Inpatient suicide is a significant problem, accounting for the third-highest ratio(17.8 %) of suicides in South Korea in 2017. We aimed to investigate the characteristics of inpatient suicides using national data, evaluate risk factors, and provide recommendations for suicide prevention.

This nationwide case-control study utilized national data on all inpatient suicides from police investigations between 2013 and 2017. A total of 4998 individuals were included, comprising 833 inpatient suicides and 4165 controls. Inpatient suicide risk factors were assessed through cross-tabulations and logistic regression analyses.

Among eight hundred thirty-three individuals died by suicide in hospitals; most were male (74.9 %), older than 60 years (61.3 %), married (43.0 %), and unemployed (85.1 %). The primary method of inpatient suicide were jumping from a height (49 %), followed by hanging (39.7 %). Major depressive disorder was the most prevalent psychiatric diagnosis among inpatient suicides. The risk of inpatient suicide was significantly higher in patients with schizophrenia, dementia, and alcohol use disorder.

Effective management of hospital facilities and environments is essential to prevent inpatient suicides. Nursing hospitals treating patients with dementia require more rigorous psychiatric evaluations and facility safety standards. We recommend implementing crisis interventions and comprehensive psychiatric assessments to prevent inpatient suicide.

Suicide is a serious global public health concern. South Korea has consistently reported one of the highest suicide rates among Organization for Economic Cooperation and Development countries over the past few decades. In response to the increasing suicide rate, South Korea enacted the Suicide Prevention Act in 2011, and allocated significant budget funding for implementation of various policies according to its national strategy for suicide prevention. Suicide prevention policies, such as restricting access to highly hazardous pesticides, implementing emergency room-based follow-up management programs, and adhering to safety guidelines for the media while reporting on suicide, were effective. Thereafter, the overall suicide rate and the suicide rate in older people steadily declined. However, the suicide rate among younger age groups has increased since 2017, and South Korea continues to report higher suicide rates than those of most other countries. Further research is needed to develop and implement suicide prevention strategies that address the recently changing trends.

Suicide by charcoal burning has accounted for more than 100,000 deaths. It has become an increasingly common suicide method in Hong Kong since first reported in 1998, and it has spread into South Korea, Taiwan, Japan and other countries. This systematic scoping review aimed to explore current evidence on trends, risk factors, impact of media and prevention strategies for this suicide method, and to identify research gaps.

A search for articles published from January 1998 to June 2021 was conducted through electronic databases (MEDLINE, EMBASE, SCOPUS and PsycINFO) with the keywords (suicide*) AND (charcoal). Articles describing prevalence, trends, characteristics, risk factors and prevention strategies of charcoal burning suicide deaths were included. Non-peer-reviewed articles, non-English articles, commentaries/editorials/letters, poster abstracts, reviews, meta-analyses and studies that documented only charcoal burning suicide attempters/survivors were excluded.

Eighty-eight studies were identified, most from East Asia. Charcoal burning suicide rates in Hong Kong, Taiwan and Japan has passed the peak, while continuing to increase in South Korea. Risk factors are changing and not static. Media appears to play an important role in triggering and spreading information. Restricting access to charcoal, and raising public awareness have been effective in the short term in preventing charcoal burning suicide, but there is little information on their long-term effectiveness or sustainability.

More research is required to update the development and dynamic changes of charcoal burning suicide and the contributing factors. The evidence from this review may assist in detecting and intervening early for future novel suicide methods.

Studies exploring suicide mortality on a global scale are sparse, and most evaluations were limited to certain populations.

To assess global, regional and national trends of suicide mortality.

Suicide mortality data for the period 2000-2019 were obtained from the mortality database of the World Health Organization and the Global Burden of Disease Study. Age-standardized rates (ASRs; expressed per 100000) were presented. To assess trends of suicide mortality, joinpoint regression analysis was used: The average annual percent change (AAPC) with the corresponding 95% confidence interval (95%CI) was calculated.

A total of 759028 (523883 male and 235145 female) suicide deaths were reported worldwide in 2019. The global ASR of mortality of suicide was 9.0/100000 population in both sexes (12.6 in males vs 5.4 in females). In both sexes, the highest rates were found in the region of Africa (ASR = 11.2), while the lowest rates were reported in Eastern Mediterranean (ASR = 6.4). Globally, from 2000 to 2019, ASRs of mortality of suicide had a decreasing tendency in both sexes together [AAPC = -2.4% per year; 95%CI: (-2.6)-(-2.3)]. The region of the Americas experienced a significant increase in suicide mortality over 2000-2019 unlike other regions that had a declining trend. Out of all 133 countries with a decline in suicide mortality, Barbados (AAPC = -10.0%), Grenada (AAPC = -8.5%), Serbia (AAPC = -7.6%), and Venezuela (AAPC = -6.2%) showed the most marked reduction in mortality rates. Out of all 26 countries with a rise in suicide mortality, Lesotho (AAPC = +6.0%), Cyprus (AAPC = +5.1%), Paraguay (AAPC = +3.0%), Saudi Arabia (AAPC = +2.8%), Brunei (AAPC = +2.6%), Greece (AAPC = +2.6%), Georgia (AAPC = +2.1%), and Mexico (AAPC = +2.0%), are among those with the highest increase in mortality.

Decreasing trends in suicide mortality were observed in most countries across the world. Unfortunately, the mortality of suicide showed an increasing trend in a number of populations. Further research should explore the reasons for these unfavorable trends, in order to consider and recommend more efforts for suicide prevention in these countries.

Suicide is an important health and social concern worldwide. Both suicidal ideation and suicide rates are higher in the elderly population than in other age groups; thus, more careful attention and targeted interventions are required. Therefore, we have developed a model to predict suicidal ideation in the community-dwelling elderly aged of >55 years.

A random forest algorithm was applied to those who participated in the Korea Welfare Panel. We used a total of 26 variables as potential predictors. To resolve the imbalance in the dataset resulting from the low frequency of suicidal ideation, training was performed by applying the synthetic minority oversampling technique. The performance index was calculated by applying the predictive model to the test set, which was not included in the training process.

A total of 6410 elderly Korean aged of >55 (mean, 71.48; standard deviation, 9.56) years were included in the analysis, of which 2.7% had suicidal ideation. The results for predicting suicidal ideation using the 26 chosen variables showed an AUC of 0.879, accuracy of 0.871, sensitivity of 0.750, and specificity of 0.874. The most significant variable in the predictive model was the severity of depression, followed by life satisfaction and self-esteem factors. Basic demographic variables such as age and gender demonstrated a relatively small effect.

Machine learning can be used to create algorithms for predicting suicidal ideation in community-dwelling elderly. However, there are limitations to predicting future suicidal ideation. A predictive model that includes both biological and cognitive indicators should be created in the future.

The processes and planning involved in choosing and attempting to die by a particular method of suicide are not well understood. Accounts from those who have thought about or attempted suicide using a specific method might allow us to better understand the ways in which people come to think about, plan and enact a suicide attempt.

To understand from first-person accounts the processes and planning involved in a suicide attempt on the railway.

Thematic analysis was conducted of qualitative interviews (N = 34) undertaken with individuals who had contemplated or attempted suicide by train.

Participants explained how they decided upon a particular method, time and place for a suicide attempt. Plans were described as being contingent on a number of elements (including the likelihood of being seen or interrupted), rather than being fixed in advance. Participants mentally rehearsed and evaluated a particular method, which would sometimes involve imagining in detail what would happen before, during and after an attempt. The extent to which this involved others (train drivers, partners, friends) was striking.

By giving people free reign to describe in their own words the processes they went through in planning and undertaking a suicide attempt, and by not interpreting such accounts through a lens of deficit and pathology, we can arrive at important insights into how people come to think and feel about, plan and enact a suicide attempt. The findings have implications in terms of understanding suicide risk and prevention more broadly.

Background: High suicide rate in the elderly is an important global public health problem but has not received the attention it deserves. This study aimed to examine time trends of suicide mortality for people aged 70 years and over by sex, age, and location from 1990 to 2017, and to provide predictions up to 2030. Methods: Using data from the Global Burden of Disease study 2017, we presented elderly suicide mortality changes and compared the patterns for the elderly with that for all ages. We estimated associations between socio-demographic index (SDI) and suicide mortality rates using a restricted cubic spline smoother, and predicted suicide mortality rates up to 2030. Results: In 2017, 118,813 people aged 70 years and over died from suicide, indicating a mortality rate of 27.5 per 100,000, with the highest rates in Eastern Sub-Saharan Africa, Western Sub-Saharan Africa, and Central Sub-Saharan Africa, and for countries and territories, the highest were in South Korea, Zimbabwe, Lesotho, Mozambique, and Senegal. Between 1990 and 2017, suicide mortality rate for the elderly aged 70 years and over decreased globally (percentage change -29.1%), and the largest decreases occurred in East Asia, Southern Latin America, and Western Europe. Nationally, the largest decrease was found in Chile, followed by Czech Republic, Hungary, Turkey, and Philippines. For most countries, the elderly mortality rate was higher than the age-standardized rate, with the largest percentage differences in China and countries in Sub-Saharan Africa. The elderly suicide mortality rate decreased as SDI increased, except for a slight rebound at mid to high SDI. According to projections, 10 out of 195 countries were expected to meet the SDGs indicator of a third reduction by 2030. Conclusions: Variability in suicide mortality rates for the elderly aged 70 years and over by sex, age, region, country, and SDI can guide preventive policies, but causes of the variability need further study. Comprehensive strategies should be adopted to reduce suicide rates and close the gap to the 2030 SDGs.

Suicide is a serious social and public health problem. Social stigma and prejudice reduce the accessibility of mental health care services for high-risk groups, resulting in them not receiving interventions and committing suicide. A suicide prediction model is necessary to identify high-risk groups in the general population.

We used national medical check-up data from 2009 to 2015 in Korea. The latest medical check-up data for each subject was set as an index point. Analysis was undertaken for an overall follow-up period (index point to the final tracking period) as well as for a one-year follow-up period. The training set was cross-validated fivefold. The predictive model was trained using a random forest algorithm, and its performance was measured using a separate test set not included in the training.

The analysis covered 372,813 individuals, with an average (SD) overall follow-up duration of 1.52 (1.52) years. When we predicted suicide during the overall follow-up period, the area under the receiver operating characteristic curve (AUC) was 0.849, sensitivity was 0.817, and specificity was 0.754. The performance of the predicted suicide risk model for one year from the index point was AUC 0.818, sensitivity 0.788, and specificity 0.657.

This is probably the first suicide predictive model using machine learning based on medical check-up data from the general population. It could be used to screen high-risk suicidal groups from the population through routine medical check-ups. Future studies may test preventive interventions such as exercise and alcohol in these high-risk groups.

Little is known about the detailed characteristics of patients using gas substances for self-inflicted injury in prehospital settings. The aim of this study was to investigate the characteristics, incidence trends, and outcomes of patients who used gas substances for self-inflicted injury in Osaka City, Japan, using ambulance records.

This was a retrospective observational study that used data from 2009 to 2015. We extracted details from ambulance records of self-inflicted injury patients who used gas substances. The annual incidence of self-inflicted injury by gas substance and age group and Poisson regression models were applied for calculating the annual incidence trend by type of gas substance. The main outcome was confirmed death at the scene, and we also calculated the crude odds ratios and 95% confidence intervals for each gas substance.

During the study period, there were 324 self-inflicted injury patients who used gas substances. The most commonly used gases were carbon monoxide (CO) (54.9%), followed by hydrogen sulfide (12.7%), helium (6.5%). The incidence of CO and hydrogen sulfide have subsequently decreased (P for trend = 0.023 and <0.001, respectively); however, the incidence of helium did not change during the study period (P for trend = 0.586). The mortality rate was highest in patients who used helium (66.7% [14/21]) and the crude odds ratio of helium was 3.857 (95% confidence interval, 1.267-11.745; P = 0.017) compared with hydrogen sulfide.

This study revealed that the incidence of self-inflicted injury with helium did not change and its proportion of death at the scene was high in Osaka City.

The modern society is a so-called era of big data. Whereas nearly everybody recognizes the "era of big data", no one can exactly define how big the data is a "big data". The reason for the ambiguity of the term big data mainly arises from the widespread of using that term. Along the widespread application of the digital technology in the everyday life, a large amount of data is generated every second in relation with every human behavior (i.e., measuring body movements through sensors, texts sent and received via social networking services). In addition, nonhuman data such as weather and Global Positioning System signals has been cumulated and analyzed in perspectives of big data (Kan et al. in Int J Environ Res Public Health 15(4), 2018 [1]). The big data has also influenced the medical science, which includes the field of psychiatry (Monteith et al. in Int J Bipolar Disord 3(1):21, 2015 [2]). In this chapter, we first introduce the definition of the term "big data". Then, we discuss researches which apply big data to solve problems in the clinical practice of psychiatry.