Introduction: During the coronavirus disease 2019 (COVID-19) pandemic, university students experienced unusual environmental stresses, and the number of university students with depressive symptoms increased. The pandemic had a profoundly negative impact on the mental health of first-year students because they were not prepared to face academic and social stresses. The purpose of this study was to investigate the effect of the COVID-19 pandemic on depressive symptoms, eating behaviors, and stress-coping ability among first-year university students. Methods: A total of 8,424 first-year students, 2,043 males and 1,636 females who entered university in Japan in 2021–2022 (during the pandemic) and 2,912 males and 1,833 females who entered university in Japan in 2018–2019 (before the pandemic), participated. We investigated the differences in depressive symptoms (using Beck Depression Inventory II [BDI-II]), eating behaviors (using Eating Attitudes Test-26 [EAT-26] and Bulimic Inventory Test, Edinburgh [BITE]), and stress coping (using Coping Inventory for Stressful Situations [CISS], which has three subscales) between first-year students before and during the pandemic. We divided the students into three categories (clinical, subthreshold, and nonsymptomatic) according to depressive symptoms and eating behaviors based on BDI-ll and EAT-26 scores and compared the frequencies of the three categories at two time points. Results: First-year students during the pandemic showed a higher percentage of depressive symptoms, including clinical and subthreshold levels, than first-year students before the pandemic but did not show disordered eating behaviors. Additionally, the CISS task-oriented score was significantly lower for students with depressive symptoms, including clinical and subthreshold levels, during the pandemic than before the pandemic in females. Conclusions: This study suggests that it may be important to provide first-year university students with more information about depressive symptom awareness, including clinical and subthreshold levels, and to provide appropriate ways for stress coping from many angles and early support in pandemic conditions.

During the coronavirus disease 2019 (COVID-19) pandemic, unusual environmental stressors increased (e.g., anxiety about viral infection, school closures, and reduced opportunities for interpersonal communication). The COVID-19 pandemic introduced mental health risk factors, including the threat of illness and death, isolation, and economic uncertainty [1]. Many studies have forewarned the profound emotional and psychosocial impact of the protracted COVID-19 pandemic, with suicide as a potential consequence. A recent study that examined public discourse on suicide and COVID-19 during the pandemic reported that the general public was generally concerned about governments’ responses, as well as the disquieting collateral effects on mental health, suicide, the economy, and at-risk populations [2].

Younger people seemed to be more affected by the pandemic than older people [3]. COVID-19 and subsequent measures to mitigate the spread of the disease had negative effects on higher education [4]. University students experienced very high anxiety and stress during the pandemic [4, 5], and consequently, mental health effects were reported [4]. A previous study reported that the prevalence of depressive symptoms among university students during the COVID-19 pandemic was relatively high [6]. In Japan, the first case of COVID-19 was confirmed in January 2020. A study in Japan reported that young people had a higher percentage of depressive symptoms [7]. A recent study reported that the proportion of university students with depressive or anxiety symptoms had not decreased despite the decline in COVID-19 infections [8]. Another study reported that the mean mental health of first-year university students worsened after the COVID-19 pandemic and returned to the pre-pandemic level over the next 2 years [9]. The suicide rates and the number of high-risk students with suicidal ideation in Japanese universities increased during the pandemic [9, 10]. Even before the pandemic, several studies have suggested that university students may experience mental health crises [11]. The numbers of patients with depression and university students at high risk for the onset of depression have increased. The subthreshold depressive symptoms among adolescents are highly prevalent [12], and have become the focus of increasing attention [8]. Subthreshold depression is defined by clinically significant depressive symptoms that do not meet the diagnostic criteria for depression [13]. The incidence of subthreshold depression increases steadily from 12 to 20 years of age [11, 14]. Subthreshold depression was associated with an increased lifetime prevalence of suicide attempts [15]. Some late adolescents with subthreshold depression had increased depressive symptoms and developed clinical depression over 1 year [16]. Previous studies have reported that the prevalence of depression is quite high in first-year university students [16, 17]. The first year in university students’ lives is a period of vulnerability during which young students establish, test, and adjust to new psychological identities [18]. After the start of the pandemic, online classes increased and first-year students had fewer opportunities for interpersonal communication. They were unprepared to face academic and social stresses, and some students might have felt anxious or depressed. However, few studies have evaluated the depressive symptoms of first-year students during the pandemic. Therefore, the purpose of this study was to investigate first-year students’ depressive symptoms, including clinical and subthreshold levels, during the pandemic.

The pandemic had been a leading cause of stress and feelings of loss of control [19]. Both stress and coping abilities influence health [20]. Some studies have suggested that stress-coping style is a risk factor for depressive symptoms [21]. Coping strategies play an important role in reducing stress and consequently increasing general health [22]. During the pandemic, a new lifestyle was promoted, and the stress-coping style of university students may have been affected.

Moreover, stressful and fearful situations are associated with various behavioral responses, such as disordered eating behaviors [23]. Previous studies have reported that many university students have disordered eating behaviors and that the onset of eating disorders increases from adolescence through the university period [24]. In particular, university entrance has been identified as a possible precipitating factor and a risk period during which pathogenic eating may emerge or worsen [25]. Several studies have reported the worsening of eating disorder psychopathology after the beginning of the pandemic. Studies on individuals with eating disorders generally showed worsening symptoms during the pandemic [26, 27]. Some studies have reported increases in the rates of eating disorders [28‒30]. The pandemic may also affect the eating behavior of first-year students.

The purpose of this study was to investigate the effect of the pandemic on the depressive symptoms of first-year university students. The long-lasting pandemic situation may have a negative impact on the depressive symptoms of first-year students. Several studies have indicated that the persistence of depressive symptoms in late adolescence is predictive of subsequent mental health problems [31‒33]. We previously reported that depressive symptoms were correlated with the severity of disordered eating behaviors in university students [34]. Therefore, we examined the effects of the pandemic on the mental conditions of first-year university students in Japan, including depressive symptoms, eating behaviors, and stress-coping styles, and compared the current year's results with the previous year’s results. We focused on first-year students who showed significant depressive symptoms, including clinical and subthreshold levels. We used the Beck Depression Inventory II (BDI-II) [35] to screen for depressive symptoms. We hypothesized that first-year students who entered university during the pandemic would show worsening depressive symptoms and eating behaviors, and first-year students who had significant depressive symptoms might exhibit different coping styles compared to those who entered university before the pandemic.

Participants

The participants were Japanese students who entered Hiroshima University in 2018–2019 (before the pandemic) and 2021–2022 (during the pandemic). The inclusion criteria were 18–20-year-old freshman students at Hiroshima University who completed a questionnaire. We investigated participants’ depressive symptoms, eating behaviors, and ability to cope with stress.

Procedures

This study was conducted at students’ health checkups for university entrance. The questionnaires were administered as a part of a health checkup. First-year students were informed and guided to fill out the questionnaire by the end of April through mail. We investigated differences in depressive symptoms, eating behaviors, and stress-coping styles between first-year university students before and during the pandemic. Next, we divided the students into three groups based on depressive symptoms and eating behaviors determined by BDI-II and Eating Attitudes Test-26 (EAT-26) scores for clinical, subthreshold, and nonsymptomatic groups on the basis of previous studies [16, 36, 37]. We compared the frequencies of the three groups between first-year students before and during the pandemic. The study protocol was approved by the Ethics Committee of the Hiroshima University School of Medicine (E-1767).

Measures

Beck Depression Inventory II

The original BDI-II was developed by Beck et al. [35]. This scale consists of 21 self-report items that are scored on a 4-point scale and is used to measure depressive symptoms. A high score indicates that depressive symptoms are severe. The cutoff point for clinical depression is a score of 18 points on the BDI-II [36]. The clinical group had BDI-II scores of 18 or more, the subthreshold group had scores ranging from 11 to 17, and the nondepressed group had scores of 10 or less [16, 36]. A cutoff score of 18 in the BDI-II yielded a sensitivity of 94% and a specificity of 92%. Cronbach’s alpha coefficient score was 0.87 [36]. Kojima and Furukawa [38] subsequently developed the Japanese version of the BDI-II and demonstrated its reliability and validity.

Eating Attitudes Test-26

The EAT-26 is a widely used self-report questionnaire that assesses eating attitudes and consists of 26 items [39]. The original scale consisted of 40 items (EAT-40) [40], which was subsequently shortened to the EAT-26 by Garner [39], who reported that the EAT-26 scores are highly correlated with the EAT-40 scores. The EAT-26 is a reliable, valid, and economical instrument. Answers are provided on a 6-point scale ranging from “not at all” to “extremely.” The cutoff score is 20 points; scores greater than 20 indicate a high possibility of EDs. Buddeberg-Fischer [37] delineated three categories of disordered eating behaviors based on the EAT scores: 0–9 = nondisordered, 10–19 = moderately disordered, and ≥20 = severely disordered. Mann et al. [41] reported that a threshold of 20 (on the EAT-26) yielded a sensitivity of 88% and a specificity of 96%. Cronbach’s alpha coefficient scores were 0.85–0.94 [42].

Bulimic Inventory Test, Edinburgh

The Bulimic Inventory Test, Edinburgh (BITE) is a 36-item self-report measure of bulimic symptoms [43]. This scale consists of a symptom evaluation scale (30 items) and a severity scale (6 items). Answers to the symptom evaluation scale are scored as “yes” or “no,” and answers on the severity scales are scored on a 5-point or 7-point scale ranging from “not at all” to “extremely.” The symptom evaluation scale has a minimum score of 0 and a maximum score of 30. The cutoff score for the BITE is 20 points; a symptom subscale score of 20 or more points indicates the presence of binge-eating behavior and a high possibility of bulimia nervosa. Cronbach’s alpha coefficient scores were 0.96. The BITE has satisfactory reliability and validity when used with binge-eating patients [43].

Coping Inventory for Stressful Situations

The Coping Inventory for Stressful Situations (CISS) was developed by Endler and Parker [44]. It consists of three subscales to evaluate coping behaviors: task-oriented (CISS-T: solving the problem, cognitive restructuring of the problem, or attempts to alter the situation), emotion-oriented (CISS-E: emotional responses to the problem), and avoidance-oriented (CISS-A: seeking distractions, such as socializing or hobbies) coping. It is a 48-item self-report measure scored on a 5-point scale ranging from “not at all” to “extremely.” We used the Japanese version translated by Furukawa et al. [45]. Cronbach’s alpha coefficient scores were 0.75–0.89 [46].

Data Analysis

SPSS version 28 (IBM Corporation, Armonk, NY, USA) was used for the statistical analyses. The characteristics of the participants were averaged. We used two-way analysis of variance (ANOVA) to compare the scores by time and gender. In addition, we used χ2 and residual analyses to compare the frequencies of the three groups regarding depressive symptoms and eating behaviors. One-way ANOVA was conducted to examine the differences in stress coping among first-year students with depressive symptoms (clinical and subthreshold groups) before and during the pandemic. The statistical significance level was set to p < 0.05.

Participants

A total of 8,424 first-year students of 18–20 years of age responded. In 2018–2019, 2,912 males and 1,833 females (mean age, 18.2 ± 0.5 years and 18.1 ± 0.4 years, respectively) responded. In 2021–2022, 2,043 males and 1,636 females (mean age, 18.2 ± 0.4 years and 18.1 ± 0.3 years, respectively) responded. The results of the annual checkups for first-year students are shown in Table 1.

Table 1.

Results of the annual checkups

Before the pandemic, mean (SD)During the pandemic, mean (SD)
Admission year 2018 2019 2021 2022 
Male N = 1,423 N = 1,489 N = 1,025 N = 1,018 
 Age, years 18.2 (0.5) 18.2 (0.5) 18.2 (0.4) 18.2 (0.4) 
 BMI, kg/m2 21.4 (3.0) 21.3 (3.0) 21.2 (3.0) 21.0 (2.8) 
Female N = 916 N = 917 N = 845 N = 791 
 Age, years 18.1 (0.4) 18.2 (0.4) 18.1 (0.3) 18.1 (0.3) 
 BMI, kg/m2 20.6 (2.5) 20.5 (2.4) 20.2 (2.4) 20.3 (2.4) 
Before the pandemic, mean (SD)During the pandemic, mean (SD)
Admission year 2018 2019 2021 2022 
Male N = 1,423 N = 1,489 N = 1,025 N = 1,018 
 Age, years 18.2 (0.5) 18.2 (0.5) 18.2 (0.4) 18.2 (0.4) 
 BMI, kg/m2 21.4 (3.0) 21.3 (3.0) 21.2 (3.0) 21.0 (2.8) 
Female N = 916 N = 917 N = 845 N = 791 
 Age, years 18.1 (0.4) 18.2 (0.4) 18.1 (0.3) 18.1 (0.3) 
 BMI, kg/m2 20.6 (2.5) 20.5 (2.4) 20.2 (2.4) 20.3 (2.4) 

Comparison of BDI-II, EAT-26, BITE, and CISS

We conducted a two-way ANOVA on time and gender for each scale, and the results showed significant interaction effects in BDI-II [F(1,8420) = 4.08, p < 0.05]. Next, we examined the simple main effects of time and gender, and the results significantly differed in females before and during the pandemic (p < 0.001). There were significant differences in the gender factor (EAT-26: F(1,8419) = 90.94, p < 0.001; BITE: F(1,8419) = 107.72, p < 0.001; CISS-T: F(1,8419) = 101.09, p < 0.001; CISS-E: F(1,8419) = 13.84, p < 0.001; and CISS-A: F(1,8419) = 7.01, p < 0.01) and the time factor (BDI-II: F(1,8419) = 15.08, p < 0.001; EAT-26: F(1,8419) = 12.18, p < 0.001; BITE: F(1,8419) = 304.62, p < 0.001; CISS-T: F(1,8419) = 75.06, p < 0.001; CISS-E: F(1,8419) = 20.11, p < 0.001; and CISS-A: F(1,8419) = 23.86, p < 0.001). Female students scored significantly higher on the EAT-26, BITE, and CISS-A and significantly lower on the CISS-T and CISS-E than male students. First-year students during the pandemic scored significantly higher on the BDI-II and significantly lower on the EAT-26, BITE, and three subscales of the CISS than first-year students before the pandemic. The results are shown in Table 2.

Table 2.

Results of two-way ANOVA

Before the pandemic, mean (SD)During the pandemic, mean (SD)F (gender × time)p value
malefemalemalefemale
(N = 2,912)(N = 1,833)(N = 2,043)(N = 1,636)
BDI-II 5.3 (5.4) 5.0 (5.3) 5.5 (6.1) 5.8 (6.1) 4.08 0.04* 
EAT-26 2.9 (3.5) 3.7 (4.5) 2.5 (3.5) 3.4 (4.8) 0.01 0.91 
BITE 5.2 (4.0) 6.2 (4.7) 3.6 (3.2) 4.6 (4.4) 0.09 0.76 
CISS-T 57.2 (10.9) 54.7 (10.6) 55.0 (11.7) 52.6 (10.9) 0.04 0.82 
CISS-E 41.6 (10.8) 40.5 (10.1) 40.3 (11.0) 39.7 (10.4) 1.21 0.27 
CISS-A 42.9 (11.8) 43.3 (10.6) 41.5 (11.4) 42.4 (10.2) 1.12 0.29 
Before the pandemic, mean (SD)During the pandemic, mean (SD)F (gender × time)p value
malefemalemalefemale
(N = 2,912)(N = 1,833)(N = 2,043)(N = 1,636)
BDI-II 5.3 (5.4) 5.0 (5.3) 5.5 (6.1) 5.8 (6.1) 4.08 0.04* 
EAT-26 2.9 (3.5) 3.7 (4.5) 2.5 (3.5) 3.4 (4.8) 0.01 0.91 
BITE 5.2 (4.0) 6.2 (4.7) 3.6 (3.2) 4.6 (4.4) 0.09 0.76 
CISS-T 57.2 (10.9) 54.7 (10.6) 55.0 (11.7) 52.6 (10.9) 0.04 0.82 
CISS-E 41.6 (10.8) 40.5 (10.1) 40.3 (11.0) 39.7 (10.4) 1.21 0.27 
CISS-A 42.9 (11.8) 43.3 (10.6) 41.5 (11.4) 42.4 (10.2) 1.12 0.29 

BDI-II, Beck Depression Inventory-Ⅱ; EAT-26, Eating Attitudes Test-26; BITE, Bulimic Inventory Test, Edinburgh; CISS, Coping Inventory for Stressful Situations.

*p < 0.05.

Moreover, we examined the correlation between BDI-II and EAT-26 scores; positive correlations were observed for males both before (r = 0.225, p < 0.001) and during the pandemic (r = 0.208, p < 0.001) and for females both before (r = 0.261, p < 0.001) and during the pandemic (r = 0.241, p < 0.001). Furthermore, significant positive correlations between the BDI-II and CISS-E scores were observed for males both before (r = 0.336, p < 0.001) and during the pandemic (r = 0.352, p < 0.001) and for females both before (r = 0.453, p < 0.001) and during the pandemic (r = 0.465, p < 0.001). Significant negative correlations between the BDI-II and CISS-T scores were observed for males both before (r = −0.205, p < 0.001) and during the pandemic (r = −0.177, p < 0.001) and for females both before (r = −0.193, p < 0.001) and during the pandemic (r = −0.206, p < 0.001). For males, significant negative correlations between the BDI-II and CISS-A scores were observed both before (r = −0.101, p < 0.001) and during the pandemic (r = −0.075, p < 0.05).

Three Categories of Depressive Symptoms

Three categories of depressive symptoms were defined (based on the BDI-II) before the pandemic; clinical group (3.8% of males and 3.9% of females), subthreshold group (11.4% of males and 10.3% of females), and nondepressed group (84.8% of males and 85.8% of females). During the pandemic, the categories were as follows: clinical group (5.7% of males and 5.7% of females), subthreshold group (11.9% of males and 12.4% of females), and nondepressed group (82.4% of males and 81.9% of females). The χ2 test revealed significant differences before and during the pandemic (χ2(2) = 10.176, p = 0.006 for males and χ2(2) = 10.936, p = 0.004 for females). Residual analysis revealed that the number in the clinical group was significantly higher during the pandemic (n = 116, 5.7%, adjusted standardized residual (asr) = 3.1 for males and n = 93, 5.7%, asr = 2.5 for females), and the number in the nondepressed group was significantly lower during the pandemic (n = 1,684, 82.4%, asr = −2.2 for males and n = 1,340, 81.9%, asr = −3.1 for females). The results are shown in Table 3.

Table 3.

Three categories of depressive symptoms and eating behaviors

Before the pandemicDuring the pandemic
Male 
Depressive symptoms 
 Clinical 
  n (%) 111 (3.8) 116 (5.7) 
  asr −3.1 3.1 
 Subthreshold 
  n (%) 332 (11.4) 243 (11.9) 
  asr −0.5 0.5 
 Nondepressed 
  n (%) 2,469 (84.8) 1,684 (82.4) 
  asr 2.2 −2.2 
Eating behaviors 
 Severely disordered 
  n (%) 15 (0.5) 12 (0.6) 
  asr −0.3 0.3 
 Moderately disordered 
  n (%) 140 (4.8) 81 (4.0) 
  asr 1.4 −1.4 
 Nondisordered 
  n (%) 2,757 (94.7) 1,950 (95.4) 
  asr −1.2 1.2 
Female 
Depressive symptoms 
 Clinical 
  n (%) 71 (3.9) 93 (5.7) 
  asr −2.5 2.5 
 Subthreshold 
  n (%) 189 (10.3) 203 (12.4) 
  asr −1.9 1.9 
 Nondepressed 
  n (%) 1,573 (85.8) 1,340 (81.9) 
  asr 3.1 −3.1 
Eating behaviors 
 Severely disordered 
  n (%) 21 (1.1) 29 (1.8) 
  asr −1.5 1.5 
 Moderately disordered 
  n (%) 164 (9.0) 116 (7.1) 
  asr 2.0 −2.0 
 Nondisordered 
  n (%) 1,648 (89.9) 1,491 (91.1) 
  asr −1.2 1.2 
Before the pandemicDuring the pandemic
Male 
Depressive symptoms 
 Clinical 
  n (%) 111 (3.8) 116 (5.7) 
  asr −3.1 3.1 
 Subthreshold 
  n (%) 332 (11.4) 243 (11.9) 
  asr −0.5 0.5 
 Nondepressed 
  n (%) 2,469 (84.8) 1,684 (82.4) 
  asr 2.2 −2.2 
Eating behaviors 
 Severely disordered 
  n (%) 15 (0.5) 12 (0.6) 
  asr −0.3 0.3 
 Moderately disordered 
  n (%) 140 (4.8) 81 (4.0) 
  asr 1.4 −1.4 
 Nondisordered 
  n (%) 2,757 (94.7) 1,950 (95.4) 
  asr −1.2 1.2 
Female 
Depressive symptoms 
 Clinical 
  n (%) 71 (3.9) 93 (5.7) 
  asr −2.5 2.5 
 Subthreshold 
  n (%) 189 (10.3) 203 (12.4) 
  asr −1.9 1.9 
 Nondepressed 
  n (%) 1,573 (85.8) 1,340 (81.9) 
  asr 3.1 −3.1 
Eating behaviors 
 Severely disordered 
  n (%) 21 (1.1) 29 (1.8) 
  asr −1.5 1.5 
 Moderately disordered 
  n (%) 164 (9.0) 116 (7.1) 
  asr 2.0 −2.0 
 Nondisordered 
  n (%) 1,648 (89.9) 1,491 (91.1) 
  asr −1.2 1.2 

asr, adjusted standardized residual.

Three Categories of Eating Behaviors

Three categories of eating behaviors were defined (based on the EAT-26) before the pandemic: severely disordered group (0.5% of males and 1.1% of females), moderately disordered group (4.8% of males and 9.0% of females), and nondisordered group (94.7% of males and 89.9% of females). During the pandemic, the groups were as follows: severely disordered group (0.6% of males and 1.8% of females), moderately disordered group (4.0% of males and 7.1% of females), and nondisordered group (95.4% of males and 91.1% of females) (Table 3). The χ2 test revealed significant differences between time points for females (χ2(2) = 6.194, p = 0.045). Residual analysis revealed that the number in the moderately disordered group was significantly lower during the pandemic for females (n = 116, 7.1%, asr = −2.0).

Comparison of CISS Scores between Students with Depressive Symptoms before and during the Pandemic

The results of one-way ANOVA revealed that the CISS-T score was significantly lower for female students in the depressive symptom groups (clinical and subthreshold groups) during the pandemic than before the pandemic. There was no significant difference for male students. The results are shown in Table 4.

Table 4.

Comparison of CISS between students with depressive symptoms before and during the pandemic

Before the pandemic,During the pandemic,F
mean (SD)mean (SD)
Male N = 443 N = 359   
 CISS-T 52.9 (11.1) 51.7 (12.1) 2.19  
 CISS-E 48.8 (9.1) 47.5 (9.6) 3.84  
 CISS-A 41.2 (11.2) 40.1 (10.8) 1.96  
Female N = 260 N = 296   
 CISS-T 51.3 (10.9) 49.1 (10.3) 5.77 
 CISS-E 49.3 (9.0) 48.0 (8.9) 2.76  
 CISS-A 42.4 (10.0) 41.4 (10.0) 1.42  
Before the pandemic,During the pandemic,F
mean (SD)mean (SD)
Male N = 443 N = 359   
 CISS-T 52.9 (11.1) 51.7 (12.1) 2.19  
 CISS-E 48.8 (9.1) 47.5 (9.6) 3.84  
 CISS-A 41.2 (11.2) 40.1 (10.8) 1.96  
Female N = 260 N = 296   
 CISS-T 51.3 (10.9) 49.1 (10.3) 5.77 
 CISS-E 49.3 (9.0) 48.0 (8.9) 2.76  
 CISS-A 42.4 (10.0) 41.4 (10.0) 1.42  

CISS, Coping Inventory for Stressful Situations.

*p < 0.05.

The aim of this study was to investigate the effects of the pandemic on depressive symptoms, eating behaviors, and stress-coping ability in first-year university students. In this study, we found that first-year students during the pandemic showed a higher percentage of depressive symptoms, including clinical and subthreshold levels, than first-year students before the pandemic, but this was not observed for disordered eating behaviors. Additionally, the CISS-T score was significantly lower for female students with depressive symptoms during the pandemic than for those before the pandemic.

The BDI-II scores were significantly higher in first-year female students who entered during the pandemic than in first-year female students who entered before the pandemic. There was a significant interaction between the effects of gender and time on the BDI-II scores. Although there was no significant difference for males, the number of nondepressed students was significantly lower among the students during the pandemic for both males and females. A previous study reported that 24.7% of people had depressive symptoms before the COVID-19 pandemic, while 52.5% had depressive symptoms during the COVID-19 pandemic [47]. In university students, 419 first-year students showed that the prevalence of moderate-to-severe depression increased from 21.5 to 31.7% [48]. Our results are consistent with those of previous studies. In this study, our data reported that the pandemic may have had an effect on depressive symptoms, including clinical and subthreshold levels for first-year students, and female students may be at higher risk than male students. A previous study reported that subthreshold depression can engender severe functional impairment, adversely affecting academic performance and social activity [49]. Moreover, prolonged pandemics may cause fatigue. A recent study reported that a significant proportion of university students experience pandemic fatigue [50]. It is possible that pandemic fatigue may have affected depressive symptoms. Therefore, our results suggest that early detection of depressive symptoms, including subthreshold levels in first-year students, is important, and more attention should be given to female students after the start of a public health crisis such as the pandemic.

Regarding eating behaviors, first-year students during the pandemic scored significantly lower on the EAT-26 and BITE than first-year students before the pandemic. χ2 tests revealed that the number of females with moderately disordered eating behaviors was significantly lower among first-year students during the pandemic than before the pandemic. Contrary to our predictions, our results showed that the pandemic did not worsen the eating behaviors of first-year students. Previous studies reported that difficulties in interpersonal relationships were potential factors in the development and maintenance of body-image disturbances and altered eating behaviors [51, 52]. One possible interpretation of the results is that first-year students during the pandemic may have felt less difficulty in interpersonal relationships because they had fewer opportunities for interpersonal communication than before the pandemic. However, further research is needed to address this issue.

In this study, we found that for female students with depressive symptoms, students during the pandemic scored significantly lower on the CISS-T than students before the pandemic. There were significant negative correlations between the BDI-II and CISS-T scores in both males and females. Task-oriented coping is considered an adaptive coping behavior. Previous research has shown that the use of appropriate coping strategies can reduce the occurrence of stress-related diseases [22, 53]. However, university students often develop maladaptive coping strategies instead of positive problem-solving methods when faced with pressure caused by public health emergencies [54, 55]. During the pandemic, unusual environmental stressors increased, so it may be essential to pay attention to stress-coping strategies. In a review of the methods used by the general population to cope with emergent infectious diseases [56], coping strategies focused on task solving allowed respondents to actively reduce feelings of uncertainty and increase feelings of control over their health [57]. In addition, support resources could be scarce during a serious pandemic situation [58]. A recent study suggested that to maximize existing resources, promote good mental health at home, and improve access to mental health services for the population, we should leverage telemental health services, including the use of psychiatric teleconsultation, videoconferencing, and telehealth to deliver cognitive behavioral therapy [59]. Timely psychological support could also take many forms, including telemedicine and informal support groups [58, 59]. Therefore, in high-stress situations such as the pandemic, it may be important that we provide psychological support and take many forms to improve the stress-coping ability of university students.

There are some limitations of this study that need to be addressed in future research. First, our results are limited to a single university, first-year students, and a certain period. Research on the mental health of students should be expanded to other years and to include other universities. Future studies should examine the impact of a prolonged pandemic on university life. Second, the number of participants decreased during the pandemic. Most students underwent a health checkup for university entrance before the pandemic, but fewer students underwent a health checkup during the pandemic. This is because online classes increased during the pandemic, and thus fewer came to campus. Third, pandemics often have economic impacts. The socioeconomic status may still vary over time among the participants, which was not assessed in this study. Future studies should assess this issue. Fourth, this study only considered depressive symptoms, eating behaviors, and stress coping as the effects of the pandemic. Future studies should consider anxiety, fatigue, and symptoms of other mental illnesses.

This study found that first-year university students had a higher percentage of depressive symptoms during the pandemic. Additionally, the results suggest that a low ability of task-oriented stress coping may be associated with an increased risk of depressive symptoms during the pandemic, especially in females. Our study suggests that it may be important to provide first-year university students with more information about depressive symptom awareness, including clinical and subthreshold levels, and early support in pandemic conditions. Moreover, it may be important that we provide psychological support and work to improve the stress-coping ability of university students from many angles in high-stress situations such as the pandemic.

The authors would like to thank American Journal Experts for providing English editing of the manuscript.

The study protocol was approved by the Ethics Committee of the Hiroshima University School of Medicine (E-1767). Opt-out informed consent protocol was used for use of participant data for research purposes. This consent procedure was reviewed and approved by the Ethics Committee of the Hiroshima University School of Medicine, Japan, approval number E-1767, date of decision September 25, 2019.

The authors have no conflicts of interest to declare.

This study was partially supported by JSPS KAKENHI (Grant No. JP19K08074). The funding source had no role in the study design; collection, analysis, or interpretation of data; writing of the manuscript; or decision to submit the article for publication.

Yoshie Miyake and Yuri Okamoto designed the research. Yoshie Miyake collected and analyzed the data and wrote the first draft of the manuscript. Atsuo Yoshino and Koki Takagaki provided advice on the composition of the manuscript. All authors contributed to and approved the current version of the manuscript.

All data generated or analyzed during this study are included in this article. Further inquiries can be directed to the corresponding author.

1.
Martini
M
,
Longo
P
,
Delsedime
N
,
Abbate-Daga
G
,
Panero
M
.
Increased general, eating, and body-related psychopathology in inpatients in a specialized eating disorders unit after the beginning of the COVID-19 pandemic: a retrospective comparison with the pre-pandemic period
.
J Clin Med
.
2023
;
12
(
2
):
573
.
2.
Lim
SR
,
Ng
QX
,
Xin
X
,
Lim
YL
,
Boon
ESK
,
Liew
TM
.
Public discourse surrounding suicide during the COVID-19 pandemic: an unsupervised machine learning analysis of twitter posts over a one-year period
.
Int J Environ Res Public Health
.
2022
;
19
(
21
):
13834
.
3.
Favreau
M
,
Hillert
A
,
Osen
B
,
Gärtner
T
,
Hunatschek
S
,
Riese
M
et al
.
Psychological consequences and differential impact of the COVID-19 pandemic in patients with mental disorders
.
Psychiatry Res
.
2021
;
302
:
114045
.
4.
Son
C
,
Hegde
S
,
Smith
A
,
Wang
X
,
Sasangohar
F
.
Effects of COVID-19 on college students’ mental health in the United States: interview survey study
.
J Med Internet Res
.
2020
;
22
(
9
):
e21279
.
5.
Rogowska
AM
,
Kuśnierz
C
,
Bokszczanin
A
.
Examining anxiety, life satisfaction, general health, stress and coping styles during COVID-19 pandemic in Polish sample of university students
.
Psychol Res Behav Manag
.
2020
;
13
:
797
811
.
6.
Chang
JJ
,
Ji
Y
,
Li
YH
,
Pan
HF
,
Su
PY
.
Prevalence of anxiety symptom and depressive symptom among college students during COVID-19 pandemic: a meta-analysis
.
J Affect Disord
.
2021
;
292
:
242
54
.
7.
Yamamoto
T
,
Uchiumi
C
,
Suzuki
N
,
Sugaya
N
,
Murillo-Rodriguez
E
,
Machado
S
et al
.
Mental health and social isolation under repeated mild lockdowns in Japan
.
Sci Rep
.
2022
;
12
(
1
):
8452
.
8.
Seto
M
,
Usukura
H
,
Kunii
Y
,
Hamaie
Y
,
Kodama
EN
,
Makino
Y
et al
.
Mental health problems among university students under the prolonged COVID-19 pandemic in Japan: a repeated cross-sectional survey
.
Tohoku J Exp Med
.
2023
;
260
(
1
):
1
11
.
9.
Horita
R
,
Nishio
A
,
Yamamoto
M
.
Lingering effects of COVID-19 on the mental health of first-year university students in Japan
.
PLoS One
.
2022
;
17
(
1
):
e0262550
.
10.
Fuse-Nagase
Y
,
Marutani
T
,
Tachikawa
H
,
Iwami
T
,
Yamamoto
Y
,
Moriyama
T
et al
.
Increase in suicide rates among undergraduate students in Japanese national universities during the COVID-19 pandemic
.
Psychiatry Clin Neurosci
.
2021
;
75
(
11
):
351
2
.
11.
Takagaki
K
,
Okamoto
Y
,
Jinnin
R
,
Mori
A
,
Nishiyama
Y
,
Yamamura
T
et al
.
Behavioral activation for late adolescents with subthreshold depression: a randomized controlled trial
.
Eur Child Adolesc Psychiatry
.
2016
;
25
(
11
):
1171
82
.
12.
Bertha
EA
,
Balázs
J
.
Subthreshold depression in adolescence: a systematic review
.
Eur Child Adolesc Psychiatry
.
2013
;
22
(
10
):
589
603
.
13.
Pincus
HA
,
Davis
WW
,
McQueen
LE
.
Subthreshold mental disorders. A review and synthesis of studies on minor depression and other brand names
.
Br J Psychiatry
.
1999
;
174
:
288
96
.
14.
Rohde
P
,
Beevers
CG
,
Stice
E
,
O’Neil
K
.
Major and minor depression in female adolescents: onset, course, symptom presentation, and demographic associations
.
J Clin Psychol
.
2009
;
65
(
12
):
1339
49
.
15.
An
JH
,
Jeon
HJ
,
Cho
SJ
,
Chang
SM
,
Kim
BS
,
Hahm
BJ
et al
.
Subthreshold lifetime depression and anxiety are associated with increased lifetime suicide attempts: a Korean nationwide study
.
J Affect Disord
.
2022
;
302
:
170
6
.
16.
Jinnin
R
,
Okamoto
Y
,
Takagaki
K
,
Nishiyama
Y
,
Yamamura
T
,
Okamoto
Y
et al
.
Detailed course of depressive symptoms and risk for developing depression in late adolescents with subthreshold depression: a cohort study
.
Neuropsychiatr Dis Treat
.
2017
;
13
:
25
33
.
17.
Tomoda
A
,
Mori
K
,
Kimura
M
,
Takahashi
T
,
Kitamura
T
.
One-year prevalence and incidence of depression among first-year university students in Japan: a preliminary study
.
Psychiatry Clin Neurosci
.
2000
;
54
(
5
):
583
8
.
18.
Verger
P
,
Combes
JB
,
Kovess-Masfety
V
,
Choquet
M
,
Guagliardo
V
,
Rouillon
F
et al
.
Psychological distress in first year university students: socioeconomic and academic stressors, mastery and social support in young men and women
.
Soc Psychiatry Psychiatr Epidemiol
.
2009
;
44
(
8
):
643
50
.
19.
Güzel
Â
,
Mutlu
NL
,
Molendijk
M
.
COVID-19-related changes in eating disorder pathology, emotional and binge eating and need for care: a systematic review with frequentist and Bayesian meta-analyses
.
Eat Weight Disord
.
2023
;
28
(
1
):
19
.
20.
Jordan
TR
,
Khubchandani
J
,
Wiblishauser
M
.
The impact of perceived stress and coping adequacy on the health of nurses: a pilot investigation
.
Nurs Res Pract
.
2016
;
2016
:
5843256
.
21.
Mahmoud
JS
,
Staten
R
,
Hall
LA
,
Lennie
TA
.
The relationship among young adult college students’ depression, anxiety, stress, demographics, life satisfaction, and coping styles
.
Issues Ment Health Nurs
.
2012
;
33
(
3
):
149
56
.
22.
Javadi-Pashaki
N
,
Darvishpour
A
.
Survey of stress and coping strategies to predict the general health of nursing staff
.
J Educ Health Promot
.
2019
;
8
:
74
.
23.
Yau
YH
,
Potenza
MN
.
Stress and eating behaviors
.
Minerva Endocrinol
.
2013
;
38
(
3
):
255
67
.
24.
Harrer
M
,
Adam
SH
,
Messner
EM
,
Baumeister
H
,
Cuijpers
P
,
Bruffaerts
R
et al
.
Prevention of eating disorders at universities: a systematic review and meta-analysis
.
Int J Eat Disord
.
2020
;
53
(
6
):
813
33
.
25.
Mills
JS
,
Polivy
J
,
McFarlane
TL
,
Crosby
RD
.
The natural course of eating pathology in female university students
.
Eat Behav
.
2012
;
13
(
4
):
297
304
.
26.
Branley-Bell
D
,
Talbot
CV
.
Exploring the impact of the COVID-19 pandemic and UK lockdown on individuals with experience of eating disorders
.
J Eat Disord
.
2020
;
8
:
44
.
27.
Schlegl
S
,
Maier
J
,
Meule
A
,
Voderholzer
U
.
Eating disorders in times of the COVID-19 pandemic-results from an online survey of patients with anorexia nervosa
.
Int J Eat Disord
.
2020
;
53
(
11
):
1791
800
.
28.
Miniati
M
,
Marzetti
F
,
Palagini
L
,
Marazziti
D
,
Orrù
G
,
Conversano
C
et al
.
Eating disorders spectrum during the COVID pandemic: a systematic review
.
Front Psychol
.
2021
;
12
:
663376
.
29.
Modrzejewska
A
,
Czepczor-Bernat
K
,
Modrzejewska
J
,
Matusik
P
.
Eating motives and other factors predicting emotional overeating during COVID-19 in a sample of Polish adults
.
Nutrients
.
2021
;
13
(
5
):
1658
.
30.
Khraisat
BR
,
Al-Jeady
AM
,
Alqatawneh
DA
,
Toubasi
AA
,
AlRyalat
SA
.
The prevalence of mental health outcomes among eating disorder patients during the COVID-19 pandemic: a meta-analysis
.
Clin Nutr ESPEN
.
2022
;
48
:
141
7
.
31.
Le Grange
D
,
O’Connor
M
,
Hughes
EK
,
Macdonald
J
,
Little
K
,
Olsson
CA
.
Developmental antecedents of abnormal eating attitudes and behaviors in adolescence
.
Int J Eat Disord
.
2014
;
47
(
7
):
813
24
.
32.
Colman
I
,
Wadsworth
ME
,
Croudace
TJ
,
Jones
PB
.
Forty-year psychiatric outcomes following assessment for internalizing disorder in adolescence
.
Am J Psychiatry
.
2007
;
164
(
1
):
126
33
.
33.
Stoolmiller
M
,
Kim
HK
,
Capaldi
DM
.
The course of depressive symptoms in men from early adolescence to young adulthood: identifying latent trajectories and early predictors
.
J Abnorm Psychol
.
2005
;
114
(
3
):
331
45
.
34.
Miyake
Y
,
Okamoto
Y
,
Takagaki
K
,
Yoshihara
M
.
Changes in eating attitudes and risk for developing disordered eating behaviors in college students with subthreshold eating disorders: a cohort study
.
Psychopathology
.
2023
;
56
(
4
):
276
84
.
35.
Beck
A
,
Steer
R
,
Brown
G
Manual for the Beck depression inventory-II
San Antonio, TX
Psychological Corporation
.
1996
.
36.
Kojima
M
,
Furukawa
TA
,
Takahashi
H
,
Kawai
M
,
Nagaya
T
,
Tokudome
S
.
Cross-cultural validation of the Beck depression inventory-II in Japan
.
Psychiatry Res
.
2002
;
110
(
3
):
291
9
.
37.
Buddeberg-Fischer
B
,
Bernet
R
,
Schmid
J
,
Buddeberg
C
.
Relationship between disturbed eating behavior and other psychosomatic symptoms in adolescents
.
Psychother Psychosom
.
1996
;
65
(
6
):
319
26
.
38.
Kojima
M
,
Furukawa
T
Japanese version of the Beck depression inventory
2nd ed
Tokyo
Nippon-Hyoron-sha Co
.
2003
.
39.
Garner
DM
,
Olmsted
MP
,
Bohr
Y
,
Garfinkel
PE
.
The eating attitudes test: psychometric features and clinical correlates
.
Psychol Med
.
1982
;
12
(
4
):
871
8
.
40.
Garner
DM
,
Garfinkel
PE
.
The Eating Attitudes Test: an index of the symptoms of anorexia nervosa
.
Psychol Med
.
1979
;
9
(
2
):
273
9
.
41.
Mann
AH
,
Wakeling
A
,
Wood
K
,
Monck
E
,
Dobbs
R
,
Szmukler
G
.
Screening for abnormal eating attitudes and psychiatric morbidity in an unselected population of 15-year-old schoolgirls
.
Psychol Med
.
1983
;
13
(
3
):
573
80
.
42.
Siervo
M
,
Boschi
V
,
Papa
A
,
Bellini
O
,
Falconi
C
.
Application of the SCOFF, eating attitude test 26 (EAT 26) and eating inventory (TFEQ) questionnaires in young women seeking diet-therapy
.
Eat Weight Disord
.
2005
;
10
(
2
):
76
82
.
43.
Henderson
M
,
Freeman
CP
.
A self-rating scale for bulimia. The ‘BITE
.
Br J Psychiatry
.
1987
;
150
:
18
24
.
44.
Endler
NS
,
Parker
JDA
Coping inventory for stressful situations (CISS): manual
Toronto
Malti- Health Systems Inc
.
1990
.
45.
Furukawa
T
,
Suzuki-Moor
A
,
Saito
Y
,
Hamanaka
T
.
Reliability and validity of the Japanese version of the coping inventory for stressful situations (CISS): a contribution to the cross-cultural studies of coping
.
Seishin Shinkeigaku Zasshi
.
1993
;
95
(
8
):
602
20
.
46.
Watanabe
K
,
Yokoyama
K
,
Furukawa
TA
.
Reliability and validity of the Japanese version of the coping inventory for adults for stressful situations in healthy people
.
Psychol Rep
.
2015
;
116
(
2
):
447
69
.
47.
Ettman
CK
,
Abdalla
SM
,
Cohen
GH
,
Sampson
L
,
Vivier
PM
,
Galea
S
.
Prevalence of depression symptoms in US adults before and during the COVID-19 pandemic
.
JAMA Netw Open
.
2020
;
3
(
9
):
e2019686
.
48.
Fruehwirth
JC
,
Biswas
S
,
Perreira
KM
.
The Covid-19 pandemic and mental health of first-year college students: examining the effect of Covid-19 stressors using longitudinal data
.
PloS One
.
2021
;
16
(
3
):
e0247999
.
49.
Balázs
J
,
Miklósi
M
,
Keresztény
A
,
Hoven
CW
,
Carli
V
,
Wasserman
C
et al
.
Adolescent subthreshold-depression and anxiety: psychopathology, functional impairment and increased suicide risk
.
J Child Psychol Psychiatry
.
2013
;
54
(
6
):
670
7
.
50.
Labrague
LJ
,
Ballad
CA
.
Lockdown fatigue among college students during the COVID-19 pandemic: predictive role of personal resilience, coping behaviors, and health
.
Perspect Psychiatr Care
.
2021
;
57
(
4
):
1905
12
.
51.
Fairburn
CG
,
Cooper
Z
,
Shafran
R
.
Cognitive behaviour therapy for eating disorders: a transdiagnostic theory and treatment
.
Behav Res Ther
.
2003
;
41
(
5
):
509
28
.
52.
Miyake
Y
,
Okamoto
Y
,
Onoda
K
,
Shirao
N
,
Okamoto
Y
,
Yamawaki
S
.
Brain activation during the perception of stressful word stimuli concerning interpersonal relationships in anorexia nervosa patients with high degrees of alexithymia in an fMRI paradigm
.
Psychiatry Res
.
2012
;
201
(
2
):
113
9
.
53.
Bhagyalakshmi
M
,
Ramana
BV
,
Suresh
H
,
Raj
JM
.
Assessment of the level of stress and coping strategies among patients with coronary artery disease
.
J Sci Soc
.
2012
;
39
(
3
):
136
40
.
54.
Gao
Y
,
Xu
MZ
,
Yang
YF
.
Research on coping style and related factors of college students during SARS outbreak
.
Chin Med Ethics
.
2004
;
02
:
60
3
.
55.
Huang
L
,
Lei
W
,
Xu
F
,
Liu
H
,
Yu
L
.
Emotional responses and coping strategies in nurses and nursing students during Covid-19 outbreak: a comparative study
.
PLoS One
.
2020
;
15
(
8
):
e0237303
.
56.
Chew
QH
,
Wei
KC
,
Vasoo
S
,
Chua
HC
,
Sim
K
.
Narrative synthesis of psychological and coping responses towards emerging infectious disease outbreaks in the general population: practical considerations for the COVID-19 pandemic
.
Singapore Med J
.
2020
;
61
(
7
):
350
6
.
57.
Savary
A
,
Hammouda
M
,
Genet
L
,
Godet
C
,
Bunel
V
,
Weisenburger
G
et al
.
Coping strategies, anxiety and depression related to the COVID-19 pandemic in lung transplant candidates and recipients. Results from a monocenter series
.
Respir Med Res
.
2021
;
80
:
100847
.
58.
Lee
JQ
,
Loke
W
,
Ng
QX
.
The role of family physicians in a pandemic: a blueprint
.
Healthc
.
2020
;
8
(
3
):
198
.
59.
Ng
QX
,
Chee
KT
,
De Deyn
ML
,
Chua
Z
.
Staying connected during the COVID-19 pandemic
.
Int J Soc Psychiatry
.
2020
;
66
(
5
):
519
20
.