full-scale war. At the same time, the Pearson chi2 (0.54; Pr = 0.91) and ANOVA (0.93; Pr = 0.33) tests revealed no statistically significant relationships between university relocation and GAD. The distribution of GAD across sociodemographic variables among Ukrainian researchers provides valuable insights into the mental health challenges faced during the full-scale war. Despite variations in anxiety levels across age groups, the statistical analysis indicated no significant relationship between age and GAD. This finding suggested that age alone does not significantly influence anxiety levels during wartime. Gender differences are notable, with men showing a greater incidence of severe anxiety, while women more commonly experience moderate and moderately severe anxiety. Although the Pearson chi2 test showed no significant difference, the ANOVA results confirmed a significant relationship between gender and GAD. Although the scientific degree held by researchers does not appear to significantly affect anxiety levels, those with a Doctor of Science degree exhibit the highest prevalence of severe anxiety. Furthermore, the distribution across job titles indicates that professors who hold the highest ranks experience the most severe anxiety, possibly due to increased job stress and responsibilities. The most significant finding relates to changes in residence due to the war. Compared to those who stayed in permanent locations, internal and external migrants display elevated levels of severe anxiety, indicating the psychological toll of displacement. This relationship is confirmed statistically, emphasizing the need for specialized mental health support for those impacted by relocation. Finally, university relocation does not significantly influence GAD levels, although researchers from temporarily relocated universities to Ukraine-controlled territories have a slightly greater prevalence of moderately severe anxiety. Since gender differences and changes in permanent residence emerged as notable factors in the prevalence and severity of anxiety we applied both parametric (t-test) and non-parametric (Wilcoxon rank-sum) statistical tests to determine the significance of differences between genders and between groups who migrated and those who remained in place (Table 3 ). This in-depth statistical approach allowed us to confirm whether these sociodemographic factors significantly influenced GAD levels and to identify which groups might require targeted mental health support. Table 3 Parametric and non-parametric tests for gender and change in permanent personal residence. Variable H o hypothesis Test Test statistic Pr-value Conclusion Gender GAD(female) = GAD(male) t-test t = 2.08 Pr (T > t) = 0.019 H a is accepted. Suggest GAD(male) > GAD(female) rank-sum z = 1.563 Prob>|z|=0.1 Change in permanent residence GAD(migrants) = GAD(non- migrants) t-test t=-2.95 Pr (T GAD(non-migrants) rank-sum z=-2.78 Prob>|z|=0.005 Note: 1. The t-test is parametric Student’s t-test is used for the mean comparison of two groups and is calculated in STATA. Based on the assumption that the dataset is normally distributed. 2. Rank-sum – This is a non-parametric two-sample Wilcoxon rank-sum (Mann-Whitney) test used to compare two groups. It does not require any assumptions and thus gives robust results. 3. The cut-off point for both is pr = 0.1. The lower probability values allow us to conclude that the test's results are statistically significant. The comparison between male and female researchers regarding GAD scores begins with a t-test, where the null hypothesis states no significant difference between the genders. However, the t-test results (t = 2.08, Pr(T > t) = 0.019) reveal a statistically significant difference, leading to the rejection of the null hypothesis and indicating that males have significantly higher GAD scores than females. Although this significant result is captured by the t-test, the Wilcoxon rank-sum test (z = 1.563, Prob>|z| = 0.1) shows a less pronounced distinction between the two genders, implying that the difference, while present, may be nuanced and influenced by the choice of test. For changes in permanent personal residence, the t-test (t = -2.95, Pr(T < t) = 0.001) indicated a significant difference between researchers who migrated (internal or external) and those who remained, with migrants exhibiting higher GAD scores. This finding is corroborated by the Wilcoxon rank-sum test (z = -2.78, Prob>|z| = 0.005), which supports the hypothesis that forced migration is associated with increased anxiety. This agreement across both parametric and non-parametric tests emphasizes the psychological toll of displacement, indicating a substantial mental health burden among migrants and underscoring the importance of specialized support for those who were compelled to relocate due to the full-scale war. This analysis revealed significant differences in GAD scores by gender and by changes in permanent residence. While the gender-related differences are less clear, the impact of migration on anxiety is consistently evident. This suggests the need for mental health strategies that specifically address the unique challenges faced by displaced researchers, as well as gender-informed approaches to managing anxiety among researchers in wartime. The additional calculations in Table 4 were crucial for revealing nuanced patterns and better understanding the factors influencing GAD levels among Ukrainian researchers. By dividing the respondents into "risky" (moderately severe and severe GAD) and "non-risky" (mild and moderate GAD) groups, this analysis identified distinct patterns that are not evident when examining the entire sample. This separation allowed for the identification of personal characteristics that differentiate those at higher risk of anxiety from those with milder conditions. Table 4 Regression analyses for generalized anxiety disorders and sociodemographic characteristics. Risky and non-risky GAD groups. Variable GAD GAD Non-risky group GAD Risky group Female -1.25* (0.04) 0.31 (0.43) -1.83** (0.002) Migration 2.324*** (0.001) -0.038 (0.936) 1.417* (0.023) Age 0.048 (0.89) -0.378 (0.082) 0.06 (0.86) Degree 1.265* (0.013) 0.395 (0.2) 0.729 (0.175) Job title -0.871 (0.143) -0.131 (0.726) -0.386 (0.51) University Relocation -1.192 (0.088) 0.073 (0.877) -0.819 (0.205) Constant 8.645*** (0.000) 5.375*** (0.000) 14.45*** (0.000) N 429 239 190 Note: p-values in parentheses * p < 0.05, ** p < 0.01, *** p < 0.001 Non-risky group includes those respondents who have Mild and Moderate Anxiety GAD levels Risky group includes those respondents who have Moderately Severe and Severe GAD levels Regression analysis was applied to assess the impact of variables such as gender, migration status, age, scientific degree, university Relocation, and job title on GAD levels among Ukrainian researchers in wartime. Regarding gender, females in the risky group had significantly lower GAD scores than did their male counterparts (coefficient: -1.83, p = 0.002), while in the entire sample, being female was also associated with reduced GAD scores (coefficient: -1.25, p = 0.04). Migration status is a strong predictor of higher GAD scores, particularly in the risky group (coefficient: 1.417, p = 0.023), and across the entire sample (coefficient: 2.324, p = 0.001). However, migration does not significantly impact the non-risky group. Age did not appear to significantly affect GAD levels across any group, and the scientific degree was only associated with increased GAD scores in the overall sample (coefficient: 1.265, p = 0.013), but not within specific sub-groups. Job title did not significantly influence GAD scores in any group, and university relocation had a similarly non-significant effect. Overall, these results confirmed that certain factors, including migration status and gender, strongly influenced GAD scores in the risky group. Moreover, variables such as age and job title showed no significant relationship with anxiety levels. Discussion The present study reveals anxiety among Ukrainian researchers during the ongoing full-scale war and examines sociodemographic factors related to anxiety. The results show that nearly 44.3% of participants fell into the categories of moderately severe or severe anxiety, meeting the cut-off score for a probable GAD diagnosis. In contrast, studies conducted during peacetime in different countries have reported lower anxiety levels among researchers and academic staff. For instance, Meeks, Peak, and Dreihaus reported that 38.6% of academic staff members experienced anxiety [ 29 ], while Sharma, Shrestha, and Sah reported that 26.7% of academic staff members experienced anxiety [ 30 ]. Overall, our findings align with a study by Lim et al., who conducted a meta-analysis of 41 studies on anxiety [ 20 ]. The prevalence of anxiety during a war was 43.4%, while the prevalence of anxiety postwar was 30.3%. These results are consistent with our study, which revealed high levels of anxiety among researchers during the ongoing war in Ukraine. These findings underscore the significant mental health challenges faced by researchers during wartime, highlighting the contrast to peacetime. While the data confirm the obvious negative impact of war on mental health, the figures raise serious concerns about preserving the intellectual potential of the country's scientific community. Anxiety can have detrimental long-term consequences for researchers, including impaired cognition [ 31 ], decreased productivity [ 32 ], motivation [ 33 ], and negative effects on both mental and physical health [ 34 ]. These negative consequences are essential not only for the health of individual researchers but also for maintaining the continuity and quality of scientific research during and after military conflict. Unexpected results were obtained regarding the relationship between gender and the level of anxiety. Surprisingly, our findings contrast with many studies conducted in peacetime, which typically show higher anxiety levels among women than among men, both in the general population [ 35 , 36 , 37 ] and within the academic community [ 38 , 39 , 40 ]. Traditionally, it is well documented that more women are affected by anxiety disorders than men are. However, in the context of an ongoing war, our study reveals a different scenario: men are more vulnerable to anxiety disorders. This raises crucial questions about the roles and societal expectations placed on men, regardless of their professional role and field of activity during the war and the potential for unaddressed mental health needs within this demographic. The significant difference in anxiety levels between genders was confirmed by ANOVA, underscoring the need for gender-sensitive mental health interventions. This shift underscores the profound impact that war has had on mental health, affecting traditional gender disparities in the prevalence of anxiety. One significant factor contributing to this unexpected result appears to be the roles and responsibilities men often assume during wartime, which may heighten their susceptibility to anxiety. In Ukraine, men are conscripted. The fact that male researchers remain involved in scientific activities, as opposed to actively protecting their native country, can provoke feelings of guilt or shame. Research shows that there is a correlation between guilt, shame, and anxiety [ 41 , 42 , 43 ]. However, studies have shown mixed results on the strength and significance of these correlations, indicating that guilt may not be a strong predictor of anxiety in nonclinical populations during peacetime [ 44 ]. Therefore, this issue requires a separate study to establish the relationship of such interdependence in times of military conflict. Another important finding of this study is the significant relationship between academic anxiety and temporary displacement due to the full-scale war in Ukraine. There is limited direct evidence on the specific relationship between anxiety and migration among researchers. However, the provided sources offer relevant insights into the broader context of migration and mental health, revealing that migration, whether external or internal, can be a significant stressor that increases the risk of developing mental health issues such as anxiety [ 45 , 46 , 47 , 48 ]. Additionally, humanitarian migrants are especially vulnerable to mental health problems due to the stressful circumstances surrounding their migration [ 49 , 50 ]. The results of our study show that both internal and external migrants exhibit significantly greater rates of severe anxiety than those who remain in their original locations, highlighting the profound psychological toll of displacement. Additionally, researchers who were forced to become internally displaced experienced a greater prevalence of moderately severe anxiety. Interestingly, the relocation of universities to territories controlled by Ukraine did not significantly impact anxiety levels. This suggests that the psychological effects of displacement are more closely tied to the personal disruptions experienced by researchers than to the physical relocation of their institutions. The significant relationship between forced migration and anxiety levels highlights the profound psychological toll of displacement, emphasizing the need for specialized support for migrants. We also investigated whether other sociodemographic factors, such as age, scientific degree, and job title, were significantly correlated with anxiety among Ukrainian researchers during wartime. Our findings indicate that these factors did not have a significant correlation with anxiety. This finding contrasts with other studies conducted in peacetime. For example, PhD students are more likely to experience high levels of anxiety due to the instability of their work-life balance [ 51 , 52 , 53 , 54 ]. However, this study suggested that during wartime, the usual sociodemographic factors of anxiety may not have the same significance. The unique stressors and disruptions caused by the war likely overshadow the influences of age, scientific degree, and job title on anxiety levels. Conclusion This study highlights three critical findings regarding the mental health of Ukrainian researchers during the full-scale war: the generally high level of anxiety, the unexpected gender differences in anxiety prevalence, and the significant impact of migration on anxiety levels. First, the generally high level of anxiety among Ukrainian researchers is alarming, with nearly 44.3% of participants experiencing moderately severe to severe anxiety. This prevalence is notably greater than the anxiety levels reported in peacetime studies across various populations, indicating the severe mental health toll exerted by the ongoing war. Second, contrary to existing research, which typically finds higher anxiety levels among women, our study reveals that men are more susceptible to severe anxiety during wartime. This finding suggests that the traditional gender dynamics of anxiety are altered in the context of war. The increased responsibilities and societal expectations placed on men, including conscription and protection duties, may contribute to heightened anxiety levels, necessitating gender-sensitive mental health interventions. Finally, the impact of migration, whether internal or external, significantly exacerbates anxiety among researchers. Displaced individuals exhibit greater levels of severe anxiety than those who remain in their original locations. This aligns with broader research on the psychological effects of forced displacement among researchers. These findings underscore the urgent need for targeted mental health support for displaced researchers, addressing both the immediate and long-term effects of displacement. Additionally, the results highlight the importance of developing gender-specific interventions to address the unique mental health challenges faced by researchers in conflict zones. Further research is needed to understand the long-term effects of war-related stressors and to develop and implement appropriate support strategies and interventions at the national, institutional, community, and individual levels. Addressing these challenges is crucial for preserving the intellectual potential and scientific advancement of Ukraine. Limitations Our study, the first to examine the anxiety of academics in Ukraine using a nationally representative sample during a full-scale war, has several limitations. We employed nonrandomized convenience sampling, which affects the representativeness and generalizability of our results. This approach was necessary due to the ongoing war, physical distancing, and migration within the academic community. The cross-sectional design of our study limits our ability to assess the temporality of events, making it difficult to determine causality. Additionally, relying on self-reported conditions may have led to underreporting of mental health issues and social desirability bias, and retrospective data collection does not eliminate this bias. Finally, the unknown number of individuals who viewed the online invitations complicates the determination of the survey response rate and the assessment of the sample's representativeness. Methods Study design and data collection This study used a cross-sectional analytical design to collect data through an online survey. Before the main study, a pilot test involving 15 research members was conducted to ensure the clarity of the questions and confirm that the survey could be completed within 12 minutes. The data were collected between December 2023 and February 2024. The survey, which was distributed to researchers at Ukrainian universities via email using Google Forms, maintained participant anonymity and ensured voluntary participation throughout the study. The inclusion criteria included researchers working in Ukrainian universities during the full-scale war period. Participants were informed of the study's objectives and provided informed consent before participation. However, the study's response rate could not be determined because the number of individuals who viewed the online invitation could not be assessed. Measures The online survey comprised a questionnaire, that took 10 to 15 minutes to complete. It consisted of two sections: (a) sociodemographic characteristics and (b) self-assessments. The first section collected background information, including age, gender, scientific degree, job title, changes in personal residence during the full-scale war, and university relocation due to the conflict. The second section used the self-reported Generalized Anxiety Disorder (GAD-7) questionnaire. The GAD-7 was selected due to its proven validity and reliability as a widely used screening tool for identifying and assessing the severity of GAD. It has been translated into Ukrainian, making it suitable for this study. Participants responded to how frequently they experienced anxiety symptoms over the preceding two weeks using a 4-point Likert scale (0 = not at all, 1 = several days, 2 = more than half the days, and 3 = nearly every day). Scores from the seven items were summed to provide a total score ranging from 0 to 21. Based on receiver operating characteristic analysis, GAD-7 cut-off scores of ≥ 5, ≥10, and ≥ 15 indicated mild, moderate, and severe anxiety, respectively. Statistical analysis The data generated through Google Forms ware downloaded into an Excel spreadsheet and imported into STATA® software for analysis. Before loading into STATA, logical control of the empirical basis was carried out. The median, mean, standard deviation, and percentile range (25th-75th percentile) were calculated for each anxiety level to understand the central tendencies and variability of GAD scores. These inferential statistical analyses were used to investigate the relationship between GAD levels and sociodemographic factors: 1. Contingency tables. The data distribution was analysed using contingency tables, providing an overview of the general patterns and relationships between GAD and various sociodemographic variables. 2. Chi-square test. A chi-square test of independence was used to test for statistically significant associations between categorical sociodemographic variables and GAD levels. Pearson's chi-square values and p-values were calculated using contingency tables, with a significance level of 0.1. Results with a p-value above 0.1 were considered statistically insignificant. 3. Analysis of variance (ANOVA). One-way ANOVA was used to analyse differences in mean GAD scores across sociodemographic groups. Bartlett's test for equal variances ensured the validity of ANOVA results. 4. Additional parametric and non-parametric tests. Both parametric (t-test) and non-parametric (Wilcoxon rank-sum) tests were used to compare GAD scores between specific groups. These tests revealed significant differences between genders and between those who had migrated due to the war and those who had not. The following regression equation was used to analyse the relationships between sociodemographic factors and GAD scores: $${GAD}_{i}=\alpha +{\beta }_{1}Female+{\beta }_{2}Migration+{\beta }_{3}Age+{\beta }_{4}Degree+{\beta }_{5}Job Title+{\beta }_{6}University Relocation$$ where Female is a dummy variable indicating gender (1 = female, 0 = male); and Migration is a dummy variable indicating change in permanent residence (1 = displaced, 0 = not displaced). 5. Regression analysis. Regression analysis was conducted using the Ordinary Least Squares (OLS) method to examine the effects of various personal characteristics on GAD scores. The analysis differentiated between the "at-risk" (moderately severe and severe anxiety) and "not-at-risk" (mild and moderate anxiety) groups to identify characteristics that may increase the risk of higher anxiety levels. The coefficients and their corresponding p-values are reported, with statistical significance marked at various levels (*p < 0.05, **p < 0.01, ***p < 0.001). Declarations Data availability statement The data sets used and/or analysed during the current study are available from the corresponding author upon reasonable request. Acknowledgment The research teams acknowledge the Armed Forces of Ukraine for providing safety during their research and credit their perseverance and courage for making this possible. Author contributions statement The conceptualization was made by N.T. and Y.S. The methodology was developed by N.T. and Y.S. The data were curated by U.K. The original draft was written by N.T., H.L. and A.P. The writing, review and editing were performed by Y.S. All the authors read and approved the final manuscript. Competing Interests Statement The authors declare that there are no conflicts of interest related to the conduct of this study. Ethical considerations This study adhered to relevant guidelines and regulations, complying with the Declaration of Helsinki. The Research Ethics Committee of Berdyansk State Pedagogical University approved the study under protocol number 7, dated September 10, 2023. Informed consent was obtained from all participants. References Hammoudi Halat, D., Soltani, A., Dalli, R., Alsarraj, L. & Malki, A. Understanding and fostering mental health and well-being among university faculty: a narrative review. J. Clin. Med. 12 , 4425; 10.3390/jcm12134425 (2023). World Mental Health Report: transforming mental health for all. Licence: CC BY-NC-SA 3.0 IGO; World Health Organization: Geneva, Switzerland, (2022). De Caux, B. C., Pretorius, L. & Macaulay, L. Research and teaching in a pandemic world: the challenges of establishing academic identities during times of crisis. Springer Science and Business Media LLC . 1-554 (2023). Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic. Lancet 398 , 1700-1712; 10.1016/S0140-6736(21)02143-7 (2021). World Health Organization. Anxiety disorders. https://www.who.int/news-room/fact-sheets/detail/anxiety-disorders (2024). American Psychological Association. Anxiety. APA Dictionary of Psychology https://dictionary.apa.org/anxiety (2024). Kakaje, A. et al. Mental disorder and PTSD in Syria during wartime: a nationwide crisis. BMC Psychiatry 21 , 2; 10.1186/s12888-020-03002-3 (2021). Carvajal, R. F. P. & Guedea, M. T. D. Stress in university research professors: a systematic review. Salud Ment. 44 , 249-256; 10.17711/SM.0185-3325.2021.032 (2021). Mainous, A. G. 3rd, Rahmanian, K. P., Ledford, C. J. W. & Carek, P. J. Professional identity, job satisfaction, and commitment of nonphysician faculty in academic family medicine. Fam. Med. 50 , 739-745; 10.22454/FamMed.2018.273724 (2018). Molero Jurado, M. D. M., Pérez-Fuentes, M. D. C., Oropesa Ruiz, N. F., Simón Márquez, M. D. M. & Gázquez Linares, J. J. Self-efficacy and emotional intelligence as predictors of perceived stress in nursing professionals. Medicina 55 , 237; 10.3390/medicina55060237 (2019). Barnett, M. J., Lindfelt, T., Doroudgar, S., Chan, E. & Ip, E. J. Pharmacy-faculty work-life balance and career satisfaction: comparison of national survey results from 2012 and 2018. Explor. Res. Clin. Soc. Pharm. 5 , 100112; 10.1016/j.rcsop.2022.100112 (2022). Adrian, C. M., Cox, S. S., Phelps, L. D., Schuldt, B. A. & Totten, J. W. Issues causing stress among business faculty members. J. Acad. Adm. High. Educ. 10 , 41-46 (2014). Kennedy, D. R. et al. Enhancing pharmacy faculty well-being and productivity while reducing burnout. Am. J. Pharm. Educ. 86 , 8764; 10.5688/ajpe876 (2022). Levin, J. S., Aliyeva, A. & Walker, L. From community college to university: institutionalization and neoliberalism in British Columbia and Alberta. Can. J. High. Educ. 46 , 165-180 (2016). Herbert, D. L., Coveney, J., Clarke, P., Graves, N. & Barnett, A. G. The impact of funding deadlines on personal workloads, stress and family relationships: a qualitative study of Australian researchers. BMJ Open 4 , e004462; 10.1136/bmjopen-2013-004462 (2014). Piano, M. et al. A rapid review of challenges and opportunities related to diversity and inclusion as experienced by early and mid-career academics in the medicine, dentistry and health sciences fields. BMC Med. Educ. 23 , 288; 10.1186/s12909-023-04252-x (2023). Zheng, M. et al. Covid academic pandemic: techno stress faced by teaching staff for online academic activities. Front. Psychol. 13 , 288; 10.3389/fpsyg.2022.895371 (2022). Dhont, J. et al. Conducting research in Radiation Oncology remotely during the COVID-19 pandemic: coping with isolation. Clin. Transl. Radiat. Oncol. 24 , 53-59; 10.1016/j.ctro.2020.06.006 (2020). Park, J. & Moghaddam, B. Impact of anxiety on prefrontal cortex encoding of cognitive flexibility. Neuroscience 345 , 193-202; 10.1016/j.neuroscience.2016.06.013 (2017). Lim, I. C. Z. Y. et al. Prevalence of depression, anxiety and post-traumatic stress in war- and conflict-afflicted areas: a meta-analysis. Front. Psychiatry 13 , 978703; 10.3389/fpsyt.2022.978703 (2022). Yurtsenyuk, O. & Sumariuk, B. Impact of the war on the mental health of Ukrainians: factors in formation of neurotic and stress-associated mental disorders. Art Med.; 10.21802/artm.2023.2.26.248 (2023). Kurapov, A. et al. The mental health impact of the ongoing Russian-Ukrainian war 6 months after the Russian invasion of Ukraine. Front . Psychiatry 14 , 1134780; 10.3389/fpsyt.2023.1134780 (2023). Martsenkovskyi, D. et al. Mental health in Ukraine in 2023. Eur. Psychiatry 67 , 1; 10.1192/j.eurpsy.2024.12 (2024). Tsybuliak, N. et al. Burnout dynamic among Ukrainian academic staff during the war. Sci. Rep. 13 , 17975; 10.1038/s41598-023-45229-6 (2023). Bohdanov, I., Kovachov, S., Tsybuliak, N., Lopatina, H., Popova, A. & Suchikova, Y. Resilience in wartime research: case of anticrisis management at a Ukrainian university. In 2023 IEEE 18th International Conference on Computer Science and Information Technologies (CSIT); 10.1109/csit61576.2023.10324134 (2023). Suchikova, Y., Tsybuliak, N., Lopatina, H., Shevchenko, L. & Popov, A. I. Science in times of crisis: how does the war affect the efficiency of Ukrainian scientists? Probl. Perspect. Manag. 21 , 408-424; 10.21511/ppm.21(1).2023.35 (2023). Ressler, A. et al. Alone on the frontline: the first report of PTSD prevalence and risk in de-occupied Ukrainian villages. Int. J. Soc. Psychiatry ; 10.1177/00207640241242030 (2024). Spitzer, R. L., Kroenke, K., Williams, J. B. & Löwe, B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch. Intern. Med. 166 , 1092-1097; 10.1001/archinte.166.10.1092 (2006). Meeks, K., Peak, A. S. & Dreihaus, A. Depression, anxiety, and stress among students, faculty, and staff. J. Am. Coll. Health 71 , 348-354; 10.1080/07448481.2021.1891913 (2023). Sharma, B., Shrestha, N. & Sah, S. K. Anxiety among faculty members of academic institutions of a metropolitan city: a descriptive cross-sectional study. JNMA J. Nepal Med. Assoc. 61 , 338-342; 10.31729/jnma.8133 (2023). Razavi, S. A., Shahrabi, A. & Siamian, H. The relationship between research anxiety and self-efficacy. Mater. Sociomed . 29 , 247-250; 10.5455/msm.2017.29.247-250 (2017). Erickson, S. R. et al. Severity of anxiety and work-related outcomes of patients with anxiety disorders. Depress. Anxiety 26 , 1165-1171; 10.1002/da.20624 (2009). Hall, S. A mental-health crisis is gripping science – toxic research culture is to blame. Nature 617 , 666-668; 10.1038/d41586-023-01708-4 (2023). Robinson, O. J., Vytal, K., Cornwell, B. R. & Grillon, C. The impact of anxiety upon cognition: perspectives from human threat of shock studies. Front. Hum. Neurosci. 7 , 203; 10.3389/fnhum.2013.00203 (2013). Alonso, J., Liu, Z., Evans-Lacko, S. et al. Treatment gap for anxiety disorders is global: results of the World Mental Health Surveys in 21 countries. Depress. Anxiety 35 , 195-208, 10.1002/da.22711 (2018). McLean, C. P., Asnaani, A., Litz, B. T. & Hofmann, S. G. Gender differences in anxiety disorders: prevalence, course of illness, comorbidity and burden of illness. J. Psychiatr. Res. 45 , 1027-1035; 10.1016/j.jpsychires.2011.03.006 (2011). Christiansen, D. M. Examining sex and gender differences in anxiety disorders. InTech .; 10.5772/60662 (2015). Wojtera, B. et al. Changes in psychological distress among Polish medical university teachers during the COVID-19 pandemic. PLoS One 17 , e0278311; 10.1371/journal.pone.0278311 (2022). Oducado, R. M., Rabacal, J., Moralista, R. & Tamdang, K. Perceived stress due COVID-19 pandemic among employed professional teachers. iJERI 305-316; 10.46661/ijeri.5284 (2020). Deiana, G. et al. Gender equality in the Italian academic context. Results from the IGEA project. Front. Public Health 11 , 1125496; 10.3389/fpubh.2023.1125496 (2023). Gao, Q., Zhang, K., Cao, Y. et al. The effect of negative workplace gossip about supervisor on workplace deviance and impression management: the mediating roles of anxiety and guilt. J. Bus. Psychol. 39 , 435-454; 10.1007/s10869-023-09888-6 (2024). Cândea, D. M. & Szentagotai-Tătar, A. Shame-proneness, guilt-proneness and anxiety symptoms: a meta-analysis. J. Anxiety Disord. 58 , 78-106; 10.1016/j.janxdis.2018.07.005 (2018). Taylor, L.-A., Reid, J. & Jagroop-Dearing, A. The impacts of the COVID-19 traffic light system on staff in tertiary education in New Zealand. Educ. Sci. 14 , 48; 10.3390/educsci14010048 (2024). Gojowy, A. et al. Sense of guilt and anxiety in depression. Eur. Psychiatr y 26 , 644-644 (2011). Brunnet, A. E., Kristensen, C. H., Lobo, N. dos S. & Derivois, D. Migration experience and mental health: a qualitative study in France and Brazil. Int. J. Soc. Psychiatry 68 , 376-383; 10.1177/0020764021999695 (2022). Liao, Z. X., Tan, X. M. & Zhao, Y. Y. Association between internal migration experience and depressive symptoms: analysis of PSID data. BMC Public Health 23 , 1145; 10.1186/s12889-023-16073-0 (2023). Derluyn, I. et al. The impact of trauma and daily hardships on the mental health of unaccompanied refugee minors detained in Libya. BJPsych Open 9 , E8; 10.1192/bjo.2022.622 (2023). Popovych, I., Hudimova, A., Bokhonkova, Yu., Savchuk, O., Hoian, I. & Shevchenko, N. Dispositional mental states of internally displaced university teachers under martial law: gender differences. J. Educ. Cult. Soc. 14 , 171-187; 10.15503/jecs2023.2.171.181 (2023). Essayagh, F. et al. The prevalence and risk factors for anxiety and depression symptoms among migrants in Morocco. Sci. Rep. 13 , 3740; 10.1038/s41598-023-30715-8 (2023). Kuzikova, S. B., Zlyvkov, V. L. & Lukomska, S. O. Traumatic experience of residents of the de-occupied territories of Ukraine. Insight Psychol. Dimens. Soc. 9 , 228-243; 10.32999/KSU2663-970X/2023-9-13 (2023). Andrews, E. J., Harper, S., Cashion, T., Palacios-Abrantes, J., Blythe, J., Daly, J. et al. Supporting early career researchers: insights from interdisciplinary marine scientists. ICES J. Mar. Sci. 77 , 476-485; 10.1093/icesjms/fsz247 (2020). Belavy, D. L., Owen, P. J. & Livingston, P. M. Do successful PhD outcomes reflect the research environment rather than academic ability? PLoS One 15 , e0236327; 10.1371/journal.pone.0236327 (2020). Satinsky, E. N. et al. Systematic review and meta-analysis of depression, anxiety, and suicidal ideation among Ph.D. students. Sci. Rep. 11 , 14370; 10.1038/s41598-021-93687-7 (2021). Woolston, C. Postdoc survey reveals disenchantment with working life. Nature 587 , 505-508; 10.1038/d41586-020-03191-7 (2020). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 07 Nov, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 26 Aug, 2024 Reviews received at journal 23 Aug, 2024 Reviewers agreed at journal 13 Aug, 2024 Reviews received at journal 12 Aug, 2024 Reviews received at journal 07 Jul, 2024 Reviewers agreed at journal 23 Jun, 2024 Reviewers agreed at journal 22 Jun, 2024 Reviewers invited by journal 21 Jun, 2024 Editor assigned by journal 21 Jun, 2024 Editor invited by journal 21 Jun, 2024 Submission checks completed at journal 20 Jun, 2024 First submitted to journal 19 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4603070","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":324457622,"identity":"80fa07cf-9909-4e4b-977a-daa27663a998","order_by":0,"name":"Natalia Tsybuliak","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIie2PsWrDMBCGz6g0ix7AoXkIT3JDjf0gXSQE7tQ3CEYlkC5+gLxE1s4KhkymWlWy1HjtoNFDh57dDl1sZyxUH+hOHPfxcwAezx+GRkAUgE7wHzzp6WWCj/dK0Ct5r6iLFPhRqmE2qcQLc3RBV6ziUOzCrjbp4bnClE1yP6asS0lC4BVd78VuWdqzfKkFKqf8UY0okZaAiqaRxRTqzpJpVAJVjSumJR3wYlCWn+5VMtPMKFZeYwoZlBtqdcrsXIpt2S3P8Zay2d6tasmZxRQ+dYsRrXVJkcULeXz7OKUZMw/Nu9sko8oA/25XIRahfk1mIQ5LduGyx+Px/CO+ALfYZyJlN5IqAAAAAElFTkSuQmCC","orcid":"","institution":"Berdyansk State Pedagogical University","correspondingAuthor":true,"prefix":"","firstName":"Natalia","middleName":"","lastName":"Tsybuliak","suffix":""},{"id":324457623,"identity":"3aff1add-97cd-4d78-92d2-625ee751e95d","order_by":1,"name":"Uliana Kolomiiets","email":"","orcid":"","institution":"Sumy State University","correspondingAuthor":false,"prefix":"","firstName":"Uliana","middleName":"","lastName":"Kolomiiets","suffix":""},{"id":324457624,"identity":"ea31e97e-f2b3-490d-b0b0-827d63020ec7","order_by":2,"name":"Hanna Lopatina","email":"","orcid":"","institution":"Berdyansk State Pedagogical University","correspondingAuthor":false,"prefix":"","firstName":"Hanna","middleName":"","lastName":"Lopatina","suffix":""},{"id":324457625,"identity":"5d342d0d-4fb3-4960-b22e-cc0ae867b4dc","order_by":3,"name":"Anastasia Popova","email":"","orcid":"","institution":"Berdyansk State Pedagogical University","correspondingAuthor":false,"prefix":"","firstName":"Anastasia","middleName":"","lastName":"Popova","suffix":""},{"id":324457626,"identity":"2cbf7769-b622-40cd-8a31-e0fa345ca31f","order_by":4,"name":"Yana Suchikova","email":"","orcid":"","institution":"Berdyansk State Pedagogical University","correspondingAuthor":false,"prefix":"","firstName":"Yana","middleName":"","lastName":"Suchikova","suffix":""}],"badges":[],"createdAt":"2024-06-19 04:18:54","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4603070/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4603070/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-78052-8","type":"published","date":"2024-11-07T15:57:09+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":68749829,"identity":"5a0dc093-8de9-4c5f-bf79-ea0543e0af5a","added_by":"auto","created_at":"2024-11-11 16:06:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":779685,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4603070/v1/a51753b5-5558-4813-98f1-fd0f81914595.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"War, Researchers, and Anxiety: Evidence from Ukraine","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe mental health of academic communities is a crucial aspect of their well-being and productivity. Modern research indicates an increase in mental health issues among researchers due to the challenges posed by the academic and social environment. These issues can negatively impact their efficiency, education quality, and research activities [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In 2022, the World Health Organization (WHO) declared mental health a \u0026ldquo;growing crisis\u0026rdquo;, highlighting the exacerbation of mental disorders due to the COVID-19 pandemic [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], which also had a significant impact on the academic environment [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAnxiety is one of the most common mental health issues among researchers [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], constituting one of the most severe mental health conditions and ranking among the top 25 causes of disease burden worldwide [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. According to the WHO, anxiety disorders are characterized by excessive fear, worry, and related behavioural disturbances [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAnxiety is an emotion accompanied by a sense of danger and physical symptoms of tension when a person anticipates a potential threat, disaster, or failure. This anticipatory state mobilizes the body for action: muscle tension, breathing quickens, and heart rate accelerates. Anxiety is characterized as a future-oriented and persistent response to an unclear, diffuse threat [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSymptoms of anxiety can be severe enough to cause significant distress or substantial impairment in functioning [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. High levels of anxiety among researchers are often caused by psychological stress changes. These changes include a lack of control and emotional exhaustion, resulting from overload, multitasking, demanding evaluation systems, the complexity of the academic path, and lack of recognition [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], including limited autonomy, insufficient resources, poor support, numerous conflicting types of work, and personal duties, as well as an imbalance between work and personal life [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Specific factors of anxiety in academic communities are associated with operating within a progressive discourse of competition, productivity pressure, accountability, and the commercialization of education [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], the absence of guarantees for contract renewal, and the constant fear that employment may depend on funding outcomes or grant awards [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], as well as the developing digital world, which causes 'technostress' among members of academic communities [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. This creates a constant feeling of tension, anxiety, and uncertainty, negatively impacting the productivity and well-being of researchers, reducing their effectiveness, and worsening their health, including physical and psychological symptoms, even in peaceful and calm times [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAnother factor exacerbating anxiety and affecting the mental health of researchers is military conflicts. Studies have shown that direct exposure to military actions significantly increases the risk of developing generalized anxiety disorder (GAD) and post-traumatic stress disorder (PTSD), especially among people who are directly in conflict zones, who are experiencing physical violence, or who are witnessing severe human suffering [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The impact of war also includes socioeconomic stresses and disruptions in social connections, which can cause mental health to deteriorate further in the long term [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn Ukraine, where the full-scale war has been ongoing for more than two years, the mental health of the academic community faces significant challenges. In the context of general research on the impact of war on mental health, a study by Yurtsenyuk and Sumariuk (2023) revealed a high prevalence of mental disorders, including depression, anxiety, and PTSD, among Ukrainians, reflecting a global trend identified by the WHO, where one in five participants in armed conflicts experience mental disorders, equivalent to approximately 9.6\u0026nbsp;million Ukrainians who potentially may have mental health issues such as depression, anxiety disorders, and stress disorders, including PTSD [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The impact of war varies depending on gender, age, and living conditions, with higher levels of anxiety, depression, and stress among those directly affected by military actions and increased levels of traumatic symptoms among women and young people [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, there is limited specific information on the mental health of Ukrainian researchers. Existing studies are fragmented, indicating gaps in research on the impact of war on their mental health. Prolonged military conflicts significantly increase the level of burnout, especially among women [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], increase the use of psychoactive substances, and contribute to the emergence of symptoms of depression, fatigue, loneliness, and worsening mental health [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. These data confirm a significant increase in post-traumatic symptoms among the researchers and their negative impact on research and educational institutions, particularly due to war-related factors such as migration, university displacement, loss of homes, social isolation, and constant life-threatening danger. Additionally, instability in critical infrastructure operations, including issues with electricity, communication, and internet access, exacerbates these challenges [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This underscores the need for the development of specialized support programs to mitigate the impact on mental health [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The absence of systematic studies analysing the prevalence and severity of anxiety among researchers during wartime underscores the need to enhance scientific efforts in this direction to develop effective support strategies. These strategies impact the productivity, mental health and well-being of researchers, as well as the country's academic potential and economic resilience.\u003c/p\u003e \u003cp\u003eThe primary aim of this study was to assess the prevalence and severity of anxiety among Ukrainian researchers during the war. Although the war in Ukraine began in 2014 in some regions, our study focuses on the impact of the full-scale war that has continued since 2022. This full-scale war means there is no safe place, and people in every part of the country are experiencing the effects of the war. Specifically, this study seeks to identify the researchers' sociodemographic factors that significantly influence anxiety levels in academia, focusing on differences by gender, migration status, age, scientific degree, job title, and university relocation due to occupation of Ukrainian territories by Russian troops.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe study included a total of 429 Ukrainian researchers, representing a diverse cross-section of individuals affected by the full-scale war in Ukraine. The data in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e reveal the prevalence and severity of GAD.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGeneralized anxiety disorders among Ukrainian researchers in wartime.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLevel of GAD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGAD values\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDistribution, N\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDistribution, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGAD, median (25\u0026ndash;75 percentile)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGAD, mean\u003c/p\u003e \u003cp\u003e(standard deviation)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMild anxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e(2\u0026ndash;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.44\u003c/p\u003e \u003cp\u003e(1.35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate anxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026ndash;9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003cp\u003e(6\u0026ndash;8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.97\u003c/p\u003e \u003cp\u003e(1.28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerately severe anxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u0026ndash;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003cp\u003e(11\u0026ndash;13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.84\u003c/p\u003e \u003cp\u003e(1.42)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSevere anxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u0026ndash;21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18\u003c/p\u003e \u003cp\u003e(16\u0026ndash;21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18.08\u003c/p\u003e \u003cp\u003e(2.37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.55\u003c/p\u003e \u003cp\u003e(5.52)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eNote:\u003c/p\u003e \u003cp\u003e1. GAD values \u0026ndash; the cut-off points used for differentiating respondents\u0026rsquo; anxiety levels.\u003c/p\u003e \u003cp\u003e2. N \u0026ndash; number of respondents.\u003c/p\u003e \u003cp\u003e3. 25\u0026ndash;75 percentile \u0026ndash; shows the median GAD score for each of the four anxiety levels.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOver 80% of respondents had moderate to severe anxiety disorders, with the largest group in the moderate range (37.1% with a median score of 7 and a mean of 6.97). The second largest group, comprising nearly one-fourth of respondents, was in the moderately severe range (24.0%, median score 12, mean 11.84). One fifth of respondents (20.1%, median score 18, mean 18.08) had severe anxiety. The smallest group had no anxiety or mild anxiety (18.6%, median score 3, mean 2.44).\u003c/p\u003e \u003cp\u003eThe overall mean score of 9.55 suggested that the majority of participants exhibited moderate anxiety levels on average. At the same time, using the GAD-7 scoring system by Spitzer et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], where a score of 10 or greater indicates a probable case of GAD, this analysis showed that nearly 44.3% of participants fall into the categories of moderately severe or severe anxiety, meeting the cut-off score for a probable GAD diagnosis. This finding underscores the significant mental health challenges faced by researchers.\u003c/p\u003e \u003cp\u003eTo better understand the relationship between GAD and various sociodemographic factors among Ukrainian researchers, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the distribution of GAD across different variables using statistical analyses.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of generalized anxiety disorders across sociodemographic variables among Ukrainian researchers.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eSubcategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGAD, mean\u003c/p\u003e \u003cp\u003e[st.d.]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eLevel of GAD, % (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eTests\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eName\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDistribution, %\u003c/p\u003e \u003cp\u003e(N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003cp\u003e[st.d.]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMild Anxiety\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eModerate Anxiety\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eModerately Severe Anxiety\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSevere Anxiety\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePearson Chi\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e[Pr]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eANOVA\u003c/p\u003e \u003cp\u003e[Pr\u0026thinsp;\u0026gt;\u0026thinsp;Chi\u003csup\u003e2\u003c/sup\u003e]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnder 35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17%\u003c/p\u003e \u003cp\u003e(73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e2.39\u003c/p\u003e \u003cp\u003e[0.87]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.46\u003c/p\u003e \u003cp\u003e[5.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.4% (12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e42.5% (31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e24.7% (18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e16.4% (12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e3.54\u003c/p\u003e \u003cp\u003e[0.94]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003cp\u003e[0.71]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u0026ndash;45 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.4%\u003c/p\u003e \u003cp\u003e(153)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.69\u003c/p\u003e \u003cp\u003e[5.47]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18.4% (28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e36.8% (56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21.7% (33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23.1% (35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46\u0026ndash;60 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.9%\u003c/p\u003e \u003cp\u003e(167)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.43\u003c/p\u003e \u003cp\u003e[5.62]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.2% (32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e36.5% (61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e24.5% (41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.8% (33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61 older\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.7%\u003c/p\u003e \u003cp\u003e(37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.64\u003c/p\u003e \u003cp\u003e[6.11]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.7% (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e29.7% (11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29.7% (11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18.9% (7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.4%\u003c/p\u003e \u003cp\u003e(109)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003cp\u003e[0.43]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.49\u003c/p\u003e \u003cp\u003e[6.45]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.1% (61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e38.1% (122)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25.0% (80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e17.8% (57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4.79\u003c/p\u003e \u003cp\u003e[0.18]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e8.69\u003c/p\u003e \u003cp\u003e[0.003]***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.6%\u003c/p\u003e \u003cp\u003e(320)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.22\u003c/p\u003e \u003cp\u003e[5.15]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.5% (19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33.9% (37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21.1% (23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e27.5% (30)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eScientific Degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhD Students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.4%\u003c/p\u003e \u003cp\u003e(83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e2.83\u003c/p\u003e \u003cp\u003e[0.88]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.06\u003c/p\u003e \u003cp\u003e[5.14]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.7% (18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e39.8% (33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25.3% (21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13.3% (11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e9.95\u003c/p\u003e \u003cp\u003e[0.36]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e1.61\u003c/p\u003e \u003cp\u003e[0.65]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhD Degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.6%\u003c/p\u003e \u003cp\u003e(273)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.58\u003c/p\u003e \u003cp\u003e[5.48]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.0% (52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37.0% (101)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23.1% (63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e20.9% (57)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDoctor of Science\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17%\u003c/p\u003e \u003cp\u003e(73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003cp\u003e[5.94]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.7% (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e34.2% (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26.0% (19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e26.0% (19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eJob Title\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAssistant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.6%\u003c/p\u003e \u003cp\u003e(41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003cp\u003e[0.82]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.58\u003c/p\u003e \u003cp\u003e[5.04]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.1% (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41.5% (17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22.0% (9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.5% (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e5.37\u003c/p\u003e \u003cp\u003e[0.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003cp\u003e[0.7]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSenior Lecturer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.5%\u003c/p\u003e \u003cp\u003e(71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003cp\u003e[5.63]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.1% (15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33.8% (24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26.8% (19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18.3% (13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAssociate Professor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57.4%\u003c/p\u003e \u003cp\u003e(246)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.38\u003c/p\u003e \u003cp\u003e[5.45]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.3% (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37.4% (92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23.2% (57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.1% (47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProfessor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.5%\u003c/p\u003e \u003cp\u003e(71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.66\u003c/p\u003e \u003cp\u003e[5.91]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.3% (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e36.6% (26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25.4% (18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e26.8% (19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eChange in permanent personal residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInternal Migrants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.1%\u003c/p\u003e \u003cp\u003e(129)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003cp\u003e[0.73]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.45\u003c/p\u003e \u003cp\u003e[5.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.3% (21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33.3% (43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e24.0% (31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e26.4% (34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eGrouped yes-no\u003c/p\u003e \u003cp\u003e9.13\u003c/p\u003e \u003cp\u003e[0.03]**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eGrouped yes-no\u003c/p\u003e \u003cp\u003e1.76\u003c/p\u003e \u003cp\u003e[0.18]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExternal Migrants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.4%\u003c/p\u003e \u003cp\u003e(62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.34\u003c/p\u003e \u003cp\u003e[5.69]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.2% (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30.6% (19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27.4% (17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e25.8% (16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRemained in Place\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.5%\u003c/p\u003e \u003cp\u003e(238)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.85\u003c/p\u003e \u003cp\u003e[5.25]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.6% (49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40.8% (97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23.1% (55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15.5% (37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUniversity Relocation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRemained Permanent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.9%\u003c/p\u003e \u003cp\u003e(270)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003cp\u003e[0.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.51\u003c/p\u003e \u003cp\u003e[5.67]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.6% (53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37.0% (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23.4% (63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e20.0% (54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003cp\u003e[0.91]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003cp\u003e[0.33]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRelocated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.1%\u003c/p\u003e \u003cp\u003e(159)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003cp\u003e[5.29]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.1% (27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37.1% (59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25.2% (40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.6% (31)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003eNote:\u003c/p\u003e \u003cp\u003e1. (N) \u0026ndash; number of respondents, indicated in parentheses.\u003c/p\u003e \u003cp\u003e2. [st.d] \u0026ndash; standard deviation, indicated in square brackets.\u003c/p\u003e \u003cp\u003e3. Pearson Chi\u003csup\u003e2\u003c/sup\u003e [Pr] \u0026ndash; results of the calculations of Chi-squared value, and\u0026nbsp;the Pearson r\u0026nbsp;coefficient\u0026nbsp;[Pr]\u0026nbsp;which is the two tailed significance level calculated using contingency tables in STATA. We are using\u0026nbsp;0.1 or below as our\u0026nbsp;cutoff point for the significance level.\u003c/p\u003e \u003cp\u003e4. ANOVA [Pr\u0026thinsp;\u0026gt;\u0026thinsp;Chi\u003csup\u003e2\u003c/sup\u003e] presents the results from Bartlett's test for equal variances, calculated in STATA using a one-way analysis of variance. As before, the cutoff point for Pr\u0026thinsp;\u0026gt;\u0026thinsp;Chi2 is 0.1statistically insignificant results.\u003c/p\u003e \u003cp\u003e5. Grouped yes-no \u0026ndash; For the variable \u0026ldquo;change of permanent resident,\u0026rdquo; the tests are applied for two groups instead of the three presented in the table. Thus, the first group, \u0026ldquo;yes,\u0026rdquo; includes respondents who have experienced a change of permanent residence due to war, and \u0026ldquo;no,\u0026rdquo; includes those who do not have such experience.\u003c/p\u003e \u003cp\u003e6. *** and ** \u0026ndash; mean pr\u0026thinsp;\u0026lt;\u0026thinsp;0.01 and pr\u0026thinsp;\u0026lt;\u0026thinsp;0.05, respectively.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eAge and anxiety.\u003c/em\u003e The prevalence of anxiety disorders appears relatively consistent across age groups. However, younger participants under 35 years of age had the highest percentages of moderate anxiety (42.5%) and moderately severe anxiety (24.7%). The lowest percentage of participants with severe anxiety (16.4%) was also observed in this group. Among those aged 35\u0026ndash;45 years, 18.4% had mild anxiety, 36.8% had moderate anxiety, 21.7% had moderate severe anxiety, and 23.1% had severe anxiety. Among the 46\u0026ndash;60 age groups, 19.2% had mild anxiety, 36.5% had moderate anxiety, 24.5% had moderate severe anxiety, and 19.8% had severe anxiety. For those aged 61 and older, the distribution shifted slightly: mild anxiety was reported by 21.7%, moderate anxiety by 29.7%, moderately severe anxiety by 29.7%, and severe anxiety by 18.9%.\u003c/p\u003e \u003cp\u003eThe data indicate that moderate anxiety is the most prevalent level across all age groups. However, younger respondents (under 35 years) tended to have higher levels of moderate anxiety, while older respondents (61\u0026thinsp;+\u0026thinsp;years) had the highest prevalence of moderately severe anxiety. Severe anxiety is most pronounced in the 35\u0026ndash;45 age group. Despite these variations, the statistical analysis indicated that there was no significant relationship between age and GAD (Pearson chi2: 3.54, Pr\u0026thinsp;=\u0026thinsp;0.94; ANOVA: 1.39, Pr\u0026thinsp;=\u0026thinsp;0.71). This suggests that while anxiety levels vary across age groups, age alone does not have a statistically significant influence on anxiety levels during wartime.\u003c/p\u003e \u003cp\u003e \u003cem\u003eGender and anxiety.\u003c/em\u003e The data indicate some gender differences in the prevalence of anxiety disorders. Mild anxiety affected a similar proportion of females (19.1%) and males (17.5%). However, moderate anxiety is more prevalent among women, affecting 38.1% compared to 33.9% of men. The gap widened slightly with moderately severe anxiety, affecting 25% of females and 21.1% of males. Notably, severe anxiety showed a marked difference, affecting a greater percentage of men (27.5%) than women (17.8%).\u003c/p\u003e \u003cp\u003eOverall, the data reveal notable differences between men and women. Men have a greater prevalence of severe anxiety (27.5%), while women are more commonly found in the moderate and moderately severe anxiety categories (38.1% and 25.0%, respectively). Overall, the mean GAD score wass greater among men (10.49, SD: 6.45) than women (9.22, SD: 5.15). The Pearson Chi2 test (4.79, Pr\u0026thinsp;=\u0026thinsp;0.18) was not statistically significant, but the ANOVA result (Pr\u0026thinsp;\u0026gt;\u0026thinsp;Chi2\u0026thinsp;=\u0026thinsp;0.003) indicated that gender had a significant relationship with GAD.\u003c/p\u003e \u003cp\u003e \u003cem\u003eScientific degree and anxiety.\u003c/em\u003e Among PhD students, moderate anxiety is the most prevalent (39.8%), and severe anxiety is the least common (13.3%). Those with a PhD showed a relatively even distribution across the four anxiety levels, while participants with a Doctor of Science degree exhibited the highest proportion of severe anxiety (26.0%) and a higher mean score (10.6, SD: 5.94). Despite these patterns, the Pearson chi2 (9.95, Pr\u0026thinsp;=\u0026thinsp;0.36) and ANOVA tests (1.61, Pr\u0026thinsp;=\u0026thinsp;0.65) indicated that the scientific degree had no significant relationship with GAD.\u003c/p\u003e \u003cp\u003e \u003cem\u003eJob title and anxiety.\u003c/em\u003e The assistants had the highest prevalence of moderate anxiety (41.5%) and a relatively balanced distribution across other anxiety levels. Senior Lecturers showed similar proportions across the four levels, while Associate Professors had the highest prevalence of moderate anxiety (37.4%). Professors had the highest prevalence of severe anxiety (26.8%). This suggests that as researchers progress to higher job positions, they may experience increased stress and mental health challenges. Despite this trend, statistical analysis revealed no significant relationship between job title and GAD (Pearson chi2: 5.37, Pr\u0026thinsp;=\u0026thinsp;0.8; ANOVA: 1.39, Pr\u0026thinsp;=\u0026thinsp;0.7).\u003c/p\u003e \u003cp\u003e \u003cem\u003eChange in permanent personal residence and anxiety.\u003c/em\u003e Internal migrants had the highest prevalence of severe anxiety (26.4%) and moderately severe anxiety (24.0%), with a mean GAD score of 10.45 (SD: 5.8). The external migrants also exhibited a high prevalence of severe anxiety (25.8%) and moderately severe anxiety (27.4%). Those who remained in place had a relatively low prevalence of severe anxiety (15.5%) and the highest prevalence of moderate anxiety (40.8%). Overall, internal and external migrants tend to have higher proportions of severe anxiety than those who stay in permanent locations. The elevated levels of severe anxiety among migrants highlight the psychological toll of personal forced displacement due to the full-scale war. The \"grouped yes-no\" analysis simplifies the categories into those who did or did not change residence due to the war, revealing a significant relationship between change of residence and GAD (Pearson Chi2: 9.13, Pr\u0026thinsp;=\u0026thinsp;0.03).\u003c/p\u003e \u003cp\u003e \u003cem\u003eUniversity relocation and anxiety.\u003c/em\u003e The distribution of anxiety levels was similar in both groups. Among those who worked at a university, which is a permanent location, mild anxiety affected 19.6% of participants, while moderate anxiety was most prevalent, impacting 37.0%. Moderately severe anxiety affects 23.4%, and severe anxiety impacts 20.0%. Among researchers who temporarily relocated universities to Ukraine-controlled territories, mild anxiety was reported by 17.1% of participants, and moderate anxiety remained the most common at 37.1%. Moderately severe anxiety affects 25.2%, while severe anxiety is present in 19.6%. Overall, the data indicate that moderate anxiety is the most prevalent level across both groups. The proportion of severe anxiety remains comparable between those who have worked at a university based on permanent campus location and those who have worked at a relocated university (20.0% and 19.6%, respectively). However, researchers from relocated universities have a slightly higher prevalence of moderately severe anxiety. These trends suggest that university relocation may have introduced additional stress factors that were not significant factors during the full-scale war. At the same time, the Pearson chi2 (0.54; Pr\u0026thinsp;=\u0026thinsp;0.91) and ANOVA (0.93; Pr\u0026thinsp;=\u0026thinsp;0.33) tests revealed no statistically significant relationships between university relocation and GAD.\u003c/p\u003e \u003cp\u003eThe distribution of GAD across sociodemographic variables among Ukrainian researchers provides valuable insights into the mental health challenges faced during the full-scale war. Despite variations in anxiety levels across age groups, the statistical analysis indicated no significant relationship between age and GAD. This finding suggested that age alone does not significantly influence anxiety levels during wartime. Gender differences are notable, with men showing a greater incidence of severe anxiety, while women more commonly experience moderate and moderately severe anxiety. Although the Pearson chi2 test showed no significant difference, the ANOVA results confirmed a significant relationship between gender and GAD. Although the scientific degree held by researchers does not appear to significantly affect anxiety levels, those with a Doctor of Science degree exhibit the highest prevalence of severe anxiety. Furthermore, the distribution across job titles indicates that professors who hold the highest ranks experience the most severe anxiety, possibly due to increased job stress and responsibilities. The most significant finding relates to changes in residence due to the war. Compared to those who stayed in permanent locations, internal and external migrants display elevated levels of severe anxiety, indicating the psychological toll of displacement. This relationship is confirmed statistically, emphasizing the need for specialized mental health support for those impacted by relocation. Finally, university relocation does not significantly influence GAD levels, although researchers from temporarily relocated universities to Ukraine-controlled territories have a slightly greater prevalence of moderately severe anxiety.\u003c/p\u003e \u003cp\u003eSince gender differences and changes in permanent residence emerged as notable factors in the prevalence and severity of anxiety we applied both parametric (t-test) and non-parametric (Wilcoxon rank-sum) statistical tests to determine the significance of differences between genders and between groups who migrated and those who remained in place (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This in-depth statistical approach allowed us to confirm whether these sociodemographic factors significantly influenced GAD levels and to identify which groups might require targeted mental health support.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParametric and non-parametric tests for gender and change in permanent personal residence.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eH\u003csub\u003eo\u003c/sub\u003e hypothesis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTest\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTest statistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePr-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eConclusion\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGAD(female)\u0026thinsp;=\u0026thinsp;GAD(male)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003et-test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;2.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePr (T\u0026thinsp;\u0026gt;\u0026thinsp;t)\u0026thinsp;=\u0026thinsp;0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eH\u003csub\u003ea\u003c/sub\u003e is accepted. Suggest GAD(male)\u0026thinsp;\u0026gt;\u0026thinsp;GAD(female)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003erank-sum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ez\u0026thinsp;=\u0026thinsp;1.563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProb\u0026gt;|z|=0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChange in permanent residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGAD(migrants)\u0026thinsp;=\u0026thinsp;GAD(non- migrants)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003et-test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et=-2.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePr (T\u0026thinsp;\u0026lt;\u0026thinsp;t)\u0026thinsp;=\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eH\u003csub\u003ea\u003c/sub\u003e is accepted. Suggest GAD(migrants)\u0026thinsp;\u0026gt;\u0026thinsp;GAD(non-migrants)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003erank-sum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ez=-2.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProb\u0026gt;|z|=0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eNote:\u003c/p\u003e \u003cp\u003e1. The t-test is parametric Student\u0026rsquo;s t-test is used for the mean comparison of two groups and is calculated in STATA. Based on the assumption that the dataset is normally distributed.\u003c/p\u003e \u003cp\u003e2. Rank-sum \u0026ndash; This is a non-parametric two-sample Wilcoxon rank-sum (Mann-Whitney) test used to compare two groups. It does not require any assumptions and thus gives robust results.\u003c/p\u003e \u003cp\u003e3. The cut-off point for both is pr\u0026thinsp;=\u0026thinsp;0.1. The lower probability values allow us to conclude that the test's results are statistically significant.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe comparison between male and female researchers regarding GAD scores begins with a t-test, where the null hypothesis states no significant difference between the genders. However, the t-test results (t\u0026thinsp;=\u0026thinsp;2.08, Pr(T\u0026thinsp;\u0026gt;\u0026thinsp;t)\u0026thinsp;=\u0026thinsp;0.019) reveal a statistically significant difference, leading to the rejection of the null hypothesis and indicating that males have significantly higher GAD scores than females. Although this significant result is captured by the t-test, the Wilcoxon rank-sum test (z\u0026thinsp;=\u0026thinsp;1.563, Prob\u0026gt;|z| = 0.1) shows a less pronounced distinction between the two genders, implying that the difference, while present, may be nuanced and influenced by the choice of test.\u003c/p\u003e \u003cp\u003eFor changes in permanent personal residence, the t-test (t = -2.95, Pr(T\u0026thinsp;\u0026lt;\u0026thinsp;t)\u0026thinsp;=\u0026thinsp;0.001) indicated a significant difference between researchers who migrated (internal or external) and those who remained, with migrants exhibiting higher GAD scores. This finding is corroborated by the Wilcoxon rank-sum test (z = -2.78, Prob\u0026gt;|z| = 0.005), which supports the hypothesis that forced migration is associated with increased anxiety. This agreement across both parametric and non-parametric tests emphasizes the psychological toll of displacement, indicating a substantial mental health burden among migrants and underscoring the importance of specialized support for those who were compelled to relocate due to the full-scale war.\u003c/p\u003e \u003cp\u003eThis analysis revealed significant differences in GAD scores by gender and by changes in permanent residence. While the gender-related differences are less clear, the impact of migration on anxiety is consistently evident. This suggests the need for mental health strategies that specifically address the unique challenges faced by displaced researchers, as well as gender-informed approaches to managing anxiety among researchers in wartime.\u003c/p\u003e \u003cp\u003eThe additional calculations in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e were crucial for revealing nuanced patterns and better understanding the factors influencing GAD levels among Ukrainian researchers. By dividing the respondents into \"risky\" (moderately severe and severe GAD) and \"non-risky\" (mild and moderate GAD) groups, this analysis identified distinct patterns that are not evident when examining the entire sample. This separation allowed for the identification of personal characteristics that differentiate those at higher risk of anxiety from those with milder conditions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression analyses for generalized anxiety disorders and sociodemographic characteristics. Risky and non-risky GAD groups.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGAD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGAD\u003c/p\u003e \u003cp\u003eNon-risky group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGAD\u003c/p\u003e \u003cp\u003eRisky group\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.25*\u003c/p\u003e \u003cp\u003e(0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003cp\u003e(0.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.83**\u003c/p\u003e \u003cp\u003e(0.002)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMigration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.324***\u003c/p\u003e \u003cp\u003e(0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.038\u003c/p\u003e \u003cp\u003e(0.936)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.417*\u003c/p\u003e \u003cp\u003e(0.023)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003cp\u003e(0.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.378\u003c/p\u003e \u003cp\u003e(0.082)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003cp\u003e(0.86)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDegree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.265*\u003c/p\u003e \u003cp\u003e(0.013)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.395\u003c/p\u003e \u003cp\u003e(0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.729\u003c/p\u003e \u003cp\u003e(0.175)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJob title\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.871\u003c/p\u003e \u003cp\u003e(0.143)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.131\u003c/p\u003e \u003cp\u003e(0.726)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.386\u003c/p\u003e \u003cp\u003e(0.51)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity Relocation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.192\u003c/p\u003e \u003cp\u003e(0.088)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003cp\u003e(0.877)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.819\u003c/p\u003e \u003cp\u003e(0.205)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.645***\u003c/p\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.375***\u003c/p\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.45***\u003c/p\u003e \u003cp\u003e(0.000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eNote:\u003c/p\u003e \u003cp\u003ep-values in parentheses\u003c/p\u003e \u003cp\u003e* p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003cp\u003eNon-risky group includes those respondents who have Mild and Moderate Anxiety GAD levels\u003c/p\u003e \u003cp\u003eRisky group includes those respondents who have Moderately Severe and Severe GAD levels\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRegression analysis was applied to assess the impact of variables such as gender, migration status, age, scientific degree, university Relocation, and job title on GAD levels among Ukrainian researchers in wartime. Regarding gender, females in the risky group had significantly lower GAD scores than did their male counterparts (coefficient: -1.83, p\u0026thinsp;=\u0026thinsp;0.002), while in the entire sample, being female was also associated with reduced GAD scores (coefficient: -1.25, p\u0026thinsp;=\u0026thinsp;0.04). Migration status is a strong predictor of higher GAD scores, particularly in the risky group (coefficient: 1.417, p\u0026thinsp;=\u0026thinsp;0.023), and across the entire sample (coefficient: 2.324, p\u0026thinsp;=\u0026thinsp;0.001). However, migration does not significantly impact the non-risky group. Age did not appear to significantly affect GAD levels across any group, and the scientific degree was only associated with increased GAD scores in the overall sample (coefficient: 1.265, p\u0026thinsp;=\u0026thinsp;0.013), but not within specific sub-groups. Job title did not significantly influence GAD scores in any group, and university relocation had a similarly non-significant effect.\u003c/p\u003e \u003cp\u003eOverall, these results confirmed that certain factors, including migration status and gender, strongly influenced GAD scores in the risky group. Moreover, variables such as age and job title showed no significant relationship with anxiety levels.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study reveals anxiety among Ukrainian researchers during the ongoing full-scale war and examines sociodemographic factors related to anxiety. The results show that nearly 44.3% of participants fell into the categories of moderately severe or severe anxiety, meeting the cut-off score for a probable GAD diagnosis. In contrast, studies conducted during peacetime in different countries have reported lower anxiety levels among researchers and academic staff. For instance, Meeks, Peak, and Dreihaus reported that 38.6% of academic staff members experienced anxiety [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], while Sharma, Shrestha, and Sah reported that 26.7% of academic staff members experienced anxiety [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Overall, our findings align with a study by Lim et al., who conducted a meta-analysis of 41 studies on anxiety [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The prevalence of anxiety during a war was 43.4%, while the prevalence of anxiety postwar was 30.3%. These results are consistent with our study, which revealed high levels of anxiety among researchers during the ongoing war in Ukraine.\u003c/p\u003e \u003cp\u003eThese findings underscore the significant mental health challenges faced by researchers during wartime, highlighting the contrast to peacetime. While the data confirm the obvious negative impact of war on mental health, the figures raise serious concerns about preserving the intellectual potential of the country's scientific community. Anxiety can have detrimental long-term consequences for researchers, including impaired cognition [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], decreased productivity [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], motivation [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], and negative effects on both mental and physical health [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. These negative consequences are essential not only for the health of individual researchers but also for maintaining the continuity and quality of scientific research during and after military conflict.\u003c/p\u003e \u003cp\u003eUnexpected results were obtained regarding the relationship between gender and the level of anxiety. Surprisingly, our findings contrast with many studies conducted in peacetime, which typically show higher anxiety levels among women than among men, both in the general population [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] and within the academic community [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Traditionally, it is well documented that more women are affected by anxiety disorders than men are. However, in the context of an ongoing war, our study reveals a different scenario: men are more vulnerable to anxiety disorders. This raises crucial questions about the roles and societal expectations placed on men, regardless of their professional role and field of activity during the war and the potential for unaddressed mental health needs within this demographic. The significant difference in anxiety levels between genders was confirmed by ANOVA, underscoring the need for gender-sensitive mental health interventions.\u003c/p\u003e \u003cp\u003eThis shift underscores the profound impact that war has had on mental health, affecting traditional gender disparities in the prevalence of anxiety. One significant factor contributing to this unexpected result appears to be the roles and responsibilities men often assume during wartime, which may heighten their susceptibility to anxiety. In Ukraine, men are conscripted. The fact that male researchers remain involved in scientific activities, as opposed to actively protecting their native country, can provoke feelings of guilt or shame. Research shows that there is a correlation between guilt, shame, and anxiety [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. However, studies have shown mixed results on the strength and significance of these correlations, indicating that guilt may not be a strong predictor of anxiety in nonclinical populations during peacetime [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Therefore, this issue requires a separate study to establish the relationship of such interdependence in times of military conflict.\u003c/p\u003e \u003cp\u003eAnother important finding of this study is the significant relationship between academic anxiety and temporary displacement due to the full-scale war in Ukraine. There is limited direct evidence on the specific relationship between anxiety and migration among researchers. However, the provided sources offer relevant insights into the broader context of migration and mental health, revealing that migration, whether external or internal, can be a significant stressor that increases the risk of developing mental health issues such as anxiety [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Additionally, humanitarian migrants are especially vulnerable to mental health problems due to the stressful circumstances surrounding their migration [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe results of our study show that both internal and external migrants exhibit significantly greater rates of severe anxiety than those who remain in their original locations, highlighting the profound psychological toll of displacement. Additionally, researchers who were forced to become internally displaced experienced a greater prevalence of moderately severe anxiety. Interestingly, the relocation of universities to territories controlled by Ukraine did not significantly impact anxiety levels. This suggests that the psychological effects of displacement are more closely tied to the personal disruptions experienced by researchers than to the physical relocation of their institutions. The significant relationship between forced migration and anxiety levels highlights the profound psychological toll of displacement, emphasizing the need for specialized support for migrants.\u003c/p\u003e \u003cp\u003eWe also investigated whether other sociodemographic factors, such as age, scientific degree, and job title, were significantly correlated with anxiety among Ukrainian researchers during wartime. Our findings indicate that these factors did not have a significant correlation with anxiety. This finding contrasts with other studies conducted in peacetime. For example, PhD students are more likely to experience high levels of anxiety due to the instability of their work-life balance [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. However, this study suggested that during wartime, the usual sociodemographic factors of anxiety may not have the same significance. The unique stressors and disruptions caused by the war likely overshadow the influences of age, scientific degree, and job title on anxiety levels.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study highlights three critical findings regarding the mental health of Ukrainian researchers during the full-scale war: the generally high level of anxiety, the unexpected gender differences in anxiety prevalence, and the significant impact of migration on anxiety levels.\u003c/p\u003e \u003cp\u003eFirst, the generally high level of anxiety among Ukrainian researchers is alarming, with nearly 44.3% of participants experiencing moderately severe to severe anxiety. This prevalence is notably greater than the anxiety levels reported in peacetime studies across various populations, indicating the severe mental health toll exerted by the ongoing war.\u003c/p\u003e \u003cp\u003eSecond, contrary to existing research, which typically finds higher anxiety levels among women, our study reveals that men are more susceptible to severe anxiety during wartime. This finding suggests that the traditional gender dynamics of anxiety are altered in the context of war. The increased responsibilities and societal expectations placed on men, including conscription and protection duties, may contribute to heightened anxiety levels, necessitating gender-sensitive mental health interventions.\u003c/p\u003e \u003cp\u003eFinally, the impact of migration, whether internal or external, significantly exacerbates anxiety among researchers. Displaced individuals exhibit greater levels of severe anxiety than those who remain in their original locations. This aligns with broader research on the psychological effects of forced displacement among researchers.\u003c/p\u003e \u003cp\u003eThese findings underscore the urgent need for targeted mental health support for displaced researchers, addressing both the immediate and long-term effects of displacement. Additionally, the results highlight the importance of developing gender-specific interventions to address the unique mental health challenges faced by researchers in conflict zones. Further research is needed to understand the long-term effects of war-related stressors and to develop and implement appropriate support strategies and interventions at the national, institutional, community, and individual levels. Addressing these challenges is crucial for preserving the intellectual potential and scientific advancement of Ukraine.\u003c/p\u003e"},{"header":"Limitations","content":"\u003cp\u003eOur study, the first to examine the anxiety of academics in Ukraine using a nationally representative sample during a full-scale war, has several limitations. We employed nonrandomized convenience sampling, which affects the representativeness and generalizability of our results. This approach was necessary due to the ongoing war, physical distancing, and migration within the academic community. The cross-sectional design of our study limits our ability to assess the temporality of events, making it difficult to determine causality. Additionally, relying on self-reported conditions may have led to underreporting of mental health issues and social desirability bias, and retrospective data collection does not eliminate this bias. Finally, the unknown number of individuals who viewed the online invitations complicates the determination of the survey response rate and the assessment of the sample's representativeness.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec7\"\u003e\n \u003ch2\u003eStudy design and data collection\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003eThis study used a cross-sectional analytical design to collect data through an online survey. Before the main study, a pilot test involving 15 research members was conducted to ensure the clarity of the questions and confirm that the survey could be completed within 12 minutes. The data were collected between December 2023 and February 2024. The survey, which was distributed to researchers at Ukrainian universities via email using Google Forms, maintained participant anonymity and ensured voluntary participation throughout the study. The inclusion criteria included researchers working in Ukrainian universities during the full-scale war period. Participants were informed of the study's objectives and provided informed consent before participation. However, the study's response rate could not be determined because the number of individuals who viewed the online invitation could not be assessed.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cp\u003eThe online survey comprised a questionnaire, that took 10 to 15 minutes to complete. It consisted of two sections: (a) sociodemographic characteristics and (b) self-assessments. The first section collected background information, including age, gender, scientific degree, job title, changes in personal residence during the full-scale war, and university relocation due to the conflict.\u003c/p\u003e\n\u003cp\u003eThe second section used the self-reported Generalized Anxiety Disorder (GAD-7) questionnaire. The GAD-7 was selected due to its proven validity and reliability as a widely used screening tool for identifying and assessing the severity of GAD. It has been translated into Ukrainian, making it suitable for this study. Participants responded to how frequently they experienced anxiety symptoms over the preceding two weeks using a 4-point Likert scale (0 = not at all, 1 = several days, 2 = more than half the days, and 3 = nearly every day). Scores from the seven items were summed to provide a total score ranging from 0 to 21. Based on receiver operating characteristic analysis, GAD-7 cut-off scores of ≥ 5, ≥10, and ≥ 15 indicated mild, moderate, and severe anxiety, respectively.\u003c/p\u003e\n\u003cdiv id=\"Sec9\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003eThe data generated through Google Forms ware downloaded into an Excel spreadsheet and imported into STATA® software for analysis. Before loading into STATA, logical control of the empirical basis was carried out.\u003c/p\u003e\n \u003cp\u003eThe median, mean, standard deviation, and percentile range (25th-75th percentile) were calculated for each anxiety level to understand the central tendencies and variability of GAD scores. These inferential statistical analyses were used to investigate the relationship between GAD levels and sociodemographic factors:\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cspan\u003e\u003cem\u003e1. Contingency tables.\u003c/em\u003e The data distribution was analysed using contingency tables, providing an overview of the general patterns and relationships between GAD and various sociodemographic variables.\u003cbr\u003e\u003c/span\u003e \u003cspan\u003e\u003cem\u003e2. Chi-square test.\u003c/em\u003e A chi-square test of independence was used to test for statistically significant associations between categorical sociodemographic variables and GAD levels. Pearson's chi-square values and p-values were calculated using contingency tables, with a significance level of 0.1. Results with a p-value above 0.1 were considered statistically insignificant.\u003cbr\u003e\u003c/span\u003e \u003cspan\u003e\u003cem\u003e3. Analysis of variance (ANOVA).\u003c/em\u003e One-way ANOVA was used to analyse differences in mean GAD scores across sociodemographic groups. Bartlett's test for equal variances ensured the validity of ANOVA results.\u003cbr\u003e\u003c/span\u003e \u003cspan\u003e\u003cem\u003e4. Additional parametric and non-parametric tests.\u003c/em\u003e Both parametric (t-test) and non-parametric (Wilcoxon rank-sum) tests were used to compare GAD scores between specific groups. These tests revealed significant differences between genders and between those who had migrated due to the war and those who had not. The following regression equation was used to analyse the relationships between sociodemographic factors and GAD scores:\u003cbr\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cdiv id=\"Equa\"\u003e\n \u003cdiv id=\"FileID_Equa\" name=\"EquationSource\"\u003e$${GAD}_{i}=\\alpha +{\\beta }_{1}Female+{\\beta }_{2}Migration+{\\beta }_{3}Age+{\\beta }_{4}Degree+{\\beta }_{5}Job Title+{\\beta }_{6}University Relocation$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003ewhere Female is a dummy variable indicating gender (1 = female, 0 = male); and Migration is a dummy variable indicating change in permanent residence (1 = displaced, 0 = not displaced).\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e5. Regression analysis.\u003c/em\u003e Regression analysis was conducted using the Ordinary Least Squares (OLS) method to examine the effects of various personal characteristics on GAD scores. The analysis differentiated between the \"at-risk\" (moderately severe and severe anxiety) and \"not-at-risk\" (mild and moderate anxiety) groups to identify characteristics that may increase the risk of higher anxiety levels. The coefficients and their corresponding p-values are reported, with statistical significance marked at various levels (*p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data sets used and/or analysed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research teams acknowledge the Armed Forces of Ukraine for providing safety during their research and credit their perseverance and courage for making this possible.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAuthor contributions statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe conceptualization was made by N.T. and Y.S. The methodology was developed by N.T. and Y.S. The data were curated by U.K. The original draft was written by N.T., H.L. and A.P. The writing, review and editing were performed by Y.S. All the authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCompeting Interests Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no conflicts of interest related to the conduct of this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eEthical considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study adhered to relevant guidelines and regulations, complying with the Declaration of Helsinki. The Research Ethics Committee of Berdyansk State Pedagogical University approved the study under protocol number 7, dated September 10, 2023. Informed consent was obtained from all participants.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHammoudi Halat, D., Soltani, A., Dalli, R., Alsarraj, L. \u0026amp; Malki, A. Understanding and fostering mental health and well-being among university faculty: a narrative review. \u003cem\u003eJ. Clin. Med.\u003c/em\u003e\u003cstrong\u003e12\u003c/strong\u003e, 4425; 10.3390/jcm12134425 (2023).\u003c/li\u003e\n\u003cli\u003eWorld Mental Health Report: transforming mental health for all. Licence: CC BY-NC-SA 3.0 IGO; World Health Organization: Geneva, Switzerland, (2022).\u003c/li\u003e\n\u003cli\u003eDe Caux, B. C., Pretorius, L. \u0026amp; Macaulay, L. Research and teaching in a pandemic world: the challenges of establishing academic identities during times of crisis. \u003cem\u003eSpringer Science and Business Media LLC\u003c/em\u003e. 1-554 (2023).\u003c/li\u003e\n\u003cli\u003eGlobal prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic. \u003cem\u003eLancet\u003c/em\u003e\u003cstrong\u003e398\u003c/strong\u003e, 1700-1712; 10.1016/S0140-6736(21)02143-7 (2021).\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. \u003cem\u003eAnxiety disorders. \u003c/em\u003ehttps://www.who.int/news-room/fact-sheets/detail/anxiety-disorders (2024).\u003c/li\u003e\n\u003cli\u003eAmerican Psychological Association. Anxiety. \u003cem\u003eAPA Dictionary of Psychology\u003c/em\u003ehttps://dictionary.apa.org/anxiety (2024).\u003c/li\u003e\n\u003cli\u003eKakaje, A. et al. Mental disorder and PTSD in Syria during wartime: a nationwide crisis. \u003cem\u003eBMC Psychiatry\u003c/em\u003e\u003cstrong\u003e21\u003c/strong\u003e, 2; 10.1186/s12888-020-03002-3 (2021).\u003c/li\u003e\n\u003cli\u003eCarvajal, R. F. P. \u0026amp; Guedea, M. T. D. Stress in university research professors: a systematic review. \u003cem\u003eSalud Ment.\u003c/em\u003e\u003cstrong\u003e44\u003c/strong\u003e, 249-256; 10.17711/SM.0185-3325.2021.032 (2021). \u003c/li\u003e\n\u003cli\u003eMainous, A. G. 3rd, Rahmanian, K. P., Ledford, C. J. W. \u0026amp; Carek, P. J. Professional identity, job satisfaction, and commitment of nonphysician faculty in academic family medicine. \u003cem\u003eFam. Med.\u003c/em\u003e\u003cstrong\u003e50\u003c/strong\u003e, 739-745; 10.22454/FamMed.2018.273724 (2018).\u003c/li\u003e\n\u003cli\u003eMolero Jurado, M. D. M., P\u0026eacute;rez-Fuentes, M. D. C., Oropesa Ruiz, N. F., Sim\u0026oacute;n M\u0026aacute;rquez, M. D. M. \u0026amp; G\u0026aacute;zquez Linares, J. J. Self-efficacy and emotional intelligence as predictors of perceived stress in nursing professionals. \u003cem\u003eMedicina \u003c/em\u003e\u003cstrong\u003e55\u003c/strong\u003e, 237; 10.3390/medicina55060237 (2019).\u003c/li\u003e\n\u003cli\u003eBarnett, M. J., Lindfelt, T., Doroudgar, S., Chan, E. \u0026amp; Ip, E. J. Pharmacy-faculty work-life balance and career satisfaction: comparison of national survey results from 2012 and 2018. \u003cem\u003eExplor. Res. Clin. Soc. Pharm.\u003c/em\u003e\u003cstrong\u003e5\u003c/strong\u003e, 100112; 10.1016/j.rcsop.2022.100112 (2022).\u003c/li\u003e\n\u003cli\u003eAdrian, C. M., Cox, S. S., Phelps, L. D., Schuldt, B. A. \u0026amp; Totten, J. W. Issues causing stress among business faculty members. \u003cem\u003eJ. Acad. Adm. High. Educ.\u003c/em\u003e\u003cstrong\u003e10\u003c/strong\u003e, 41-46 (2014).\u003c/li\u003e\n\u003cli\u003eKennedy, D. R. et al. Enhancing pharmacy faculty well-being and productivity while reducing burnout. \u003cem\u003eAm. J. Pharm. Educ. \u003c/em\u003e\u003cstrong\u003e86\u003c/strong\u003e, 8764; 10.5688/ajpe876 (2022).\u003c/li\u003e\n\u003cli\u003eLevin, J. S., Aliyeva, A. \u0026amp; Walker, L. From community college to university: institutionalization and neoliberalism in British Columbia and Alberta. \u003cem\u003eCan. J. High. Educ. \u003c/em\u003e\u003cstrong\u003e46\u003c/strong\u003e, 165-180 (2016).\u003c/li\u003e\n\u003cli\u003eHerbert, D. L., Coveney, J., Clarke, P., Graves, N. \u0026amp; Barnett, A. G. The impact of funding deadlines on personal workloads, stress and family relationships: a qualitative study of Australian researchers. \u003cem\u003eBMJ Open\u003c/em\u003e\u003cstrong\u003e4\u003c/strong\u003e, e004462; 10.1136/bmjopen-2013-004462 (2014).\u003c/li\u003e\n\u003cli\u003ePiano, M. et al. A rapid review of challenges and opportunities related to diversity and inclusion as experienced by early and mid-career academics in the medicine, dentistry and health sciences fields. \u003cem\u003eBMC Med. Educ.\u003c/em\u003e\u003cstrong\u003e23\u003c/strong\u003e, 288; 10.1186/s12909-023-04252-x (2023).\u003c/li\u003e\n\u003cli\u003eZheng, M. et al. Covid academic pandemic: techno stress faced by teaching staff for online academic activities. \u003cem\u003eFront. Psychol.\u003c/em\u003e\u003cstrong\u003e13\u003c/strong\u003e, 288; 10.3389/fpsyg.2022.895371 (2022).\u003c/li\u003e\n\u003cli\u003eDhont, J. et al. Conducting research in Radiation Oncology remotely during the COVID-19 pandemic: coping with isolation. \u003cem\u003eClin. Transl. Radiat. Oncol.\u003c/em\u003e\u003cstrong\u003e24\u003c/strong\u003e, 53-59; 10.1016/j.ctro.2020.06.006 (2020).\u003c/li\u003e\n\u003cli\u003ePark, J. \u0026amp; Moghaddam, B. Impact of anxiety on prefrontal cortex encoding of cognitive flexibility. \u003cem\u003eNeuroscience\u003c/em\u003e\u003cstrong\u003e345\u003c/strong\u003e, 193-202; 10.1016/j.neuroscience.2016.06.013 (2017).\u003c/li\u003e\n\u003cli\u003eLim, I. C. Z. Y. et al. Prevalence of depression, anxiety and post-traumatic stress in war- and conflict-afflicted areas: a meta-analysis. \u003cem\u003eFront. Psychiatry\u003c/em\u003e\u003cstrong\u003e13\u003c/strong\u003e, 978703; 10.3389/fpsyt.2022.978703 (2022).\u003c/li\u003e\n\u003cli\u003eYurtsenyuk, O. \u0026amp; Sumariuk, B. Impact of the war on the mental health of Ukrainians: factors in formation of neurotic and stress-associated mental disorders. \u003cem\u003eArt Med.;\u003c/em\u003e10.21802/artm.2023.2.26.248 (2023).\u003c/li\u003e\n\u003cli\u003eKurapov, A. et al. The mental health impact of the ongoing Russian-Ukrainian war 6 months after the Russian invasion of Ukraine. \u003cem\u003eFront\u003c/em\u003e. \u003cem\u003ePsychiatry\u003c/em\u003e\u003cstrong\u003e14\u003c/strong\u003e, 1134780; 10.3389/fpsyt.2023.1134780 (2023).\u003c/li\u003e\n\u003cli\u003eMartsenkovskyi, D. et al. Mental health in Ukraine in 2023. \u003cem\u003eEur. Psychiatry\u003c/em\u003e\u003cstrong\u003e67\u003c/strong\u003e, 1; 10.1192/j.eurpsy.2024.12 (2024).\u003c/li\u003e\n\u003cli\u003eTsybuliak, N. et al. Burnout dynamic among Ukrainian academic staff during the war. \u003cem\u003eSci. Rep.\u003c/em\u003e\u003cstrong\u003e13\u003c/strong\u003e, 17975; 10.1038/s41598-023-45229-6 (2023).\u003c/li\u003e\n\u003cli\u003eBohdanov, I., Kovachov, S., Tsybuliak, N., Lopatina, H., Popova, A. \u0026amp; Suchikova, Y. Resilience in wartime research: case of anticrisis management at a Ukrainian university. In \u003cem\u003e2023 IEEE 18th International Conference on Computer Science and Information Technologies\u003c/em\u003e (CSIT); 10.1109/csit61576.2023.10324134 (2023).\u003c/li\u003e\n\u003cli\u003eSuchikova, Y., Tsybuliak, N., Lopatina, H., Shevchenko, L. \u0026amp; Popov, A. I. Science in times of crisis: how does the war affect the efficiency of Ukrainian scientists? \u003cem\u003eProbl. Perspect. Manag.\u003c/em\u003e\u003cstrong\u003e21\u003c/strong\u003e, 408-424; 10.21511/ppm.21(1).2023.35 (2023).\u003c/li\u003e\n\u003cli\u003eRessler, A. et al. Alone on the frontline: the first report of PTSD prevalence and risk in de-occupied Ukrainian villages. \u003cem\u003eInt. J. Soc. Psychiatry\u003c/em\u003e; 10.1177/00207640241242030 (2024).\u003c/li\u003e\n\u003cli\u003eSpitzer, R. L., Kroenke, K., Williams, J. B. \u0026amp; L\u0026ouml;we, B. A brief measure for assessing generalized anxiety disorder: the GAD-7. \u003cem\u003eArch. Intern. Med. \u003c/em\u003e\u003cstrong\u003e166\u003c/strong\u003e, 1092-1097; 10.1001/archinte.166.10.1092 (2006).\u003c/li\u003e\n\u003cli\u003eMeeks, K., Peak, A. S. \u0026amp; Dreihaus, A. Depression, anxiety, and stress among students, faculty, and staff. \u003cem\u003eJ. Am. Coll. Health\u003c/em\u003e\u003cstrong\u003e71\u003c/strong\u003e, 348-354; 10.1080/07448481.2021.1891913 (2023).\u003c/li\u003e\n\u003cli\u003eSharma, B., Shrestha, N. \u0026amp; Sah, S. K. Anxiety among faculty members of academic institutions of a metropolitan city: a descriptive cross-sectional study. \u003cem\u003eJNMA J. Nepal Med. Assoc.\u003c/em\u003e\u003cstrong\u003e61\u003c/strong\u003e, 338-342; 10.31729/jnma.8133 (2023).\u003c/li\u003e\n\u003cli\u003eRazavi, S. A., Shahrabi, A. \u0026amp; Siamian, H. The relationship between research anxiety and self-efficacy. \u003cem\u003eMater. Sociomed\u003c/em\u003e. \u003cstrong\u003e29\u003c/strong\u003e, 247-250; 10.5455/msm.2017.29.247-250 (2017).\u003c/li\u003e\n\u003cli\u003eErickson, S. R. et al. Severity of anxiety and work-related outcomes of patients with anxiety disorders. \u003cem\u003eDepress. Anxiety\u003c/em\u003e\u003cstrong\u003e26\u003c/strong\u003e, 1165-1171; 10.1002/da.20624 (2009).\u003c/li\u003e\n\u003cli\u003eHall, S. A mental-health crisis is gripping science \u0026ndash; toxic research culture is to blame. \u003cem\u003eNature\u003c/em\u003e\u003cstrong\u003e617\u003c/strong\u003e, 666-668; 10.1038/d41586-023-01708-4 (2023).\u003c/li\u003e\n\u003cli\u003eRobinson, O. J., Vytal, K., Cornwell, B. R. \u0026amp; Grillon, C. The impact of anxiety upon cognition: perspectives from human threat of shock studies. \u003cem\u003eFront. Hum. Neurosci.\u003c/em\u003e\u003cstrong\u003e7\u003c/strong\u003e, 203; 10.3389/fnhum.2013.00203 (2013).\u003c/li\u003e\n\u003cli\u003eAlonso, J., Liu, Z., Evans-Lacko, S. et al. Treatment gap for anxiety disorders is global: results of the World Mental Health Surveys in 21 countries. \u003cem\u003eDepress. Anxiety\u003c/em\u003e\u003cstrong\u003e35\u003c/strong\u003e, 195-208, 10.1002/da.22711 (2018).\u003c/li\u003e\n\u003cli\u003eMcLean, C. P., Asnaani, A., Litz, B. T. \u0026amp; Hofmann, S. G. Gender differences in anxiety disorders: prevalence, course of illness, comorbidity and burden of illness. \u003cem\u003eJ. Psychiatr. Res.\u003c/em\u003e\u003cstrong\u003e45\u003c/strong\u003e, 1027-1035; 10.1016/j.jpsychires.2011.03.006 (2011).\u003c/li\u003e\n\u003cli\u003eChristiansen, D. M. Examining sex and gender differences in anxiety disorders. \u003cem\u003eInTech\u003c/em\u003e.; 10.5772/60662 (2015).\u003c/li\u003e\n\u003cli\u003eWojtera, B. et al. Changes in psychological distress among Polish medical university teachers during the COVID-19 pandemic. \u003cem\u003ePLoS One\u003c/em\u003e\u003cstrong\u003e17\u003c/strong\u003e, e0278311; 10.1371/journal.pone.0278311 (2022).\u003c/li\u003e\n\u003cli\u003eOducado, R. M., Rabacal, J., Moralista, R. \u0026amp; Tamdang, K. Perceived stress due COVID-19 pandemic among employed professional teachers. \u003cem\u003eiJERI\u003c/em\u003e 305-316; 10.46661/ijeri.5284 (2020).\u003c/li\u003e\n\u003cli\u003eDeiana, G. et al. Gender equality in the Italian academic context. Results from the IGEA project. \u003cem\u003eFront. Public Health\u003c/em\u003e\u003cstrong\u003e11\u003c/strong\u003e, 1125496; 10.3389/fpubh.2023.1125496 (2023).\u003c/li\u003e\n\u003cli\u003eGao, Q., Zhang, K., Cao, Y. et al. The effect of negative workplace gossip about supervisor on workplace deviance and impression management: the mediating roles of anxiety and guilt. \u003cem\u003eJ. Bus. Psychol.\u003c/em\u003e\u003cstrong\u003e39\u003c/strong\u003e, 435-454; 10.1007/s10869-023-09888-6 (2024).\u003c/li\u003e\n\u003cli\u003eC\u0026acirc;ndea, D. M. \u0026amp; Szentagotai-Tătar, A. Shame-proneness, guilt-proneness and anxiety symptoms: a meta-analysis. \u003cem\u003eJ. Anxiety Disord.\u003c/em\u003e\u003cstrong\u003e58\u003c/strong\u003e, 78-106; 10.1016/j.janxdis.2018.07.005 (2018).\u003c/li\u003e\n\u003cli\u003eTaylor, L.-A., Reid, J. \u0026amp; Jagroop-Dearing, A. The impacts of the COVID-19 traffic light system on staff in tertiary education in New Zealand. \u003cem\u003eEduc. Sci.\u003c/em\u003e\u003cstrong\u003e14\u003c/strong\u003e, 48; 10.3390/educsci14010048 (2024).\u003c/li\u003e\n\u003cli\u003eGojowy, A. et al. Sense of guilt and anxiety in depression. \u003cem\u003eEur. Psychiatr\u003c/em\u003ey \u003cstrong\u003e26\u003c/strong\u003e, 644-644 (2011).\u003c/li\u003e\n\u003cli\u003eBrunnet, A. E., Kristensen, C. H., Lobo, N. dos S. \u0026amp; Derivois, D. Migration experience and mental health: a qualitative study in France and Brazil. \u003cem\u003eInt. J. Soc. Psychiatry\u003c/em\u003e\u003cstrong\u003e68\u003c/strong\u003e, 376-383; 10.1177/0020764021999695 (2022).\u003c/li\u003e\n\u003cli\u003eLiao, Z. X., Tan, X. M. \u0026amp; Zhao, Y. Y. Association between internal migration experience and depressive symptoms: analysis of PSID data. \u003cem\u003eBMC Public Health\u003c/em\u003e\u003cstrong\u003e23\u003c/strong\u003e, 1145; 10.1186/s12889-023-16073-0 (2023).\u003c/li\u003e\n\u003cli\u003eDerluyn, I. et al. The impact of trauma and daily hardships on the mental health of unaccompanied refugee minors detained in Libya. \u003cem\u003eBJPsych Open\u003c/em\u003e\u003cstrong\u003e9\u003c/strong\u003e, E8; 10.1192/bjo.2022.622 (2023).\u003c/li\u003e\n\u003cli\u003ePopovych, I., Hudimova, A., Bokhonkova, Yu., Savchuk, O., Hoian, I. \u0026amp; Shevchenko, N. Dispositional mental states of internally displaced university teachers under martial law: gender differences. \u003cem\u003eJ. Educ. Cult. Soc.\u003c/em\u003e\u003cstrong\u003e14\u003c/strong\u003e, 171-187; 10.15503/jecs2023.2.171.181 (2023).\u003c/li\u003e\n\u003cli\u003eEssayagh, F. et al. The prevalence and risk factors for anxiety and depression symptoms among migrants in Morocco. \u003cem\u003eSci. Rep.\u003c/em\u003e\u003cstrong\u003e13\u003c/strong\u003e, 3740; 10.1038/s41598-023-30715-8 (2023).\u003c/li\u003e\n\u003cli\u003eKuzikova, S. B., Zlyvkov, V. L. \u0026amp; Lukomska, S. O. Traumatic experience of residents of the de-occupied territories of Ukraine. \u003cem\u003eInsight Psychol. Dimens. Soc.\u003c/em\u003e\u003cstrong\u003e9\u003c/strong\u003e, 228-243; 10.32999/KSU2663-970X/2023-9-13 (2023).\u003c/li\u003e\n\u003cli\u003eAndrews, E. J., Harper, S., Cashion, T., Palacios-Abrantes, J., Blythe, J., Daly, J. et al. Supporting early career researchers: insights from interdisciplinary marine scientists. \u003cem\u003eICES J. Mar. Sci.\u003c/em\u003e\u003cstrong\u003e77\u003c/strong\u003e, 476-485; 10.1093/icesjms/fsz247 (2020).\u003c/li\u003e\n\u003cli\u003eBelavy, D. L., Owen, P. J. \u0026amp; Livingston, P. M. Do successful PhD outcomes reflect the research environment rather than academic ability? \u003cem\u003ePLoS One\u003c/em\u003e\u003cstrong\u003e15\u003c/strong\u003e, e0236327; 10.1371/journal.pone.0236327 (2020).\u003c/li\u003e\n\u003cli\u003eSatinsky, E. N. et al. Systematic review and meta-analysis of depression, anxiety, and suicidal ideation among Ph.D. students. \u003cem\u003eSci. Rep.\u003c/em\u003e\u003cstrong\u003e11\u003c/strong\u003e, 14370; 10.1038/s41598-021-93687-7 (2021).\u003c/li\u003e\n\u003cli\u003eWoolston, C. Postdoc survey reveals disenchantment with working life. \u003cem\u003eNature\u003c/em\u003e\u003cstrong\u003e587\u003c/strong\u003e, 505-508; 10.1038/d41586-020-03191-7 (2020).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4603070/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4603070/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe ongoing war in Ukraine has significantly impacted the mental health of academic researchers, with anxiety emerging as a predominant issue. This study assessed the prevalence and severity of generalized anxiety disorder (GAD) among Ukrainian researchers during conflict, considering factors such as gender, age, migration status, scientific degree, and job title. The findings revealed that 44.3% of participants experienced moderately severe to severe anxiety, with migration due to the full-scale war being a significant predictor of higher anxiety levels. Notably, male researchers exhibit higher anxiety levels than their female counterparts, contrary to typical peacetime trends, suggesting that wartime responsibilities and societal expectations may play a crucial role. The data underscore the need for targeted mental health support, particularly for displaced researchers, and highlight the importance of developing gender-specific interventions. These insights are vital for informing policies and support programs to enhance researchers' mental health and productivity in conflict zones, ensuring the continuity and quality of scientific research during and after the war.\u003c/p\u003e","manuscriptTitle":"War, Researchers, and Anxiety: Evidence from Ukraine","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-10 07:11:34","doi":"10.21203/rs.3.rs-4603070/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-26T04:35:31+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-23T19:20:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"188245743716237679410942217169027251311","date":"2024-08-13T12:10:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-12T07:39:02+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-07T12:36:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"258501295217591584668715693521694734188","date":"2024-06-24T03:16:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"142860299546668037239999950810583623525","date":"2024-06-22T11:15:17+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-22T01:54:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-22T01:42:25+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-06-21T18:03:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-20T08:36:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-06-19T04:17:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d4c96501-0e7c-47ee-a9c3-fee4db1bfc84","owner":[],"postedDate":"July 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-11-11T15:59:35+00:00","versionOfRecord":{"articleIdentity":"rs-4603070","link":"https://doi.org/10.1038/s41598-024-78052-8","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-11-07 15:57:09","publishedOnDateReadable":"November 7th, 2024"},"versionCreatedAt":"2024-07-10 07:11:34","video":"","vorDoi":"10.1038/s41598-024-78052-8","vorDoiUrl":"https://doi.org/10.1038/s41598-024-78052-8","workflowStages":[]},"version":"v1","identity":"rs-4603070","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"identity":"rs-4603070","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}