Factors Associated With Depression and Anxiety in Korean Adolescents During the COVID-19 Pandemic

Honey Kim; Min Jhon; Ju-Wan Kim; Hee-Ju Kang; Seunghyong Ryu; Jae-Min Kim; Ju-Yeon Lee; Sung-Wan Kim

doi:10.30773/pi.2021.0365

Psychiatry Investig > Volume 19(7); 2022 > Article

Kim, Jhon, Kim, Kang, Ryu, Kim, Lee, and Kim: Factors Associated With Depression and Anxiety in Korean Adolescents During the COVID-19 Pandemic

Original Article

Psychiatry Investigation 2022;19(7):551-561.

Published online: July 21, 2022

DOI: https://doi.org/10.30773/pi.2021.0365

Factors Associated With Depression and Anxiety in Korean Adolescents During the COVID-19 Pandemic

Honey Kim¹

, Min Jhon¹

, Ju-Wan Kim¹

, Hee-Ju Kang¹

, Seunghyong Ryu¹

, Jae-Min Kim¹

, Ju-Yeon Lee^1,²

, Sung-Wan Kim^1,²

¹Department of Psychiatry, Chonnam National University Medical School, Gwangju, Republic of Korea

²Gwangju Bukgu Community Mental Health and Welfare Center, Gwangju, Republic of Korea

Correspondence: Sung-Wan Kim, MD, PhD Department of Psychiatry, Chonnam National University Medical School, 160 Baekseo-ro, Dong-gu, Gwangju 61469, Republic of Korea Tel: +82-62-220-6148, Fax: +82-62-225-2351, E-mail: swkim@chonnam.ac.kr

Correspondence: Ju-Yeon Lee, MD, PhD Department of Psychiatry, Chonnam National University Medical School, 160 Baekseo-ro, Dong-gu, Gwangju 61469, Republic of Korea Tel: +82-62-220-6146, Fax: +82-62-225-2351, E-mail: dabium@hanmail.net

Received December 1, 2021 Revised March 7, 2022 Accepted June 2, 2022

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Objective

This study was performed to identify factors associated with depression and anxiety among Korean adolescents during the coronavirus disease (COVID-19) pandemic.

Methods

We conducted a cross-sectional study of 1,898 Korean adolescents (55.2% male, 44.8% female) ranging in age from 12 to 17 years (mean±standard deviaion age, 15.4±2.6 years). Depression and anxiety were defined as a Patient Health Questionnaire-9 score ≥10 and Generalized Anxiety Disorder-7 score ≥10, respectively. Other questionnaires included sociodemographic data, psychosocial stresses, and experiences in association with COVID-19. Psychiatric scales included Gratitude Questionnaire-6, Perceived Stress Scale-10, and UCLA Loneliness Scale-3.

Results

The prevalence rates of depressive and anxiety symptoms among participants were 13.8% and 21.0%, respectively. Multivariable logistic regression analysis revealed that female sex, fear of COVID-19 infection, low gratitude were risk factors for depression. Fear of COVID-19 infection, increased TV watching time, and academic-related stress were risk factors for anxiety.

Conclusion

Depression and anxiety were prevalent during the pandemic in Korean adolescents, and were associated with fear of COVID-19 infection. Providing appropriate information on COVID-19, helping adolescents manage academic-related stress and maintain daily life patterns, and implementing interventions to foster gratitude are important for preventing depression and anxiety in Korean adolescents.

Keywords: COVID-19, Adolescents, Depression, Anxiety, Risk factor, Protective factor

INTRODUCTION

More than 2 years have passed since the novel coronavirus disease (COVID-19) pandemic began [1]. The effects of the COVID-19 pandemic have not been limited to physical illness or death; massive changes have occurred worldwide, ranging from alterations in individuals’ daily lives to a global economic crisis and sociocultural changes [2]. The COVID-19 pandemic can be thought of as an epidemic disaster. Many studies have revealed that variable psychological problems, including depression and anxiety, increase in frequency in various populations during epidemics (e.g., severe acute respiratory syndrome, Middle East respiratory syndrome) [3-5]. Adolescence is a developmental period characterized by increased vulnerability to the effects of disasters [6]. Considering the psychosocial characteristics of adolescents, who are not yet capable of fully supporting and caring for themselves or conveying their emotional needs to others (i.e., dependent on families and communities), they are at greater risk than adults during epidemics [7]. Such disasters can negatively form the biological, psychological, and interpersonal development of adolescents, which is associated with future mental and physical diseases, interpersonal problems, and high-risk behaviors [8]. Several studies suggest that adolescents subjects to trauma are vulnerable to chronic biopsychosocial impairment [9,10]. One study reported that adolescents were vulnerable to depression and anxiety during infectious disease outbreaks [11,12]. Therefore, it is necessary to examine changes in the lifestyle and psychological status of adolescents during the current COVID-19 pandemic. Major changes are taking place in the daily lives of adolescents during COVID-19 pandemic, including postponement of school opening, online classes, and restriction to indoor environments, all of which may have a huge psychological and social impact [6,13]. Around the world, 91% of schools have been closed due to the imposition of social distancing measures in response to the COVID-19 pandemic. In Korea, the opening of schools was postponed to March 23, 2020, and online classes started on March 31, 2020. Since then, face-to-face learning has alternated with online classes depending on the spread of COVID-19 infection. School closures deprives adolescents of school-based peer interactions and regular routines, and can therefore hinder their psychological and physical development [14]. In addition, the shift to an online learning environment revealed inequalities in the distribution of learning resources among adolescents (e.g., internet connection quality, caregivers who can help with learning, and the availability of a space for independent learning). While lifestyle changes due to COVID-19 pandemic likely have a psychological impact on adolescents, few studies have evaluated the impact of epidemics on the mental health of adolescents compared to adults. Moreover, no studies have examined the effects of the COVID-19 pandemic on the mental health of Koran adolescents and associated factors. During the COVID-19 pandemic, many studies focused on mental health, but few evaluated protective factors against mental health problems, especially depression and anxiety [15,16]. Here, we attempted to identify protective factors to inform future therapeutic interventions. Factors that protect against psychological problems during disasters include gratitude, social support, resilience, and life satisfaction [17,18]. Therefore, we evaluated gratitude in our participants considering its potential importance for psychiatric interventions. A literature review indicated that gratitude helps to reduce the psychological distress caused by disasters, and is related to fewer symptoms of post-traumatic stress disorder and increased levels of wellbeing, optimism, and happiness [19,20]. The present study was performed to determine the prevalence rates of depression and anxiety, and to identify risk and protective factors of them, among Korean adolescents during the COVID-19 pandemic. This study provides basic data to facilitate the establishment of programs and systems for psychological support of Korean adolescents during the COVID-19 pandemic.

METHODS

Study design and participants

This cross-sectional study surveyed 1,898 middle and high school students (55.2% male, 44.8% female) aged 12-17 years (mean±standard deviation [SD] age, 15.4±2.6 years) living in Gwangju Metropolitan City from April to July 2020, during the opening of schools that had been postponed by the COVID-19 pandemic. After removing the data of participants with incomplete questionnaires, 1,783 participants were included in the analysis. The participants were 1,898 Korean students, including 1,395 middle school (73.5%) middle schools and 503 (26.5%) high school students. Of the participants, 27.3% were religious and 72.7% were not. The academic achievement levels were good, average, and poor for 33.7%, 37.1%, and 29.2% of the participants, respectively. In total, 4.5% of the participants had a physical illness and 0.5% had a mental illness (defined as currently taking medication for a condition). The investigator explained the purpose of the study to the participants, distributed the questionnaires in sealed envelopes to those who consented, and collected them directly after completion. We assured the participants that the collected data would be kept anonymous and used only for research purposes. The study was approved by the Research Ethics Review Committee of Chonnam National University Hospital (approval number CNUH-2020-157). When participants checked consent, this survey was conducted. All methods were performed in accordance with the guidelines and regulations set by the University Institutional Review Board.

Sociodemographic and clinical characteristics

Sociodemographic data included age, sex, school level (middle or high school), religious status (yes or no), academic achievement level (poor/average or good), presence of physical or mental illness (defined as currently taking medication for a condition; yes or no), confirmed COVID-19 experience (yes or no), and quarantine experience (yes or no) of oneself and acquaintances. Participants were clinically assessed in terms of depression, anxiety, and related factors, such as perceived stress, loneliness, gratitude, and psychosocial experiences and stress associated with the COVID-19 pandemic [21].

Outcome measures

Depression

Depression was assessed using the Korean version of the Patient Health Questionnaire-9 (PHQ-9). PHQ-9 items were scored based on frequency using a 4-point Likert scale ranging from 0 (not at all) to 3 (nearly every day). Higher scores reflect more severe depression [22]. A cutoff score ≥10 was used as an indicator of clinically relevant symptoms of depression. The PHQ-9 has good internal consistency (Cronbach’s α=0.80-0.90; 0.859 in this study) [23]. The Korean version of the PHQ-9 is a reliable and valid tool for screening and assessing depressive symptoms in Korean populations [24]. The PHQ-9 has been used to assess depression in adolescents in many studies [23,25].

Anxiety

Anxiety was assessed using the Korean version of the Generalized Anxiety Disorder-7 (GAD-7) scale. The GAD-7 items were scored based on frequency using a 5-point Likert scale ranging from 0 (not at all) to 4 (nearly every day) [26]. Higher scores indicate more severe anxiety. A cutoff score ≥10 was used as an indicator of clinically relevant symptoms of anxiety [27]. The GAD-7 has high reliability and validity, with a Cronbach’s alpha of 0.90-0.92 [28,29]. In this study, the internal consistency of the GAD-7 was acceptable (Cronbach’s α=0.898).

Gratitude

Gratitude was measured using the Korean version of the Gratitude Questionnaire-6 (K-GQ-6) adapted by Kwon et al. [30]. The K-GQ-6 items were scored based on intensity using a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree), with higher scores indicating a more grateful attitude and more positive emotions [31]. We analyzed total scores and the internal consistency was acceptable (Cronbach’s α=0.703).

Perceived stress

The Perceived Stress Scale-10 (PSS-10) evaluates perceived stress over the past month using a 5-point Likert scale ranging from 0 (never) to 4 (very often), with higher scores indicating greater perceived stress [32]. Cohen et al. [33] developed the PSS-10 and demonstrated its reliability and validity. Questions 1-3, 6, 9, and 10 of the PSS-10 are scored conventionally; questions 4, 5, 7, and 8 are reversely scored. We used the Korean version of the PSS-10, which has good reliability and validity [32]. The internal consistency of the PSS-10 was high (Cronbach’s α=0.767).

Loneliness

Loneliness was assessed using UCLA Loneliness Scale developed by Russell et al. [34]. We used the Korean version of UCLA Loneliness Scale adapted by Kim [35]. The scale was adapted to assess perceived isolation, with higher scores indicating greater loneliness [35]. The Cronbach’s α of UCLA Loneliness Scale-3 was 0.756, indicating acceptable internal consistency.

Psychosocial experiences and stress

To assess psychosocial experiences and stress associated with the COVID-19 pandemic, we developed a questionnaire based on a literature review [36,37] and our clinical opinions (Supplementary Table 1 in the online-only Data Supplement). Ten questions were used to assess psychosocial experiences and 15 were used to assess psychosocial stress related to the COVID-19 pandemic. Four of the 10 psychosocial experience questions were related to COVID-19 infection and quarantine experience, while the remaining six were related to changes in daily life patterns during the pandemic. The 15 psychosocial stress questions were distributed over four factors: fear of COVID-19 infection (7 items), academic-related stress (3 items), stress caused by changes in eating and sleeping patterns (3 items), and stress caused by changes in daily activities (2 items). The items were scored based on intensity using a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The scores for each factor were calculated by dividing the summed score for the items by the number of items. Higher scores indicate more severe psychosocial stress in relation to the COVID-19 pandemic.

Statistical analysis

The analysis was conducted by dividing the subjects into groups according to the presence or absence of depression and anxiety. The chi-square test was performed to compare sociodemographic factors between the groups. Reliability was verified by calculating Cronbach’s α coefficient, which reflects internal consistency. Binary logistic regression analysis was used to identify factors affecting depression and anxiety in the study participants; those factors were then subjected to univariate analysis. Variables that were significant in the univariate analyses were adjusted for in multivariate analysis, and the adjusted odds ratio (OR) and confidence intervals (CIs) were calculated. SPSS for Windows ver. 21.0 (IBM Corp., Armonk, NY, USA) was used to perform the statistical tests. All statistical tests were two-tailed, and p<0.05 was taken to indicate statistical significance.

RESULTS

The 1,783 participants included in this study consisted of 979 male (54.9%) and 804 female (45.1%) adolescents ranging in age from 12 to 17 years (mean±SD age, 15.4±1.7 years). The overall prevalence rates of depression and anxiety were 13.8% and 21.0%, respectively.

Table 1 shows the sociodemographic characteristics of the cohort and their associations with depression and anxiety. The depression and anxiety rates were higher among female than male adolescents (17.0% vs. 11.3%, respectively, χ²=11.578, p<0.001; 24.2% vs. 18.3%, respectively, χ²=8.967, p=0.003). There were no significant differences in depression or anxiety according to school level, religious status, academic achievement level, presence of mental illness, or presence of a physical illness (Table 1).

Table 2 shows the results of the univariate logistic regression analysis performed to detect factors associated with depression and anxiety. Female sex, longer TV watching time, and a higher PSS-10 score were associated with a significantly increased risk of depression. Higher scores on questions about COVID-19-related psychosocial stress, including fear of COVID-19 infection, and academic-related stress, were positively associated with depression. However, the GQ-6 score was significantly negatively associated with depression. Female sex, poor/average academic achievement (compared to good), and longer TV watching time were associated with a significantly increased risk of anxiety. Higher scores on questions about COVID-19-related psychosocial stress, including fear of COVID-19 infection, and academic-related stress were associated with an increased risk of anxiety (Table 2).

In logistic regression analyses, dependent variables are categorical data divided according to the presence or absence of depression and anxiety based on using PHQ-9 and GAD-7, respectively. In both Tables 3 and 4, the chosen independent variables significant at p<0.05 (sex, academic achievement level, TV watching time, fear of COVID-19 infection, academic related stress, perceived stress, and gratitude) were included as covariates in multivariable logistic regression analysis. The results of multivariable logistic regression analysis of depression and anxiety are shown in Tables 3 and 4. Female sex, high level of fear regarding COVID-19 infection, and low gratitude were risk factors for Depression (Table 3). A change in daily life patterns during the COVID-19 pandemic, especially watching more TV, was a risk factor for anxiety. Psychosocial stress related to COVID-19, such as a high level of fear regarding COVID-19 infection and academic-related stress, were risk factors for anxiety (Table 4).

Exploratory factor analysis was conducted to verify the validity of the 15 psychosocial stress questions, grouped according to the four factors described above. The Kaiser-Meyer-Olkin was high (0.874), and the result of Bartlett’s test of sphericity indicated the suitability of exploratory factor analysis (χ²=11,967.27, p<0.001). The commonality value of all questions exceeded 0.4. Varimax rotation was performed and four subfactors had initial eigenvalues of ≥1; the cumulative amount of variance explained was 68.05%. Supplementary Table 1 (in the online-only Data Supplement) gives the eigenvalue and variance values for each factor.

We conducted supplementary analyses for subjects with both depression and anxiety symptoms. We performed the chi-square test to compare sociodemographic factors between groups (subjects with both depression and anxiety vs. other subjects). In this subgroup analysis, only sex factor showed significant difference (χ²=10.85, p<0.001). And we performed multivariable logistic regression analysis to detect risk factors for comorbid depression and anxiety symptoms. In this subgroup analysis, female sex (OR=1.666; 95% CI, 1.186-2.340; p=0.003), high level of fear of COVID-19 infection (OR=1.787; 95% CI, 1.485-2.149; p<0.001) and academic-related stress (OR=1.164; 95% CI, 1.007-1.344; p=0.040) were risk factors for comorbid depression and anxiety symptoms.

DISCUSSION

This study was performed to investigate the prevalence rates of depression and anxiety (and the risk and protective factors therefor) during the COVID-19 pandemic in Korean adolescents. This study investigated the prevalence rates of depression and anxiety and psychosocial experiences during the COVID-19 pandemic in Korean adolescents. In addition, the effects of sociodemographic and psychosocial experience variables of the subjects on depression and anxiety during the COVID-19 pandemic were investigated. The main results and clinical and policy implications of this study are as follows.

The results showed that depression and anxiety had prevalence rates of 13.8% and 21.0%, respectively. These incidences of depression and anxiety among Korean adolescents were similar to or higher than those in previous studies conducted in China during the COVID-19 pandemic [25,38]. As both depression and anxiety are significantly affected by environmental factors, including the sociocultural and economic context, we compared the results of the present study with those of a previous survey of Korean adolescents conducted before the COVID-19 pandemic; depression and anxiety were more prevalent in our survey [39]. Although it did not use the same scale as this study, the prevalence of depression from August 2014 to January 2015 was 13.6% in a cross-sectional study of 1,991 students from 30 middle and high schools in Korea [39]. In addition, a survey of children and adolescents conducted in four regions of Korea from September 2016 to December 2017 showed a prevalence rate of anxiety of 15.7% among middle and high school students [40]. Insufficient statistical data are available regarding the mental health status of Korean adolescents, and the diagnostic test tools used differ between studies; nevertheless, the above results suggest that the prevalence of depression and anxiety among Korean adolescents has increased since the beginning of the COVID-19 pandemic.

The present study showed that fear of COVID-19 infection was a risk factor for depression and anxiety in Korean adolescents. Fear of infection associated with new infectious diseases, such as COVID-19, tends to be exacerbated by the fear of infecting others, fear of being quarantined, and social stigma, in addition to uncertainty caused by a lack of information [41,42]. In this study, these fears were grouped into one factor (fear of COVID-19 infection) and then analyzed. Consistent with several previous studies, fear of infection, fear of spreading disease to others, and social stigma related to infectious disease strongly influenced the likelihood of depression and anxiety in this study [43-45]. Excessive fear of infection or disease transmission and social stigma were associated with a lack of knowledge and exposure to misinformation regarding COVID-19 [46,47]. The latest and most accurate information on diseases, and appropriate countermeasures for prevention (e.g., mask wearing and hand washing), can reduce the severity of depression and anxiety [1,48-51]. Taken together, the results of the present and previous studies suggest that it is necessary for the government and health authorities to provide accurate, up-to-date information and education on preventive methods for new infectious diseases [1,23].

Anxiety was significantly associated with increased TV watching time in this study. According to previous studies conducted in adult populations, during the COVID-19 pandemic, the prevalence rate of anxiety was high in those with longer TV watching times [52,53]. In addition, increased TV watching time may be associated with increased exposure to COVID-19-related news, decreased physical activity, and fewer social interactions [54-56]. Previous studies have shown that increased exposure to COVID-19-related news was associated with depression and anxiety [57-59]. Disaster-related TV exposure was associated with post-traumatic stress syndrome (PTSS) in teenagers not directly exposed to the disasters [60-62]. In addition, there was a positive relation between the total amount of news consumed and the level of psychological trauma in the disaster context [63]. In epidemic disasters, an appropriate level of media consumption reduces anxiety and promotes behavior that can prevent disease, whereas excessive media use can increase anxiety [64]. Detailed descriptions of the COVID-19 pandemic, such as the numbers of confirmed COVID-19 cases and deaths, have been reported on TV every day. This study showed that increased time watching TV was a risk factor for anxiety, possibly because of exposure to large amounts of detailed information on the pandemic [65,66]. Previous studies showed that sedentary behavior, such as watching TV, is positively correlated with anxiety, while physical activity protects against anxiety [67]. Several physiological mechanisms can explain the negative correlation between physical activity and anxiety [57]. The group with increased TV watching time in this study may have had fewer social interactions, which can lead to a sense of social isolation and loneliness, both of which are risk factors for anxiety [21,68,69]. Therefore, it is necessary to be aware of increases in passive sedentary behavior, such as TV watching, among adolescents during the COVID-19 pandemic. In addition, adults should encourage adolescents to engage in physical activity at home or outdoors, and to avoid excessive media consumption.

The results of the present study showed that the risk of anxiety was increased in participants with higher levels of academic-related stress. This study included questionnaire items regarding academic stressors. A previous online survey of American high school students conducted during the COVID-19 pandemic showed that the most salient stressors were academic (e.g., excessive homework, lack of motivation to learn, and time management) [70]. A study of 5,175 Chinese children and adolescents conducted during the lockdown period for COVID-19 showed that difficulties related to online classes caused depression and anxiety [71]. Various facets of online learning (e.g., reduced opportunity for interaction, imbalance in the distribution of learning resources, and concerns about poor academic achievement) may promote psychological distress in children and adolescents [3]. It is thus necessary to determine whether adolescents are experiencing academic-related stress, especially difficulties related to online classes, and to help them accordingly.

Female sex was a risk factor for depression in this study. In a meta-analysis examining the prevalence of depression and anxiety symptoms in children and adolescents during the COVID-19 pandemic, females experienced higher levels of both in relation to the disease than males [72]. Other studies reported higher rates of depression, anxiety, sleep problems, and PTSS in women than men during infectious disease outbreaks [6,23,25,73,74]. These findings suggest that girls may be more vulnerable to psychological distress than boys during infectious disease outbreaks. The government and health authorities should identify high-risk groups and provide early interventions.

This study showed that gratitude can protect against depression. In previous studies, gratitude had a negative correlation with depressive and posttraumatic stress disorder symptoms [75,76]. Other studies showed that gratitude was associated with many positive factors, including positive reframing, social support, self-esteem, life satisfaction, and sense of control, all of which are associated with reductions in depression [18,77]. In particular, our previous study of the general adult population showed that gratitude significantly protected against depression during the pandemic [31]. Gratitude might enhance people’s coping resources and emotional well-being in the face of negative events [78,79]. In a study of American adolescents conducted during school closures due to the COVID-19 pandemic, “secondary engagement” coping mechanisms, such as gratitude, were associated with persistent positive emotions [80,81]. Taken together, the results of this and previous studies suggest that gratitude employed during the COVID-19 pandemic can buffer the negative effects of disasters, improving adolescents’ mood and restoring a sense of control [82]. Encouraging adolescents to use gratitude during the pandemic may help prevent psychological conditions such as depression [83,84]. In addition, interventions fostering gratitude are needed to improve the mental health of adolescents.

In addition, we conducted supplementary analyses for participants with both depression and anxiety symptoms as it is likely that adolescents show both symptoms. The study showed that the risk factors for comorbid depression and anxiety symptoms were increased in participants with higher levels of fear of COVID-19 infection and academic-related stress, and female. Each of these factors was described above as a risk factor for depression and anxiety, and also acted as a risk factor in the group with comorbid depression and anxiety. Depression and anxiety frequently coexist and share a general etiological process [85]. Previous studies suggest neuro-biologic similarities between depressive and anxiety disorders (serotonergic and noradrenergic dysfunction has been identified in depressive and anxiety disorders) [86,87]. In a national survey of United States, 58% of respondents with depression also had an anxiety disorder [88]. Also comorbid depression occurs in 90% of participants with anxiety disorders [86]. As such, depression and anxiety commonly coexist and have biological similarities, so it seems that risk factors are also shared as shown in the results of this study.

This study had several limitations. First, as it was conducted on a population of teenagers in one city, the results may not be generalizable to other populations. Second, the cross-sectional design precludes inferences regarding causality. Finally, this study enrolled only adolescents who volunteered to participate. Some adolescents with depression and anxiety may have been unable to participate due to the severity of their psychological symptoms. Despite these limitations, this study provides data that could help predict and prevent negative psychological problems in Korean adolescents during the COVID-19 pandemic, by shedding light on risk and protective factors for depression and anxiety. Further research is needed to determine the psychological effects of this prolonged pandemic on Korean adolescents.

Conclusions

This study revealed the prevalence of depression and anxiety among Korean adolescents increased during the COVID-19 pandemic. The fear of COVID-19 infection was significantly associated with the prevalence of depression and anxiety. The risk of anxiety was increased in participants with longer TV watching times and higher levels of academic-related stress. The results suggest that it is necessary to reassure adolescents through the provision of accurate and up-to-date information on methods for preventing COVID-19 infection. In addition, efforts are needed to reduce the social stigma associated with the disease, and attention should be paid to adolescents exhibiting increased passive sedentary behavior, such as watching TV. It is necessary to check for academic-related stress and provide help as appropriate. This study showed that a gratitude disposition has a protective effect against depression. As gratitude is helpful in relieving psychological distress during a disaster, and promotes feelings of well-being, optimism, and happiness, strategies to foster gratitude are needed to improve the mental health of adolescents. Efforts are also needed to determine other risk factors for depression and anxiety, and to provide appropriate interventions for adolescents during prolonged infectious disease disasters. The results of this study will contribute to the development of interventions and policies to prevent psychological problems among Korean adolescents caused by societal changes associated with the COVID-19 pandemic.

Supplementary Materials

The online-only Data Supplement is available with this article at https://doi.org/10.30773/pi.2021.0365.

Supplementary Table 1.

Factor analysis of the questionnaire on psychosocial stress associated with COVID-19

pi-2021-0365-suppl1.pdf

Notes

Availability of Data and Material

The datasets generated or analyzed during the study are available from the corresponding author on reasonable request.

Conflicts of Interest

Jae-Min Kim and Sung-Wan Kim, contributing editors of the Psychiatry Investigation, were not involved in the editorial evaluation or decision to publish this article. All remaining authors have declared no conflicts of interest.

Author Contributions

Conceptualization: Sung-Wan Kim, Ju-Yeon Lee. Data curation: Honey Kim, Min Jhon. Formal analysis: Honey Kim, Ju-Wan Kim. Funding acquisition: Sung-Wan Kim. Investigation: all authors. Methodology: all authors. Supervision: Hee-Ju Kang, Seunghyong Ryu, Jae-Min Kim. Writing—original draft: Honey Kim. Writing—review & editing: Ju-Yeon Lee, Sung-Wan Kim.

Funding Statement

This research was supported by grants of Patient-Centered Clinical Research Coordinating Center (PACEN) funded by the Ministry of Health & Welfare, Republic of Korea (grants number: HI19C0481, HC19C0316). The funders were not involved in the conception, design, analysis or interpretation of this study.

ACKNOWLEDGEMENTS

The authors would like to thank Dahye Ban, Bomsori Park, Shinhyun Moon, and Daeun Choi of Gwangju Bukgu Mental Health Welfare Center for collecting data.

Table 1.

Sociodemographic characteristics of Korean adolescents according to the presence of depression and anxiety during the COVID-19 pandemic

Variables	N (%)	Depression (+)			Anxiety (+)
Variables	N (%)	N (%)	χ²	p	N (%)	χ²	p
Sex (N=1,732)			11.578	<0.001^***		8.967	0.003^**
Male	955 (55.1)	108 (11.3)			175 (18.3)
Female	777 (44.9)	132 (17.0)			189 (24.3)
School level (N=1,732)			1.512	0.219		0.162	0.687
Middle school	1,279 (73.8)	185 (14.5)			264 (20.6)
High school	453 (26.2)	55 (12.1)			100 (22.1)
Religious (N=1,711)			0.661	0.416		0.339	0.560
Yes	473 (27.6)	71 (15.0)			105 (22.2)
No	1,238 (72.4)	167 (13.5)			257 (20.8)
Academic achievement level (N=1,677)			1.042	0.594		5.435	0.066
Good	567 (33.8)	72 (12.7)			101 (17.8)
Average	622 (37.1)	91 (14.6)			139 (22.3)
Poor	488 (29.1)	70 (13.9)			112 (23.0)
Underlying mental illness (N=1,725)			0.531	0.466		0.355	0.551
Yes	9 (0.5)	2 (22.2)			1 (11.1)
No	1,716 (99.5)	237 (13.8)			363 (21.2)
Underlying physical illness (N=1,726)			1.936	0.164		0.632	0.427
Yes	78 (4.5)	15 (19.2)			19 (24.4)
No	1,648 (95.5)	225 (13.7)			345 (20.9)

^** p<0.01;

^*** p<0.001

Table 2.

Results of univariate logistic regression analysis to detect risk factors for depression and anxiety during the COVID-19 pandemic

Variables		Depression			Anxiety
Variables		OR	95% CI	p	OR	95% CI	p
Sociodemographic characteristics
	Sex, female	1.605	1.120-2.111	<0.001^***	1.424	1.129-1.795	0.003^**
	School level, middle school	1.224	0.887-1.689	0.219	0.948	0.731-1.229	0.687
	Religious, yes	1.133	0.839-1.530	0.416	1.079	0.835-1.395	0.560
	Academic achievement level, poor	1.151	0.808-1.640	0.435	1.373	1.016-1.855	0.039^*
	Academic achievement level, average	1.178	0.845-1.643	0.334	1.342	1.008-1.786	0.044^*
	Underlying mental illness, yes	1.783	0.368-8.634	0.472	0.065	4.351-0.534	0.557
	Underlying physical illness, yes	1.506	0.843-2.690	0.167	0.729	2.110-1.240	0.427
COVID-19 infection and quarantine experience
	Personal infection experience, yes	1.241	0.144-10.67	0.844	0.754	0.088-6.472	0.797
	Experience of infected acquaintances, yes	1.355	0.510-3.600	0.542	1.198	0.508-2.826	0.680
	Personal quarantine experience, yes	1.134	0.631-2.039	0.674	1.328	0.814-2.165	0.256
	Experience of quarantine of acquaintances, yes	1.034	0.747-1.431	0.839	1.194	0.911-1.563	0.199
Questionnaire items related to changes in daily life patterns during the COVID-19 pandemic
	Convenience food intake, increased	1.125	0.846-1.496	0.419	1.104	0.866-1.407	0.424
	Sleeping time, increased	0.975	0.723-1.316	0.869	1.106	0.861-1.420	0.431
	TV watching time, increased	1.365	1.011-1.841	0.042^*	1.411	1.093-1.821	0.008^**
	Internet usage, increased	1.226	0.931-1.615	0.146	0.981	0.775-1.242	0.874
	PC or smartphone usage, increased	1.143	0.868-1.506	0.341	1.065	0.842-1.134	0.600
	Exercise, increased	0.844	0.585-1.217	0.363	1.141	0.852-1.526	0.376
Questionnaire items related to psychosocial stress associated with COVID-19
	Fear of COVID-19 infection, score	1.736	1.485-2.028	<0.001^***	1.786	1.563-2.040	<0.001^***
	Academic-related stress, score	1.157	1.030-1.300	0.014^*	1.167	1.057-1.289	0.002^**
	Stress caused by changes in eating and sleeping patterns, score	1.112	0.982-1.259	0.094	1.055	0.949-1.172	0.324
	Stress caused by changes in daily activities, score	1.117	0.986-1.265	0.083	1.091	0.983-1.121	0.102
Psychiatric scales
	UCLA Loneliness Scale-3, score	1.041	0.953-1.138	0.369	0.996	0.992-1.075	0.909
	Perceived Stress Scale-10, score	1.031	1.007-1.056	0.011^*	1.009	0.989-1.029	0.396
	Korean version of the Gratitude Questionnaire-6, score	0.967	0.944-0.991	0.006^**	0.997	0.977-1.018	0.776

^* p<0.05;

^** p<0.01;

^*** p<0.001.

OR, odds ratio; CI, confidence interval

Table 3.

Results of multiple logistic regression analysis to detect risk factors for depression during the COVID-19 pandemic

Variables		OR	95% CI	p
Sociodemographic characteristics
	Sex, female	1.386	1.012-1.897	0.042^*
Questionnaire items related to changes in daily life patterns during the COVID-19 pandemic
	Increase in TV watching time, yes	1.331	0.951-1.864	0.095
Questionnaire items related to psychosocial stress associated with COVID-19
	Fear of COVID-19 infection, score	1.799	1.515-2.136	<0.001^***
	Academic-related stress, score	1.134	0.992-1.297	0.066
Psychiatric scale
	Perceived Stress Scale-10, score	1.003	0.971-1.036	0.844
	Korean version of the Gratitude Questionnaire-6, score	0.962	0.936-0.989	0.005^**

^* p<0.05;

^** p<0.01;

^*** p<0.001.

OR, odds ratio; CI, confidence interval

Table 4.

Multiple logistic regression analysis to detect risk factors for anxiety during the COVID-19 pandemic

Variables		OR	95% CI	p
Sociodemographic characteristics
	Sex, female	1.286	0.997-1.659	0.053
	Academic achievement level, poor	1.362	0.994-1.865	0.054
	Academic achievement level, average	1.273	0.945-1.715	0.112
Questionnaire items related to changes in daily life pattern during COVID-19 pandemic
	Increase in TV watching time, yes	1.394	1.059-1.836	0.018^*
Questionnaire items related to psychosocial stress associated with COVID-19
	Fear of COVID-19 infection, score	1.829	1.595-2.098	<0.001^***
	Academic-related stress, score	1.135	1.019-1.265	0.022^**

^* p<0.05;

^** p<0.01;

^*** p<0.001.

OR, odds ratio; CI, confidence interval

REFERENCES

1. Wang C, Horby PW, Hayden FG, Gao GF. A novel coronavirus outbreak of global health concern. Lancet 2020;395:470-473.

2. Kim SW, Su KP. Using psychoneuroimmunity against COVID-19. Brain Behav Immun 2020;87:4-5.

3. Peng EY, Lee MB, Tsai ST, Yang CC, Morisky DE, Tsai LT, et al. Population-based post-crisis psychological distress: an example from the SARS outbreak in Taiwan. J Formos Med Assoc 2010;109:524-532.

4. Park HY, Park WB, Lee SH, Kim JL, Lee JJ, Lee H, et al. Posttraumatic stress disorder and depression of survivors 12months after the outbreak of Middle East respiratory syndrome in South Korea. BMC Public Health 2020;20:605

5. Douglas PK, Douglas DB, Harrigan DC, Douglas KM. Preparing for pandemic influenza and its aftermath: mental health issues considered. Int J Emerg Ment Health 2009;11:137-144.

6. Guessoum SB, Lachal J, Radjack R, Carretier E, Minassian S, Benoit L, et al. Adolescent psychiatric disorders during the COVID-19 pandemic and lockdown. Psychiatry Res 2020;291:113264

7. Weems CF. Biological correlates of child and adolescent responses to disaster exposure: a bio-ecological model. Curr Psychiatry Rep 2015;17:51

8. Deighton S, Neville A, Pusch D, Dobson K. Biomarkers of adverse childhood experiences: a scoping review. Psychiatry Res 2018;269:719-732.

9. Ogle CM, Rubin DC, Siegler IC. The impact of the developmental timing of trauma exposure on PTSD symptoms and psychosocial functioning among older adults. Dev Psychol 2013;49:2191-2200.

10. Panchal U, Salazar de Pablo G, Franco M, Moreno C, Parellada M, Arango C, et al. The impact of COVID-19 lockdown on child and adolescent mental health: systematic review. Eur Child Adolesc Psychiatry 2021;Aug 18 [Epub] https://doi.org/10.1007/s00787-021-01856-w.

11. Singh S, Roy D, Sinha K, Parveen S, Sharma G, Joshi G. Impact of COVID-19 and lockdown on mental health of children and adolescents: a narrative review with recommendations. Psychiatry Res 2020;293:113429

12. Cost KT, Crosbie J, Anagnostou E, Birken CS, Charach A, Monga S, et al. Mostly worse, occasionally better: impact of COVID-19 pandemic on the mental health of Canadian children and adolescents. Eur Child Adolesc Psychiatry 2022;31:671-684.

13. Ghosh R, Dubey MJ, Chatterjee S, Dubey S. Impact of COVID -19 on children: special focus on the psychosocial aspect. Minerva Pediatr 2020;72:226-235.

14. Bahn GH. Coronavirus disease 2019, school closures, and children’s mental health. J Korean Acad Child Adolesc Psychiatry 2020;31:74-79.

15. Nearchou F, Flinn C, Niland R, Subramaniam SS, Hennessy E. Exploring the impact of COVID-19 on mental health outcomes in children and adolescents: a systematic review. Int J Environ Res Public Health 2020;17:8479

16. Franic T, Dodig-Curkovic K. Covid-19, child and adolescent mental health - Croatian (in)experience. Ir J Psychol Med 2020;37:214-217.

17. Lambert NM, Fincham FD, Stillman TF. Gratitude and depressive symptoms: the role of positive reframing and positive emotion. Cogn Emot 2012;26:615-633.

18. Mccullough ME, Emmons RA, Tsang JA. The grateful disposition: a conceptual and empirical topography. J Pers Soc Psychol 2002;82:112-127.

19. Mead JP, Fisher Z, Tree JJ, Wong PTP, Kemp AH. Protectors of wellbeing during the COVID-19 pandemic: key roles for gratitude and tragic optimism in a UK-based cohort. Front Psychol 2021;12:647951

20. Bazargan-Hejazi S, Dehghan K, Chou S, Bailey S, Baron K, Assari S, et al. Hope, optimism, gratitude, and wellbeing among health professional minority college students. J Am Coll Health 2021;Aug 3 [Epub] https://doi.org/10.1080/07448481.2021.1922415.

21. Lee CM, Cadigan JM, Rhew IC. Increases in loneliness among young adults during the COVID-19 pandemic and association with increases in mental health problems. J Adolesc Health 2020;67:714-717.

22. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med 2001;16:606-613.

23. Zhou SJ, Zhang LG, Wang LL, Guo ZC, Wang JQ, Chen JC, et al. Prevalence and socio-demographic correlates of psychological health problems in Chinese adolescents during the outbreak of COVID-19. Eur Child Adolesc Psychiatry 2020;29:749-758.

24. Han C, Jo SA, Kwak JH, Pae CU, Steffens D, Jo I, et al. Validation of the Patient Health Questionnaire-9 Korean version in the elderly population: the Ansan Geriatric study. Compr Psychiatry 2008;49:218-223.

25. Liu Y, Yue S, Hu X, Zhu J, Wu Z, Wang J, et al. Associations between feelings/behaviors during COVID-19 pandemic lockdown and depression/anxiety after lockdown in a sample of Chinese children and adolescents. J Affect Disord 2021;284:98-103.

26. Ahn JK, Kim Y, Choi KH. The psychometric properties and clinical utility of the Korean version of GAD-7 and GAD-2. Front Psychiatry 2019;10:127

27. Spitzer RL, Kroenke K, Williams JB, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med 2006;166:1092-1097.

28. Löwe B, Decker O, Müller S, Brähler E, Schellberg D, Herzog W, et al. Validation and standardization of the Generalized Anxiety Disorder Screener (GAD-7) in the general population. Med Care 2008;46:266-274.

29. Kertz S, Bigda-Peyton J, Bjorgvinsson T. Validity of the generalized anxiety disorder-7 scale in an acute psychiatric sample. Clin Psychol Psychother 2013;20:456-464.

30. Kwon SJ, Kim KH, Lee HS. Validation of the Korean version of gratitude questionnaire. Korean Journal of Health Psychology 2006;11:177-190.

31. Kim SW, Park IH, Kim M, Park AL, Jhon M, Kim JW, et al. Risk and protective factors of depression in the general population during the COVID-19 epidemic in Korea. BMC Psychiatry 2021;21:445

32. Park SY, Colvin KF. Psychometric properties of a Korean version of the Perceived Stress Scale (PSS) in a military sample. BMC Psychol 2019;7:58

33. Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav 1983;24:385-396.

34. Russell D, Peplau LA, Cutrona CE. The revised UCLA Loneliness Scale: concurrent and discriminant validity evidence. J Pers Soc Psychol 1980;39:472-480.

35. Kim OS. Korean version of the revised UCLA loneliness scale: reliability and validity test. J Nurs Acad Soc 1997;27:871-879.

36. Nickell LA, Crighton EJ, Tracy CS, Al-Enazy H, Bolaji Y, Hanjrah S, et al. Psychosocial effects of SARS on hospital staff: survey of a large tertiary care institution. CMAJ 2004;170:793-798.

37. Kim M, Park IH, Kang YS, Kim H, Jhon M, Kim JW, et al. Comparison of psychosocial distress in areas with different COVID-19 prevalence in Korea. Front Psychiatry 2020;11:593105

38. Meade J. Mental health effects of the COVID-19 pandemic on children and adolescents: a review of the current research. Pediatr Clin North Am 2021;68:945-959.

39. Yun JY, Chung H, Sim JA, Yun YH. Prevalence and associated factors of depression among Korean adolescents. PLoS One 2019;14:e0223176

40. Prevalence and risk factors of psychiatric disorders in child and adolescent population -school based research-. Available at: https://doi.org/10.23000/TRKO201800042948. Accessed October 31, 2021.

41. Brooks SK, Webster RK, Smith LE, Woodland L, Wessely S, Greenberg N, et al. The psychological impact of quarantine and how to reduce it: rapid review of the evidence. Lancet 2020;395:912-920.

42. Lipai TP. The COVID-19 pandemic: depression, anxiety, stigma and impact on mental health. Probl Sotsialnoi Gig Zdravookhranenniiai Istor Med 2020;28:922-927.

43. Grover S, Sahoo S, Mishra E, Gill KS, Mehra A, Nehra R, et al. Fatigue, perceived stigma, self-reported cognitive deficits and psychological morbidity in patients recovered from COVID-19 infection. Asian J Psychiatr 2021;64:102815

44. Sakib N, Akter T, Zohra F, Bhuiyan AKMI, Mamun MA, Griffiths MD. Fear of COVID-19 and depression: a comparative study among the general population and healthcare professionals during COVID-19 pandemic crisis in Bangladesh. Int J Ment Health Addict 2021;Feb 19 [Epub] https://doi.org/10.1007/s11469-020-00477-9.

45. Balakrishnan V, Ng KS, Kaur W, Govaichelvan K, Lee ZL. COVID-19 depression and its risk factors in Asia Pacific - a systematic review and meta-analysis. J Affect Disord 2022;298(Pt B):47-56.

46. Saeed F, Mihan R, Mousavi SZ, Reniers RL, Bateni FS, Alikhani R, et al. A narrative review of stigma related to infectious disease outbreaks: what can be learned in the face of the Covid-19 pandemic? Front Psychiatry 2020;11:565919

47. Haddad C, Bou Malhab S, Malaeb D, Sacre H, Saadeh D, Mourtada V, et al. Stigma toward people with COVID-19 among the Lebanese population: a cross-sectional study of correlates and mediating effects. BMC Psychol 2021;9:164

48. Zhou R, Chen H, Zhu L, Chen Y, Chen B, Li Y, et al. Mental health status of the elderly Chinese population during COVID-19: an online cross-sectional study. Front Psychiatry 2021;12:645938

49. Bressington DT, Cheung TCC, Lam SC, Suen LKP, Fong TKH, Ho HSW, et al. Association between depression, health beliefs, and face mask use during the COVID-19 pandemic. Front Psychiatry 2020;11:571179

50. Kwan RYC, Lee PH, Cheung DSK, Lam SC. Face mask wearing behaviors, depressive symptoms, and health beliefs among older people during the COVID-19 pandemic. Front Med (Lausanne) 2021;8:590936

51. Xiong J, Lipsitz O, Nasri F, Lui LMW, Gill H, Phan L, et al. Impact of COVID-19 pandemic on mental health in the general population: a systematic review. J Affect Disord 2020;277:55-64.

52. Werneck AO, Silva DR, Malta DC, Souza-Júnior PRB, Azevedo LO, Barros MBA, et al. Physical inactivity and elevated TV-viewing reported changes during the COVID-19 pandemic are associated with mental health: a survey with 43,995 Brazilian adults. J Psychosom Res 2021;140:110292

53. Werneck AO, Silva DR, Malta DC, Souza-Júnior PRB, Azevedo LO, Barros MBA, et al. Changes in the clustering of unhealthy movement behaviors during the COVID-19 quarantine and the association with mental health indicators among Brazilian adults. Transl Behav Med 2021;11:323-331.

54. Arend AK, Blechert J, Pannicke B, Reichenberger J. Increased screen use on days with increased perceived COVID-19-related confinements—a day level ecological momentary assessment study. Front Public Health 2021;8:623205

55. Hallgren M, Nguyen TT, Owen N, Vancampfort D, Dunstan DW, Wallin P, et al. Associations of sedentary behavior in leisure and occupational contexts with symptoms of depression and anxiety. Prev Med 2020;133:106021

56. Lee YR, Lee JY, Park IH, Kim M, Jhon M, Kim JW, et al. The relationships among media usage regarding COVID-19, knowledge about infection, and anxiety: structural model analysis. J Korean Med Sci 2020;35:e426

57. Bendau A, Petzold MB, Pyrkosch L, Mascarell Maricic L, Betzler F, Rogoll J, et al. Associations between COVID-19 related media consumption and symptoms of anxiety, depression and COVID-19 related fear in the general population in Germany. Eur Arch Psychiatry Clin Neurosci 2021;271:283-291.

58. Pfefferbaum B, Nitiéma P, Newman E. Is viewing mass trauma television coverage associated with trauma reactions in adults and youth? A meta‐analytic review. J Trauma Stress 2019;32:175-185.

59. Liu C, Liu Y. Media exposure and anxiety during COVID-19: the mediation effect of media vicarious traumatization. Int J Environ Res Public Health 2020;17:4720

60. Pfefferbaum B, Nixon SJ, Tivis RD, Doughty DE, Pynoos RS, Gurwitch RH, et al. Television exposure in children after a terrorist incident. Psychiatry 2001;64:202-211.

61. Pfefferbaum B, Tucker P, Pfefferbaum RL, Nelson SD, Nitiéma P, Newman E. Media effects in youth exposed to terrorist incidents: a historical perspective. Curr Psychiatry Rep 2018;20:11

62. Pfefferbaum B, Newman E, Nelson SD, Nitiéma P, Pfefferbaum RL, Rahman A. Disaster media coverage and psychological outcomes: descriptive findings in the extant research. Curr Psychiatry Rep 2014;16:464

63. Bodas M, Siman-Tov M, Peleg K, Solomon Z. Anxiety-inducing media: the effect of constant news broadcasting on the well-being of Israeli television viewers. Psychiatry 2015;78:265-276.

64. Pat-Horenczyk R, Bergman YS, Schiff M, Goldberg A, Cohen A, Leshem B, et al. COVID-19 related difficulties and perceived coping among university and college students: the moderating role of media-related exposure and stress. Eur J Psychotraumatol 2021;12:1929029

65. Scott SR, Rivera KM, Rushing E, Manczak EM, Rozek CS, Doom JR. “I hate this”: a qualitative analysis of adolescents’ self-reported challenges during the COVID-19 pandemic. J Adolesc Health 2021;68:262-269.

66. McCanlies EC, Mnatsakanova A, Andrew ME, Burchfiel CM, Violanti JM. Positive psychological factors are associated with lower PTSD symptoms among police officers: post Hurricane Katrina. Stress Health 2014;30:405-415.

67. Edwards MK, Loprinzi PD. Experimentally increasing sedentary behavior results in increased anxiety in an active young adult population. J Affect Disord 2016;204:166-173.

68. Morrissette M. School closures and social anxiety during the COVID-19 pandemic. J Am Acad Child Adolesc Psychiatry 2021;60:6-7.

69. Palgi Y, Shrira A, Ring L, Bodner E, Avidor S, Bergman Y, et al. The loneliness pandemic: loneliness and other concomitants of depression, anxiety and their comorbidity during the COVID-19 outbreak. J Affect Disord 2020;275:109-111.

70. Lau AL, Chi I, Cummins RA, Lee TM, Chou KL, Chung LW. The SARS (Severe Acute Respiratory Syndrome) pandemic in Hong Kong: effects on the subjective wellbeing of elderly and younger people. Aging Ment Health 2008;12:746-760.

71. Racine N, McArthur BA, Cooke JE, Eirich R, Zhu J, Madigan S. Global prevalence of depressive and anxiety symptoms in children and adolescents during COVID-19: a meta-analysis. JAMA Pediatr 2021;175:1142-1150.

72. Ma L, Mazidi M, Li K, Li Y, Chen S, Kirwan R, et al. Prevalence of mental health problems among children and adolescents during the COVID-19 pandemic: a systematic review and meta-analysis. J Affect Disord 2021;293:78-89.

73. Liu S, Yang L, Zhang C, Xu Y, Cai L, Ma S, et al. Gender differences in mental health problems of healthcare workers during the coronavirus disease 2019 outbreak. J Psychiatr Res 2021;137:393-400.

74. Pappa S, Ntella V, Giannakas T, Giannakoulis VG, Papoutsi E, Katsaounou P. Prevalence of depression, anxiety, and insomnia among healthcare workers during the COVID-19 pandemic: a systematic review and meta-analysis. Brain Behav Immun 2020;88:901-907.

75. McGuire AP, Fogle BM, Tsai J, Southwick SM, Pietrzak RH. Dispositional gratitude and mental health in the U.S. veteran population: results from the National Health and Resilience Veterans Study. J Psychiatr Res 2021;135:279-288.

76. Vieselmeyer J, Holguin J, Mezulis A. The role of resilience and gratitude in posttraumatic stress and growth following a campus shooting. Psychol Trauma 2017;9:62-69.

77. McCanlies EC, Gu JK, Andrew ME, Violanti JM. The effect of social support, gratitude, resilience and satisfaction with life on depressive symptoms among police officers following Hurricane Katrina. Int J Soc Psychiatry 2018;64:63-72.

78. Tugade MM, Fredrickson BL, Barrett LF. Psychological resilience and positive emotional granularity: examining the benefits of positive emotions on coping and health. J Pers 2004;72:1161-1190.

79. Fredrickson BL. The role of positive emotions in positive psychology. The broaden-and-build theory of positive emotions. Am Psychol 2001;56:218-226.

80. Tu KM, Erath SA, El-Sheikh M. Coping responses moderate prospective associations between marital conflict and youth adjustment. J Fam Psychol 2016;30:523-532.

81. Wang MT, Toro JD, Scanlon CL, Schall JD, Zhang AL, Belmont AM, et al. The roles of stress, coping, and parental support in adolescent psychological well-being in the context of COVID-19: a daily-diary study. J Affect Disord 2021;294:245-253.

82. Van Dusen JP, Tiamiyu MF, Kashdan TB, Elhai JD. Gratitude, depression and PTSD: assessment of structural relationships. Psychiatry Res 2015;230:867-870.

83. Hallis L, Cameli L, Bekkouche NS, Knäuper B. Combining cognitive therapy with acceptance and commitment therapy for depression: a group therapy feasibility study. J Cogn Psychother 2017;31:171-190.

84. Bui THT, Nguyen TNT, Pham HD, Tran CT, Ha TH. The mediating role of self-compassion between proactive coping and perceived stress among students. Sci Prog 2021;104:368504211011872

85. Garber J, Brunwasser SM, Zerr AA, Schwartz KT, Sova K, Weersing VR. Treatment and prevention of depression and anxiety in youth: test of cross‐over effects. Depress Anxiety 2016;33:939-959.

86. Gorman JM. Comorbid depression and anxiety spectrum disorders. Depress Anxiety 1996-1997;4:160-168.

87. Liebowitz MR, Hollander E, Schneier F, Campeas R, Fallon B, Welkowitz L, et al. Anxiety and depression: discrete diagnostic entities? J Clin Psychopharmacol 1990;10(3 Suppl):61S-66S.

88. Kessler RC, McGonagle KA, Zhao S, Nelson CB, Hughes M, Eshleman S, et al. Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States. Results from the National Comorbidity Survey. Arch Gen Psychiatry 1994;51:8-19.