Role of Stigma in Moderating the Effects of Loneliness on Mental Health Problems Among Patients With COVID-19 in South Korea

Article information

Psychiatry Investig. 2024;21(6):590-600
Publication date (electronic) : 2024 June 24
doi :
1Department of Psychiatry, National Center for Mental Health, Seoul, Republic of Korea
2Mental Health Research Institute, National Center for Mental Health, Seoul, Republic of Korea
Correspondence: Subin Park, MD, PhD Mental Health Research Institute, National Center for Mental Health, 127 Yongmasan-ro, Gwangjin-gu, Seoul 04933, Republic of Korea Tel: +82-2-2204-0103, Fax: +82-2-2204-0362, E-mail:
Received 2024 January 14; Revised 2024 March 6; Accepted 2024 March 15.



This study examined the factors affecting depression, anxiety, and suicidal ideation among patients with coronavirus disease-2019 (COVID-19) during the early phase of COVID-19 in South Korea and investigated the role of stigma in moderating the effects of loneliness on mental health problems among these patients.


Conducted as part of the COVID-19 Mental Health Panel Survey over 12 weeks in 2021, this survey enrolled participants aged 15–79 years, applying standardized weights for ratio correction, and collected 640 completed questionnaires. Demographic characteristics were analyzed using descriptive statistics. Suicidal ideation, anxiety, and depression post-COVID-19 were examined using t-tests and logistic regression. The PROCESS macro explored stigma’s moderating effects on loneliness and mental health outcomes.


Results showed that 7.9% and 10.0% of the enrolled participants were at risk for anxiety and depression, respectively, with 3% contemplating suicide post-COVID-19. Stigma positively impacted depression and anxiety, acting as a significant moderator for loneliness, and mental health, with a stronger effect for higher stigma perception. Unemployment and college education elevated mental health risks in COVID-19 cases. Low health satisfaction and poor sleep were linked to suicidal ideation, while fatigue and COVID-19 stigma increased depression and anxiety risks. Loneliness was significantly associated with suicidal ideation, depression, and anxiety.


Unemployment, college education, low health satisfaction, and poor sleep were linked to suicidal ideation. Fatigue and COVID-19 stigma raised depression/anxiety risks. Loneliness correlated with suicidal thoughts, depression, and anxiety. Stigma moderated the link between loneliness and mental health issues.


A novel coronavirus pneumonia, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first detected in China in late December 2019. Subsequently, after its extensive spread in numerous countries, the World Health Organization (WHO) declared coronavirus disease-2019 (COVID-19) an international health emergency; the WHO declared it a pandemic on March 11, 2020 [1]. In the case of novel infectious diseases, such as COVID-19, the uncertainty and persistence of risk factors, insufficient information on transmission patterns, lethality, and the development of vaccines and treatments contribute to escalated fear and anxiety among people [2]. Pandemics bring about dramatic changes not only in physical health but also have adverse effects on mental health [3]. A meta-analysis of 50 studies on COVID-19 showed that the pooled prevalence of psychological problems included poor sleep quality (40%), stress (34%), psychological distress (34%), insomnia (30%), post-traumatic stress symptoms (27%), anxiety (26%), and depression (26%). 4 According to the “COVID-19 National Mental Health Status Survey” conducted by the Ministry of Health and Welfare and the Korean Society for Traumatic Stress Studies in March, May, September, and December of 2020 and March, June, September, and December of 2021, the average depression score, evaluated using the patient health questionnaire (PHQ-9) scale (total score of 27), consistently remained in the 5-point range, higher than the 2019 results from a local community health survey (2.1 points). The proportion of individuals at risk of depression was notably elevated, reaching 18.1% in December 2021, compared to 3.2% in the 2019 community health survey [5].

Infectious diseases can cause psychosocial issues not only because of the disease itself but also because of stigma and discrimination against the infected population. Stigma involves socially distrustful attitudes or behaviors, classifying individuals with perceived negative differences as “undesirable others” [6]. Previous research has demonstrated the existence of two types of stigma: public and self-stigma [7]. Public stigma refers to the negative attitudes of the public towards people with devalued characteristics [8]. Public stigmatization can be problematic because large-scale negative perceptions of a group can lead to stereotyping, prejudice, and discrimination [7]. Self-stigma is defined as a reduction in self-esteem or sense of self-worth due to the self-perceived social unacceptability of the individual [9]. Self-stigma occurs when people internalize public attitudes and experience numerous negative consequences [10].

Diseases related to stigma vary in degree and type depending on the illness characteristics. In the case of infectious diseases with potentially fatal consequences, stigmatization tends to be rationalized and intensified [11]. Individuals affected by disease-related stigma may internalize social stigma and discrimination, leading to feelings of guilt, self-blame, and shame. Isolation and deterred professional help-seeking behaviors may further deteriorate quality of life [12]. Stigma and discrimination associated with COVID-19 have been found to negatively affect the mental health and daily lives of survivors, causing issues such as insomnia and depression [13,14]. The stigma and discrimination against COVID-19 patients have been influenced by major events during the epidemic, such as group infections in vulnerable facilities like mental hospitals and cults. Stigma decreased, particularly after a surge in the number of confirmed cases, but it seemed to have been particularly severe during the early stages of the COVID-19 pandemic [15].

Self-stigma and the perception of public stigma are more common among lonely people than among others [16]. Loneliness is a negative psychological state that arises when people are dissatisfied with the quantity or quality of their social relationships [17]. Several studies suggest that loneliness is a stigmatizing condition in which people attribute more negative characteristics to lonely individuals than to non-lonely ones [18-20]. People who feel lonely and socially isolated tend to be perceived as socially inept, poorly adjusted, unlikeable, and generally incompetent [21,22]. Such negative perception makes some lonely people refrain from sharing their experiences due to feelings of embarrassment (i.e., self-stigma) [23], fear of judgement, or rejection from others (i.e., social stigma).

Loneliness and social isolation are closely related to the prevalence of mental disorders, such as anxiety, depression [24,25], and alcohol addiction [26]. Cross-sectional associations have been found between loneliness and several mental health problems including depression [27], anxiety [28], and suicidal ideation [29]. During the early stages of the COVID-19 pandemic, extreme social distancing was implemented due to rapid transmission. As a result, people experienced social isolation that they have not encountered previously, leading to expressions of loneliness [30]. Increased loneliness during the COVID-19 pandemic has been associated with an exacerbated decline in physical function, mental health deterioration, and cognitive function worsening [31].

This study aimed to investigate the factors that affect depression, anxiety, and suicidal ideation among confirmed COVID-19 patients during the early stages of the pandemic, from 2020 to 2021. This study focused on the role of stigma against COVID-19, and perceived loneliness on mental health outcomes (i.e., depression, anxiety, and suicidal ideation). Specifically, this study aimed to assess whether the stigma associated with confirmed COVID-19 patients acts as a significant moderating factor in the relationship between loneliness, and mental health problems.


Sample and design

This study was conducted as part of the COVID-19 Mental Health Panel Survey of the general public. The residents of the 180 sample households that were randomly selected using a probability sampling technique during the general public survey introduced acquaintances with a history of COVID-19 to the researcher. Additionally, the examination was conducted after recruiting participants with prior COVID-19 infection experience by investigating potential participants through confirmed mass infection cases. This method was employed because the COVID-19 confirmation rate in Korea at the time of the survey was low (approximately 0.8%), making it impossible to recruit participants using a probability sampling technique. The investigation was conducted by recruiting participants corresponding to each cell of the sex and age distribution tables. The age range of the participants was 15–79 years. A row with a sufficient number of assigned subjects was skipped. Among the remaining rows, the respondents with the earliest table allocation orders were investigated. The composition ratio of the sample from each group (region, sex, and age) and the population composition ratio were corrected to match, and the final standardized weight for each group was calculated and applied.

This survey was conducted for approximately 12 weeks, from September 8 to November 29, 2021. In total, 640 questionnaires were completed. On September 6, 2021, surveyor training was conducted for 126 surveyors nationwide. Collective sessions or individual video training sessions were conducted considering the social distancing measures in each region (seven regions) due to the spread of COVID-19. The training included an introduction to the overall survey, an explanation of the survey process, survey table education, computer-assisted personal interview education, and practical classes. After training, a test was conducted to check the investigators’ understanding of the educational content, and retraining was conducted for questions with a high rate of wrong answers.


To evaluate suicidal ideation, participants were asked whether they had seriously considered suicide since the occurrence of COVID-19, with options of yes or no. Depression and anxiety scores were measured using the PHQ-9 (total score of 27) [32] and the Generalized Anxiety Disorder Questionnaire-7 (GAD-7, total score of 21) [33], respectively, with consideration of the group of individuals with a cutoff score of 10 or higher as the high-risk group.

Demographic characteristics of the patients, including sex, age, marital status, educational status, employment status, family income, and region, were collected. Sex was categorized as male or female. Age was categorized into five groups: 15–29, 30–39, 40–49, 50–59, and 60–79 years. Marital status was divided into three categories: married, not living with a partner (divorced, separated, or widowed), and unmarried. Educational status was divided into two categories: high school graduation or lower and college graduation or higher. Employment status was categorized as employed or unemployed. Family income was categorized into four categories (million won): 1.5 or lower, 1.5–2.99, 3–4.99, 5 million or more.

Data regarding the timing of COVID-19 confirmation and its severity (i.e., asymptomatic, mild, and moderate to severe) were also collected. COVID-19 vaccination experience was assessed using a yes or no response. Health satisfaction was assessed using a Likert scale ranging from 0 (very satisfied) to 10 (very dissatisfied) in response to the question, “How satisfied are you with your personal health since the onset of COVID-19?” Fatigue was evaluated using the Chronic Fatigue Scale (CFS-K, total score of 33) [34]. Sleep quality was assessed using the Korean version of the Pittsburgh Sleep Quality Index (PSQI-K, total score of 21) [35], with higher scores indicating poorer sleep quality.

In terms of loneliness experienced in the past month, participants responded to four items on a scale of 1 (not at all) to 4 (very much): 1) “I feel lonely”, 2) “I feel isolated”, 3) “I can rely on family or friends for comfort”, and 4) “I have someone who can help with my daily routine.” The scores for items (3, 4) were reversed, and the sum of the responses for items 1) to 4) was calculated as the loneliness score [36].

For stigma related to COVID-19 confirmation, participants responded on a 1 (not at all) to 4 (very much) scale to eight items: 1) “I feel isolated from the world since knowing I am infected”, 2) “It is risky to tell others that I am infected”, 3) “I worry that people will blame me when they know I am a confirmed case”, 4) “Most of the infected people are criticized by people around them”, 5) “I try to hide the fact that I am infected”, 6) “Most people feel uncomfortable when there is an infected person around them”, 7) “I was hurt because of people’s reactions when they found out that I am infected with COVID-19”, and 8) “I am ashamed that I am infected.” The total score was used as the “stigma score” [37].

Ethics statement

This study was approved by the Institutional Review Board of the National Center for Mental Health Institutional Review Board (IRB No.116271-2021-30). Before the interview, each respondent was informed of the objectives and methods of the survey. Each respondent signed an informed consent form collected through a tablet.

Statistical analyses

Descriptive statistics were used to identify the demographic characteristics of the participants, including means and standard deviations, to examine the frequencies and percentages of the variables. Differences and relationships in suicidal ideation, anxiety, and depression according to the participants’ characteristics were analyzed using an independent t-test for continuous variables and a chi-squared test for categorical variables. Logistic regression analysis was performed to identify factors affecting suicidal ideation, anxiety, and depression after the COVID-19 infection. The adjusted odds ratio (OR) was calculated by correcting for demographic, health-related, and psychological variables that appeared to be significantly different between the groups. T-test and one-way analysis of variance were used to examine the group differences in stigma scores among the respondents based on demographic variables like sex, age, and vaccination status. All statistical analyses were performed using SPSS version 21.0 for Windows (IBM Corp., Armonk, NY, USA), and the statistical significance level was set at p<0.05.

The PROCESS macro (version 4.3) proposed by Hayes was used to specifically investigate the moderating effects of stigma on the relationship between loneliness and mental health problems (i.e., suicidal ideation, depression, and anxiety) and the related conditional effects. To reduce multicollinearity issues in the analysis of moderating effects, mean centering was applied to the independent (loneliness scale) and moderator (stigma score) variables before creating interaction terms, which were then generated using mean-centered values. The conditional effects of independent variables on dependent variables were calculated. To test these effects, a simple slope analysis using the pick-a-point approach was employed. The statistical significance of the moderating effects was tested using bootstrapping with 5,000 bootstrap samples, and Process Macro Model 1 was applied. This analytical approach utilizing the PROCESS macro aims to provide a detailed understanding of the moderating effect of stigma on the relationships between loneliness and mental health outcomes such as suicidal ideation, depression, and anxiety, along with an examination of the conditional effects of these interactions.


The demographic and sociological characteristics of the patients are presented in Table 1. Among the participants in this study, 50.3% were male and 49.7% were female. Participants aged 60–79 years old accounted for 27.2%, those aged 50–59 years old made up 20.0%, and those aged 40–49 years old represented 16.9%. A majority of 68.3% were from Seoul/Incheon/Gyeonggi/Gangwon, followed by 10.2% from Daegu/Gyeongbuk, 9.4% from Busan/Ulsan/Gyeongnam, 6.8% from Daejeon/Chungcheong/Sejong, and 5.4% from Gwangju/Jeonra/Jeju. Participants with a college degree or higher constituted 40.9% and those with a high school education or lower accounted for 59.1%. Employed participants made up 67.7% of the sample. Most confirmed COVID-19 cases occurred in the second half of 2021 at 47.2%, followed by 39.0% in the first half of 2021, and 13.8% in 2020. Symptom severity was mild or showed abnormalities in 68.9% of cases, with 31.1% being asymptomatic.

Demographic and clinical characteristics of confirmed COVID-19 respondents (N=640)

A total of 8.0% and 10.0% of participants were at risk for anxiety and depression, respectively. Overall, 3% of participants reported serious consideration of suicide after the onset of COVID-19.

Regarding experiences of stigma due to COVID-19, out of a total of 4 points, the three highest scores with their corresponding items were 2.82 points: “people are uncomfortable with the fact that there are confirmed patients around”, 2.58 points: “I think I am out of touch with the world”, and 2.55: “I am worried that people will blame me if I get COVID-19.” Stigma scores were significantly higher in females (male vs. female: 18.72 vs. 20.11, t=3.08, p<0.002) and unvaccinated individuals (vaccinated vs. unvaccinated: 15.59 vs. 18.13, t=2.14, p<0.033) but lower in respondents diagnosed during the second half of 2021 (2020 vs. first half of 2021 vs. second half of 2021: 20.29 vs. 20.98 vs. 17.86, F=22.75, p<0.001). Additionally, differences in stigma levels were observed across different family income brackets (Table 2).

Stigma scores of confirmed COVID-19 respondents (total score of 32)

Suicidal ideation was higher among individuals with a college degree, a monthly household income below 1.5 million won, and those who had not received the COVID-19 vaccine, reporting lower health satisfaction, poor sleep quality, higher fatigue, and increased loneliness than the control group (Supplementary Table 1 in the online-only Data Supplement). Logistic regression analysis using suicidal ideation as the outcome variable and significant variables identified through chi-squared and independent sample t-tests revealed that higher PSQI-K scores (indicating lower sleep quality) (p=0.007, OR: 1.32, 95% confidence interval [CI] 1.08–1.62), higher loneliness scores (p=0.006, OR: 1.38 [95% CI 1.10–1.75]), and lower post-COVID-19 health satisfaction (p=0.037, OR: 1.39 [95% CI 1.02–1.90]) were associated with an increased risk of suicidal ideation. Moreover, individuals with a college degree or higher (p=0.018, OR: 5.42 [95% CI 1.33–22.07]) showed a higher risk of suicidal ideation (Table 3).

Binary logistic regression for suicidal ideation among confirmed COVID-19 patients

Individuals at risk for anxiety were more likely to be unemployed or have a monthly household income below 1.5 million won, reporting lower health satisfaction, poor sleep quality, higher fatigue, increased stigma perception, and a greater feeling of loneliness than the control group (Supplementary Table 2 in the online-only Data Supplement). Logistic regression analysis indicated that higher fatigue (p<0.001, OR: 1.14 [95% CI 1.06–1.21]), increased stigma perception (p=0.013, OR: 1.08 [95% CI 1.02–1.16]), and increased feeling of loneliness (p=0.018, OR: 1.16 [95% CI 1.03–1.31]) were associated with an increased risk of anxiety. Unemployment (p=0.025, OR: 2.22 [95% CI 1.11–4.46]) was also linked to a higher risk of anxiety (Table 4).

Binary logistic regression for anxiety high-risk groups among confirmed COVID-19 patients

The at-risk group for depression included more unemployed individuals, those with a college degree, those with a monthly household income below 1.5 million won, and those who had not received the COVID-19 vaccine and reported lower health satisfaction, poor sleep quality, higher fatigue, increased stigma perception, and a greater feeling of loneliness than the control group (Supplementary Table 3 in the online-only Data Supplement). Logistic regression analysis revealed that higher PSQI-K scores (indicating lower sleep quality) (p=0.048, OR: 1.13 [95% CI 1.00–1.26]), higher fatigue (p=0.006, OR: 1.09 [95% CI 1.03–1.17]), increased stigma perception (p= 0.001, OR: 1.11 [95% CI 1.04–1.18]), and higher loneliness scores (p<0.001, OR: 1.30 [95% CI 1.16–1.47]) were associated with an increased risk of depression. Being unemployed (p=0.040, OR: 2.02 [95% CI 1.03–3.96]), having a college degree or higher (p=0.047, OR: 1.95 [95% CI 1.01–3.76]), and not receiving the vaccine (p=0.010, OR: 2.92 [95% CI 1.30–6.55]) were also linked to a higher risk of depression (Table 5).

Binary logistic regression for depression high-risk groups among confirmed COVID-19 patients

In our investigation of the moderating effect of stigma on the relationship between loneliness and mental health problems, we observed that stigma positively impacted depression and anxiety. Stigma acted as a significant moderating factor for loneliness and mental health problems, with a larger effect size associated with higher stigma perception (Figures 1 and 2).

Figure 1.

Moderating effect of stigma on the relationship between loneliness and suicidal ideation, anxiety, and depression. **p<0.01; ***p<0.001.

Figure 2.

Interaction between loneliness and suicidal ideation, anxiety, and depression. GAD-7, Anxiety Disorder Questionnaire-7; PHQ-9, Patient Health Questionnaire-9.


Novel infectious diseases such as COVID-19 impact individuals and society, leading to anxiety, stress, and stigmatization [38]. According to related studies, the prevalence of mental illnesses, including anxiety, depression, and stress, during the COVID-19 pandemic was found to be 26%–30% [39]. One of the main reasons for this psychological distress was the uncertainty surrounding novel infectious diseases, such as COVID-19, including factors such as the nature of the disease, progression, prognosis, and mortality, which remain unknown [40]. Uncertainty is a crucial cognitive process that triggers arousal and emotional reactions and serves as a major cause of various mental diseases, such as anxiety and depression [41].

This study assessed anxiety, depression, and suicidal ideation in individuals infected during the early stages of the COVID-19 pandemic. In summary, the risk of mental health issues was higher among the unemployed and individuals with a college degree. Low satisfaction with health and poor sleep quality increase the risk of suicidal ideation. In addition, high levels of fatigue and COVID-19-related stigma are linked to an increased risk of depression and anxiety. Loneliness was significantly associated with suicidal ideation, depression, and anxiety.

While previous studies have reported inconsistent results regarding the relationship between mental health, sex, and age during the COVID-19 pandemic [42-44], this study confirmed that sex and age were unrelated to mental health. Lower socioeconomic status (SES) has long been associated with an increased risk of poor mental health [45]. Across countries, the mental health of the unemployed and of those experiencing financial insecurity is worse than that of the general population [46]. In the United Kingdom, anxiety scores were measured continuously for 20 weeks from the onset of the first lockdown in March 2020, and higher anxiety scores were consistently reported among people with lower education or lower income [47]. However, trends in changing mental health status and SES were inconsistent across all populations. For example, in the United States, a survey in April 2020 found that people with higher SES (educational attainment and household income) reported sharper declines in life satisfaction and greater increases in depressive symptoms than those with lower SES, compared to the survey results in 2019 [46]. In this study, we found that individuals who reported unemployment and a low household income exhibited higher rates of suicidal ideation, depression, and anxiety. Additionally, a higher risk of mental health issues has been identified among those with higher levels of education, particularly college graduates.

A significant association was observed between poor sleep quality, suicidal ideation, and depression, which is consistent with previous research. During the acute phase of infection, physical and mental stress can trigger the release of proinflammatory cytokines, which may disrupt the metabolism and cardiovascular function related to sleep [48]. Sleep problems can impair emotional and attentional regulation and lead to hypersensitivity and concentration problems [49].

The association between high fatigue levels and anxiety and depression was consistent with that found in previous studies. Fatigue is known as a major sequela in COVID-19 survivors [50], and according to a study that followed up with COVID-19 survivors for one year, fatigue was not significantly associated with the severity of clinical symptoms of COVID-19 but showed a higher association with psychopathological symptoms [51].

Loneliness and social isolation have been associated with depression, anxiety, and suicidal ideation. It is a distressing emotion stemming from the gap between desired and actual social relationships [17]. According to previous studies conducted in the early period of COVID-19, individuals who experienced significant loneliness due to a lack of social support and social isolation were more vulnerable to mental disorders [52-54].

Stigma was associated with anxiety and depression, and further analysis revealed that stigma acted as a moderating factor in the relationship between loneliness and mental health problems. The COVID-19 pandemic has provoked stigmatization and discriminatory behavior against people who have or might have COVID-19 [55].

In this study, females, unvaccinated individuals, and respondents diagnosed with COVID-19 before the first half of 2021 showed notably higher stigma scores. Females are considered to be at a higher risk of “long-COVID” syndrome compared to males, experiencing more severe physical and psychological symptoms from SARS-CoV-2 infection [56], potentially impairing their abilities to cope with stigma [57]. High levels of stigma in unvaccinated individuals could be attributed to the prevailing discriminatory social attitudes towards people who have not received the COVID-19 vaccine. Previous literature has indicated that vaccinated individuals express negative sentiments and prejudices toward the unvaccinated, manifesting as exclusion from social interactions and deprivation of support for political rights (e.g., vaccine passports) [58]. These sentiments arise from the perception that unvaccinated individuals bear greater responsibility and culpability for undermining public health efforts and prolonging the pandemic. Such faulting tendencies are particularly pronounced in societies that strongly emphasize collective norms [59]. Meanwhile, our findings indicate a substantial decline in stigma levels toward individuals infected during the latter half of 2021 compared to those infected in the early wave of the COVID-19 pandemic; this was consistent with prior research [60,61]. This decline in discriminatory behavior may be attributed to the accumulation of knowledge about COVID-19 over time and its dissemination among the general population, resulting in a less stigmatizing social environment [62].

Stigma impacts health-related outcomes, not only as a barrier to receiving timely diagnosis and appropriate treatment but also as an important variable that increases mental health disorders such as anxiety and depression [63]. The impact of stigma can be long-term, affecting a person beyond the acute phase of illness, even after they are no longer symptomatic [64]. This study confirms that reducing stigma can mitigate the negative impact of loneliness on mental health. Stigma has been associated with many infections, such as human immunodeficiency virus (HIV), severe acute respiratory syndrome (SARS), and the Ebola virus, and it has been observed that disease-related stigma decreases with appropriate interventions [65]. For example, information-based strategies can be used to reduce negative attitudes and perceived stigma within communities [64]. The intervention for HIV-related stigma highlights the effectiveness of implementing anti-stigmatizing campaigns [60] utilizing unifying symbols such as the globally recognized red ribbon, and fostering community activities as effective measures [53]. The red ribbon is a powerful symbol of HIV/AIDS awareness, care, empathy, and support globally [63].

Early media reports on infectious disease outbreaks in vulnerable settings such as specific religious groups and mental health facilities, including the expression of stigma, have been found to contribute to the formation of critical public opinion towards infected individuals. This, in turn, results in enduring social and psychological disadvantages for survivors and their families even after recovery [15,66]. The choice of language and metaphors is critical for de-stigmatizing efforts [67,68]. The WHO has issued guidelines aimed at preventing COVID-19-related stigma, emphasizing the importance of use of restricted language to avoid stigma propagation and dissemination of inaccurate information by individuals, media, and governments [55]. Considering that stigma is time- and context-specific [69], it is expected that changes in circumstances, such as increased vaccine availability, a drastic increase in COVID-19 cases, and shifts in symptomatology due to viral mutations, may influence the extent of stigma. Therefore, subsequent research should re-examine the changes in stigma and their association with mental health in light of these evolving circumstances.


In this study, a random sampling method was employed among the general population to find individuals with COVID-19 experience. Residents from 180 selected census tracts were approached, and households were asked to introduce acquaintances who were confirmed COVID-19 patients. Additionally, recruitment involved investigating subjects through those who were part of group infections and utilizing the personal networks of the surveyors. Therefore, there may be limitations to the representativeness of the sample constructed using non-probability sampling.

Furthermore, during the early stages of the COVID-19 pandemic, infections occurred in densely populated groups of socially underprivileged individuals, such as those in mental hospitals and nursing homes. Infections in specific religious communities have also been reported. These incidents likely influenced not only demographic characteristics but also the social stigma and discrimination associated with them.

Considering potential variations in the rate of confirmed cases, the occurrence of viral variants, and changes in social stigma, assessing the degree of anxiety, depression, and suicidal ideation in relation to the different phases of the pandemic has become crucial.

Furthermore, as a cross-sectional design does not allow the establishment of causation between independent and dependent variables, a prospective longitudinal study is needed to gain deeper insights into these relationships.


This study sought to identify factors influencing suicidal ideation, anxiety, and depression among individuals who received a confirmed COVID-19 diagnosis during the initial phases of the pandemic from 2020 to 2021.

The research findings revealed that unemployed and college-graduate confirmed COVID-19 patients were at a higher risk for mental health issues. Lower levels of health satisfaction and poor sleep quality were associated with an increased risk of suicidal ideation. Moreover, heightened fatigue and perception of stigma due to COVID-19 were specifically linked to an elevated risk of depression and anxiety.

Loneliness is significantly correlated with suicidal thoughts, depression, and anxiety. Furthermore, stigma has emerged as a notable moderating factor in the relationship between loneliness, and mental health problems.

Supplementary Materials

The online-only Data Supplement is available with this article at

Supplementary Table 1.

Characteristics of suicidal ideation among confirmed COVID-19 patients

Supplementary Table 2.

Characteristics of anxiety high-risk groups among confirmed COVID-19 patients

Supplementary Table 3.

Characteristics of depression high-risk groups among confirmed COVID-19 patients



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

Subin Park, a contributing editor of the Psychiatry Investigation, was not involved in the editorial evaluation or decision to publish this article. All remaining authors have declared no conflicts of interest.

Author Contributions

Conceptualization: Subin Park, Donghui Park. Data curation: Subin Park, Donghui Park. Formal analysis: Donghui Park, Subin Park. Funding acquisition: Subin Park. Investigation: Donghui Park, Subin Park. Methodology: Donghui Park, Subin Park. Project administration: Subin Park. Resources: Subin Park. Software: Donghui Park, Subin Park. Supervision: Subin Park. Validation: Donghui Park, Subin Park. Visualization: Donghui Park, Subin Park. Writing—original draft: Donghui Park. Writing—review & editing: Subin Park.

Funding Statement

This research was funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI22C1156).




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Article information Continued

Figure 1.

Moderating effect of stigma on the relationship between loneliness and suicidal ideation, anxiety, and depression. **p<0.01; ***p<0.001.

Figure 2.

Interaction between loneliness and suicidal ideation, anxiety, and depression. GAD-7, Anxiety Disorder Questionnaire-7; PHQ-9, Patient Health Questionnaire-9.

Table 1.

Demographic and clinical characteristics of confirmed COVID-19 respondents (N=640)

Variables Weighted value
 Male 322 (50.3)
 Female 318 (49.7)
Age (yr)
 15–29 132 (20.6)
 30–39 98 (15.3)
 40–49 108 (16.9)
 50–59 128 (20.0)
 60–79 174 (27.2)
 Seoul/Incheon/Gyeonggi/Gangwon 437 (68.3)
 Daegu/Gyeongbuk 65 (10.2)
 Busan/Ulsan/Gyeongnam 60 (9.4)
 Daejeon/Chungcheong/Sejong 43 (6.8)
 Gwangju/Jeonra/Jeju 35 (5.4)
Marital status
 Unmarried 206 (32.2)
 Married 346 (54.1)
 Divorced/separated/widowed 88 (13.8)
Educational status
 High school graduation or lower 378 (59.1)
 College graduation or higher 262 (40.9)
Employment status
 Employed 433 (67.7)
 Unemployed 207 (32.3)
Family income (million won)
 <1.5 61 (9.5)
 1.5–2.99 161 (25.1)
 3–4.99 186 (29.1)
 ≥5 232 (36.3)
Timing of COVID-19 confirmation
 Year of 2020 88 (13.8)
 First half of 2021 (January–June) 249 (39.0)
 Second half of 2021 (July–December) 302 (47.2)
Symptom severity
 Asymptomatic 199 (31.1)
 Mild 406 (63.3)
 Moderate to severe 36 (5.6)
COVID-19 vaccination (yes) 559 (87.3)
Suicidal ideation positive groups 19 (3.0)
Anxiety high-risk groups 51 (8.0)
Depression high-risk groups 64 (10.0)

Values are presented as number (%). COVID-19, coronavirus disease-2019

Table 2.

Stigma scores of confirmed COVID-19 respondents (total score of 32)

Variables Stigma index t-value F p Post-hoc (Scheffe)
Sex 3.08 0.002
 Male 18.72±5.68
 Female 20.11±5.75
Age (yr) 1.09 0.360
 15–29 19.20±6.04
 30–39 19.13±5.14
 40–49 19.82±4.97
 50–59 18.73±6.08
 60–79 19.97±6.05
Marital status 0.88 0.414
 Unmarried 19.26±5.72
 Married 19.65±5.59
 Divorced/separated/widowed 18.79±6.46
Educational status 1.07 0.284
 High school graduation or lower 19.20±5.96
 College graduation or higher 19.70±5.44
Employment status 0.53 0.598
 Employed 19.32±5.55
 Unemployed 19.59±6.18
Family Income (million won) 2.81 0.039 d<b
 <1.5a 19.12±6.75
 1.5–2.99b 20.48±5.57
 3–4.99c 19.32±5.75
 ≥5d 18.81±5.53
Timing of COVID-19 confirmation 22.75 <0.001 c<a, b
 Year of 2020a 20.29±5.62
 First half of 2021 (January–June)b 20.98±5.43
 Second half of 2021 (July–December)c 17.86±5.67
Symptom severity 2.16 0.117
 Asymptomatic 18.84±6.05
 Mild 19.56±5.64
 Moderate to severe 20.79±5.22
COVID-19 vaccination 2.14 0.033
 Yes 15.59±5.78
 No 18.13±5.42

Values are presented as mean±standard deviation unless otherwise indicated. COVID-19, coronavirus disease-2019

Table 3.

Binary logistic regression for suicidal ideation among confirmed COVID-19 patients

B SE Wald df p OR 95% CI
Sex 0.01 0.66 0.00 1 0.993 1.01 0.28–3.64
Age (yr) 0.03 0.02 1.54 1 0.215 1.03 0.98–1.08
Educational status 1.69 0.72 5.57 1 0.018 5.42 1.33–22.07
Employment status -0.99 0.84 1.40 1 0.236 0.37 0.07–1.91
COVID-19 vaccination 1.18 0.71 2.79 1 0.095 3.25 0.82–12.95
Family income (million won)
 <1.5 1.21 1.21 1.00 1 0.317 3.37 0.31–36.37
 3–4.99 0.17 0.98 0.03 1 0.861 1.19 0.18–8.01
 ≥5 0.61 0.91 0.44 1 0.508 1.83 0.31–10.95
Health satisfaction of COVID-19 survivors 0.33 0.16 4.34 1 0.037 1.39 1.02–1.90
PSQI-K 0.28 0.10 7.23 1 0.007 1.32 1.08–1.62
CFS-K 0.06 0.06 0.92 1 0.337 1.06 0.95–1.18
Loneliness index 0.33 0.12 7.56 1 0.006 1.38 1.10–1.75
Constants -13.11 2.24 34.30 1 <0.001 0.00

Reference group: male, high school graduate or lower, employed, COVID-19 vaccinated person, family income (million won) 1.5–2.99. COVID-19, coronavirus disease-2019; SE, standard error; OR, odds ratio; CI, confidence interval; PSQI-K, Pittsburgh Sleep Quality Index (total score 21); CFS-K, Chronic Fatigue Scale (total score 33)

Table 4.

Binary logistic regression for anxiety high-risk groups among confirmed COVID-19 patients

B SE Wald df p OR 95% CI
Sex -0.13 0.35 0.13 1 0.714 0.88 0.45–1.74
Age (yr) 0.02 0.01 1.91 1 0.167 1.02 0.99–1.04
Employment status 0.80 0.36 5.06 1 0.025 2.22 1.11–4.46
Family income (million won)
 <1.5 -0.71 0.06 1.40 1 0.236 0.50 0.15–1.60
 3–4.99 -1.22 0.06 4.15 1 0.042 0.30 0.09–0.96
 ≥5 0.61 0.41 2.24 1 0.135 1.84 0.83–4.08
Health satisfaction of COVID-19 survivors 0.09 0.08 1.25 1 0.263 1.09 0.94–1.26
PSQI-K 0.08 0.06 1.78 1 0.183 1.08 0.96–1.22
CFS-K 0.13 0.03 13.79 1 <0.001 1.14 1.06–1.21
Stigma index 0.08 0.03 6.20 1 0.013 1.08 1.02–1.16
Loneliness index 0.15 0.06 5.60 1 0.018 1.16 1.03–1.31
Constants -8.70 1.22 51.15 1 <0.001 0.00

Reference group: male, high school graduate or lower, employed, COVID-19 vaccinated person, family income (million won) 1.5–2.99. COVID-19, coronavirus disease-2019; SE, standard error; OR, odds ratio; CI, confidence interval; PSQI-K, Pittsburgh Sleep Quality Index (total score 21); CFS-K, Chronic Fatigue Scale (total score 33)

Table 5.

Binary logistic regression for depression high-risk groups among confirmed COVID-19 patients

B SE Wald df p OR 95% CI
Sex -0.31 0.32 0.89 1 0.345 0.74 0.39–1.39
Age (yr) -0.01 0.01 1.76 1 0.184 0.99 0.97–1.01
Educational status 0.67 0.34 3.94 1 0.047 1.95 1.01–3.76
Employment status 0.70 0.34 4.21 1 0.040 2.02 1.03–3.96
COVID-19 vaccination 1.07 0.41 6.72 1 0.010 2.92 1.30–6.55
Family income (million won)
 <1.5 -0.05 0.59 0.01 1 0.938 0.96 0.30–3.01
 3–4.99 -1.29 0.57 5.14 1 0.023 0.28 0.09–0.84
 ≥5 0.40 0.38 1.10 1 0.094 1.50 0.71–3.18
Health satisfaction of COVID-19 survivors 0.02 0.07 0.10 1 0.757 1.02 0.89–1.17
PSQI-K 0.12 0.06 3.92 1 0.048 1.13 1.00–1.26
CFS-K 0.09 0.03 7.49 1 0.006 1.09 1.03–1.17
Stigma index 0.10 0.03 10.25 1 0.001 1.11 1.04–1.18
Loneliness index 0.27 0.06 19.32 1 <0.001 1.30 1.16–1.47
Constants -7.87 1.07 53.99 1 <0.001 0.00

Reference group: male, high school graduate or lower, employed, COVID-19 vaccinated person, family income (million won) 1.5–2.99. COVID-19, coronavirus disease-2019; SE, standard error; OR, odds ratio; CI, confidence interval; PSQI-K, Pittsburgh Sleep Quality Index (total score 21); CFS-K, Chronic Fatigue Scale (total score 33)