Warning signs in a period of acute risk for suicide attempt: The utility of count- and combination-based classification.

OBJECTIVE: This study sought to establish if models involving the specific combinations of identifiable behavioral warning signs (WS; i.e., alcohol use, suicidal communications, preparation of personal affairs, experiencing negative interpersonal life events) for a suicide attempt outperformed a simpler count model of WS to distinguish an acute risk period (the six hours prior to a suicide attempt) from a control period (a matched six-hour period the day prior). METHOD: Generalized linear mixed models tested all logical combinations of four behavioral WS in addition to a count variable of the number of behavioral warning signs. For the count variable, receiver operating characteristic curve analysis was utilized to determine the optimal cut point for the number of endorsed WS. RESULTS: Area under the curve (AUC) compared classification across all models, with the count model demonstrating similar classification performance to the best multivariate model (AUCs of 0.72 and 0.73, respectively), with an optimal cut point of endorsing one or more WS. CONCLUSION: Although determinations of acute risk should be informed by multiple sources of information, this study suggests a relatively simple count-based approach that considers the presence of one (or more) behavioral WS may be used as a potential indication of increased acute risk for suicide attempt.

[Utility of the classification analysis in the typology of the the suicide attempt in a hospital population.] / Utilidad del análisis de clasificación en la tipología del intento de suicidio en una población hospitalaria.

OBJECTIVE: Subjects who attempt suicide are not a homogeneous group. Numerous studies accredit different subtypes of individuals with suicide attempts. One of the main applications of classification analysis is the segmentation and selection of the subject's characteristics. The objective of this study is to identify groups of subjects with a suicide attempt and to discover the relationships between them in the hospital population of an area of the Community of Madrid. METHODS: In a case-control study, the classification tree technique based on the CHAID (Chi-square automatic interaction detector) algorithm, included in the SPSS 23.0 program, was applied to a sample of 201 subjects admitted to a highly complex hospital of Madrid. Impulsiveness, couple conflict, psychiatric history and depression were evaluated. RESULTS: Three subtypes or differentiable profiles of the subject related to the suicide attempt have been obtained, (high profile 144 cases 71.64%, medium 35 cases 17.41% and low 22 cases 10.94% of basic risk patterns) with high application value to the clinical setting. CONCLUSIONS: The typologies found allow us to adapt preventive measures on the suicide attempt and carry out focused clinical interventions of a preventive and predictive nature.

OBJETIVO: Las personas que intentan suicidarse no constituyen un grupo homogéneo. Numerosos estudios acreditan distintos subtipos de individuos con intentos de suicidio. Una de las principales aplicaciones del análisis de clasificación es la segmentación y selección de las características del sujeto. El objetivo de este estudio fue identificar grupos de sujetos con intentos de suicidio y descubrir las relaciones entre ellos en la población hospitalaria de un área de la Comunidad de Madrid. METODOS: En un estudio de caso-control se aplicó la técnica de árbol de clasificación basado en el algoritmo CHAID (Chi-square automatic interaction detector), incluido en el programa SPSS 23.0, sobre una muestra de 201 sujetos ingresados en un hospital de alta complejidad de Madrid. Se evaluaron la impulsividad, la conflictividad de pareja, los antecedentes psiquiátricos y la depresión. RESULTADOS: Se obtuvieron tres subtipos o perfiles diferenciables del sujeto vinculados al intento de suicidio (perfil alto 144 casos 71,64%, medio 35 casos 17,41% y bajo 22 casos 10,94% de patrones básicos de riesgo), con alto valor de aplicación al ámbito clínico. CONCLUSIONES: Las tipologías encontradas permiten adecuar medidas preventivas sobre el intento de suicidio y realizar intervenciones clínicas focalizadas de carácter preventivo y predictor.

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Selection of Clinical Text Features for Classifying Suicide Attempts.

Research has demonstrated cohort misclassification when studies of suicidal thoughts and behaviors (STBs) rely on ICD-9/10-CM diagnosis codes. Electronic health record (EHR) data are being explored to better identify patients, a process called EHR phenotyping. Most STB phenotyping studies have used structured EHR data, but some are beginning to incorporate unstructured clinical text. In this study, we used a publicly-accessible natural language processing (NLP) program for biomedical text (MetaMap) and iterative elastic net regression to extract and select predictive text features from the discharge summaries of 810 inpatient admissions of interest. Initial sets of 5,866 and 2,709 text features were reduced to 18 and 11, respectively. The two models fit with these features obtained an area under the receiver operating characteristic curve of 0.866-0.895 and an area under the precision-recall curve of 0.800-0.838, demonstrating the approach's potential to identify textual features to incorporate in phenotyping models.

Characteristics of a First Suicide Attempt that Distinguish Between Adolescents Who Make Single Versus Multiple Attempts.

Although a history of a suicide attempt is the strongest predictor of future suicide attempts, not all adolescents who make an attempt engage in repetitive suicidal behavior. The present study sought to determine whether certain characteristics of a first suicide attempt (e.g., age of first attempt, method of attempt used, intent seriousness, medical lethality, and receipt of treatment after attempt) can distinguish between adolescents who make single versus multiple suicide attempts. Adolescents (N = 95) who were psychiatrically hospitalized and their guardian completed a diagnostic interview to gather information on all lifetime suicide attempts. A multivariate hierarchical logistic regression was conducted, predicting single attempt versus multiple attempt status. Of the first-attempt characteristics examined, only age of first attempt, OR = 0.33, 95% CI [0.17-0.63], p = .001, and receipt of treatment following attempt, OR = 0.28, 95% CI [0.09-0.88], p = .028, significantly distinguished SA vs. MA status, even after controlling for current age and depression at the time of first attempt. Female and White participants were overrepresented in this sample, which limits generalization to more heterogenous and diverse samples. The cross-sectional nature of data introduces the potential for retrospective recall bias. Younger age of first attempt and lack of receipt of mental health treatment following a first attempt were associated with multiple attempt status. These findings highlight the importance of early mental health screening, parental psychoeducation, and linkage to mental health care after a suicide attempt.

Suicidal and self-harm presentations to Emergency Departments: The challenges of identification through diagnostic codes and presenting complaints.

BACKGROUND: The accuracy of data on suicide-related presentations to Emergency Departments (EDs) has implications for the provision of care and policy development, yet research on its validity is scarce. OBJECTIVE: To test the reliability of allocation of ICD-10 codes assigned to suicide and self-related presentations to EDs in Queensland, Australia. METHOD: All presentations due to suicide attempts, non-suicidal self-injury (NSSI) and suicidal ideation between 1 July 2017 and 31 December 2017 were reviewed. The number of presentations identified through relevant ICD-10-AM codes and presenting complaints in the Emergency Department Information System were compared to those identified through an application of an evolutionary algorithm and medical record review (gold standard). RESULTS: A total of 2540 relevant presentations were identified through the gold standard methodology. Great heterogeneity of ICD-10-AM codes and presenting complaints was observed for suicide attempts (40 diagnostic codes and 27 presenting complaints), NSSI (27 and 16, respectively) and suicidal ideation (38 and 34, respectively). Relevant ICD codes applied as primary or secondary diagnosis had very low sensitivity in detecting cases of suicide attempts (18.7%), NSSI (38.5%) and suicidal ideation (42.3%). A combination of ICD-10-AM code and a relevant presenting complaint increased specificity, however substantially reduced specificity and positive predictive values for all types of presentations. ED data showed bias in detecting higher percentages of suicide attempts by Indigenous persons (10.1% vs. 6.9%) or by cutting (28.1% vs. 10.3%), and NSSI by female presenters (76.4% vs. 67.4%). CONCLUSION: Suicidal and self-harm presentations are grossly under-enumerated in ED datasets and should be used with caution until a more standardised approach to their formulation and recording is implemented.

Comparing Suicide Risk Factors Among Individuals with a History of Aborted, Interrupted, and Actual Suicide Attempts.

Recent standardized nomenclature has suggested distinctions among aborted, interrupted, and actual suicide attempts. This study examined differences in self-reported symptoms among individuals with a history of aborted, interrupted, and actual suicide attempts. 167 young adults with a history of suicidality completed self-report measures of suicide attempt history and current symptoms, a clinical interview assessing past suicidal behavior, and a pain tolerance task. Only 78.8% of participants who initially reported a suicide attempt history were classified as suicide attempters following the clinical interview. Individuals who reported only aborted attempts during the clinical interview reported less severe clinical symptoms than those reporting a history of at least one actual attempt. Individuals with a history of actual suicide attempts may represent a more clinically severe group than those with a history of aborted attempts only.

Suicide and all-cause mortality in a high-risk cohort: A latent class approach.

OBJECTIVE: To use latent class analysis to group patients consulted to an emergency psychiatry consultation service and assess occurrence of suicide attempts and all-cause mortality across groups. METHOD: Latent class analysis was used to classify individuals assessed by psychiatry in the emergency department of the two teaching hospitals in Winnipeg, Canada. A second latent class analysis was done on individuals presenting with a suicide attempt. Indicators variables included a variety of clinically assessed factors, such as presentation suicidality and occurrence of anxiety/depression/psychosis, and prior medical treatment. Two post-treatment indicators were used; suicide attempt hospitalizations and all-cause mortality within 12 months of assessment. RESULTS: Latent class analysis identified 8 classes for all presentations (n = 5292) and 3 classes for the attempter subgroup (n = 730). Although there is considerable overlap in indicators among the classes certain indicators differentiated between the groups: suicide attempt presentation, prior psychiatric treatment, psychotropic medication polypharmacy, childhood abuse, and addictions. Although the presence of deaths and future attempts varied between the identified groups, there were no groups with a >10% proportion of individuals with either of these outcomes. CONCLUSIONS: Potential exists for latent class-based assessments, but additional samples with better indicators are needed.

Contemporary Classifications of Suicidal Behaviors.

Background: The absence of agreed-upon terminology, definitions, and operational classifications has hampered research in the field of suicidology for many decades. Aims and Method: We systematically reviewed contemporary classifications of suicidal behavior using the scope of the classification (comprehensive vs. restricted or single behaviors), and the presence or absence of a classification scheme and an operational definition of intent as features to enable analysis and comparison. Results: A chronological perspective shows that classification systems tend to be more and more precise and operational for clinical and research field work. However, on an international level, the development of classifications appears to precede the establishment of agreed-upon definitions and terms to describe suicidal behavior. Limitations: The review was conducted in English only. Conclusion: Universal agreement on definitions and terms for suicidal behavior should precede the development of classifications.

Utilidad del análisis de clasificación en la tipología del intento de suicidio en una población hospitalaria / Utility of the classification analysis in the typology of the the suicide attempt in a hospital population

OBJETIVO: Las personas que intentan suicidarse no constituyen un grupo homogéneo. Numerosos estudios acreditan distintos subtipos de individuos con intentos de suicidio. Una de las principales aplicaciones del análisis de clasificación es la segmentación y selección de las características del sujeto. El objetivo de este estudio fue identificar grupos de sujetos con intentos de suicidio y descubrir las relaciones entre ellos en la población hospitalaria de un área de la Comunidad de Madrid. MÉTODOS: En un estudio de caso-control se aplicó la técnica de árbol de clasificación basado en el algoritmo CHAID (Chi-square automatic interaction detector), incluido en el programa SPSS 23.0, sobre una muestra de 201 sujetos ingresados en un hospital de alta complejidad de Madrid. Se evaluaron la impulsividad, la conflictividad de pareja, los antecedentes psiquiátricos y la depresión. RESULTADOS: Se obtuvieron tres subtipos o perfiles diferenciables del sujeto vinculados al intento de suicidio (perfil alto 144 casos 71,64%, medio 35 casos 17,41% y bajo 22 casos 10,94% de patrones básicos de riesgo), con alto valor de aplicación al ámbito clínico. CONCLUSIONES: Las tipologías encontradas permiten adecuar medidas preventivas sobre el intento de suicidio y realizar intervenciones clínicas focalizadas de carácter preventivo y predicto

OBJECTIVE: Subjects who attempt suicide are not a homogeneous group. Numerous studies accredit different subtypes of individuals with suicide attempts. One of the main applications of classification analysis is the segmentation and selection of the subject's characteristics. The objective of this study is to identify groups of subjects with a suicide attempt and to discover the relationships between them in the hospital population of an area of the Community of Madrid. METHODS: In a case-control study, the classification tree technique based on the CHAID (Chi-square automatic interaction detector) algorithm, included in the SPSS 23.0 program, was applied to a sample of 201 subjects admitted to a highly complex hospital of Madrid. Impulsiveness, couple conflict, psychiatric history and depression were evaluated. RESULTS: Three subtypes or differentiable profiles of the subject related to the suicide attempt have been obtained, (high profile 144 cases 71.64%, medium 35 cases 17.41% and low 22 cases 10.94% of basic risk patterns) with high application value to the clinical setting. CONCLUSIONS: The typologies found allow us to adapt preventive measures on the suicide attempt and carry out focused clinical interventions of a preventive and predictive nature

[Risk factors for suicide attempts in people with depressive disorders treated in secondary health care]. / Factores de riesgo para intento de suicidio en personas con trastorno depresivo en atención secundaria.

BACKGROUND: Depression is the most common psychiatric disorder in people with suicidal behavior. The knowledge of its risk factors should help to design preventive strategies. AIM: To describe suicidal behavior and risk factors for attempted suicide in people with major depressive disorders (MDD). MATERIAL AND METHODS: A 12-month follow-up study was conducted in 112 outpatients at three psychiatric care centers of Ñuble, Chile, with baseline and quarterly assessments. Demographic, psychosocial and clinical factors as potential risk factors of suicide attempts, were assessed. A clinical interview with DSM-IV diagnostic criteria checklist, Hamilton Depression Scale and the List of Threatening Experiences and Multidimensional Scale of Perceived Social Support were applied. RESULTS: Sixty seven percent of participants had suicidal ideation and 43.8% had attempted suicide. Suicide risk was significantly higher in participants with a single major depressive episode (odds ratio [OR] = 3.98; 95% confidence intervals [CI] = 1,29-12,32 p = 0.02) and those with previous suicide attempts (OR = 13.15; 95% CI = 3,87-44.7 p < 0.01). Young age, not having a partner, being unemployed, having a severe major depressive episode, having psychotic symptoms, having a personality disorder and being devoid of medical illness increased the risk of suicide attempts, but they did not reach statistical significance. CONCLUSIONS: Significant risk factors should be specially considered when designing suicide preventive strategies in patients with MDD.

Factores de riesgo para intento de suicidio en personas con trastorno depresivo en atención secundaria / Risk factors for suicide attempts in people with depressive disorders treated in secondary health care

Background: Depression is the most common psychiatric disorder in people with suicidal behavior. The knowledge of its risk factors should help to design preventive strategies. Aim: To describe suicidal behavior and risk factors for attempted suicide in people with major depressive disorders (MDD). Material and Methods: A 12-month follow-up study was conducted in 112 outpatients at three psychiatric care centers of Ñuble, Chile, with baseline and quarterly assessments. Demographic, psychosocial and clinical factors as potential risk factors of suicide attempts, were assessed. A clinical interview with DSM-IV diagnostic criteria checklist, Hamilton Depression Scale and the List of Threatening Experiences and Multidimensional Scale of Perceived Social Support were applied. Results: Sixty seven percent of participants had suicidal ideation and 43.8% had attempted suicide. Suicide risk was significantly higher in participants with a single major depressive episode (odds ratio [OR] = 3.98; 95% confidence intervals [CI] = 1,29-12,32 p = 0.02) and those with previous suicide attempts (OR = 13.15; 95% CI = 3,87-44.7 p < 0.01). Young age, not having a partner, being unemployed, having a severe major depressive episode, having psychotic symptoms, having a personality disorder and being devoid of medical illness increased the risk of suicide attempts, but they did not reach statistical significance. Conclusions: Significant risk factors should be specially considered when designing suicide preventive strategies in patients with MDD.

Are Gender Differences in DSM-5 PTSD Symptomatology Explained by Sexual Trauma?

Although many studies have assessed gender differences in posttraumatic stress disorder (PTSD) prevalence, few examine individual PTSD symptoms (PTSSs). Hypothesizing that trauma differences explain many gender differences in symptomatology, this is the first known study to adjust PTSSs for trauma type, and to compare gender differences in those with sexual traumas. Using a cross-sectional survey methodology in a sample of adult outpatients (n = 775), we examined gender, trauma type, PTSSs, suicide, alcohol, and tobacco. Among those with trauma (n = 483), women generally had more severe symptoms than men, but after adjusting for trauma type, only physical reactivity (p = .0002), excessive startle (p = .0005), external avoidance (p = .0007), internal avoidance (p = .0008), psychological reactivity (p = .0009), and suicide attempts (p = .001) remained significantly worse among women, whereas men more commonly reported alcohol problems (p = .007). Among those with PTSD (n = 164), there were no significant PTSS gender differences. Those with sexual trauma had worse symptoms (particularly amnesia) compared with non-sexual trauma (p < .0001 for PTSD diagnosis and total severity), including within each gender. Among those with sexual trauma (n = 157), men had worse recklessness (p = .004) and more commonly reported tobacco (p = .02), whereas women more commonly attempted suicide (p = .02) and had worse avoidance (p = .04). However, when isolating the effects of sexual trauma beyond other traumas, there were no significant symptom difference-in-differences between genders. Our findings suggest that, while women have higher PTSD rates, men with PTSD present similarly. In addition, while women have higher sexual trauma rates, men may have similarly severe responses. Most gender differences in PTSD presentation appear to be explained by trauma type, particularly women having higher rates of sexual trauma. We discuss potential biopsychosocial explanations.

Issues in Developing a Surveillance Case Definition for Nonfatal Suicide Attempt and Intentional Self-harm Using International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) Coded Data.

Suicide and intentional self-harm are among the leading causes of death in the United States. To study this public health issue, epidemiologists and researchers often analyze data coded using the International Classification of Diseases (ICD). Prior to October 1, 2015, health care organizations and providers used the clinical modification of the Ninth Revision of ICD (ICD-9-CM) to report medical information in electronic claims data. The transition in October 2015 to use of the clinical modification of the Tenth Revision of ICD (ICD-10-CM) resulted in the need to update methods and selection criteria previously developed for ICD-9-CM coded data. This report provides guidance on the use of ICD-10-CM codes to identify cases of nonfatal suicide attempts and intentional self-harm in ICD-10-CM coded data sets. ICD-10-CM codes for nonfatal suicide attempts and intentional self-harm include: X71-X83, intentional self-harm due to drowning and submersion, firearms, explosive or thermal material, sharp or blunt objects, jumping from a high place, jumping or lying in front of a moving object, crashing of motor vehicle, and other specified means; T36-T50 with a 6th character of 2 (except for T36.9, T37.9, T39.9, T41.4, T42.7, T43.9, T45.9, T47.9, and T49.9, which are included if the 5th character is 2), intentional self-harm due to drug poisoning (overdose); T51-T65 with a 6th character of 2 (except for T51.9, T52.9, T53.9, T54.9, T56.9, T57.9, T58.0, T58.1, T58.9, T59.9, T60.9, T61.0, T61.1, T61.9, T62.9, T63.9, T64.0, T64.8, and T65.9, which are included if the 5th character is 2), intentional self-harm due to toxic effects of nonmedicinal substances; T71 with a 6th character of 2, intentional self-harm due to asphyxiation, suffocation, strangulation; and T14.91, Suicide attempt. Issues to consider when selecting records for nonfatal suicide attempts and intentional self-harm from ICD-10-CM coded administrative data sets are also discussed.

Classification of attempted suicide by cluster analysis: A study of 888 suicide attempters presenting to the emergency department.

BACKGROUND: It is essential to understand the latent structure of the population of suicide attempters for effective suicide prevention. The aim of this study was to identify subgroups among Korean suicide attempters in terms of the details of the suicide attempt. METHODS: A total of 888 people who attempted suicide and were subsequently treated in the emergency rooms of 17 medical centers between May and November of 2013 were included in the analysis. The variables assessed included demographic characteristics, clinical information, and details of the suicide attempt assessed by the Suicide Intent Scale (SIS) and Columbia-Suicide Severity Rating Scale (C-SSRS). Cluster analysis was performed using the Ward method. RESULTS: Of the participants, 85.4% (n = 758) fell into a cluster characterized by less planning, low lethality methods, and ambivalence towards death ("impulsive"). The other cluster (n = 130) involved a more severe and well-planned attempt, used highly lethal methods, and took more precautions to avoid being interrupted ("planned"). The first cluster was dominated by women, while the second cluster was associated more with men, older age, and physical illness. LIMITATIONS: We only included participants who visited the emergency department after their suicide attempt and had no missing values for SIS or C-SSRS. CONCLUSIONS: Cluster analysis extracted two distinct subgroups of Korean suicide attempters showing different patterns of suicidal behaviors. Understanding that a significant portion of suicide attempts occur impulsively calls for new prevention strategies tailored to differing subgroup profiles.

Blurred Boundaries - A Qualitative Study of How Acts of Self-Harm and Attempted Suicide Are Defined by Mental Health Practitioners.

BACKGROUND: There is no commonly accepted definition of the term self-harm, and there is an ongoing debate about whether or not it should include acts of attempted suicide. The use of this language in clinical practice has not previously been explored. AIMS: To investigate if, and how, practitioners distinguish between acts of self-harm and attempted suicide, and present any implications for practice. METHOD: We conducted semistructured interviews with a random sample of 18 frontline practitioners from 10 mental health wards and completed a thematic analysis of interview data. RESULTS: Most participants described self-harm and attempted suicide as distinct behaviors. Characteristics of the act, disclosures of intent, and the level of distress observed were commonly used to differentiate between self-harm and attempted suicide. Very few participants believed that people who self-harm may also feel suicidal. Practitioners confidently described two different behaviors, yet self-harm and attempted suicide were often conflated, revealing the challenges and complexities associated with the separation of these acts in clinical practice. LIMITATIONS: Clinicians working in other settings or disciplines may have different views. Participants' accounts may not be an accurate representation of what happens in practice. CONCLUSION: This study adds to a body of evidence which argues against the dichotomous separation of these behaviors into acts of suicidal and nonsuicidal self-harm.Our findings suggest there is no common understanding of the boundaries between self-harm and attempted suicide among frontline clinicians. The language currently used, and consequent practice, particularly with regard to risk assessment, is problematic. Efforts should be made to operationalize terms around suicidal behavior and to incorporate these into training for clinical staff.

Classification of suicide attempters in schizophrenia using sociocultural and clinical features: A machine learning approach.

OBJECTIVE: Suicide is a major concern for those afflicted by schizophrenia. Identifying patients at the highest risk for future suicide attempts remains a complex problem for psychiatric interventions. Machine learning models allow for the integration of many risk factors in order to build an algorithm that predicts which patients are likely to attempt suicide. Currently it is unclear how to integrate previously identified risk factors into a clinically relevant predictive tool to estimate the probability of a patient with schizophrenia for attempting suicide. METHODS: We conducted a cross-sectional assessment on a sample of 345 participants diagnosed with schizophrenia spectrum disorders. Suicide attempters and non-attempters were clearly identified using the Columbia Suicide Severity Rating Scale (C-SSRS) and the Beck Suicide Ideation Scale (BSS). We developed four classification algorithms using a regularized regression, random forest, elastic net and support vector machine models with sociocultural and clinical variables as features to train the models. RESULTS: All classification models performed similarly in identifying suicide attempters and non-attempters. Our regularized logistic regression model demonstrated an accuracy of 67% and an area under the curve (AUC) of 0.71, while the random forest model demonstrated 66% accuracy and an AUC of 0.67. Support vector classifier (SVC) model demonstrated an accuracy of 67% and an AUC of 0.70, and the elastic net model demonstrated and accuracy of 65% and an AUC of 0.71. CONCLUSION: Machine learning algorithms offer a relatively successful method for incorporating many clinical features to predict individuals at risk for future suicide attempts. Increased performance of these models using clinically relevant variables offers the potential to facilitate early treatment and intervention to prevent future suicide attempts.

Subtypes of suicide attempters based on longitudinal childhood profiles of co-occurring depressive, anxious and aggressive behavior symptoms.

Because suicide attempts are multi-determined events, multiple pathways to suicidal behaviors exist. However, as a low-frequency behavior, within group differences in trajectories to attempts may not emerge when examined in samples including non-attempters. We used longitudinal latent profile analysis to identify subtypes specific for suicide attempters based on longitudinal trajectories of childhood clinical symptoms (i.e., depression, anxiety, and aggression measured in 2nd, 4th-7th grades) for 161 young adults (35.6% male; 58.6% African American) who attempted suicide between ages 13-30 from a large, urban community-based, longitudinal prevention trial (n = 2311). Differences in psychiatric diagnoses, suicide attempt characteristics, criminal history and traumatic stress history were studied. Three subtypes emerged: those with all low (n = 32%), all high (n = 16%), and high depressive/anxious, but low aggressive (n = 52%) symptoms. Those with the highest levels of all symptoms were significantly more likely to report a younger age of suicide attempt, and demonstrate more substance abuse disorders and violent criminal histories. Prior studies have found that childhood symptoms of depression, anxiety and aggression are malleable targets; interventions directed at each reduce future risk for suicidal behaviors. Our findings highlight the link of childhood aggression with future suicidal behaviors extending this research by examining childhood symptoms of aggression in the context of depression and anxiety.