³Division of Biostatistics, Department of Academic Research, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea

⁴Workplace Mental Health Institute, Kangbuk Samsung Hospital, Seoul, Republic of Korea

⁵Media Real Research Korea Co., Ltd., Seoul, Republic of Korea

Correspondence: Sung Joon Cho, MD, PhD Department of Psychiatry, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, 29 Saemunan-ro, Jongno-gu, Seoul 03181, Republic of Korea Tel: +82-2 2001-2214, Fax: +82-2-2001-2211, E-mail: sungjoon.cho@samsung.com

Correspondence: Sang-Won Jeon, MD, PhD Department of Psychiatry, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, 29 Saemunan-ro, Jongno-gu, Seoul 03181, Republic of Korea Tel: +82-2-2001-2214, Fax: +82-2-2001-2211, E-mail: swj.jeon@samsung.com

*These authors contributed equally to this work.

Received 2024 May 2; Revised 2024 July 2; Accepted 2024 August 5.

Abstract

Objective

This study aimed to examine the psychiatric impact of the Seoul Halloween crowd crush on individuals related to the victims compared to the general population. It also explores the moderating effect of resilience on the relationship between trauma exposure and psychiatric symptoms.

Methods

In total, 2,220 participants completed various post-incident questionnaires (Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, Hwa-byung symptom scale, post-traumatic stress disorder checklist for DSM-5, and Brief Resilience Scale) 30 days after the incident. Moderation analyses were conducted using the PROCESS macro in the statistical package for the social sciences.

Results

Individuals related to the victims exhibited higher symptom severity and a greater risk for clinically significant levels of depression, anxiety, anger, and post-traumatic stress disorder (PTSD) (odds ratio=3.28, 3.33, 1.51, and 4.39 respectively). The impact of relevance to victims on anxiety and PTSD symptoms was moderated by resilience, with a stronger effect observed for individuals with low resilience (β=3.51, 95% confidence interval [CI] 2.78–4.24 for anxiety and β=14.53, 95% CI 12.43–16.63 for PTSD) than for those with high resilience (β=1.69, 95% CI 0.72–2.65 for anxiety and β=8.33, 95% CI 5.56–11.09 for PTSD).

Conclusion

When related to the victims, it was found that not only PTSD, but also depression, anxiety, and anger could intensify. Resilience emerged as a potential buffer against these adverse effects, emphasizing its significance in mitigating the psychiatric impact of community trauma.

Keywords: Post-traumatic stress disorders; Community psychiatry; Anxiety disorder; Mood disorder

INTRODUCTION

On October 29, 2022, a tragic crowd crush in Seoul’s Itaewon district during a Halloween festival resulted in 159 deaths and more than 200 injuries [1]. Many young attendees lost their lives in this mass traumatic incident that occurred in a public alley. The scenes were recorded and widely shared on social media, causing a profound emotional impact nationwide. Traditionally, trauma involves direct confrontation with death [2], however, the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) [3] includes indirect exposure, such as learning about the event happening to a loved one. With media advancements and social media, research indicates a broader impact of traumatic events. Prior research [4-6] indicates that traumatic events impact the mental health of local or national populations, termed “community trauma,” affecting many or having broader social consequences [7]. While studies [8-10] suggest that indirectly affected individuals typically recover quickly without progressing to post-traumatic stress disorder (PTSD), survivors, direct witnesses, professionals in related fields, and family members of victims often experience prolonged mental health deterioration [11,12].

Previous epidemiological studies confirmed that symptoms of PTSD can coexist and potentially intensify symptoms of depression and anxiety [7,8]. Other studies noted that individuals associated with victims experience distress in the form of anxiety-related symptoms, even if they did not directly experience the trauma [13-15]. Embitterment, described in the cultural context of South Korea as Hwa-byung, is highlighted in the aftermath of the Seoul ferry accident. According to a study [16] conducted on individuals associated with the victims of the Seoul ferry accident, embitterment increases up to 1 year after the incident, and the tendency thereof influences other psychiatric symptoms. Many survivors of trauma and individuals related to the victims often experience significant deterioration in their mental health. These changes persist for an extended period.

Most people experience traumatic events [17,18], with 50%–84% of the general population expected to encounter at least one [19,20]. While traumatic events can lead to diverse psychiatric symptoms, most individuals demonstrate resilience, the ability to adapt and maintain mental well-being despite adversity [21]. Bonanno categorizes responses to trauma, noting that following a traumatic event, some recover after initial mental health decline, others deteriorate gradually or persistently, and some sustain mental well-being throughout [18]. Resilience is defined as the ability to maintain stable and healthy levels of psychological and physiological functioning despite disruptive events, with resilient individuals returning to normal functioning and positive experiences over time. Resilience refers to a buffer that facilitates recovery amid adversity. It is a dynamic process acquired throughout one’s lifetime, not an inherent trait. Previous research [22] demonstrated resilience as a significant protective factor for the mental health of survivors in the aftermath of disasters: significantly lower levels of depression and PTSD symptoms were found in groups with high resilience. Another study [23] revealed that the depressive symptoms of individuals who experienced childhood abuse or trauma were moderated by resilience. Enhancing resilience through individual interventions or social support reduces PTSD and psychological distress after trauma exposure. However, research on whether resilience prevents the deterioration of mental health when a given community is exposed to the same community trauma remains insufficient.

Thus, in the context of community trauma, this study aims to examine the differences in psychiatric distress experienced between individuals related to victims and the general population. In addition, the research investigates whether resilience can serve as a protective factor for the mental health of those related to victims. Hence, this study sought to investigate these mechanisms as the conceptual framework (Figure 1). Two hypotheses were formulated: 1) individuals related to victim experience greater psychiatric distress than the general population in the aftermath of community trauma. 2) Resilience has a moderating effect on the mental health of individuals related to victims. The study will contribute insights for the development of policies and therapeutic strategies related to community trauma.

Figure 1.

Conceptual framework. PTSD, post-traumatic stress disorder.

METHODS

Participants

A survey was administered via a mobile application that allowed participants to guide their own responses, with the aim of evaluating psychiatric distress in the aftermath of the Seoul Halloween crowd crush. Data were gathered between November 30 and December 1, 2022, 32 to 33 days after the incident, which is during the PTSD period. Push notifications were sent to 41,000 individuals registered on a research panel who used smartphones or tablets. Of these, 2,792 people willingly participated in the survey. To ensure a representative sample of South Korean adults, we used quota allocation sampling based on the September to November 2022 National Resident Registration Demographics considering age, gender, and regional distribution. Participants were chosen to match these demographics. We then removed participants as each quota was met based on response time order, yielding 2,300 participants. After excluding those unaware of the incident, 2,220 participants were included in the final analysis (Supplementary Figure 1). Participants’ identities were encrypted during data collection. They completed a self-reported written questionnaire via a mobile app. Successful participants received an incentive in the form of TNC coin cryptocurrency.

The study protocols were granted approval by the Institutional Review Board of Kangbuk Samsung Hospital and were conducted in accordance with the most recent iteration of the Declaration of Helsinki and the principles of Good Clinical Practice (Approval number: KBSMC 2023-01-016). The waiver of the informed consent requirement was justified due to the utilization of solely de-identified data.

Covariables and outcomes

We obtained data regarding age, gender, and region of residence. In addition, we collected information on participants’ relevance to the victims. Participants were asked whether they were close friends, colleagues, acquaintances of the Seoul Halloween crowd crush victims, family members or relatives of the victims, survivors of the incident, direct witnesses of the incident, or if none of these applied to them. Those who selected any of the options other than “none of these” were classified as relevant/witness, while those who selected “none of these” were classified as not relevant.

After the incident, the severity of participants’ experiences of depression, anxiety, anger, and PTSD symptoms was measured using brief self-report questionnaires. To evaluate the severity of depression, the Patient Health Questionnaire-9 (PHQ-9) [24] was used. The scale consists of 9 questions measured on a 4-point Likert scale, with higher scores indicating more severe symptoms. The cutoff point for screening major depressive disorder is 10 [25]. Cronbach’s alpha was 0.908. The Generalized Anxiety Disorder-7 (GAD-7) [26], a 7-item questionnaire measured on a 4-point Likert scale, was used to evaluate participants’ anxiety level. Higher scores indicate higher levels of anxiety and worry. A cutoff score of 10 was used as a threshold to indicate a clinically significant level of anxiety [27]. Cronbach’s alpha was 0.943. In this study, the severity of anger was measured using the Hwa-byung symptom scale [28,29]. Hwa-byung, a culture-related syndrome linked to Korea’s distinct socio-cultural environment, refers to various clinical manifestations marked by explosive outbursts arising from suppressed feelings of injustice. The 15-item self-report Hwa-byung symptom scale was measured on 5-point Likert scale, where a higher score indicates a greater intensity of angry feelings. A score of 30 is clinically useful as a cutoff score. Cronbach’s alpha was 0.963. The post-traumatic stress disorder checklist for DSM-5 (PCL-5) [30] is a 20-item self-report measure assessing the DSM-5 symptoms of PTSD. The scale uses a 5-point Likert scale, with higher scores indicating a higher severity of PTSD. The cutoff point for screening PTSD was 33 [31]. Cronbach’s alpha was 0.969.

The level of resilience was measured by the Brief Resilience Scale (BRS) [32], a 6-item self-report questionnaire measured on a 5-point Likert scale. A higher BRS score indicates that the respondent is more resilient. Cronbach’s alpha for the BRS was 0.787.

Statistical analysis

Quota allocation sampling stratified by age, gender, and area of residence ensured national representativeness. In accordance with the National Standards for Election Opinion Polling of South Korea [33], we further verified the national representativeness of the sample and met the criteria of having more than 1,000 participants.

Frequency analysis and descriptive statistics were used to examine participants’ characteristics. Correlation analyses of resilience and psychiatric symptoms were performed. Furthermore, chi-squared tests and an independent t-test were employed to compare the covariates between participants who were relevant to the victims and those who were not. An analysis of covariance and post-hoc Bonferroni test adjusted for potential confounders (age, gender, and area of residence) were used to compare the psychiatric distress between participants who were relevant and not relevant to victims. Crude and adjusted odds ratios with 95% confidence intervals (CIs) were used to estimate the association between relevance to victims and psychiatric symptoms such as depression (PHQ-9 ≥10), anxiety (GAD-7 ≥10), anger (Hwa-byung symptom scale ≥30), and PTSD (PCL-5 ≥33).

The moderation model was analyzed using Model 1 in the PROCESS marco in SPSS developed by Hayes [34]. A 95% bootstrap resampling procedure (5,000 samples) was used in the analysis. The moderation analysis was performed using each independent variable (relevance to the victim), four dependent variables (depression, anxiety, anger, and PTSD), and one moderator (resilience). Control variables such as age, gender, and region of residence were introduced in the model as covariates. To test for a moderating effect, the effect of the independent variable on the dependent variable, effect of the moderator on the dependent variable, and interaction effect on the dependent variable need to be significant. If the CI included zero, then there was no significant effect at the significance level of 5%. The moderation effect of resilience was shown by examining the conditional effects at the mean and one standard deviation (SD) above and below the mean of resilience. The analyses were conducted using IBM SPSS Statistics version 26.0 (IBM Corp., Armonk, NY, USA).

RESULTS

Sociodemographic and clinical characteristics of the study participants

The sociodemographic and clinical characteristics of participants are described in Supplementary Table 1. Table 1 shows the characteristics of two groups; 1,907 participants related to victims and 313 participants not related to victims. Among participants related to victims, there were 100 direct witnesses, 187 close friends, colleagues, or acquaintances of the victims, 20 family members or relatives of the victims, and 6 survivors of the incident. The mean age of the relevant group was 46.23±14.73, and that of the not relevant group was 47.75±13.51, with no significant difference. However, the proportion of male was significantly higher in the relevant group (55.3%) than in the not relevant group (47.4%) (χ²=6.66, p=0.010). The residence of the relevant group was significantly concentrated toward Seoul (χ²=10.98, p=0.004), where the incident occurred. The severity of depression (F=113.50, p<0.001), anxiety (F=139.17, p<0.001), anger (F=44.27, p<0.001), and PTSD (F= 280.06, p<0.001) symptoms were all significantly higher in the relevant group. We demonstrate the difference between the two groups in Supplementary Figure 2. Resilience (F=23.65, p<0.001) was significantly lower in the relevant group.

Table 1.

Sociodemographic and clinical characteristics of study participants with and without relevance to the victims 30 days after the Seoul Halloween crowd crush

Association between relevance to victims and post-traumatic psychiatric symptoms 30 days after trauma

Table 2 shows the prevalence of a clinically significant level of depression, anxiety, anger, and PTSD symptoms among participants related to victims and those not related to victims, as well as the crude and adjusted odds ratios for each psychiatric symptom. There was a consistent association between being related to victims and all measured psychiatric symptoms. Participants related to victims exhibited significantly higher levels of depression, anxiety, anger, and PTSD symptoms. The crude odds ratios for depression, anxiety, anger, and PTSD symptoms were 3.20 (95% CI 2.49–4.12), 3.31 (95% CI 2.53–4.34), 1.46 (95% CI 1.14–1.88), and 4.45 (95% CI 3.36–5.90), respectively. When controlling for age, gender, and region of residence, the adjusted odds ratios for depression, anxiety, anger, and PTSD symptoms were 3.28 (95% CI 2.54–4.23), 3.33 (95% CI 2.54–4.38), 1.51 (95% CI 1.18–1.95), and 4.39 (95% CI 3.30–5.84), respectively.

Table 2.

Crude and adjusted odds-ratios with 95% CI for the association between relevance to victims with depression, anxiety, anger, and PTSD

Correlations

Table 3 shows that resilience was negatively correlated with symptom severity of depression (r=-0.391, p<0.001), anxiety (r=-0.401, p<0.001), anger (r=-0.459, p<0.001), and PTSD (r=-0.354, p<0.001).

Table 3.

Correlation matrix of resilience, depression, anxiety, anger, and PTSD

Moderating effect of resilience on the association between relevance to victims and post-traumatic psychiatric symptoms 30 days after trauma

Age, gender, and region of residence were controlled in the following moderating effect evaluations. The PROCESS macro developed by Hayes [34] was used to determine the moderating effect of resilience in the relationship between relevance to victims and psychiatric symptoms 30 days after trauma.

Table 4 presents the results of the moderating analysis when resilience was entered as a moderator in the association between relevance to the victims and the severity of depression, anxiety, anger, and PTSD symptoms. The results suggested that the interaction between relevance and resilience had significant effects on symptoms of anxiety (β=-0.23, 95% CI -0.40– -0.06) and PTSD (β=-0.78, 95% CI -1.26– -0.30). However, the interaction did not have significant effects on depression symptoms and severity of anger. Thus, resilience moderates the association between relevance with anxiety and PTSD symptoms.

Table 4.

Results of the moderation analysis with depression, anxiety, anger, and PTSD predicted by relevance to the victims moderated by level of resilience (N=2,220)^*

The effect of the relevance to victims on anxiety and PTSD symptoms was examined using simple main effects analyses at the mean and one SD above and below the mean of resilience. Figure 2 shows an interpretation of this moderating effect, where the predicted anxiety and PTSD symptoms values were a function of relevance and resilience. Simple slope tests revealed that the effect of relevance on anxiety symptoms is stronger for participants with low levels of resilience (β=3.51, 95% CI 2.78–4.24) than for those with high levels of resilience (β=1.69, 95% CI 0.72–2.65). The effect of relevance on PTSD symptoms is stronger for participants with low levels of resilience (β=14.53, 95% CI 12.43–16.63) than for those with high levels of resilience (β=8.33, 95% CI 5.56–11.09).

Figure 2.

Simple slope analysis shows that resilience moderated the relation between relevance to victims and psychiatric symptoms. Functions are graphed for three levels of resilience: 1 standard deviation below the mean, mean, and 1 standard deviation above the mean. A: Resilience as a moderator in the association between relevance to victims and depressive symptoms. B: Resilience as a moderator in the association between relevance to victims and anxiety symptoms. C: Resilience as a moderator in the association between relevance to victims and level of anger. D: Resilience as a moderator in the association between relevance to victims and PTSD symptoms. PHQ-9, Patient Health Questionnaire-9; GAD-7, Generalized Anxiety Disorder-7; PCL-5, post-traumatic stress disorder checklist for DSM-5; DSM-5, Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition; PTSD, post-traumatic stress disorder.

DISCUSSION

This study is significant as it is the first to demonstrate the moderating effect of resilience on post-traumatic psychiatric symptoms experienced by the public related to the victims of the Seoul Halloween crowd crush. We found that being related to victims was a significant risk factor of a higher and clinically significant level of post-traumatic psychiatric symptoms including depression, anxiety, anger, and PTSD 30 days after the incident. Moreover, resilience was validated as a protective factor that buffers an increase in anxiety and PTSD symptoms when being related to victims.

Individuals related to victims often lived in the outskirts of Seoul, where the traumatic event occurred, showing lower resilience. Prior research [35] indicates that trauma can reduce resilience, highlighting the need for therapy to strengthen resilience and prevent worsening psychiatric symptoms and negative worldviews. Individuals related to victims showed significantly higher clinical levels of depression, anxiety, anger, and PTSD, with significantly higher rates than those unrelated to victims. While PTSD is well-recognized as the primary post-traumatic condition, prior studies [17,36-38] revealed various psychiatric comorbidities. PTSD often co-occurs with depression and anxiety, sharing risk factors like specific genes, a pessimistic attributional style, or lack of social support [39-41]. Newer concepts like post-traumatic embitterment disorder also highlight significant post-trauma anger [42]. This feeling, akin to the Korean Hwa-byung syndrome [43], involves a feeling of having been let down and experiencing injustice and helplessness, along with the urge to fight back and inability to identify a proper goal. In a South Korean survey (among those aged 18–35 years), 45.2% reported heightened embitterment linked to increased exposure to adverse life events [44]. This suggests that anger often surfaces post-trauma, even if not explicitly covered in the DSM-5 criteria. Consistent with prior research, the study revealed an aggravation of not only PTSD symptoms, but also of depression, anxiety, and anger among individuals connected to victims after the Seoul Halloween crowd crush.

The negative association found between resilience and post-traumatic psychiatric symptom severity in this study aligns with the findings of several other studies [45-48] indicating that resilience has a predictive effect on mental health following trauma. There are numerous biological findings related to resilience. Various genes associated with resilience have been identified, and epigenetic changes triggered by exposure to developmental stress or childhood trauma, modifications in glucocorticoid signaling related to stress, neurobiological profiles including serotonergic, dopaminergic, neuropeptide Y, endocannabinoid, oxytocin, and glutamatergic systems, and functional changes in the limbic system and forebrain have been linked to resilience [49,50]. Individuals with lower resilience may biologically exhibit vulnerability to stress, which could lead to experiencing severe psychiatric symptoms following exposure to trauma. Moreover, individuals who have experienced trauma often find that their world no longer makes sense [51,52]. Resilience after trauma includes the restoring of these beliefs and formation of positive perspectives, which enable individuals to overcome the trauma and find new meaning [53]. After trauma, resilience helps individuals establish positive social relationships with family, friends, or professionals [54]. Through social support and connection, resilience may aid in overcoming trauma [55]. It is also associated with self-regulation skills [56-58]: individuals with high resilience can manage emotions and develop effective coping strategies to navigate stress efficiently [59]. Moreover, people with high resilience can find positive experiences and perspectives even after trauma, contributing to the maintenance of their mental well-being [60]. Finally, resilience encompasses the process of self-acceptance,61,62 empowering individuals to overcome trauma by gaining a better sense of control and stability through understanding and accepting their emotions and experiences [63].

An especially intriguing aspect of this study is the implication of a moderating effect of resilience on anxiety and PTSD symptoms among individuals related to victims. Resilience factors such as cognitive reappraisal and positive emotions may serve as buffers against the impact of trauma or adversity. Previous research associated cognitive reappraisal with reducing physiological arousal in adults [64], and positive emotions have been linked to reducing autonomic arousal and promoting efficient cardiovascular recovery following stress exposure [65]. Cognitive reappraisal has also been associated with lower anxiety symptoms in individuals exposed to stress [66]. Furthermore, studies suggested that PTSD can impact immune function and increase inflammatory biomarkers [67,68], with changes in inflammatory activity associated with decreased hippocampal volume and higher PTSD symptom severity in Gulf War veterans [69]. Resilience can also mitigate inflammation caused by exposure to trauma or stress [70], and it is associated with lower levels of inflammatory cytokines [71]. Another resilience factor, higher coping self-efficacy, is linked to positive adjustment and lower PTSD symptoms in individuals exposed to trauma [72,73]. Contrary to the results of previous studies [23,74,75], this research found that resilience had a significant moderating effect on anxiety and PTSD symptoms, but not on depression and anger. Unlike depression and anger, anxiety and PTSD symptoms can be associated with unpredictable situations, which could be linked to a sense of safety. A prior study [76] viewed stress response as a subcortical reaction to uncertainty. Safety perception led to prefrontal inhibition of the stress response. Individual anxiety about uncertainty decreased in learned safety situations, with the study indicating anxiety and stress responses in the context of generalized unsafety. Resilience is enhanced by positive experiences of safety during early childhood [77], and individuals with high levels of resilience tend to approach trauma events with a positive attitude, forming less distrust toward the world thereafter [78]. Owing to the role of resilience linked to this sense of safety, it can have a protective effect against anxiety and symptoms of PTSD that may manifest when a sense of safety diminishes in unpredictable situations. However, these speculative arguments are beyond the scope of our study. Thus, further research is needed to clarify how resilience moderates the worsening of anxiety and PTSD symptoms, distinguishing them from depression and anger.

In addition to its contributions, this study also has several limitations. First, there is potential for selection bias in this study, as the subjects were self-selected volunteers. To address this issue, the study employed the quota allocation sampling method, matching age, gender, and region of residence at the time of the traumatic event. Furthermore, the use of self-reported subjective scales to assess emotional distress and resilience introduces the possibility of response bias. However, careful steps were taken to exclude careless responses during data processing. Future studies employing objective measures could provide more accurate insights into the effects of resilience on mental health. Second, because the study was cross-sectional, longitudinal trajectories of changes in post-traumatic psychiatric symptoms could not be determined. Thus, longitudinal studies are required to elucidate the associations and extend the current findings. Third, while resilience encompasses both individual traits and socio-cultural contexts, our study only evaluated individual characteristics and did not consider other factors. Future research to incorporate a more comprehensive assessment, including of the influence of socio-cultural contexts, is needed to provide a more nuanced understanding of resilience and its impact.

In conclusion, this study is the first to use moderation analysis to investigate the possible moderating effect of resilience on the development of post-traumatic psychiatric symptoms, especially anxiety and PTSD in the Korean population related to victims of the Seoul Halloween crowd crush. The findings show that individuals with greater resilience are more inclined to encounter reduced emotional discomfort within the group subsequent to a catastrophic event. The significance of resilience becomes apparent in relation to the mental well-being of individuals, hence warranting its consideration in forthcoming initiatives pertaining to trauma preparedness, governmental interventions, and educational endeavors. Comprehensive additional research is needed to investigate factors facilitating resilience to provide insights for the development of effective interventions against post-traumatic psychiatric symptoms.

Supplementary Materials

The Supplement is available with this article at https://doi.org/10.30773/pi.2024.0154.

Supplementary Table 1.

Sociodemographic and clinical characteristics of the study participants 30 days after the Seoul Halloween crowd crush (N=2,220)

pi-2024-0154-Supplementary-Table-1.pdf

Supplementary Figure 1.

Selection of study participants.

pi-2024-0154-Supplementary-Fig-1.pdf

Supplementary Figure 2.

The comparison of symptom severity for depression (A), anxiety (B), anger (C), and PTSD (PCL-5) (D) within the 30 days following the traumatic event between participants who are related and those who are not related to the victims. **p<0.001. PHQ-9, Patient Health Questionnaire-9; GAD-7, Generalized Anxiety Disorder-7; PCL-5, post-traumatic stress disorder checklist for DSM-5; DSM-5, Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition; PTSD, post-traumatic stress disorder.

pi-2024-0154-Supplementary-Fig-2.pdf

Notes

Availability of Data and Material

The datasets generated or analyzed during the study are not publicly available due to the inclusion of sensitive personal information and privacy concerns but are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors have no potential conflicts of interest to disclose.

Author Contributions

Conceptualization: Sung Joon Cho, Sang-Won Jeon. Data curation: Kwang-yeol Lee, Nahyun Oh. Formal analysis: Mi Yeon Lee. Funding acquisition: Sra Jung, Sung Joon Cho. Investigation: Sra Jung, Sung Joon Cho, Sang-Won Jeon. Methodology: Mi Yeon Lee. Project administration: Sung Joon Cho, Sang-Won Jeon. Supervision: Sung Joon Cho, Sang-Won Jeon. Validation: Kang-Seob Oh, Young-Chul Shin, Dong-Won Shin, Junhyung Kim, Eun Soo Kim, Sun Wook Jung. Visualization: Se Youl Kim, Sra Jung. Writing—original draft: Se Youl Kim, Sra Jung. Writing—review & editing: Se Youl Kim, Sra Jung, Sung Joon Cho, Sang-Won Jeon.

Funding Statement

This study was supported by the Lee Si-Hyung Social Psychiatry Research Fund (2023) from the Korean Neuropsychiatric Research Foundation. This work was supported by KBSMC-SKKU Future Clinical Convergence Academic Research Program, Kangbuk Samsung Hospital & Sungkyunkwan University, 2024.

Acknowledgements

None

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	Relevance to the victims		Statistics	p
	No (N=1,907)	Yes (N=313)	Statistics	p
Age (yr)	47.75±13.51	46.23±14.73	t=1.71	0.088
Gender			χ²=6.66	0.010
Male	904 (47.4)	173 (55.3)
Female	1,003 (52.6)	140 (44.7)
Region of residence			χ²=10.98	0.004
Seoul	368 (19.3)	82 (26.2)
Metropolitan area	588 (30.8)	74 (23.6)
Local area	951 (49.9)	157 (50.2)
Clinical characteristics (scores)^* estimated mean±SEM
Depression (PHQ-9)	5.96±0.11	9.02±0.27	F=113.50	<0.001
Anxiety (GAD-7)	4.46±0.11	7.83±0.27	F=139.17	<0.001
Anger (Hwa-byung symptom scale)	19.41±0.31	24.98±0.78	F=44.27	<0.001
PTSD (PCL-5)	11.80±0.30	25.36±0.75	F=280.06	<0.001
Resilience (BRS)	19.30±0.09	18.16±0.22	F=23.65	<0.001

	High score	Low score	Crude odds-ratio (95% CI)	Adjusted odds-ratio^† (95% CI)
Depression (PHQ-9)
Not relevant^‡	350 (18.4)	1,557 (81.6)	1.00	1.00
Relevant/witness^‡	131 (41.9)	182 (58.1)	3.20 (2.49–4.12)^*	3.28 (2.54–4.23)^*
Anxiety (GAD-7)
Not relevant^‡	249 (13.1)	1,658 (86.9)	1.00	1.00
Relevant/witness^‡	104 (33.2)	209 (66.8)	3.31 (2.53–4.34)^*	3.33 (2.54–4.38)^*
Anger (Hwa-byung symptom scale)
Not relevant^‡	526 (27.6)	1,381 (72.4)	1.00	1.00
Relevant/witness^‡	112 (35.8)	201 (64.2)	1.46 (1.14–1.88)^*	1.51 (1.18–1.95)^*
PTSD (PCL-5)
Not relevant^‡	182 (9.5)	1,725 (90.5)	1.00	1.00
Relevant/witness^‡	100 (31.9)	213 (68.1)	4.45 (3.36–5.90)^*	4.39 (3.30–5.84)^*

	1	2	3	4	5
1. Resilience (BRS)	1
2. Depression (PHQ-9)	-0.391^**	1
3. Anxiety (GAD-7)	-0.401^**	0.837^**	1
4. Anger (Hwa-byung symptom scale)	-0.459^**	0.710^**	0.745^**	1
5. PTSD (PCL-5)	-0.354^**	0.634^**	0.690^**	0.591^**	1

	B	SE	LCI	UCI	F	p
Depression (PHQ-9)					48.135	<0.001
Relevance to the victims–Yes	4.749	1.587	1.637	7.862
Resilience	-0.440	0.025	-0.489	-0.391
Relevant×resilience	-0.120	0.086	-0.288	0.048
Adjusted R² of the final model	0.193
Anxiety (GAD-7)					53.725	<0.001
Relevance to the victims–Yes	7.006	1.571	3.926	10.086
Resilience	-0.438	0.025	-0.487	-0.390
Relevant×resilience	-0.230	0.085	-0.397	-0.064
Adjusted R² of the final model	0.211
Relevance → Anxiety
Low resilience (-SD)	3.510	0.372	2.780	4.240
Medium resilience	2.598	0.277	2.055	3.140
High resilience (+SD)	1.685	0.491	0.723	2.648
Anger (Hwa-byung symptom scale)					60.211	<0.001
Relevance to the victims–Yes	11.131	4.451	2.401	19.860
Resilience	-1.524	0.071	-1.662	-1.386
Relevant×resilience	-0.400	0.241	-0.872	0.071
Adjusted R² of the final model	0.231
PTSD (PCL-5)					61.698	<0.001
Relevance to the victims–Yes	26.408	4.518	17.549	35.267
Resilience	-1.046	0.072	-1.187	-0.906
Relevant×resilience	-0.783	0.244	-1.261	-0.304
Adjusted R² of the final model	0.235
Relevance → PTSD
Low resilience (-SD)	14.527	1.070	12.428	16.625
Medium resilience	11.426	0.796	9.865	12.987
High resilience (+SD)	8.326	1.411	5.558	11.093