Predictors Of Suicide Attempts Research Articles

Suicide attempts during adolescence: Testing the system dynamics of the interpersonal theory of suicide.

Despite increased efforts to prevent suicide, attempts to die by suicide are rising amongst youth in the United States. Testing causal theories that depict suicide attempts from an adolescent development perspective could bolster prevention and intervention efforts. This study using system dynamics modeling to appraise whether a prevalent theory of suicide, the Interpersonal Theory of Suicide, predicts suicide attempts across adolescence. A system dynamics computational simulation model was conceptualized based on the Interpersonal Theory of Suicide, as described by Joiner and Van Orden et al. This model was parameterized with representative longitudinal data on adolescents in the United States who attempted suicide across four waves from the National Longitudinal Survey of Adolescent and Adult Health. Though able to predict exponential growth in suicide attempts for early adolescents, the Interpersonal Theory of Suicide, when specified as a dynamic theory, did not adequately predict the nonlinear changes in suicide attempts from adolescence into adulthood. The theory was amended with potential feedback loops from literature and tested for fit. The study builds on a field of emerging views that suicide dynamics should be tested to account for nonlinear feedback effects. Results suggest that the Interpersonal Theory of Suicide should be amended to include the effect of interventions after an attempt and the dynamic developmental processes during adolescence that affect suicide behaviors over time.

Neutrophil to-lymphocyte and platelet-to-lymphocyte ratios as biomarkers for suicidal behavior in children and adolescents with depression or anxiety treated with selective serotonin reuptake inhibitors

BackgroundBoth the neutrophil/lymphocyte ratio (NLR) and the platelet/lymphocyte ratio (PLR) have been proposed as biomarkers of suicidal risk in adults with depression. We examined whether these ratios may be considered biomarkers for suicidal behavior in young patients with major depressive or anxiety disorders before treatment with selective serotonin reuptake inhibitors (SSRIs), or as biomarkers for the adverse event of SSRI-associated suicidality. MethodsChildren and adolescents meeting criteria for major depressive or anxiety disorder were recruited. Serum levels of three pro-inflammatory cytokines (TNF-α, IL-6, IL-1β) were assessed; and NLR and PLR calculated, from blood samples collected at baseline and after 8 weeks treatment with SSRI. A Mann-Whitney test was performed to evaluate differences in NLR and PLR between children with and without a history of a suicide attempt prior to treatment. We compared hematological parameters before and after treatment, and between children who developed SSRI-associated suicidality versus children without treatment emergent suicidality. ResultsAmong 91 children and adolescents (aged 13.9 ± 2.4 years), baseline NLR and PLR were significantly higher among those with a history of a suicide attempt versus those without such history. Statistically significant correlations were found for the suicide ideation subscale in the Columbia suicide severity rating scale with both baseline NLR and PLR. Baseline NLR and PLR were similar in children who did and did not develop SSRI-associated suicidality after 8 weeks. In the final logistic regression model (χ2 = 18.504, df = 4, p value = 0.001), after controlling for sex, depression severity and IL-6 levels, NLR was significantly associated with a past suicide attempt (β = 1.247, p = 0.019; OR [95% CI] = 3.478 [1.230–9.841]), with a NLR cut-off value of = 1.76 (area under the curve = 0.75 (95% CI = 0.63–0.88, sensitivity = 73%, and specificity = 71%, p value = 0.003). ConclusionsHigh NLR and PLR values may be associated with suicidal behavior in depressed and anxious children and adolescents. NLR appears as a better predictor of suicide attempt than PLR, and thus may be a useful biomarker of suicidality in young patients with depression or anxiety.

Psychotic experiences, sexual minority status, and suicidal behavior among young adult college students in the United States.

Psychotic experiences significantly predict suicidal behaviors; however, it is unknown whether these associations are conditional on sexual minority status. We analyzed cross-sectional data from the Healthy Minds Study (N = 109,975), which was collected between September 2020 and June 2021 from young adult (aged 18-34) students from across 140 colleges across the United States. Having psychotic experiences and sexual minority status were associated with significantly greater odds of reporting suicidal ideation, suicide plan, and suicide attempt, adjusting for sociodemographic characteristics. We found significant interactions between psychotic experiences and sexual minority status, such that the relations between psychotic experiences and suicidal behaviors were stronger among heterosexual students than among sexual minority students. However, the interactions disappeared for suicidal ideation and plans after adjusting for socio-behavioral risk factors. Future research can explore whether psychotic experiences predict suicide attempts among sexual minority status behavior socio-behavioral risk factors.

Patient characteristics prior to suicide attempts among Hispanics compared to non-Hispanic whites in the United States

BackgroundSuicide rates among Hispanics in the United States are much lower than rates among Whites. The reasons for this difference are uncertain, therefore we compared patient characteristics between Hispanic and White patients with a suicide attempt. MethodsPatients with a suicide attempt (n = 8641) between 2012 and 2018 were identified by ICD-9 and ICD-10 codes in a nationally distributed electronic health record data base. Patient demographics, geographic region, health services use, depression treatment, psychiatric and physical comorbidities were measured in the 2 years prior to a suicide attempt. ResultsMost patients with a suicide attempt were White (78.6%) and 6.2% were Hispanic, a majority were 36–64 years of age and 57.3% were female. Younger age and lack of health insurance were significantly (p < .0001) more common among Hispanic compared to White patients with a suicide attempt. Depression treatment was significantly (p < .0001) less common among Hispanic vs. White patients. Sleep disorder and all psychiatric and substance use disorders, except for drug use disorder, were significantly (p-value range: 0.026–<0.0001) more prevalent in the two years before suicide attempt in White patients. ConclusionsDiagnosed psychopathology is more common among White vs. Hispanic patients who attempt suicide. Lack of insurance and low depression treatment rates may be associated with suicide attempt among Hispanics. Additional research is needed to determine the mix of factors that predict suicide attempt among Whites, Hispanics, and other minorities.

The Indirect Effect of Prefrontal Gray Matter Volume on Suicide Attempts among Individuals with Major Depressive Disorder.

Trait impulsivity is a known risk factor for suicidality, and the prefrontal cortex plays a key role in impulsivity and its regulation. However, the relationship between trait impulsivity, neural basis, and suicidality has been inconsistent. Therefore, this study aimed to explore the relationship between impulsivity and its structural correlates (prefrontal gray matter volume), suicidal ideation, and actual suicide attempts. A total of 87 individuals with major depressive disorder participated in study, and the gray matter volume of the prefrontal regions was extracted from T1 images based on region of interest masks. The variables for the mediation models were selected based on correlation analysis and tested for their ability to predict suicide attempts, with impulsivity and suicidal ideation as the mediation variables and gray matter volume as the independent variable. A significant correlation was observed between suicidal ideation and the left dorsolateral prefrontal cortex and right dorsomedial prefrontal cortex. The dual-mediation model revealed a significant indirect relationship between gray matter volume in both regions and suicide attempts mediated by motor impulsivity and suicidal ideation. The counterintuitive positive relationship between gray matter volume and suicidality was also discussed.

Pregnancy and miscarriage predict suicide attempts but not substance use among dual-systems involved female adolescents

BackgroundTo examine the associations between adolescent pregnancy and pregnancy outcomes on substance use and suicide attempts in a sample who is at greater risk for substance use and suicide attempts — those who have been involved with the juvenile justice and child welfare systems. MethodsUsing a prospective, longitudinal design, we examined the role of adolescent pregnancy outcomes on risk for suicide attempts and substance use among a sample of 166 female adolescents with juvenile justice system and child welfare involvement. ResultsOf participants, 36% (n = 60) reported at least one adolescent pregnancy with a total of 109 pregnancies reported. Adolescent pregnancy was associated with an increase in later suicide attempts (aOR = 1.68, 95% CI 1.06–2.72). Miscarriage was associated with a 2-fold increase in the likelihood of later suicide attempts, (aOR = 2.12, 95% CI 1.10–4.12). No participants who reported induced abortion (n = 13) reported suicide attempts. Adolescent pregnancy, miscarriage, and abortion were not significantly associated with later substance use (Ps > 0.05). ConclusionsHealthcare professionals should conduct routine screening for suicidality in the months following a miscarriage, offer education to caregivers about how to support youth who experience pregnancy loss, provide additional social supports and familiarize themselves with local and virtual behavioral health resources to prevent suicide attempts among female adolescents who are at high risk and experience miscarriage.

The influence of personality disorder in predicting suicidal behaviour in common mental disorders: A 30-year study.

Two hundred ten patients with anxiety and depressive disorders were followed up over 30 years. Personality status was assessed at baseline using the Personality Assessment Schedule (PAS), an instrument that classifies personality disorder in a similar way to the new ICD‐11 classification. Assessments of suicidal behaviour were made at 5, 12 and 30 years and suicidal thoughts at 12 and 30 years and analysed by personality status, clinical diagnosis and scores on the General Neurotic Syndrome Scale, a combined diagnosis of mixed anxiety depression and personality dysfunction. Suicide attempts were most frequent in the first 5 years of the study and reduced over time. Baseline personality status was the best predictor of suicide attempts at 5 years (no personality disorder 29.3%, personality disorder 51.6%, p = 0.006), and at 12 years (no personality disorder 11.9%, personality disorder 25.7%, p = 0.042), but no important differences were found at 30 years, when comorbid mental state disorder was the strongest predictor (p < 0.001). Similar but less marked findings were found for the general neurotic syndrome. It is concluded that the presence of personality disorder is a robust predictor of suicidal behaviour in the shorter term but in the long‐term comorbid pathology is a better predictor.

Opioid-related variables did not improve suicide risk prediction models in samples with mental health diagnoses.

Suicide risk prediction models derived from machine learning of electronic health records and insurance claims are an innovation in suicide prevention. Some models do not include opioid-related variables despite the relationship between opioids and suicide. This study evaluated whether inclusion of opioid-related variables improved suicide risk prediction models developed by the Mental Health Research Network. Approximately 630 opioid-related variables and interactions terms were introduced into existing suicide prediction models run in datasets of patient visits in mental health care (n = 27,755,401 visits) or primary care when a mental health diagnosis was given (n = 19,340,461 visits). Training and validation datasets were created. LASSO regression with 10-fold validation identified variables to be added to the models. The new models predicting suicide attempts and suicide deaths in the mental health specialty visit sample performed as well as the existing models (new C-statistic for attempts model = 0.855, CI: 0.853-0.857 versus original C-statistic = 0.851, CI 0.848-0.853; death model = 0.868, CI: 0.856-0.879 versus 0.861, CI 0.848-0.875). The new model for suicide death in the primary care sample improved (0.855, CI: 0.837-0.874 versus 0.833, CI 0.813-0.853) while performance of the new model for suicide attempt in that sample degraded (0.843, CI: 0.839-0.847 versus 0.853, CI 0.849-0.857). Analyses did not include patients without recent care, data did not include illicit opioid use or unrecognized opioid use disorder. Among patients with mental health diagnoses, inclusion of opioid-related variables did not improve prediction of suicide risk beyond mental health predictors.

Predictors of Suicide Attempt among Middle School Students with Suicidal Ideation: Analysis of Data from the 15th (2019) Korea Youth Risk Behavior Web-based Survey

Purpose: This study aimed to identify the factors influencing suicide attempts among middle school students with suicidal ideation.Methods: Data were from the 2019 Youth Health Risk Behavior Web-based survey collected by the Korea Centers for Disease Control and Prevention. The data were analyzed using the SPSS program.Results: Participants were 29,384 middle school students, there were 14.1% of suicide ideation, and 22.2% of them attempted suicide. Among the students with suicidal thoughts, suicide attempts were higher in those who had experiences of alcohol drinking, smoking, substance abuse, and sexual intercourse.Conclusion: Therefore, to prevent suicide accidents among middle school students, there is a need for strategies that would reduce problem behavior such as alcohol drinking, smoking, sexual intercourse, and substance abuse. For middle school students who have already experienced problem behavior, efficient plans should be established for screening, prevention, and treatment of the high-risk groups in suicide attempts.

Validating a predictive algorithm for suicide risk with Alaska Native populations.

The American Indian/Alaska Native (AI/AN) suicide rate in Alaska is twice the state rate and four times the U.S. rate. Healthcare systems need innovative methods of suicide risk detection. The Mental Health Research Network (MHRN) developed suicide risk prediction algorithms in a general U.S. We applied MHRN predictors and regression coefficients to electronic health records of AI/AN patients aged ≥13years with behavioral health diagnoses and primary care visits between October 1, 2016, and March 30, 2018. Logistic regression assessed model accuracy for predicting and stratifying risk for suicide attempt within 90days after a visit. We compared expected to observed risk and assessed model performance characteristics. 10,864 patients made 47,413 primary care visits. Suicide attempt occurred after 589 (1.2%) visits. Visits in the top 5% of predicted risk accounted for 40% of actual attempts. Among visits in the top 0.5% of predicted risk, 25.1% were followed by suicide attempt. The best fitting model had an AUC of 0.826 (95% CI: 0.809-0.843). The MHRN model accurately predicted suicide attempts among AI/AN patients. Future work should develop clinical and operational guidance for effective implementation of the model with this population.

The role of pain, hopelessness, belonging, and suicide capacity in predicting suicide attempt in people with psychiatric disorders

Background. The idea and attempt of suicide are highly predictive of deaths due to suicide and can lead to several negative consequences for both the individual and his family and for society. Therefore, this study was conducted with the aim of the role of pain, hopelessness, belonging and suicidal capacity in predicting suicide attempt in people with psychiatric disorders. Methods. The research method of this study was correlational and the statistical population included all individuals referred to psychiatric outpatient clinics of Razi Hospital in Tabriz in 2020-2021. Sample sizes According to Klein criterion and according to the 62-item questionnaire, 298 subjects were selected. Research tools also include the Suicide Attempt Scale, the Suicide Capacity Scale and to examine the three variables of pain, hopelessness and belonging to the Suicide Motivation Questionnaire were used. Structural equation modeling was used to analyze the data using Smart pls software version 2. Results. In this study, 63.3% of the respondents were men and 36.7% of the respondents were women. The mean and standard deviation of the age of the respondents was 37.26±10.88 years. According to the results of the path coefficients between hopelessness with suicide capacity (β= 0.63), sense of belonging with suicide capacity (β= 0.28) and suicide attempt (β= 0.21), suicide capacity with suicide attempt (β= 0.59) were at a significant level (P&lt;0.05). On the other hand, suicidal capacity had a significant mediating role in the relationship between hopelessness and sense of belonging with suicide attempt. Conclusion. The results showed that the three-step model of suicide has the ability to predict suicide attempt in the community of patients with psychiatric disorders. Practical Implications. The results of this study are very important for professionals who work with people with psychiatric disorders to distinguish the idea of suicide from suicide attempt.

Predicting the risk of suicide attempt in a depressed population: Development and assessment of an efficient predictive nomogram

The purpose of this study was to develop and validate a user-friendly suicide attempt risk nomogram in depression, supporting timely interventions by clinicians. We collected clinical data of 273 depressed patients from January 2020 to January 2021. Suicide attempt was assessed conducting the Mini International Neuropsychiatric Interview. First, optimized features were filtrated through the least absolute shrinkage and selection operator regression analysis. Subsequently, we selected variables with nonzero coefficients and entered them into multiple logistic regression model and nomogram function to construct a visual predicting suicide attempt model. Additionally, the C-index, calibration plot and decision curve analysis, were applied to assess discrimination, calibration, and clinical practicability. Finally, the bootstrapping validation was applied to assess internal validation. Finally, eleven clinical features are screened out in the prediction nomogram. The model presented tiptop calibration and pleasant discrimination with a C-index of 0.853. A towering C-index value, up to 0.799, could also be attained in the interval validation analysis. In addition, decision curve analysis exhibited that our predictive model is clinically effective when the threshold is no less than 1%. These results demonstrate this predictive model was helpful for clinicians assessing the inpatient's suicide attempt recently and implementing individualized treatment strategies.

Prediction of Suicide Attempts Using Clinician Assessment, Patient Self-report, and Electronic Health Records

Half of the people who die by suicide make a health care visit within 1 month of their death. However, clinicians lack the tools to identify these patients. To predict suicide attempts within 1 and 6 months of presentation at an emergency department (ED) for psychiatric problems. This prognostic study assessed the 1-month and 6-month risk of suicide attempts among 1818 patients presenting to an ED between February 4, 2015, and March 13, 2017, with psychiatric problems. Data analysis was performed from May 1, 2020, to November 19, 2021. Suicide attempts 1 and 6 months after presentation to the ED were defined by combining data from electronic health records (EHRs) with patient 1-month (n = 1102) and 6-month (n = 1220) follow-up surveys. Ensemble machine learning was used to develop predictive models and a risk score for suicide. A total of 1818 patients participated in this study (1016 men [55.9%]; median age, 33 years [IQR, 24-46 years]; 266 Hispanic patients [14.6%]; 1221 non-Hispanic White patients [67.2%], 142 non-Hispanic Black patients [7.8%], 64 non-Hispanic Asian patients [3.5%], and 125 non-Hispanic patients of other race and ethnicity [6.9%]). A total of 137 of 1102 patients (12.9%; weighted prevalence) attempted suicide within 1 month, and a total of 268 of 1220 patients (22.0%; weighted prevalence) attempted suicide within 6 months. Clinicians' assessment alone was little better than chance at predicting suicide attempts, with externally validated area under the receiver operating characteristic curve (AUC) of 0.67 for the 1-month model and 0.60 for the 6-month model. Prediction accuracy was slightly higher for models based on EHR data (1-month model: AUC, 0.71; 6 month model: AUC, 0.65) and was best using patient self-reports (1-month model: AUC, 0.76; 6-month model: AUC, 0.77), especially when patient self-reports were combined with EHR and/or clinician data (1-month model: AUC, 0.77; and 6 month model: AUC, 0.79). A model that used only 20 patient self-report questions and an EHR-based risk score performed similarly well (1-month model: AUC, 0.77; 6 month model: AUC, 0.78). In the best 1-month model, 30.7% (positive predicted value) of the patients classified as having highest risk (top 25% of the sample) made a suicide attempt within 1 month of their ED visit, accounting for 64.8% (sensitivity) of all 1-month attempts. In the best 6-month model, 46.0% (positive predicted value) of the patients classified at highest risk made a suicide attempt within 6 months of their ED visit, accounting for 50.2% (sensitivity) of all 6-month attempts. This prognostic study suggests that the ability to identify patients at high risk of suicide attempt after an ED visit for psychiatric problems improved using a combination of patient self-reports and EHR data.

Predicting suicide attempts among U.S. Army soldiers after leaving active duty using information available before leaving active duty: results from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS).

Suicide risk is elevated among military service members who recently transitioned to civilian life. Identifying high-risk service members before this transition could facilitate provision of targeted preventive interventions. We investigated the feasibility of doing this by attempting to develop a prediction model for self-reported suicide attempts (SAs) after leaving or being released from active duty in the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS). This study included two self-report panel surveys (LS1: 2016–2018, LS2: 2018–2019) administered to respondents who previously participated while on active duty in one of three Army STARRS 2011–2014 baseline self-report surveys. We focus on respondents who left active duty >12 months before their LS survey (n=8899). An ensemble machine learning model using predictors available prior to leaving active duty was developed in a 70% training sample and validated in a 30% test sample. The 12-month self-reported SA prevalence (SE) was 1.0% (0.1). Test sample AUC (SE) was .74 (.06). The 15% of respondents with highest predicted risk included nearly two-thirds of 12-month SAs and over 80% of medically serious 12-month SAs. These results show that it is possible to identify soldiers at high post-transition self-report SA risk before the transition. Future model development is needed to examine prediction of SAs assessed by administrative data and using surveys administered closer to the time of leaving active duty.

Moral injury and peri- and post-military suicide attempts among post-9/11 veterans.

Our goal was to examine the association between moral injury, mental health, and suicide attempts during military service and after separation by gender in post-9/11 veterans. A nationally representative sample of 14057 veterans completed a cross-sectional survey. To examine associations of exposure to potentially morally injurious events (PMIEs; witnessing, perpetrating, and betrayal) and suicidal self-directed violence, we estimated two series of multivariable logistic regressions stratified by gender, with peri- and post-military suicide attempt as the dependent variables. PMIE exposure accounted for additional risk of suicide attempt during and after military service after controlling for demographic and military characteristics, current mental health status, and pre-military history of suicidal ideation and attempt. Men who endorsed PMIE exposure by perpetration were 50% more likely to attempt suicide during service and twice as likely to attempt suicide after separating from service. Men who endorsed betrayal were nearly twice as likely to attempt suicide during service; however, this association attenuated to non-significance after separation in the fully adjusted models. In contrast, women who endorsed betrayal were over 50% more likely to attempt suicide during service and after separation; PMIE exposure by perpetration did not significantly predict suicide attempts before or after service among women in the fully adjusted models. Our findings indicate that suicide assessment and prevention programs should consider the impact of moral injury and attend to gender differences in this risk factor in order to provide the most comprehensive care.

Service-Connected Disabilities and Suicide Attempts in Veterans: The Moderating Role of Mental Health Care Utilization

United States veteran suicide rates have increased over the past two decades. Designations of service-connected disabilities (designations tied to injury during military service) are also increasing, especially those associated with mental health disorders. However, recent research around disability and suicide in veterans is mixed, and no research has been completed on the association between disability and mental health service utilization. The current study hoped to fill these gaps in the literature with a secondary data analysis of a sample of 36,048 Veterans Healthcare Administration (VHA) veterans. Mental health disorders and demographics were controlled for in a logistic regression model predicting suicide attempt status by the intersection of service-connected disability and mental health care utilization. Mental health service visits moderated the positive relationship between service-connected disability designations and suicide attempts; those who utilized services were less likely to attempt suicide, especially those at higher service-connected disability designations with mental health disorders. The results suggest individuals who have disability designations that also seek help are less likely to make a suicide attempt. The study was limited by scope of the sample (only VHA veterans with service connected disabilities). Results have implications for preventative interventions in the VHA/Veterans Benefits Administration.

Adverse Childhood Experiences and Suicidality and Self-Harm in Persons in Secure Forensic Care.

Prior research suggests a greater degree of suicidality and self-harm behavior in those involved with criminal justice and forensic mental health systems. Such individuals also evidence increased exposure to early childhood adversity, which is often associated with suicide risk. Other significant predictors of suicidality have been noted within forensic populations, however, including indicators of specific psychopathology and situational and demographic factors. These populations present with overlapping risk factors that remain underexamined. In the current study, 182 persons residing in secure forensic psychiatric care following incidents of illegal and aggressive behavior were evaluated. Adverse childhood experiences and other empirically derived potential predictors of suicide attempts and self-harm were examined via binomial logistic regression. Findings indicate frequent experiences of early adversity across participants, and that a combination of race, individual adverse childhood experiences, number of biological children, and diagnoses of either posttraumatic stress disorder or borderline personality disorder were significant predictors of suicide attempts, self-harm behavior, and first hospitalization resulting from a suicide attempt. Clinical and research implications are discussed.

Predictors of suicide attempts in male UK gamblers seeking residential treatment

BackgroundDisordered gambling can have serious negative consequences for the individual and those around them. Previous research has indicated that disordered gamblers are at an increased risk of suicidal thoughts, ideation and attempts. The current study sought to utilise data from a clinical sample to identify factors that are associated with prior suicide attempts. MethodsThe sample included 621 patients entering a gambling-specific residential facility in the UK. A series of Chi-Square analyses and binary logistic regressions were run to identify clinical and sociodemographic variables associated with suicide attempts. ResultsOf the 20 variables analysed using Chi-square statistics, five were significantly associated with the outcome variable (lifetime attempted suicide): loss of family relationships, loss of home, prior depression, prior suicidal thoughts, and medication use. Regression analysis showed that individuals were more likely to have reported suicide attempts if they had experienced loss of family relationships (1.65 times), loss of a home (1.87 times), prior depression (3.2 times), prior suicidal thoughts (6.14 times), or were taking medication (1.95 times) compared to those not reporting such individual events. ConclusionsDisordered gamblers are vulnerable to suicide; a number of factors have been identified in the current study that predict an increased likelihood of attempted suicide. The factors mainly revolve around loss: not financial loss, but rather disintegration of an individual’s support network and deterioration in the individual’s mental health. Findings indicate that isolation and negative affect associated with gambling are most influential in attempted suicide and should therefore be more strongly considered when creating and providing the legislative, educational and treatment environments for those experiencing gambling related harm.

Comparison of the factors for suicidal ideation and suicide attempt: a comprehensive examination of stress, view of life, mental health, and alcohol use.

This study was performed to examine the elements that cause suicidal ideation to develop into a suicide attempt by comparing the factors related to suicidal ideation and attempt. The subjects in the study were 5982 employees, who received mental health screening from January 2016 to December 2019 in Korea. Multivariate binary logistic regression analysis was performed with suicidal ideation and suicide attempt as dependent variables respectively. While suicidal ideation was associated with both moderate and severe grades of depression and alcohol consumption, only severe grades of depression and alcohol consumption were associated with suicide attempts. Among family, interpersonal, work-related, and financial stress, which were significant predictors of suicidal ideation, only family stress predicted suicide attempts. Whereas dissatisfaction with the present, regret for the past, and hopelessness for the future were all predictors for suicidal ideation, only regret for the past was a significant predictor of suicide attempts. The distinctive impact of family stress on suicide attempts suggests that family support can play a pivotal role in suicide prevention, and the significant impact of regret for the past on suicide attempts indicates the need for a cognitive approach ina high-risk population. Finally, the substantial impact of alcohol on suicide attempts compared to suicidal ideation suggests the importance of alcohol regulation in suicide prevention.

Criminalising Mental Disorder-Induced Attempted Suicide in Malaysia: Breaking the Silence

Every 40 years, a person commits suicide somewhere in the world. Suicide claims the lives of over 800,000 individuals each year, accounting for about 1.4 percent of all deaths globally. In this spectrum, mental disorders are among the strongest predictors of suicide attempts with depression, substance abuse, and psychosis being the most common risk factors. Regardless of suicides being an unprecedented epidemic in the society, Malaysia is one of the few which remains the archaic law in statutes, that criminalises suicide and punishes anyone who attempts or commits any act leading to the commission of such an offence with a sentence of one year in prison, a fine, or both. The present research thus aims at highlighting the challenges of prosecuting attempted suicides in Malaysia based on the attitude of the judiciary, thus addressing the weaknesses of Section 309 of the Penal Code of which the provision for criminalising suicide rests. Employing the doctrinal research methodology, systematic means of legal reasoning based on statutory materials, conventional legal theories, and related case law pertinent to the criminalising of attempted suicide in Malaysia are produced. In dealing with issues as intricate as suicides and mental disorder, the present research argues that the focus should be to develop a regulatory framework that facilitate access to appropriate care in a professional and sensitive manner instead of punishment.