Distinguishing the relevant features of frequent suicide attempters

Workplace interventions to prevent suicide: A scoping review

OBJECTIVES

To map organisational interventions for workplace suicide prevention, identifying the effects, mechanisms, moderators, implementation and economic costs, and how interventions are evaluated.

BACKGROUND

Suicide is a devastating event that can have a profound and lasting impact on the individuals and families affected, with the highest rates found among adults of work age. Employers have a legal and ethical responsibility to provide a safe working environment for their employees, which includes addressing the issue of suicide and promoting mental health and well-being.

METHODS

A realist perspective was taken, to identify within organisational suicide prevention interventions, what works, for whom and in what circumstances. Published and unpublished studies in six databases were searched. To extract and map data on the interventions the Effect, Mechanism, Moderator, Implementation, Economic (EMMIE) framework was used. Mechanisms were deductively analysed against Bronfenbrenner's socio-ecological model.

RESULTS

From 3187 records screened, 46 papers describing 36 interventions within the military, healthcare, the construction industry, emergency services, office workers, veterinary surgeons, the energy sector and higher education. Most mechanisms were aimed at the individual's immediate environment, with the most common being education or training on recognising signs of stress, suicidality or mental illness in oneself. Studies examined the effectiveness of interventions in terms of suicide rates, suicidality or symptoms of mental illness, and changes in perceptions, attitudes or beliefs, with most reporting positive results. Few studies reported economic costs but those that did suggested that the interventions are cost-effective.

CONCLUSIONS

It seems likely that organisational suicide prevention programmes can have a positive impact on attitudes and beliefs towards suicide as well reducing the risk of suicide. Education, to support individuals to recognise the signs and symptoms of stress, mental ill health and suicidality in both themselves and others, is likely to be an effective starting point for successful interventions.

Can clinical and subclinical forms of narcissism be considered risk factors for suicide-related outcomes? A systematic review

BACKGROUND

Clinical and subclinical forms of narcissism may increase suicide risk. However, little is known and there are controversies on this topic. This systematic review aims at providing an overview of studies investigating this association.

METHODS

We used PubMed, Scopus, and PsycInfo databases and followed PRISMA. We focused on cohort, case-control, cross-sectional and case series studies. We referred to both clinical (i.e., narcissistic personality disorder (NPD) and/or NPD criteria) and subclinical forms (i.e., grandiose and vulnerable narcissistic traits) of narcissism. Moreover, we considered: Suicidal Ideation (SI), Non-Suicidal Self-Injury(s) (NSSI), Deliberate Self-Harm (DSH), Suicide Attempt(s) (SA), Suicide Risk (SR), and Capability for Suicide.

RESULTS

We included 47 studies. Lack of association between NPD diagnosis/criteria and suicide-related outcomes (SI) or mixed results (SA) were found. Higher homogeneity emerged when considering narcissistic traits. Vulnerable narcissism was associated with SI, less impulsive NSSI, and DSH. Grandiose narcissism was associated with severe NSSI and multiple SA with high intent to die, but it was protective against SI and SR. Vulnerable narcissism seemed to be associated with suicide-related outcomes characterized by low intent to die, while grandiose narcissism seemed to be a risk factor for outcomes with high planning and severity.

LIMITATIONS

Between-study heterogeneity and lack of longitudinal studies.

CONCLUSIONS

Assessing suicide risk in subjects with clinical or subclinical forms of narcissism may be useful. Moreover, considering the most vulnerable form of narcissism, and not just the grandiose one, may contribute to a more nuanced risk stratification and to the identification of distinct therapeutic approaches.

Machine learning and the prediction of suicide in psychiatric populations: a systematic review

Machine learning (ML) has emerged as a promising tool to enhance suicidal prediction. However, as many large-sample studies mixed psychiatric and non-psychiatric populations, a formal psychiatric diagnosis emerged as a strong predictor of suicidal risk, overshadowing more subtle risk factors specific to distinct populations. To overcome this limitation, we conducted a systematic review of ML studies evaluating suicidal behaviors exclusively in psychiatric clinical populations. A systematic literature search was performed from inception through November 17, 2022 on PubMed, EMBASE, and Scopus following the PRISMA guidelines. Original research using ML techniques to assess the risk of suicide or predict suicide attempts in the psychiatric population were included. An assessment for bias risk was performed using the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) guidelines. About 1032 studies were retrieved, and 81 satisfied the inclusion criteria and were included for qualitative synthesis. Clinical and demographic features were the most frequently employed and random forest, support vector machine, and convolutional neural network performed better in terms of accuracy than other algorithms when directly compared. Despite heterogeneity in procedures, most studies reported an accuracy of 70% or greater based on features such as previous attempts, severity of the disorder, and pharmacological treatments. Although the evidence reported is promising, ML algorithms for suicidal prediction still present limitations, including the lack of neurobiological and imaging data and the lack of external validation samples. Overcoming these issues may lead to the development of models to adopt in clinical practice. Further research is warranted to boost a field that holds the potential to critically impact suicide mortality.

The use of machine learning on administrative and survey data to predict suicidal thoughts and behaviors: a systematic review

Background

Machine learning is a promising tool in the area of suicide prevention due to its ability to combine the effects of multiple risk factors and complex interactions. The power of machine learning has led to an influx of studies on suicide prediction, as well as a few recent reviews. Our study distinguished between data sources and reported the most important predictors of suicide outcomes identified in the literature.

Objective

Our study aimed to identify studies that applied machine learning techniques to administrative and survey data, summarize performance metrics reported in those studies, and enumerate the important risk factors of suicidal thoughts and behaviors identified.

Methods

A systematic literature search of PubMed, Medline, Embase, PsycINFO, Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Allied and Complementary Medicine Database (AMED) to identify all studies that have used machine learning to predict suicidal thoughts and behaviors using administrative and survey data was performed. The search was conducted for articles published between January 1, 2019 and May 11, 2022. In addition, all articles identified in three recently published systematic reviews (the last of which included studies up until January 1, 2019) were retained if they met our inclusion criteria. The predictive power of machine learning methods in predicting suicidal thoughts and behaviors was explored using box plots to summarize the distribution of the area under the receiver operating characteristic curve (AUC) values by machine learning method and suicide outcome (i.e., suicidal thoughts, suicide attempt, and death by suicide). Mean AUCs with 95% confidence intervals (CIs) were computed for each suicide outcome by study design, data source, total sample size, sample size of cases, and machine learning methods employed. The most important risk factors were listed.

Results

The search strategy identified 2,200 unique records, of which 104 articles met the inclusion criteria. Machine learning algorithms achieved good prediction of suicidal thoughts and behaviors (i.e., an AUC between 0.80 and 0.89); however, their predictive power appears to differ across suicide outcomes. The boosting algorithms achieved good prediction of suicidal thoughts, death by suicide, and all suicide outcomes combined, while neural network algorithms achieved good prediction of suicide attempts. The risk factors for suicidal thoughts and behaviors differed depending on the data source and the population under study.

Conclusion

The predictive utility of machine learning for suicidal thoughts and behaviors largely depends on the approach used. The findings of the current review should prove helpful in preparing future machine learning models using administrative and survey data.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022333454 identifier CRD42022333454.

Predicting suicide attempts among Norwegian adolescents without using suicide-related items: a machine learning approach

Introduction

Research on the classification models of suicide attempts has predominantly depended on the collection of sensitive data related to suicide. Gathering this type of information at the population level can be challenging, especially when it pertains to adolescents. We addressed two main objectives: (1) the feasibility of classifying adolescents at high risk of attempting suicide without relying on specific suicide-related survey items such as history of suicide attempts, suicide plan, or suicide ideation, and (2) identifying the most important predictors of suicide attempts among adolescents.

Methods

Nationwide survey data from 173,664 Norwegian adolescents (ages 13-18) were utilized to train a binary classification model, using 169 questionnaire items. The Extreme Gradient Boosting (XGBoost) algorithm was fine-tuned to classify adolescent suicide attempts, and the most important predictors were identified.

Results

XGBoost achieved a sensitivity of 77% with a specificity of 90%, and an AUC of 92.1% and an AUPRC of 47.1%. A coherent set of predictors in the domains of internalizing problems, substance use, interpersonal relationships, and victimization were pinpointed as the most important items related to recent suicide attempts.

Conclusion

This study underscores the potential of machine learning for screening adolescent suicide attempts on a population scale without requiring sensitive suicide-related survey items. Future research investigating the etiology of suicidal behavior may direct particular attention to internalizing problems, interpersonal relationships, victimization, and substance use.

Lifetime suicidal-related behaviour among patients in treatment for substance use disorder: A cross-sectional study

Suicidal-related behaviours are an important concern in individuals who present with substance use disorders (SUDs). The distinction among the specific characteristics of the different patients might help to improve prevention strategies. We describe and compare the sociodemographic characteristics, severity of addiction, and psychopathology of the participants depending on the severity of their lifetime suicidal behaviour. In addition, we examine whether the number of suicide attempts can be estimated based on the variables that differentiate the groups. A sample of 318 men and 86 women who sought treatment for addiction were assessed. The sample was divided into: no ideation or attempts, suicidal ideation, one suicide attempt, and two or more suicide attempts. The group with two or more suicide attempts exhibited a greater severity in the addiction profile. The group with one suicide attempt presented a higher psychopathological symptomatology at the time of the assessment. The severity of the Psychiatric area was related to the group with two or more attempts and to the number of suicide attempts. The presence of any number of attempts is associated with greater severity of addiction. Providing specific intervention strategies for SUD patients depending on their suicidal behaviours is promising for clinical application.

Severity features of suicide attempters with epilepsy

BACKGROUND

After the Food and Drug Administration alert about antiepileptic medication and suicide, incident epilepsy has been associated with first or recurrent suicide attempts independently of psychiatric comorbidities and antiepileptic treatment. Following this thread, the aim of this study was to analyze if epilepsy was associated with a higher severity of lifetime suicide attempts (SAs).

METHODS

Analyses were carried out on 1677 adults hospitalized between 1999 and 2012 after a SA in a specialized ward for affective episodes. Five severity features were studied: frequent SAs (>2), early onset of first SA (≤26 years), history of violent SA, high suicide intent and high lethality of the SA. Adjusted logistic regression models were used to estimate the association between the lifetime diagnosis of epilepsy and the severity features.

RESULTS

Among suicide attempters, ninety-three patients reported a lifetime diagnosis of epilepsy (5.5%). Epileptic patients diagnosed after the first SA were more likely to be frequent suicide attempters than non-epileptic ones. They showed also higher SA planification scores.

LIMITATIONS

Diagnosis accuracy is limited by the use of self-reports for epilepsy. The lack of precise information about the disease course and treatment have not allowed for further statistical analysis. With regard to psychiatric comorbidities, personality disorders could not be taken into account.

CONCLUSIONS

Suicide attempters with epilepsy present an increased severity in some aspects of their suicidal behavior regardless of demographic and clinical variables. Our results give support to the existence of a bidirectional association between epilepsy and suicidal behavior.

Predicting the Risk of Future Multiple Suicide Attempt among First-Time Suicide Attempters: Implications for Suicide Prevention Policy

Suicide is listed in the top ten causes of death in Taiwan. Previous studies have pointed out that psychiatric patients having suicide attempts in their history are more likely to attempt suicide again than non-psychiatric patients. Therefore, how to predict the future multiple suicide attempts of psychiatric patients is an important issue of public health. Different from previous studies, we collect the psychiatric patients who have a suicide diagnosis in the National Health Insurance Research Database (NHIRD) as the study cohort. Study variables include psychiatric patients’ characteristics, medical behavior characteristics, physician characteristics, and hospital characteristics. Three machine learning techniques, including decision tree (DT), support vector machine (SVM), and artificial neural network (ANN), are used to develop models for predicting the risk of future multiple suicide attempts. The Adaboost technique is further used to improve prediction performance in model development. The experimental results show that Adaboost+DT performs the best in predicting the behavior of multiple suicide attempts among psychiatric patients. The findings of this study can help clinical staffs to early identify high-risk patients and improve the effectiveness of suicide prevention.

Psychotherapeutic interventions for the prevention of suicide re-attempts: a systematic review

A history of suicide attempt (SA) is a strong predictor of future suicide re-attempts or suicide. The aim of this systematic review is to evaluate the efficacy of psychotherapeutic interventions specifically designed for the prevention of suicide re-attempts. A systematic search from 1980 to June 2020 was performed via the databases PubMed and Google Scholar. Only randomized controlled trials were included which clearly differentiated suicidal self-harm from non-suicidal self-injury in terms of intent to die. Moreover, psychotherapeutic interventions had to be focused on suicidal behaviour and the numbers of suicide re-attempts had to be used as outcome variables. By this procedure, 18 studies were identified. Statistical comparison of all studies revealed that psychotherapeutic interventions in general were significantly more efficacious than control conditions in reducing the risk of future suicidal behaviour nearly by a third. Separate analyses revealed that cognitive-behavioural therapy as well as two different psychodynamic approaches were significantly more efficacious than control conditions. Dialectical behaviour therapy and elementary problem-solving therapy were not superior to control conditions in reducing the number of SAs. However, methodological reasons may explain to some extent these negative results. Considering the great significance of suicidal behaviour, there is unquestionably an urgent need for further development of psychotherapeutic techniques for the prevention of suicide re-attempts. Based on the encouraging results of this systematic review, it can be assumed that laying the focus on suicidal episodes might be the key intervention for preventing suicide re-attempts and suicides.

Highlighting psychological pain avoidance and decision-making bias as key predictors of suicide attempt in major depressive disorder-A novel investigative approach using machine learning

OBJECTIVE

Predicting suicide is notoriously difficult and complex, but a serious public health issue. An innovative approach utilizing machine learning (ML) that incorporates features of psychological mechanisms and decision-making characteristics related to suicidality could create an improved model for identifying suicide risk in patients with major depressive disorder (MDD).

METHOD

Forty-four patients with MDD and past suicide attempts (MDD_SA, N = 44); 48 patients with MDD but without past suicide attempts (MDD_NS, N = 48-42 of whom with suicide ideation [MDD_SI, N = 42]), and healthy controls (HCs, N = 51) completed seven psychometric assessments including the Three-dimensional Psychological Pain Scale (TDPPS), and one behavioral assessment, the Balloon Analogue Risk Task (BART). Descriptive statistics, group comparisons, logistic regressions, and ML were used to explore and compare the groups and generate predictors of suicidal acts.

RESULTS

MDD_SA and MDD_NS differed in TDPPS total score, pain arousal and avoidance subscale scores, suicidal ideation scores, and relevant decision-making indicators in BART. Logistic regression tests linked suicide attempts to psychological pain avoidance and a risk decision-making indicator. The resultant key ML model distinguished MDD_SA/MDD_NS with 88.2% accuracy. The model could also distinguish MDD_SA/MDD_SI with 81.25% accuracy. The ML model using hopelessness could classify MDD_SI/HC with 94.4% accuracy.

CONCLUSION

ML analyses showed that motivation to avoid intolerable psychological pain, coupled with impaired decision-making bias toward under-valuing life's worth are highly predictive of suicide attempts. Analyses also demonstrated that suicidal ideation and attempts differed in potential mechanisms, as suicidal ideation was more related to hopelessness. ML algorithms show useful promises as a predictive instrument.

Trajectories in suicide attempt method lethality over a five-year period: Associations with suicide attempt repetition, all-cause, and suicide mortality

It is not known if there are discernible patterns in method lethality over successive episodes of self–harm and, if so, how these may be differentially associated with risks of self–harm repetition and suicide. Latent trajectory modelling estimated variation in patterns of suicide attempt lethality in 1,719 individuals attended by ambulance services on at least three occasions between 2012 and 2016. Cox regression modelling investigated hazards of suicide attempt repetition, all–cause, and suicide mortality as a function of these patterns. Two distinct trajectories provided optimal fit (BIC: –39,464.92). The first (Low/Moderate to Low/Moderate Lethality group; 92.5%) consisted of those consistently using methods associated with low to moderate potential lethality throughout the observation period. The second (High to Low/Moderate Lethality group; 7.5%) consisted of those who initially used methods with higher potential lethality but who switched to methods characterised by lower lethality. There were no significant differences between groups in the hazards of reattempting suicide (Hazard Ratio [HR] = 1.41, 95% CI 0.76 to 2.59) or all–cause mortality (HR = 1.21, 95% CI 0.63 to 2.32). However, those assigned to the High to Low/Moderate Lethality trajectory group may be at greater risk of suicide (Sub–Hazard Ratio [SHR] = 2.82, 95% CI 1.16 to 6.86). There may be discernible sub–groups of patients with important differences in clinical treatment needs and suicide risk profiles. These differences should be considered when undertaking psychosocial risk/needs assessments with those presenting to clinical services following self-harm.

Identifying Distinguishable Clinical Profiles Between Single Suicide Attempters and Re-Attempters

More than 800,000 individuals die from suicide each year in the world, which has a devastating impact on families and society. Ten to twenty times more attempt suicide. Previous studies showed that suicide attempters represent a heterogeneous group regarding demographic characteristics, individual characteristics of a suicidal attempt, and the assumed clinical factors, e.g., hopelessness or impulsivity, thus differently contributing to the likelihood of suicidal behavior. Therefore, in the present study, we aim to give a comprehensive clinical description of patients with repeated suicide attempts compared to single attempters. We explored putative differences between groups in clinical variables and personality traits, sociodemographic information, and specific suicide attempt-related information. A sample of patients with a recent suicide attempt (n = 252), defined according to DSM-5 criteria for a suicidal behavior disorder (SBD), was recruited in four psychiatric hospitals in Thuringia, Germany. We used a structured clinical interview to assess the psychiatric diagnosis, sociodemographic data, and to collect information regarding the characteristics of the suicide attempt. Several clinical questionnaires were used to measure the suicide intent and suicidal ideations, depression severity, hopelessness, impulsivity, aggression, anger expression, and the presence of childhood trauma. Univariate and multivariate statistical methods were applied to evaluate the postulated risk factors and, to distinguish groups based on these measures. The performed statistical analyses indicated that suicide attempters represent a relatively heterogeneous group, nevertheless associated with specific clinical profiles. We demonstrated that the re-attempters had more severe psychopathology with significantly higher levels of self-reported depression, suicidal ideation as well as hopelessness. Furthermore, re-attempters had more often first-degree relatives with suicidal behavior and emotional abuse during childhood. They also exhibited a higher degree of specific personality traits, i.e., more "urgency" as a reaction to negative emotions, higher excitability, higher self-aggressiveness, and trait anger. The multivariate discriminant analysis significantly discriminated the re-attempters from single attempters by higher levels of self-aggressiveness and suicidal ideation. The findings might contribute to a better understanding of the complex mechanisms leading to suicidal behavior, which might improve the early identification and specific treatment of subjects at risk for repeated suicidal behavior.

Artificial Intelligence and Suicide Prevention: A Systematic Review of Machine Learning Investigations

Suicide is a leading cause of death that defies prediction and challenges prevention efforts worldwide. Artificial intelligence (AI) and machine learning (ML) have emerged as a means of investigating large datasets to enhance risk detection. A systematic review of ML investigations evaluating suicidal behaviors was conducted using PubMed/MEDLINE, PsychInfo, Web-of-Science, and EMBASE, employing search strings and MeSH terms relevant to suicide and AI. Databases were supplemented by hand-search techniques and Google Scholar. Inclusion criteria: (1) journal article, available in English, (2) original investigation, (3) employment of AI/ML, (4) evaluation of a suicide risk outcome. N = 594 records were identified based on abstract search, and 25 hand-searched reports. N = 461 reports remained after duplicates were removed, n = 316 were excluded after abstract screening. Of n = 149 full-text articles assessed for eligibility, n = 87 were included for quantitative synthesis, grouped according to suicide behavior outcome. Reports varied widely in methodology and outcomes. Results suggest high levels of risk classification accuracy (>90%) and Area Under the Curve (AUC) in the prediction of suicidal behaviors. We report key findings and central limitations in the use of AI/ML frameworks to guide additional research, which hold the potential to impact suicide on broad scale.

Identifying and Predicting Intentional Self-Harm in Electronic Health Record Clinical Notes: Deep Learning Approach

BACKGROUND

Suicide is an important public health concern in the United States and around the world. There has been significant work examining machine learning approaches to identify and predict intentional self-harm and suicide using existing data sets. With recent advances in computing, deep learning applications in health care are gaining momentum.

OBJECTIVE

This study aimed to leverage the information in clinical notes using deep neural networks (DNNs) to (1) improve the identification of patients treated for intentional self-harm and (2) predict future self-harm events.

METHODS

We extracted clinical text notes from electronic health records (EHRs) of 835 patients with International Classification of Diseases (ICD) codes for intentional self-harm and 1670 matched controls who never had any intentional self-harm ICD codes. The data were divided into training and holdout test sets. We tested a number of algorithms on clinical notes associated with the intentional self-harm codes using the training set, including several traditional bag-of-words-based models and 2 DNN models: a convolutional neural network (CNN) and a long short-term memory model. We also evaluated the predictive performance of the DNNs on a subset of patients who had clinical notes 1 to 6 months before the first intentional self-harm event. Finally, we evaluated the impact of a pretrained model using Word2vec (W2V) on performance.

RESULTS

The area under the receiver operating characteristic curve (AUC) for the CNN on the phenotyping task, that is, the detection of intentional self-harm in clinical notes concurrent with the events was 0.999, with an F1 score of 0.985. In the predictive task, the CNN achieved the highest performance with an AUC of 0.882 and an F1 score of 0.769. Although pretraining with W2V shortened the DNN training time, it did not improve performance.

CONCLUSIONS

The strong performance on the first task, namely, phenotyping based on clinical notes, suggests that such models could be used effectively for surveillance of intentional self-harm in clinical text in an EHR. The modest performance on the predictive task notwithstanding, the results using DNN models on clinical text alone are competitive with other reports in the literature using risk factors from structured EHR data.

Suicide and suicide attempts in adults: exploring suicide risk 24 months after a psychiatric emergency room visit

Objective:

Suicide risk (including attempted and completed suicide) should be measured over short periods of time after contacting health services. The objective of this study was to identify the patterns of attempted and completed suicides within 24-months of a psychiatric emergency department visit, as well as to investigate predictive risk factors, including sociodemographic and clinical variables, previous suicidal behavior, and service utilization.

Method:

A convenience sample (n=147), recruited at a general hospital’s psychiatric emergency room, included patients with suicidal ideation, suicidal plans or previous suicide attempts. These patients were followed for 24 months, focusing on two main outcomes: attempted and completed suicides.

Results:

After six months there were no completed suicides and 36 suicide attempts, while after 24 months there were seven completed suicides and 69 suicide attempts. A final logistic regression model for suicide attempts at 24 months identified somatic pathology and the number of previous psychiatric hospitalizations as predictive factors, with a good area under the receiver operating characteristic curve.

Conclusions:

The findings showed distinct patterns of attempted and completed suicides over time, indicating the importance of a systematic multidisciplinary suicide risk evaluation in psychiatric emergency rooms.

Psychiatric diagnosis, gender, aggression, and mode of attempt in patients with single versus repeated suicide attempts

There is evidence that patients with multiple suicide attempts in their history are at greater risk to repeat attempt and eventually die by suicide compared to those with a single attempt. This cross-sectional study aimed to explore possible differences in clinical characteristics between patients with a single attempt and patients with repeated attempts. Two hundred thirty one patients hospitalised in psychiatric department after suicide attempt were studied. Comparisons were made in relation to age, gender, psychiatric diagnosis, aggression, depression severity, suicide intent and mode of attempt. Highest frequencies of patients with repeated attempts were found for bipolar disorder (69%) and lowest for adjustment/personality disorders (39%). In patients with repeated attempts, female gender was associated with non-violent attempt mode. Depressive symptomatology was higher in patients with repeated attempts among females. In patients with depression those with repeated attempts were younger than patients with single attempt. In patients with mood disorders, total aggression and hostility scores were higher in females with repeated attempts but not in males. Psychiatric diagnosis, gender and attempt mode are features that differentiate patients with single and repeated attempts and should be considered to identify patients at increased risk to repeat attempt and design effective prevention interventions.

Childhood maltreatment, anxiety disorders and outcome in borderline personality disorder

INTRODUCTION

Anxiety disorders are a frequent in borderline personality disorder (BPD) and are associated with more severe symptomatology and poorer functional outcomes. Their presence in BPD is also believed to be the consequence of early life adversities. The aim of our study was to examine the relationship between comorbid anxiety disorders, childhood maltreatment and severity of BPD.

METHODS

388 BPD outpatients were assessed for lifetime anxiety disorders and history of childhood maltreatment. Severity of BPD was measured by the number of DSM-IV BPD criteria, history of suicide attempts, hospitalizations, psychotic symptoms, comorbid substance use disorder, other comorbid disorders, level of depression, hopelessness, impulsivity and trait anger. We used logistic regressions to test the association between childhood maltreatment and anxiety disorders and the effect of those factors on severity indicators RESULTS: More than half of the participants suffered from two or more anxiety disorders. The most common comorbidity was social phobia. Childhood maltreatment was associated with an increased number of anxiety disorders. Both anxiety disorders and childhood maltreatment had, independently from one another, an effect on severity indicators. Anxiety disorders were significantly associated with the number of DSM-IV BPD criteria, suicide attempts and psychotic symptoms. Anxiety disorders had an impact on the level of depression and hopelessness, whereas childhood maltreatment impacted impulsivity and anger trait.

CONCLUSION

Our results show the importance of comorbid anxiety disorders in BPD, as well as their impact on severity. Anxiety disorders and childhood maltreatment should be considered by healthcare professionals to ensure optimal care. Furthermore, interventions targeting those issues need to be developed.

Tobacco smoking and other substance use disorders associated with recurrent suicide attempts in bipolar disorder

BACKGROUND

Suicide attempts (SA) are more frequent in bipolar disorder (BD) than in most other mental disorders. Prevention strategies would benefit from identifying the risk factors of SA recurrence in BD. Substance use disorders (SUD) (including tobacco-related) are strongly associated with both BD and SA, however, their specific role for the recurrence of SA in BD remains inadequately investigated. Thus, we tested if tobacco smoking - with or without other SUDs - was independently associated with recurrent SA in BD.

METHODS

916 patients from France and Norway with ascertained diagnoses of BD and reliable data about SA and SUD were classified as having no, single, or recurrent (≥2) SA. Five SUD groups were built according to the presence/absence/combination of tobacco, alcohol (AUD) and cannabis use disorders. Multinomial logistic regression was used to identify the correlates of SA recurrence.

RESULTS

338 (37%) individuals reported at least one SA, half of whom (173, 51%) reported recurrence. SUD comorbidity was: tobacco smoking only, 397 (43%), tobacco smoking with at least another SUD, 179 (20%). Regression analysis showed that tobacco smoking, both alone and comorbid with AUD, depressive polarity of BD onset and female gender were independently associated with recurrent SA.

LIMITATIONS

Lack of data regarding the relative courses of SA and SUD and cross-national differences in main variables.

CONCLUSION

Tobacco smoking with- or without additional SUD can be important risk factors of SA recurrence in BD, which is likely to inform both research and prevention strategies.

Association of symptoms of attention deficit-hyperactivity disorder and impulsive-aggression with severity of suicidal behavior in adult attempters

Literature emphasizes the relationship between attention deficit-hyperactivity disorder (ADHD) and suicidal behavior (SB). However, the link between ADHD and the severity of SB is yet to be determined. We investigated the association between a probable diagnosis of ADHD and the severity of SB in 539 hospitalized suicide attempters, and determined the role of comorbid psychiatric diagnoses. The severity of SB was defined as the number of suicide attempts, age at first suicide attempt, seriousness and violence of suicide attempts. A diagnosis of probable adult ADHD (probable ADHD) was defined as the presence of both current ADHD symptoms and ADHD symptoms in childhood. We evaluated the combined effect of high impulsive-aggression levels and probable ADHD. Probable ADHD was not associated with early or frequent suicide attempts after adjustment for psychiatric disorders and treatment intake. High levels of impulsive-aggression increased the risk of an early suicide attempt, particularly in patients with ADHD symptoms, and independently of other clinical factors. The association between serious suicide attempts and probable ADHD remained significant after adjustment. Although ADHD is involved in suicidal vulnerability, psychiatric comorbidities and impulsive-aggression appear to largely explain the severity of SB in adult attempters with ADHD symptoms.

Mining social networks to improve suicide prevention: A scoping review

Attention about the risks of online social networks (SNs) has been called upon reports describing their use to express emotional distress and suicidal ideation or plans. On the Internet, cyberbullying, suicide pacts, Internet addiction, and "extreme" communities seem to increase suicidal behavior (SB). In this study, the scientific literature about SBs and SNs was narratively reviewed. Some authors focus on detecting at-risk populations through data mining, identification of risks factors, and web activity patterns. Others describe prevention practices on the Internet, such as websites, screening, and applications. Targeted interventions through SNs are also contemplated when suicidal ideation is present. Multiple predictive models should be defined, implemented, tested, and combined in order to deal with the risk of SB through an effective decision support system. This endeavor might require a reorganization of care for SNs users presenting suicidal ideation.

The use of machine learning in the study of suicidal and non-suicidal self-injurious thoughts and behaviors: A systematic review

BACKGROUND

Machine learning techniques offer promise to improve suicide risk prediction. In the current systematic review, we aimed to review the existing literature on the application of machine learning techniques to predict self-injurious thoughts and behaviors (SITBs).

METHOD

We systematically searched PsycINFO, PsycARTICLES, ERIC, CINAHL, and MEDLINE for articles published through February 2018.

RESULTS

Thirty-five articles met criteria to be included in the review. Included articles were reviewed by outcome: suicide death, suicide attempt, suicide plan, suicidal ideation, suicide risk, and non-suicidal self-injury. We observed three general aims in the use of SITB-focused machine learning analyses: (1) improving prediction accuracy, (2) identifying important model indicators (i.e., variable selection) and indicator interactions, and (3) modeling underlying subgroups. For studies with the aim of boosting predictive accuracy, we observed greater prediction accuracy of SITBs than in previous studies using traditional statistical methods. Studies using machine learning for variable selection purposes have both replicated findings of well-known SITB risk factors and identified novel variables that may augment model performance. Finally, some of these studies have allowed for subgroup identification, which in turn has helped to inform clinical cutoffs.

LIMITATIONS

Limitations of the current review include relatively low paper sample size, inconsistent reporting procedures resulting in an inability to compare model accuracy across studies, and lack of model validation on external samples.

CONCLUSIONS

We concluded that leveraging machine learning techniques to further predictive accuracy and identify novel indicators will aid in the prediction and prevention of suicide.

Sleep and circadian rhythms as possible trait markers of suicide attempt in bipolar disorders: An actigraphy study

BACKGROUND

The poor prognostic of Bipolar disorders (BD) is closely linked to deaths by suicide. Sleep and circadian abnormalities are observed during all phases of BD and are also associated with suicide attempt (SA). In this context, this study sought to identify specific sleep and circadian rhythms markers associated with suicidal attempt in euthymic patients with BD.

METHODS

The sample (N = 236) comprised 3 groups: 147 patients with BD including 57 with a history of SA and 90 without (NoSA), and 89 healthy controls (HC). All participants were recorded during 21 days with actigraphy.

RESULTS

SA was associated with women gender (p = 0.03), familial history of SA (p = 0.03), mixed episodes (p = 0.001), and benzodiazepines (p = 0.019). SA, compared to noSA, had a morning phase preference (p = 0.04), and were more vigorous on the circadian type inventory (p = 0.04), and tended to suffer more from insomnia (45% versus 25% respectively, p = 0.10). SA was also associated with an earlier onset of daily activity assessed with actigraphy (M10 onset: p = 0.01). Backward stepwise linear regression indicated that a combination of four variables (Gender, vigour, insomnia, M10onset) significantly differentiated patients with SA from NoSA (p = 0.03).

LIMITATIONS

Cross-sectional design, and no examination of suicidal behaviors' subgroups such as first attempters or repeaters, or violent suicide attempt.

CONCLUSIONS

Woman gender, vigorous circadian type, insomnia and an earlier daily activity appeared independently associated with SA in BD. If these biomarkers are confirmed in prospective studies, they should be screened and used to prevent suicide, with the development of personal and targeted chronobiological treatments.

Gender-specific study of recurrent suicide attempts in outpatients with multiple substance use disorders

BACKGROUND

people suffering from substance use disorders (SUD) often die by suicide, so that the prevention of suicide attempts (SA) remains a top priority in this population. SA recurrence is common and is associated with suicide death, but this phenotype has been overlooked in SUD populations. Thus, we aimed at identifying the risk factors of SA recurrence in SUD, controlling for both gender and levels of exposure to addictive substances, including tobacco.

METHODS

we consecutively recruited 433 treatment-seeking outpatients with either opiate or cocaine use disorder and assessed their lifetime history of addictive and suicidal symptoms by standardized questionnaires. They were reliably classified as never, single or recurrent (≥ 2) suicide attempters, whose characteristics were identified by multinomial regression, stratified by gender; and compared to our previous work on serious SA in order to identify common or different risk profiles.

RESULTS

86/140 (61%) suicide attempters reported recurrence. The mean number of SA was 3.1. Recurrence was independently associated with psychiatric hospitalization in both genders, with nicotine dependence in men and with sedative use disorders in women.

LIMITATIONS

psychiatric diagnoses were derived from the current medication regimen.

CONCLUSION

specific and possibly avoidable/treatable risk factors for the recurrence of SA in SUD have been identified for the first time, opening new avenues for research and prevention in this high-risk population. Apart from nicotine dependence, these risk factors were very similar to those of serious SA. Although this comparison is indirect for now, it suggests a common liability towards suicidal behavior.

Youth Suicide Deaths: Investigation of Clinical Predictors in a Statewide Sample

Death by suicide is a significant cause of mortality among youth. However, there is limited information on the demographic and clinical factors associated with youth suicide deaths. The objective of this study was to link large statewide databases to describe demographic, clinical, and cause of death characteristics among youth who died by suicide. We examined 1,218 decedents under age 26 who died by suicie between 2000 and 2014. Eighteen died before age 12, 53 died between ages 12 and 14, 292 died between ages 15 and 18, and 855 died between ages 19 and 25. Most were male (83%), and firearm was most common cause of death; 28% previously attempted suicide, 31% had a mental health diagnosis, and 17% were prescribed psychotropic medication. Younger children died by hanging/smothering (89% of all 7- to 11-year olds), and overdose/poisoning increased progressively with age. Adolescents had a higher proportion of females than young adults (23% vs. 14%, p = .002). Combining data from the medical examiner and large hospital systems allows examination of youth suicide from a developmental perspective. Differences between age groups included gender, method, diagnosed mental illness, and diagnosis of attention deficit hyperactivity disorder. These data point to missed opportunities for effective interventions for specific developmental stages.

Single Versus Multiple Suicide Attempts: A Prospective Examination of Psychiatric Factors and Wish to Die/Wish to Live Index Among Military and Civilian Psychiatrically Admitted Patients

Individuals with multiple suicide attempts have a greater risk for eventual suicide death. We investigated clinical differences in participants with single versus multiple suicide attempts. Individuals with multiple attempts were more likely to have severe depressive symptoms, drug use disorder, and a higher wish to die. Borderline personality disorder traits and drug use disorder were significant predictors of multiple attempts when adjusting for other psychiatric disorders. Participants with multiple attempts sustained higher suicidal ideation-worst and wish to die/wish to live-worst scores during the 3-month assessment period. Clinical differences between individuals with multiple versus single attempts point to the need of tailored suicide prevention efforts.

Variables related to suicide attempt in a Spanish province over a three-year period (2009-2011)

The aim was to identify and describe socio demographic and clinical variables in individuals who have made a suicide attempt. An analysis of electronically stored records on persons admitted to the emergency departments of a northern health district during the period 2009-2011 for mental disorders was conducted. The records of 826 patients (30.1% of the total), where 485 (58.7%) were female, aged between 14 and 94 years (M = 49.3; SD = 12.7), were selected. This amounted to 412 individuals (49.9%) who had made a suicide attempt, and were compared with others without prior suicide attempt. A binary logistic regression analysis was performed to examine the strongest predictors of suicide attempt. The results show that the risk of making a suicide attempt increases with age, those most at risk being aged 34 to 53 years (p < 0.01; OR = 6.99), female (p < 0.05; OR = 2.70) and unemployed (p < 0.05; OR = 4.98). The most predictive psychopathological diagnoses for suicide attempt were anxiety disorders (p < 0.01; OR = 3.95) and impulse control disorders/addictions (p < 0.01; OR = 3.76). The importance of creating specific risk and protection profiles when implementing contextualized health policies on suicide attempt prevention is discussed.

Neuroticism and anxious attachment as potential vulnerability factors of repeat suicide attempts

The recurrence risk of suicide attempts can reach 50% in the first year, each attempt increasing suicide-risk by 32%. No screening tool efficiently identifies potential repeat suicide attempters who are too often regarded as borderline personality. Our aim was to identify individual and interpersonal psychopathological dimensions that could represent a vulnerability to repeat suicide attempts. Sixty first-time and repeat suicide attempters consecutively admitted in emergency rooms were compared for fundamental dimensions of personality, patterns of attachment, personality and mental disorders using standardized questionnaires. Confounding and significantly different factors were evaluated using univariate and multivariate logistic regressions. Repeat suicide attempters differed from first-attempters by higher neuroticism and anxious attachment. Combined in an 11-item measure, these two parameters identified a 3.99 times higher risk of repeat suicide attempt. These traits associated with the other two best predictors (non-suicidal self-injury history, current psychotropic drugs) provide a vulnerability model with better screening performance compared to each factor individually. Repeat suicide attempters have more psychological features impairing emotional stability and social interactions than first attempters. Cross-sectional study design, sample size, lack of independent sample and of fearful-avoidant attachment evaluation are the main limitations. The model needs to be validated in a prospective and controlled study.

The age-specific characteristics of medically serious suicide attempters aged 15-45 years in rural China

This aim of this study was to identify unique characteristics of serious suicide attempters across different age groups. Face to face interviews were conducted with medically serious suicide attempters in rural hospitals in two provinces in China (n = 791). The sample included three age groups: 15-24, 25-34, and 35-45. While there were some consistent patterns that emerged across the age groups, there were also some significant age-related patterns that emerged. Serious suicide attempters aged 15-24 were more likely to be well educated, never married, hold Party membership, and impulsive, and to be least likely to perceive social support and be in a peasant occupation. This category also had the highest proportion of males, although still predominantly female. Those aged 24-25 were more likely to have a family history of suicide, somewhat educated, and moderately likely to be married. Those aged 35-45 were more likely to have limited education, to be ever married, to have mental disorders, to store pesticides in their home, and the least likely to be impulsive. These results highlight age-specific intervention strategies in addressing suicide.

Suicide attempters examined in a Parisian Emergency Department: Contrasting characteristics associated with multiple suicide attempts or with the motive to die

Among patients examined after a suicide attempt in a Parisian emergency department, we aimed to compare individual characteristics of i) first time and multiple suicide attempters, ii) attempters whose principal motive was "to die" and attempters who had any other motive. Information regarding sociodemographics, clinical characteristics, prior mental health care and outgoing referral was collected in 168 suicide attempters using a standardized form. Associations of these variables with suicide attempt repetition (yes or no) and with the motive underlying the attempt (to die or not) were examined using descriptive statistics and multivariable logistic regression models. Multiple attempters were more likely to have no occupation and to report previous mental health care: mental health follow-up, psychiatric medication or psychiatric hospitalization. The motive to die was not associated with the risk of multiple suicide attempts but related to past suicidal ideation and to some specific precipitating factors, including psychiatric disorder. Patients who intended to die were also more likely to be referred to inpatient than to outpatient psychiatric care. Multiple attempters and attempters who desire to die might represent two distinct high-risk groups regarding clinical characteristics and care pathways. They would probably not benefit from the same intervention strategies.

Disordered lives: Life circumstances and clinical characteristics of very frequent users of emergency departments for primary mental health complaints

This study explored the life circumstances and clinical characteristics of very frequent users of emergency departments (EDs) presenting with a primary mental health complaint. Patients with 10 or more EDs visits in 2012 with a primary psychiatric diagnosis in a Canadian regional health authority were identified from electronic administrative files. The hospital charts for these patients were thoroughly reviewed for a three-year period, from 2011 to 2013. A retrospective thematic analysis was undertaken. Very frequent users of EDs were generally young to early middle aged, unemployed, living in transient accommodations, having substance abuse diagnoses, and self-referred to EDs for a variety of psychiatric and health symptoms and/or unmet needs. Four themes were identified: 1) substance abuse and associated health and social problems; 2) common mental disorders, which may include suicidality; 3) social and personal stressors with additional common mental disorders and somatic complaints; 4) cognitive impairment with concurrent psychiatric disorders. Traditional mental health services are ineffective in dealing with patients with complex psychiatric and social problems/needs. Efforts should focus on early detection, intervention, reducing mental and behavior problems, and developing appropriate case management and treatment options. Personalized care models are needed to meet their diverse needs.

Psychopathology profiles of acutely suicidal adolescents: Associations with post-discharge suicide attempts and rehospitalization

BACKGROUND

Suicidal adolescents are heterogeneous, which can pose difficulties in predicting suicidal behavior. The Youth Self-Report (YSR) psychopathology profiles predict the future onset of psychopathology and suicide-related outcomes. The present study examined the prevalence and correlates of YSR psychopathology profiles among suicidal adolescents and prospective associations with post-discharge rates of suicide attempts and psychiatric rehospitalization.

METHODS

Participants were acutely suicidal, psychiatrically hospitalized adolescents (N=433 at baseline; n=355 at follow-up) who were enrolled in a psychosocial intervention trial during hospitalization. Psychopathology profiles were assessed at baseline. Suicide attempts and rehospitalization were assessed for up to 12 months following discharge.

RESULTS

Latent profile analysis identified four psychopathology profiles: subclinical, primarily internalizing, and moderately and severely dysregulated. At baseline, profiles differed by history of non-suicidal self-injury (NSSI) and multiple suicide attempts (MA) as well as severity of suicide ideation, hopelessness, depressive symptoms, anxiety symptoms, substance abuse, and functional impairment. The dysregulation profiles predicted suicide attempts within 3 months post-discharge. The internalizing profile predicted suicide attempts and rehospitalization at 3 and 12 months.

LIMITATIONS

This study's participants were enrolled in a randomized trial and were predominantly female, which limit generalizability. Additionally, only a history of NSSI was assessed.

CONCLUSIONS

The dysregulation profile was overrepresented among suicidal youth and associated with impairment in several domains as well as suicide attempts shortly after discharge. Adolescents with a severe internalizing profile also reported adverse outcomes throughout the study period. Psychopathology profiles warrant further examination in terms of their potential predictive validity in relation to suicide-related outcomes.

Differences and similarities of risk factors for suicidal ideation and attempts among patients with depressive or bipolar disorders

BACKGROUND

Substantial literature exists on risk factors for suicidal behaviour. However, their comparative strength, independence and specificity for either suicidal ideation or suicide attempt(s) remain unclear.

METHODS

The Helsinki University Psychiatric Consortium (HUPC) Study surveyed 287 psychiatric care patients with ICD-10-DCR depressive or bipolar disorders about lifetime suicidal behaviour, developmental history and attachment style, personality and psychological traits, current and lifetime symptom profiles, and life events. Psychiatric records were used to confirm diagnosis and complement information on suicide attempts. Multinomial regression models predicting lifetime suicidal ideation and single or repeated suicide attempts were generated.

RESULTS

Overall, 21.6% patients had no lifetime suicidal behaviour, 33.8% had lifetime suicide ideation without attempts, and 17.1% had a single and 27.5% repeated suicide attempts. In univariate analyses, lifetime suicidal behaviour was associated with numerous factors. In multivariate models, suicidal ideation was independently predicted by younger age, severe depressive disorder, bipolar disorder type II/nos, hopelessness, and childhood physical abuse. Repeated suicide attempts were independently predicted by younger age, female sex, severe depressive disorder with or without psychotic symptoms, bipolar disorder type II/nos, alcohol use disorder, borderline personality disorder traits, and childhood physical abuse.

LIMITATIONS

Cross-sectional and retrospective study design, utilization of clinical diagnoses, and relatively low response rate.

CONCLUSIONS

Risk factors for suicidal ideation and attempts may diverge both qualitatively and in terms of dose response. When effects of risk factors from multiple domains are concurrently examined, proximal clinical characteristics remain the most robust. All risk factors cluster into the group of repeated attempters.

Heavy tobacco dependence in suicide attempters making recurrent and medically serious attempts

AIMS

Tobacco dependence and suicidal behaviors have been repeatedly associated in several studies but their relationship is still unclear. We aim to investigate, specifically, the association between the level of tobacco dependence and the severity of suicidal outcomes among suicide attempters, as well as the relationship of impulsivity with both conditions.

METHODS

We examined a cross-sectional sample of 542 adult suicide attempters to compare the characteristics of the attempts depending on the level of tobacco dependence, which was assessed with the Fagerstrom test.

RESULTS

Smokers with heavy dependence (Fagerstrom ≥7) made more attempts and reached higher medical lethality compared to non-smokers. Smokers with moderate dependence were not associated with features of severity in the suicide attempts. The combination of high impulsivity and heavy tobacco dependence showed an additive effect on the number of suicide attempts.

CONCLUSIONS

A high or very high level of tobacco dependence could indicate a specific vulnerability leading to more severe suicide attempts. Impulsive attempters with heavy tobacco dependence were particularly at risk.

Can We Use Neurocognition to Predict Repetition of Self-Harm, and Why Might This Be Clinically Useful? A Perspective

Over 800,000 people die by suicide each year globally, with non-fatal self-harm 20 times more common. With each episode of self-harm, the risks of future self-harm and suicide increase, as well as personal and healthcare costs. Therefore, early delineation of those at high risk of future self-harm is important. Historically, research has focused on clinical and demographic factors, but risk assessments based on these have low sensitivity to predict repetition. Various neurocognitive factors have been associated with self-harming behavior, but it is less certain if we can use these factors clinically (i) as risk markers to predict future self-harm and (ii) to become therapeutic targets for interventions. Recent systematic reviews and meta-analyses of behavioral tasks and fMRI studies point to an emerging hypothesis for neurocognition in self-harm: an underactive pre-frontal cortex is unable to respond appropriately to non-emotional stimuli, or inhibit a hyperactive emotionally-/threat-driven limbic system. However, there is almost no imaging data examining repetition of self-harm. Extrapolating from the non-repetition data, there may be several potential neurocognitive targets for interventions to prevent repeat self-harm: cognitive training; pharmacological regimes to promote non-emotional neurocognition; or other techniques, such as repetitive transcranial magnetic stimulation. Hence, there is an urgent need for imaging studies examining repetition and to test specific hypotheses. Until we investigate the functional neurocognitive basis underlying repetition of self-harm in a systematic manner using second-generational imaging techniques, we will be unable to inform third-generational imaging and potential future clinical applications.

Prevalence and characteristics of suicide attempters and ideators among acutely admitted psychiatric hospital patients in northwest Russia and northern Norway

BACKGROUND

More knowledge about suicidality and suicide risk profiles in acute psychiatric hospital patients (both first-time and chronic patients) is needed. While numerous factors are associated with suicidality in such populations, these may differ across cultures. Better understanding of factors underlying suicide risk can be informed by cross-cultural studies, and can aid development of therapeutic and preventive measures.

METHODS

An explorative, cross-sectional cohort study was carried out. Acutely admitted patients at one psychiatric hospital in northwest Russia and two in northern Norway were included. At admission, demographic, clinical, and service use data were collected, in addition to an assessment of suicidal ideation and attempts, comprising five dichotomic questions. Data from 358 Norwegian and 465 Russian patients were analyzed with univariate and multivariate statistics. Within each cohort, attempters and ideators were compared with patients not reporting any suicidality.

RESULTS

The observed prevalence of suicidal ideation and attempts was significantly higher in the Norwegian cohort than in the Russian cohort (χ(2) = 168.1, p < 0,001). Norwegian suicidal ideators and attempters had more depressed moods, more personality disorders, and greater problems with alcohol/drugs, but fewer psychotic disorders, cognitive problems or overactivity than non-suicidal patients. Russian suicidal ideators and attempters were younger, more often unemployed, had more depressed mood and adjustment disorders, but had fewer psychotic disorders and less alcohol/drug use than the non-suicidal patients.

CONCLUSIONS

Rates of suicidal ideation and non-fatal attempts in Norwegian patients were intermediate between those previously reported for patients admitted for the first time and those typical of chronic patients. However, the significantly lower rates of suicidal ideation and non-fatal attempts in our Russian cohort as compared with the Norwegian, contrasted with what might be expected in a region with much higher suicide rates than in northern Norway. We suggest that suicide-related stigma in Russia may reduce both patient reporting and clinicians' recognition of suicidality. In both cohorts, overlapping risk profiles of ideators and attempters may indicate that ideators should be carefully evaluated and monitored, particularly those with depressed moods, alcohol/substance abuse disorders, and inadequate treatment continuity.

Suicidality and hospitalization as cause and outcome of pediatric psychiatric emergency room visits

The aim of this study was to identify predictors of suicidality in youth presenting to a pediatric psychiatric emergency room service (PPERS). To this end, we conducted a retrospective cohort study of youth aged <18 years consecutively assessed by a PPERS 01.01.2002-12.31.2002, using a 12-page semi-structured institutional evaluation form and the Columbia Classification Algorithm for Suicide Assessment. Multivariate regression analyses were conducted to identify correlates of suicidal thoughts and attempts/preparation and their relationship to outpatient/inpatient disposition. Of 1,062 youth, 265 (25.0%) presented with suicidal ideation (16.2%) or attempt/preparation (8.8%). Suicidal ideation was associated with female sex, depression, adjustment disorder, absent referral by family/friend/self, school referral, precipitant of peer conflict, and no antipsychotic treatment (p < 0.0001). Suicidal attempt/preparation was associated with female sex, depression, lower GAF score, past suicide attempt, precipitant of peer conflict, and no stimulant treatment (p < 0.0001). Compared to suicidal attempt/preparation, suicidal ideation was associated with school referral, and higher GAF score (p < 0.0001). Of the 265 patients with suicidality, 58.5% were discharged home (ideation = 72.1% vs. attempt/preparation = 33.7%, p < 0.0001). In patients with suicidal ideation, outpatient disposition was associated with higher GAF score, school referral, and adjustment disorder (p < 0.0001). In patients with suicidal attempt/preparation, outpatient disposition was associated with higher GAF score, lower acuity rating, and school referral (p < 0.0001). Suicidality is common among PPERS evaluations. Higher GAF score and school referral distinguished suicidal ideation from suicidal attempt/preparation and was associated with outpatient disposition in both presentations. Increased education of referral sources and establishment of different non-PPERS evaluation systems may improve identification of non-emergent suicidal presentations and encourage more appropriate outpatient referrals.

Gender differences in socio-demographic, clinical characteristics and psychiatric diagnosis in/of suicide attempters in a Mexican population

OBJECTIVE

The aim of the present study was to analyse demographic and clinical characteristics, as well as psychiatric diagnoses to identify gender differences in patients with attempted suicide in a Mexican population.

METHODS

Between September 2010 and September 2012, 140 suicide attempts were documented in the Department of Psychiatry at the General Hospital of Comalcalco (Hospital General de Comalcalco in Spanish) in Tabasco, Mexico. Diagnoses were established using the DSM-IV questionnaire in which Axis I and II were considered. The Suicide Intent Scale was also applied.

RESULTS

In our sample, 63.6% were females and 36.4% males. With regard to socio-demographic characteristics, the predominant marital status in males was single, and in females married (χ2=5.93, df=2, p=0.05). In occupation the male group was mainly unemployed and housewife in females (χ2=55.51, df=4, p<0.001). Male subjects were more likely to consume alcohol (χ2=20.40, df=1, p≤0.001), cannabis (χ2=16.62, df=1, p≤0.001) or tobacco. The prevalence of psychiatric diagnosis was significantly different because, the male group was mainly diagnosed with substance-related disorders, whereas female participants showed a prevalence of stress-related disorders (χ2=34.17, gl=4, p=0.0001).

CONCLUSION

Our results provide evidence that the characteristics of suicide attempt are different by gender in the Mexican population. Interventions are necessary for the development of prevention strategies that may lead to a reduction in suicidal behaviour. These preventive activities should consider the occupation for the female group and consumption of alcohol, cannabis or tobacco in the male group.

A Cross-National Tool for Assessing and Studying Suicidal Behaviors

Current methodologies employed in collecting data for suicide research present several limitations. In this article, we describe a novel method and tool to prospectively study suicidal behavior and its related risk and protective factors in different countries. This tool is a web-based database, which will initially be developed and piloted by suicide research groups from Austria, Brazil, Chile, France, Italy, Mexico, Spain, Sweden, and the US. The database will develop and integrate research tools key to collaboration, permit exploration of ethical considerations, and provide a universal interface in English, Spanish, French, Portuguese, Italian, and German that will make it possible to incorporate new groups from different countries to the network. The common database resulting of this cross-national effort will allow researchers to share and compare data across countries in a large sample of patients. Using anonymous electronic records of patients, we will: 1) determine the impact of risk and protective factors (viz. aggression and religious affiliation) in different socio-cultural environments; 2) develop a clinical model of suicidal behavior that integrates the multiple dimensions implicated; 3) try differentiating the effects of biological, environmental, and cultural factors on suicidal behavior, and 4) offer the global psychiatric research community a tool that will standardize assessment across nations, allowing for better generalization.

Posttraumatic Stress Disorder following childhood abuse increases the severity of suicide attempts

OBJECTIVE

Posttraumatic Stress Disorder (PTSD) and childhood abuse are both consistently associated with a higher risk for suicide attempts. We hypothesize that among patients reporting childhood abuse, PTSD diagnoses are correlated with an increased severity of suicidal features.

METHOD

We investigated 726 adult patients who had attempted suicide. These participants were assessed on lifetime clinical diagnoses and childhood abuse. The association of PTSD and childhood abuse dimensions with age at first suicide attempt, number of suicide attempts, violent attempts, serious attempts and suicide intent was studied. An adjusted multinomial logistic regression was performed to ascertain if childhood abuse and PTSD increased the severity of the suicidal behavior when combined.

RESULTS

Several types of childhood abuse (emotional, physical and sexual abuse) when combined with a lifetime diagnosis of PTSD showed an increased risk for more suicide attempts, serious attempts, and a higher level of suicidal intent compared with the absence of any or both risk factors.

CONCLUSION

The combination of PTSD and childhood abuse should be investigated in clinical settings due to an augmented risk for more severe suicidal behavior.

Increased severity of suicidal behavior in impulsive aggressive patients exposed to familial adversities

BACKGROUND

The mechanisms by which childhood abuse and family history of suicidal behavior (FHS) lead to an increased risk of suicidal behavior are still unknown. Impulsive aggression may play an intermediate role. We investigated whether greater scores for aggression and impulsivity might be associated with the effects of FHS and/or childhood abuse on the severity of suicidal behavior.

METHOD

We examined the scores of three scales measuring impulsive aggression in a sample of 696 suicide attempters. We compared the highest and lowest scores with regard to reports of childhood abuse and FHS using adjusted multinomial regression models. Genetic polymorphisms of the serotonergic system known to be associated with impulsive aggression were also analyzed.

RESULTS

Patients with high impulsive aggressive scores showed significant differences in sociodemographic, clinical and suicidal features compared with patients with low impulsive aggressive scores. Adjusted results showed that combinations of some types of childhood abuse and FHS, particularly emotional abuse and emotional neglect, are associated with high impulsivity and hostility scores. The SS genotype of the serotonin transporter gene (5-HTTLPR) was associated with high levels of impulsivity when the subjects reported emotional abuse [odds ratio (OR) 5.55, 95% confidence interval (CI) 1.75-17.5] or physical abuse (OR 5.03, 95% CI 1.50-16.9) in their childhood.

CONCLUSIONS

Our results support the role of impulsive aggression as one of the links that may connect childhood abuse and FHS with severity of suicidal behavior.

A cross-sectional study of major repeaters: a distinct phenotype of suicidal behavior

OBJECTIVE

The characterization of major repeaters (individuals with ≥ 5 lifetime suicide attempts) is a neglected area of research. Our aim was to establish whether or not major repeaters are a distinctive suicidal phenotype, taking into account a wide range of potential competing risks including sociodemographic characteristics, personal and familial history, psychiatric diagnoses, and personality traits.

METHOD

This cross-sectional study included 372 suicide attempters admitted to a specialized unit for suicide attempters in Montpellier University Hospital, Montpellier, France, between October 12, 2000, and June 10, 2010. Logistic regression models controlling for potential confounders were used.

RESULTS

When compared with subjects who attempted suicide < 5 times, major repeaters were more likely to be female (odds ratio [OR] = 5.54; 95% CI, 1.41-21.81), to have a lower educational level (OR = 5.1; 95% CI, 1.55-17.2), to have lifetime diagnoses of anorexia nervosa (OR = 3.45; 95% CI, 1.10-10.84) and substance dependence (OR = 5.00; 95% CI, 1.37-18.27), and to have lower levels of anger expressed outward (OR = 0.17; 95% CI, 0.06-0.47) and higher levels of trait anger (OR = 2.82; 95% CI, 1.18-6.75). Major repeaters had significantly higher suicide risk (lethality) scores (OR = 2.14; 95% CI, 1.08-4.23).

CONCLUSION

Major repeaters are a distinctive suicidal phenotype characterized by a distinctive sociodemographic (ie, female gender, low education) and clinical profile (ie, trait anger, substance dependence, anorexia nervosa). If our results are replicated, specific preventive plans should be tailored to major repeaters.

Suicide reattempters: a systematic review

The aim of this study is to identify the characteristic features of suicide reattempters. The recognition of the suicide reattempters population as a distinct clinical population may encourage future preventive and clinical work with this high-risk subgroup and thus reduce deaths. A systematic literature review was carried out in order to identify the key demographic, psychological, and clinical variables associated with the repetition of suicide attempts. In addition, we wished to analyze the operational definitions of the repetition of suicide attempts proposed in the scientific literature. Studies published from 2000 to 2012 were identified in PubMed, PsycINFO, and Web of Science databases and were selected according to predetermined criteria. We examined a total of 1480 articles and selected 86 that matched our search criteria. The literature is heterogeneous, with no consensus regarding the operational definitions of suicide reattempters. Comparison groups in the literature have also been inconsistent and include subjects making a single lifetime attempt and subjects who did not reattempt during a defined study period. Suicide reattempters were associated with higher rates of the following characteristics: unemployment, unmarried status, diagnosis of mental disorders, suicidal ideation, stressful life events, and family history of suicidal behavior. Additional research is needed to establish adequate differentiation and effective treatment plans for this population.

Suicidal ideation and risk factors in primary care patients with anxiety disorders

The presence of an anxiety disorder is associated with greater frequency of suicidal thoughts and behaviors. Given the high personal and societal costs of suicidal behaviors, suicide prevention is a priority. Understanding factors present within individuals with anxiety disorders that increase suicide risk may inform prevention efforts. The aims of the present study were to examine the prevalence of suicidal ideation and behaviors, as well as factors associated with suicide risk in patients with anxiety disorders in primary care. Data from a large scale randomized controlled study were analyzed to assess prevalence of suicidal thoughts and behaviors, as well as factors associated with suicide risk. Results revealed that suicidal ideation and behaviors were relatively common in this group. When examining mental and physical health factors jointly, presence of depression, mental health-related impairment, and social support each uniquely accounted for variance in suicide risk score. Methodological limitations include cross-sectional data collection and lack of information on comorbid personality disorders. Moreover, patients included were from a clinical trial with exclusion criteria that may limit generalizability. Results highlight the complex determinants of suicidal behavior and the need for more nuanced suicide assessment in this population, including evaluation of comorbidity and general functioning.

Characterization of suicidal behaviour with self-organizing maps

The study of the variables involved in suicidal behavior is important from a social, medical, and economical point of view. Given the high number of potential variables of interest, a large population of subjects must be analysed in order to get conclusive results. In this paper, we describe a method based on self-organizing maps (SOMs) for finding the most relevant variables even when their relation to suicidal behavior is strongly nonlinear. We have applied the method to a cohort with more than 8,000 subjects and 600 variables and discovered four groups of variables involved in suicidal behavior. According to the results, there are four main groups of risk factors that characterize the population of suicide attempters: mental disorders, alcoholism, impulsivity, and childhood abuse. The identification of specific subpopulations of suicide attempters is consistent with current medical knowledge and may provide a new avenue of research to improve the management of suicidal cases.

Individuals with single versus multiple suicide attempts over 10years of prospective follow-up

BACKGROUND

The study attempted to identify characteristics that differentiate multiple suicide attempters from single attempters in individuals with personality disorders (PDs) and/or major depression.

METHOD

Participants were 431 participants enrolled in the Collaborative Longitudinal Study of Personality Disorders from July 1996 to June 2008. Suicide attempts were assessed with the Longitudinal Interval Follow-up Evaluation at 6 and 12months, then yearly through 10years. Logistic regression was used to compare single attempters to multiple attempters on Axis I and II psychiatric disorders and personality trait variables.

RESULTS

Twenty-one percent of participants attempted suicide during the 10years of observation, with 39 (9.0%) reporting a single suicide attempt and 54 (12.5%) reporting multiple suicide attempts. Although no significant differences in were found in baseline Axis I disorders, multiple attempters were significantly more likely to meet criteria for borderline personality disorder and to have higher impulsivity scores than single attempters.

CONCLUSION

These results underscore the importance of considering both personality disorders and traits in the assessment of suicidality.

Literature-based recommendations for suicide assessment in the emergency department: a review

BACKGROUND

Suicidal ideation and attempted suicide are important presenting complaints in the Emergency Department (ED). The Joint Commission established a National Patient Safety Goal that requires screening for suicidal ideation to identify patients at risk for suicide.

OBJECTIVES

Given the emphasis on screening for suicidal ideation in the general hospital and ED, it is important for Emergency Physicians to be able to understand and perform suicide risk assessment.

METHODS

A review of literature was conducted using PubMed to determine important elements of suicide assessment in adults, ages 18 years and over, in the ED. Four typical ED cases are presented and the assessment of suicide risk in each case is discussed.

RESULTS

The goal of an ED evaluation is to appropriately determine which patients are at lowest suicide risk, and which patients are at higher or indeterminate risk such that psychiatry consultation is warranted while the patient is in the ED. Emergency clinicians should estimate this risk by taking into account baseline risk factors, such as previous suicide attempts, as well as acute risk factors, such as the presence of a suicide plan.

CONCLUSION

Although a brief screening of suicide risk in the ED does not have the sensitivity to accurately determine which patients are at highest risk of suicide after leaving the ED, patients at lowest risk may be identified. In these low-risk patients, psychiatric holds and real-time psychiatric consultation while in the ED may not be needed, facilitating more expeditious dispositions from the ED.

Genetic epistasis in female suicide attempters

BACKGROUND

Complex behaviors such as suicidal behavior likely exhibit gene-gene interactions. The main aim of this study is to explore potential single nucleotide polymorphisms combinations with epistatic effect in suicidal behavior using a data mining tool (Multifactor Dimensionality Reduction).

METHODS

Genomic DNA from peripheral blood samples was analyzed using SNPlex Technology. Multifactor Dimensionality Reduction was used to detect epistatic interactions between single nucleotide polymorphisms from the main central nervous system (CNS) neurotransmitters (dopamine: 9; noradrenaline: 19; serotonin: 23; inhibitory neurotransmitters: 60) in 889 individuals (417 men and 472 women) aged 18 years or older (585 psychiatric controls without a history of suicide attempts, and 304 patients with a history of suicide attempts). Individual analysis of association between single nucleotide polymorphisms and suicide attempts was estimated using logistic regression models.

RESULTS

Multifactor Dimensionality Reduction showed significant epistatic interactions involving four single nucleotide polymorphisms in female suicide attempters with a classification test accuracy of 60.7% (59.1%-62.4%, 95% CI): rs1522296, phenylalanine hydroxylase gene (PAH); rs7655090, dopamine receptor D5 gene (DRD5); rs11888528, chromosome 2 open reading frame 76, close to diazepam binding inhibitor gene (DBI); and rs2376481, GABA-A receptor subunit γ3 gene (GABRG3). The multivariate logistic regression model confirmed the relevance of the epistatic interaction [OR(95% CI)=7.74(4.60-13.37)] in females.

CONCLUSIONS

Our results suggest an epistatic interaction between genes of all monoamines and GABA in female suicide attempters.