Mental and Behavioral Disorders, Comorbidity, and Self-Harm: Results From Korea National Hospital Discharge In-Depth Injury Survey

Article information

Psychiatry Investig. 2025;22(4):462-474

Publication date (electronic) : 2025 April 11

doi : https://doi.org/10.30773/pi.2024.0301

Mi Jung Rho^1,*, Young-Joo Won^2,*, Hyun-Sook Lim³, Yoo-Kyung Boo^,4

¹College of Health Science, Dankook University, Cheonan, Republic of Korea

²Division of Health Administration, Yonsei University, Wonju, Republic of Korea

³Department of Healthcare Administration, Hanyang Women’s University, Seoul, Republic of Korea

⁴Department of Health Administration, College of Health Science, Dankook University, Cheonan, Republic of Korea

Correspondence: Yoo-Kyung Boo, PhD Department of Health Administration, Dankook University, 119 Dandae-ro, Dongnam-gu, Cheonan 31116, Republic of Korea Tel: +82-41-550-1473, Fax: +82-41-559-7934 E-mail: dkykb0926@dankook.ac.kr

*These authors contributed equally to this work.

Received 2024 October 2; Revised 2025 January 24; Accepted 2025 February 24.

Abstract

INTRODUCTION

Suicide accounts for the largest proportion of socioeconomic disease burden caused by diseases and accidents [1]. Suicide among highly productive people in their 20s to 40s was found to be the largest socioeconomic burden [2,3]. In particular, depression is a mental disorder closely related to suicide, and it also affects the suicide rate, which has been steadily increasing since 2000 [4]. The number of suicides in Korea in 2022 was 12,906, recording a suicide rate of 25.1 per 100,000 people [5]. In addition, the suicide rate, which is one of the standards showing the quality of life of Koreans, has ranked first among OECD countries since 2003. When comparing the age-standardized suicide rates (per 100,000 OECD standard population) of OECD member countries in 2020, Korea’s suicide rate was 24.1, the highest among OECD member countries [6], which is more than twice as high as the OECD average mortality rate of 11.0, highlighting the importance and effectiveness of policies to prevent suicide, an avoidable cause of death.

In Korea, the government has been actively pursuing policies to reduce the suicide rate [7]. Various national policies have been pursued, including the enactment of the Suicide Prevention Act in 2011, the cancellation of the re-registration of paraquat, a highly toxic pesticide, the ban on the sale of highly toxic pesticides and the opening of the Central Suicide Prevention Center in 2012, the implementation of a post-suicide management program based on emergency rooms in 2013, and the announcement of suicide reporting guidelines. In addition, efforts have been made to lower the suicide rate through active private suicide prevention projects [5]. The suicide rate in 2023 is expected to be 27.3 per 100,000 people, the highest since 2018 [8].

Suicide is the result of a complex interaction between various systems surrounding an individual, as well as the biological, cognitive, and psycho-emotional characteristics of the individual [9]. In addition, suicide is very complex and heterogeneous, including mental illness, economic, and cultural factors [10]. In general, suicidal ideas lead to suicide plans and suicide attempts, and suicide attempts lead to suicide [11]. Understanding the dynamics of suicide attempts and identifying factors that influence them is an essential component in developing effective prevention strategies [12]. Therefore, research addressing the multifaceted nature of suicide attempts, including mental health, economic, and cultural factors, is absolutely necessary.

Mental and behavioral disorders are widely recognized as major risk factors for suicide [11,13-16]. People with serious mental disorders are at significantly higher risk for suicidal behavior [17]. Among those who self-harm, those diagnosed with mental and behavioral disorders represent a particularly vulnerable group who require intensive intervention and support [18,19]. Persistent attempts at self-harm, coupled with complex mental health problems, complicate the treatment and recovery pathways [20].

The presence of comorbid diseases such as diabetes and cardiovascular disease in mental and behavioral disorders can lead to problems such as complicated diagnosis and treatment, longer hospital stay, and greater consumption of medical resources [21]. However, it also has a positive effect in accelerating patient access to medical institutions such as hospitalization or meeting medical professionals for treatment of comorbid diseases [22]. This can increase the effectiveness of managing mental and behavioral disorders and reduce the risk of suicide. However, although there are many previous studies that have investigated the relationship between suicide attempts and mental behavioral disorders [23-26], there are not many studies that have analyzed the differences according to comorbidities accompanying mental behavioral disorders.

Because of the high prevalence of comorbidities among patients who attempt self-harm, it is essential to thoroughly investigate comorbidities. The interaction between mental and behavioral disorders and various comorbidities may provide important insights into risk and protective factors that influence self-harm behavior. Therefore, this study aims to investigate the characteristics of hospitalized patients diagnosed with mental and behavioral disorders that cause self-harm and understand the characteristics of suicide attempts and suicides in these patients. In addition, we aim to derive implications for clinical perspectives and non-clinical management methods to reduce suicide among suicide attempters by identifying the characteristics of comorbidities.

METHODS

Definition

This paper includes several definitions as shown in Figure 1. First, patients diagnosed with mental or behavioral disorders among self-harm hospitalized patients refer to a person admitted to hospital after attempting self-harm. It refers to a person who has been diagnosed with a mental or behavioral disorder as the principal diagnosis after hospitalization (F00– F99 as KCD-8th code). Mental and behavioral disorders are coded starting with F: F00–F03 (dementia), F10 (mental and behavioral disorders caused by alcohol use), F11–F19 (mental and behavioral disorders caused by psychoactive substances use), F20–F29 (schizophrenia, schizotypal and delusional disorders), F30–F39 (mood [affective] disorders), remainder of F00–F99 (other disorders of mental and behavioral disorders). In this study, self-harm refers to a failed suicide attempt, a re-attempt of suicide, self-injury with a knife with suicidal intent, jumping from a high place, jumping into a moving car, or poisoning with clear suicidal intent. It is based on the 2021 KNHDIS utilization guidelines [27].

Figure 1.

Definition of target patient cohort.

Second, principal diagnosis code means the code for the diagnosis that was finally revealed after examination as the main reason for hospitalization. The principal diagnosis code is the classification number for the condition that most required treatment or testing for the patient. Through principal diagnosis code, the patient’s disease pattern can be identified. Third, additional diagnosis code refers to a classification number for a condition present at the time of hospitalization or occurring after hospitalization that affects treatment or length of stay. It contains 20 important diagnoses in the 2022 KNHDIS data. Fourth, days taken to come to hospital after selfharm were calculated as the number of days between the date of admission and the date of injury. Fifth, hospitalization period refers to the number of days between discharge date and hospitalization date. Sixth, treatment outcome refers to the patient’s condition upon discharge.

Data extraction process

We targeted to patients aged 19 years or older admitted for self-harm (n=533). Figure 2 depicts the data extraction process. First, among all self-harm hospitalized patients, this study limited to patients diagnosed with mental and behavioral disorders (F00–F99 as KCD-8th code) as the principal diagnosis code. Second, we also excluded data from patients hospitalized between 2004 and 2007 from the total data (n=105). Therefore, this study targets patients hospitalized between 2008 and 2021 (n=648). Third, this study excluded cases that did not meet the definition of target and cases where there were errors in the data (n=26). In this study, patients diagnosed with mental or behavioral disorders among self-harm hospi-talized patients refer to a person admitted to hospital after attempting self-harm. Therefore, patients whose time taken to be admitted to the hospital after injury is negative were excluded (n=21). If time taken to be admitted to the hospital after injury is negative, it means that the person has already been hospitalized before attempting self-harm. Additionally, two patients with inaccurate self-inflicted injury date data were excluded (n=3). Fourth, we deleted cases with a hospitalization period of more than 31 days (n=2). The average hospitalization period in the data was 20.5 days. There were two cases of patients with a hospitalization period of more than 31 days: 156 days and 366 days. A total of 622 patients were extracted among the target patients. Lastly, of these, 89 are patients under 19 years of age, and 533 are adult patients over 19 years of age. We focused on patients aged 19 years or older admitted for self-harm (n=533).

Figure 2.

Data extraction process.

RESULTS

Patient characteristics

Our results were described in the following order: who, when, where, what, how, and why. Firstly, for patients aged 19 years or older, the total number (unweighted cases) was 533 as shown in Table 1. In case of weighted cases, the estimate was 10,140. The average age estimate for 533 people is 43.23 years old, with a standard error of 0.847. The age range is 19 to 95 years. Females account for a higher proportion than males, reaching 59.55%. Of these, 45.23% were in the 20s to 30s age group. The proportion of patients admitted through the emergency room was 92.10%, and 7.9% were admitted through outpatient. Only 14.4% of patients underwent surgery for treatment. In addition, 46.87% of patients had one or more comorbidities. The treatment outcome was improved in 88.24% of patients, and the mortality rate was very low. Disposition was 89.90% of patients returned home, and the average length of stay was 20.52 days.

Table 1.

Patient characteristics

Occurrence and characteristics of self-harming patients by seasonal and annual

Looking at the frequency by season, the increase is large in winter and the number of patients peaks in spring (Figure 3). As summer passes and autumn progresses, the number of self-harming patients gradually decreases (Figure 3 and Supplementary Table 2).

Figure 3.

Seasonal patient occurrence trend (weighted cases).

In patients diagnosed with mental and behavioral disorders hospitalized for self-harm, there were 996 patients (9.83%. weighted cases) in the year of hospitalization in 2013. The number of patients has been increasing since 2018. The number of patients decreased during the COVID-19 pandemic in 2020, but then increased again in 2021.

Attempted self-harm related characteristics

Table 2 describes characteristics associated with self-harm attempts. These characteristics were described in the following order: where, what, how, and why. The first is a place for attempted self-harm. The first is a place for attempted selfharm. The place with the highest percentage was at home, with a rate of 66.74%. Next, unknown places (19.69%), the locations where self-harm occurs are commercial places (2.48%), medical facilities (2.42%), water, sea, and outdoors, in that order (2.36%). Second, it is about activities during attempted self-harm and 66.57% self-harmed during activities classified as “other specified activities.” The detailed classification criteria for occurs during other specified activities are as follows: walking, wandering, running without a specific purpose, standing, crawling, while sitting, doing religious/spiritual activities (doing a ritual, praying, and praying), active violence/aggression (fighting, fight at work, arguing, being upset, and attempting suicide), the victim’s activity is known, but is nothing in particular. Third is the mechanism of attempted self-harm. The mechanism of injury for 61.34% was damaged due to poisoning. Next, 22.33% were caused by stab wounds, laceration, and amputation. Fourth, regarding addictive substances, 53% of addictive substances used in self-harm were found to be antiepileptics, sedatives, sleeping pills, anti-Parkinson’s drugs, and psychotropic drugs (Table 2). The next most common addictive substances were other gases and volatile substances. Among 533 cases, in 205 cases, there was no information on the addictive substance. Fifth, it is about causes and reasons of attempted self-harm. The largest proportion, 49.18%, was self-harm due to mental problems. The next risk factor was conflicts with family, cohabitants, relatives, and friends.

Table 2.

Characteristics of patients with self-harm

Predictors of hospitalization period

First, we analyzed whether there was a difference in hospitalization period depending on whether surgery was performed by, sex, age group, addictive substance, or comorbidity (Table 3). The average total hospitalization period is 20.52 days. There was a significant difference in hospitalization period depending on whether surgery was performed (p<0.01), age group (p<0.05), addictive substances (p<0.001), and comorbidities (p<0.01). The average hospitalization period for those who had surgery was 32 days, and for those who did not have surgery, the average hospitalization period was 22.9 days, which was longer for those who had surgery. The age group with the longest hospitalization period was the 50s, at 32.5 days. There were differences in hospitalization period by age group. As a result of the post hoc test, there was a significant difference between the patient group over 80 and the age group in the 20s, 30s, and 50s (p<0.05). When the addictive substance was alcohol, the average hospitalization period was the longest at 71.57 days. Next, in the case of “other and unspecified chemicals and toxic substances,” the average hospitalization period was the second longest at 41.06 days. Narcotics and hallucinogens had the shortest average hospitalization period at 13.76 days. As a result of the post hoc test, when the addictive substance was alcohol, there was a significant difference from all groups (p<0.001).

Table 3.

Difference in hospitalization period between the groups

Second, we identified factors influencing hospitalization period (Table 4). To verify the effect of the time taken to be admitted to the hospital after injury and comorbidities on the hospitalization period, a regression analysis was performed adjusting for surgery, addictive substances, and age group.

Table 4.

Predictors influencing hospitalization period

The average time it took to be admitted to hospital after selfharm was 0.65 days. The average number of comorbidities was 1.38. The regression model was statistically significant (F=24.00, p<0.001). The explanatory power of the regression model was approximately 14.4%, including comorbidities and control variables (surgery, addictive substances, and age group). As a result of testing the significance of the regression coefficient, the number of comorbidities was found to have a significant positive effect on hospitalization period (p<0.001). It was estimated that when comorbidities increased by one disease, the hospitalization period increased by 1.89 days (B=1.89).

Comorbidity characteristics

First, we conducted network analysis between comorbidities including the principal diagnosis (Figure 4 and Supplementary Table 3). F00–F99 code (mental and behavioral disorders) have the maximum betweenness centrality (betweenness=171, degree=1,640, and closeness=0.05) (Figures 4 and 5). Betweenness centrality is an important indicator of brokerage role. In other words, it measures how much one node serves as a link to other nodes. Degree represents the amount of connection a node has to other nodes within the network. Closeness indicates how close a node is to other nodes. In case of degree, there is the highest connection between F00–F99 node (mental and behavioral disorders) and S00–T98 (poisoning and certain other consequences of externality) (degree=812). Next, the degree values were high in the order of Z00–Z99 (factors influencing health status and contact with health services, degree=63), K00–K93 (diseases of the digestive system, degree=50), J00–J99 (diseases of the respiratory system, degree=49), and I00–I99 (diseases of the circulatory system, degree=47).

Figure 4.

Network analysis between comorbidities including the principal diagnosis.

Figure 5.

Patient occurrence trend by year (weighted cases).

Among F00–F99 code, there are top 30 of principal diagnosis code: severe depressive episode without psychotic symptoms (n=91), depressive episode, unspecified (n=71), adjustment disorders (n=46), and recurrent depressive disorder, current episode severe without psychotic symptoms (n=27) (Supplementary Table 4). Disease classification codes can be found in Supplementary Table 1 [27].

Second, we conducted network analysis between comorbidities excluding the principal diagnosis (Figure 6 and Supplementary Table 5). We attempted to find the relationship between the remaining comorbidities excluding the principal diagnosis. The S00–T98 node (injury, poisoning and certain other consequences of external causes) have the maximum betweenness centrality (degree=1,02, closeness=1, and betweenness=76.05) (Figure 6). This was followed by R00–R99 (symptoms, signs and abnormal clinical and laboratory findings, NEC), F00–F99 (mental and behavioral disorders), Z00– Z99 (factors influencing health status and contact with health services), C00–D48 (neoplasms), and I00–I99 (diseases of the circulatory system). Disease classification codes can be found in Supplementary Table 1 [27].

Figure 6.

Chord diagram between comorbidities excluding the principal diagnosis.

There are top 30 of comorbidity code excluding the principal diagnosis: benzodiazepine (n=74), other antiepileptic and sedative-hypnotic drugs (n=45), and other and unspecified antidepressants (n=42) (Supplementary Table 6).

DISCUSSION

We attempted to identify the characteristics of patients diagnosed with mental and behavioral disorders and the importance of comorbidities. We obtained interesting results in patients hospitalized after attempted self-harm.

The main age group of self-harming patients diagnosed with mental and behavioral disorders was found to be in their 20s and 30s. In fact, the main age group of self-harming patients diagnosed with mental disorders is usually reported to be in their 20s and early 30s [28-30]. In this study, the proportion of female self-harming patients diagnosed with mental disorders was high, so it is necessary to classify young people and women with mental disorders as a major risk group for attempted selfharm and pay attention to them. In addition, depression stands out as a representative mental disorder in self-harming patients, and the main onset of depression is concentrated in young women in their 20s, so it is necessary to establish policies that take this into account when managing cases of mental and behavioral disorders.

Previous studies have shown that the high suicide rate among Korean women in their 20s and 30s is mainly due to mental health issues such as depression and anxiety disorders. In particular, the social stigma surrounding mental health and the difficulty in accessing treatment can be obstacles for young women to deal with their emotions or seek help. Korean society has traditionally placed high expectations on women. In addition to the burden of marriage and childbirth, the job market is very competitive, and expectations of social success can cause great stress, which can lead to suicide attempts. Due to this tendency, women have been shown to have interpersonal conflicts and stress related to suicidal thoughts. In addition, studies in Japan and Australia, as well as Korea, have shown that temporary/unstable employment is a factor that is significantly related to suicide among female workers. However, according to previous studies, the overall risk of repeated self-harm attempts is similar for men and women, and it is also reported that men are at a higher risk than women in the 20–24 age group [31]. In addition, women have been reported to have a higher risk of relapse than drug overdose [31]. Since there are various factors related to suicide, such as demographic and lifestyle factors, future research on suicide needs to be subdivided by gender, age, and socioeconomic level, along with the presence of comorbidities.

Seasonal variation in suicide rates is a well-documented phenomenon. Most studies worldwide explain that suicides peak in spring, reach a second peak in fall, and decline in winter, mainly in men and the elderly [32]. In this study, seasonal differences were clearly observed in patients who attempted suicide due to mental illness, but there were differences from previous studies. The number of suicide attempts increased from winter to spring, but unlike previous studies, there was a relative decrease in fall. Seasonal affective disorder is a seasonal pattern of recurrent major depressive episodes that occur most frequently in fall or winter and are alleviated in spring [33]. Unlike seasonal affective disorders, other forms of recurrent depression, such as bipolar or unipolar depression, occur regardless of the time of year [34]. Therefore, it may be difficult to explain the seasonal variation in the results of this study as being because many of the subjects have affective disorders. In the future, in-depth analysis of factors that show seasonal variation by limiting cases of suicide attempters to mental disorders will be necessary.

In addition, most patients with mental illness who attempted suicide harm themselves at home (66.74%), and considering that the number of patients who harm themselves increases from winter to spring, it is judged that they are more likely to harm themselves at home during a period when their activity level is relatively low. In addition, many self-harm attempts occur in daily life (while walking, sitting, or standing, etc.) (66.57%). Therefore, it is necessary to introduce a life intervention program so that these patients can sufficiently engage in outdoor activities and receive sufficient sunlight after discharge from the hospital. In addition to in-hospital treatment, it is thought that receiving psychological treatment outside the hospital [35] and lifestyle interventions such as increasing exercise or outdoor activities will also have an effect on improving the patient’s condition [36]. Therefore, continuous attention from people around the patient in their daily lives after discharge and continuous monitoring using ICT technologies such as lifestyle monitoring apps are necessary. In particular, it has been difficult to meet the increased demand with existing mental health-related services during the COVID-19 pandemic [37-39]. This has led to the search for alternative solutions such as digital mental health services. That is, it includes a wide range of mental health services, including suicide prevention, mental health promotion, and drug and alcohol addiction treatment, and since services are provided through digital platforms such as websites and mobile applications, it provides both convenience and accessibility in monitoring [40-42]. In other word, from a medical policy perspective, IoT technology and other non-clinical management methods can be used to enable continuous, non-contact management. In addition, only 49% of self-harming patients with mental illness responded that the reason for their self-harm was mental problems, even though they were diagnosed with mental and behavioral disorders as their primary diagnosis. In other words, there are cases where they are not aware of their mental problems. In addition, about 23% of cases judged conflict with friends or family as the reason for their self-harm. The reason for attempted self-harm may arise from issues other than mental problems, but clinical judgment and treatment through differentiation of the exact reason are necessary.

The majority (88%) of patients with mental illness who commit suicide are discharged after their condition improves, and the mortality rate is analyzed to be low. As in previous studies, damage due to poisoning (61.34%) was analyzed as the most common method of self-harm in this study [31]. The results are the same as previous studies [17], which found that the most common method of suicide was poisoning. Other mechanisms included stab wounds, laceration, and amputation (22.33%). The reason for the relatively low mortality rate of patients diagnosed with mental and behavioral disorders seems to be that most of the substances used in self-harm attempts are antiepileptic drugs, sedatives, sleeping pills, anti-Parkinson drugs, and psychoactive drugs that are considered to be commonly taken. Repeated suicide attempts due to easily accessible drugs such as the patient’s usual medications or sleeping pills can eventually lead to death. In addition, there are cases where mentally ill self-harming patients do not come to the emergency room immediately after self-harming, but visit the hospital as an outpatient (7.9%). Such factors can lead to repeated self-harming attempts and chronic suicide attempts, so immediate hospital visits after self-harming, along with medication management and monitoring of the patient’s condition, require attention and education from those around them.

The most common disease code for the primary diagnosis of patients with a psychiatric diagnosis was F322 (severe depressive episode without psychotic symptoms), and many cases had depression-related codes. 46.78% of self-harming patients with a psychiatric disorder had one or more comorbidities. The most common codes for comorbidities excluding the principal diagnosis code after hospitalization were T424 (benzodiazepine), T426 (other antiepileptic and sedative-hypnotic drugs), T432 (other and unspecified antidepressants), and S619 (open wound of wrist and hand, part unspecified). Chronic diseases such as hypertension and diabetes mellitus also exist, but they do not account for a large proportion. It was analyzed that comorbidities are a factor affecting the length of hospital stay, and when the number of comorbidities increases by one, the length of hospital stay increases by 1.889 days. Other studies have shown similar results, with hospitalization lengths longer in patients with comorbid mental disorders than in patients without comorbid mental disorders [43,44].

It was confirmed that the length of hospital stay significantly increases when surgery is performed or co-morbidities are present. The age group 50s had the longest average length of stay, but the average length of stay was 20.52 days, which was higher than the average length of stay for all age groups. When the addictive substance was alcohol, the average length of stay was 71.57 days. It is reported that the majority of self-harm patients often arrive at the hospital in an alcoholic state. Alcohol management is a very important point in patients who attempt self-harm or have mental illness. In addition, although the length of stay varied depending on the addictive substance, the length of stay for other and unspecified chemicals and toxic substances was 41.06 days, indicating that management of suicide attempts due to addiction is very necessary. From a clinical perspective, it will be necessary to treat mental illness, behavioral disorders, and complications in a multidisciplinary manner simultaneously to increase treatment effectiveness and reduce suicidal thoughts or attempts.

Among factors related to suicide, those with physical illness are more likely to attempt suicide, and the mortality rate is high due to not only suicide attempts but also drug abuse, smoking, alcohol abuse, and poor self-care [45,46]. Chronic diseases that limit physical function or movement, such as stroke, Parkinson’s disorder, and oral cancer, and mental disorders such as depression, bipolar disorder, and schizophrenia show consistent associations with suicide [47]. The comorbidities with the highest suicide risk were mental and behavioral disorders, and cardiovascular disease was also high [48]. This result was confirmed in the results of this study. It is also reported that the risk of suicide increases as the number of physical illnesses increases [49]. From a clinical perspective, comorbidity factors interact with social and economic factors to make clinical management more difficult, time-consuming, and resource intensive [50]. Therefore, it is necessary to identify comorbidities at the early stage of patient contact and establish a clinical treatment direction.

Despite producing these important results, this study has some limitations. First, we used the 2022 KNHDIS form Korea Disease Control and Prevention Agency. The data is about patients discharged from hospital. The population of data is patients discharged after hospitalization in a general hospital with more than 100 beds. Therefore, the characteristics of hospitals with less than 100 beds were not reflected. Therefore, it may be limited in explaining the characteristics of all self-harm that occurs in Korea. Second, sociological variables for patients are limited in this data, so there are limitations in utilizing various variables. Third, in this study, cases of self-harm in the hospital after hospitalization were excluded. This is a case that can occur in reality. Future research will also need to study these cases. Fourth, we excluded two cases with a length of stay of more than 31 days: 156 days and 366 days. If there are enough long-term patient cases exceeding 31 days, future studies including long-term hospitalized patients are also needed. Fifth, this study focused on patients diagnosed with a mental or behavioral disorder as their principal diagnosis after hospitalization. In the 2022 KNHDIS data, there are also other self-harm patients. Future research is also needed on other patient groups who do not have mental or behavioral disorders as their principal diagnosis. Sixth, the sampling design of KNHDIS is a complex sample survey, and it is recommended to do weighting for analysis. However, we analyzed the network analysis data using unweighted samples. We could not find an R package that could perform network analysis with complex sample survey data. Future research needs to conduct network analysis using weighted data. Finally, this study targeted patients who were hospitalized after attempted self-harm and diagnosed with mental and behavioral disorders (F00– F99) as the principal diagnosis code. Therefore, the disease code corresponding to mental and behavioral disorders) and poisoning and certain other consequences of externality may have emerged as major comorbidities. Therefore, it would be desirable to define S00–T98 and F00–F99 codes as one patient and conduct further research on related complications.

Despite these limitations, this study is very meaningful. In Korea, approximately 25% of adults are diagnosed with mental illness during their lifetime, and the rate of suicide attempts with mental illness is also very high. Therefore, in order to prevent suicide in people with mental and behavioral disorders, it is necessary to identify important characteristics related to suicide attempts and implement prevention and management methods, and continuous monitoring and psychological evaluation are necessary in their lives. In addition, it was confirmed how important it is to manage comorbidities in patients with mental illness who attempt self-harm. Ultimately, accurate treatment of patients with mental illness and reduction of comorbidities is a way to lower the social and clinical costs from self-harm.

Supplementary Materials

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