The role of prediction in suicide prevention

Reliability of Suicide Risk Estimates: A Vignette Study

OBJECTIVE

Suicide risk assessments are obligatory when patients express a death wish in clinical practice. Yet, suicide risk estimates based on unguided risk assessments have been shown to be of low reliability. Since generalizability of previous studies is limited, the current study aimed to assess inter-rater and intra-rater reliability of risk estimates conducted by psychotherapists and psychology students using written case vignettes.

METHOD

In total, N = 256 participants (psychology students, psychotherapists) were presented with 24 case vignettes describing patients at either low, moderate, severe or extreme risk of suicide. Participants were asked to assign a level of risk to each single vignette at a baseline assessment and again at a follow-up assessment two weeks later.

RESULTS

Risk estimates showed a low inter-rater reliability, both for students (AC1 = .35) and for psychotherapists (AC1 = .44). Intra-rater reliability was moderate for psychotherapists (AC1 = .59) and rather low for psychology students (AC1 = .47). In general, intra- and intra-rater reliability were highest for vignettes displaying "low" and "extreme" risk.

CONCLUSIONS

The results highlight that the reliability of unguided suicide risk assessments is questionable. Standardized risk assessment protocols are therefore recommended. Nonetheless, even reliable risk estimation does not imply predictive validity of risk estimates for future suicidal behavior.

Suicide prevention: reflections on progress over the past decade

Interest in preventing suicides has increased greatly in recent years. In this Personal View, we consider the general global developments related to suicide prevention that have occurred in the decade since The Lancet Psychiatry was first published in 2014. We then review specific advances during this period, first, in relation to public health initiatives, and second, with regard to clinical developments. Finally, we examine some of the challenges that currently confront individuals and organisations responsible for designing and implementing suicide prevention measures.

Emerging Themes and Research Frontiers in Suicide Prediction: A Scientometric Analysis

Suicide remains a critical global health issue despite advancements in mental health treatment. The purpose of this analysis is to emphasize the development, patterns, and noteworthy outcomes of suicide prediction research. It also helps to uncover gaps and areas of under-researched topics within suicide prediction. A scientometric analysis was conducted using Biblioshiny and VOSviewer. To thoroughly assess the academic literature on suicide prediction, various scientometric methodologies such as trend analysis and citation analysis were employed. We utilized the temporal features of the Web of Science to analyze publication trends over time. Author affiliation data were used to investigate the geographic distribution of research. Cluster analysis was performed by grouping related keywords into clusters to identify overarching themes within the literature. A total of 1,703 articles from 828 different sources, spanning from 1942 to 2023, were collected for the analysis. Machine learning techniques might have a big influence on suicide-related event prediction, which would enhance attempts at suicide prevention and intervention. The conceptual understanding of suicide prediction is enhanced by scientometric analysis, which further uncovers the research gap and literature in this area. Suicide prediction research underscores that suicidal behavior is not caused by a single factor but is the result of a complex interplay of multiple factors. These factors may include biological, psychological, social, and environmental factors. Understanding and integrating these factors into predictive models is a theoretical advancement in the field. Unlike previous bibliometric studies in the field of suicide prediction that have typically focused on specific subtopics or data sources, our analysis offers a comprehensive mapping of the entire landscape. We encompass a wide range of suicide prediction literature, including research from medical, psychological, and social science domains, thus providing a holistic overview.

Suicide-preventive compulsory admission is not a proportionate measure - time for clinicians to recognise the associated risks

Suicide is considered a global public health issue and compulsory admission is a commonly used measure to prevent suicide. However, the practice has been criticised since several studies indicate that the measure lacks empirical support and may even increase suicide risk. This paper investigates whether the practice has enough empirical support to be considered proportionate. To that end, arguments supporting compulsory admission as a suicide-preventive measure for most suicidal patients are scrutinized. The ethical point of departure is that the expected benefits of compulsory admission should outweigh the potential harms of the measure to be proportionate and defensible. It is concluded that, for most suicidal patients, suicide-preventive compulsory admission cannot be presumed to be a proportionate measure. To be so, the expected medical benefits of the measure should be greater than the potential increase in suicide risk and other harms that compulsory admission could entail. Instead of using compulsory admission as a suicide-preventive measure, extra safety measures may be needed during and after compulsory admission to prevent the risk of hospitalisation-induced suicide.

The Positive and Negative Suicidal Ideation Inventory among Portuguese Adolescents: Factor Structure and Gender Invariance

Suicide worldwide is an issue that needs to be addressed, and adolescents are an at-risk group. Assessing suicidal ideation is central to tackling the issue of suicide. The Positive and Negative Suicidal Ideation inventory is a widely validated measure of suicidal ideation, and yet, very little is known about its invariance across various groups. The present study aimed to adapt and test the PANSI's structure in a Portuguese sample while testing its gender invariance. A total of 750 middle and high school students were recruited for the study, and data were collected on various suicide risk and protective factors, including the Portuguese-translated PANSI. Data were put through exploratory and confirmatory factor analysis. Kaiser's criterion and scree plot both extracted two factors (64.10% variance explained). Confirmatory factor analysis also supported the PANSI's structure (TLI = 0.943). The PANSI showed good reliability (α ≥ 0.83) and good construct and discriminative validity. The PANSI also exhibited scalar, but not strict, invariance. Overall, these results were similar to previous versions of this scale. The PANSI is a reliable measure of suicide risk among Portuguese adolescents. Future studies should further replicate these results in other cultures and expand on them by testing for invariance across other demographic variables.

The Psychometric Properties of the Positive and Negative Suicidal Ideation Scale among Portuguese Young Adults

Preventing suicide has been a worldwide imperative for the last decade. Accurately assessing suicide risk is the first step towards prevention, and access to reliable tools that measure risk factors is essential to achieve this goal. The Positive And Negative Suicidal Ideation (PANSI) scale is a validated brief suicidal ideation scale that could prove useful to this goal due to its ability to measure both suicide risk and protective factors. The PANSI scale has been adapted to various languages and cultures across various clinical and non-clinical populations. Despite this, no Portuguese has been produced yet. The present study aimed to validate a Portuguese version of PANSI by evaluating its psychometric properties in a sample of 259 young adults. Confirmatory factor analysis showed that the PANSI showed good psychometric properties (TLI = 0.95), good reliability for positive ideation (α = 0.84), and excellent reliability for negative ideation (α = 0.96). The scale also showed good discriminative ability through prediction of a previous suicide attempt and good construct validity in both subscales. The Portuguese adaptation of the PANSI scale is a reliable measure of positive and negative suicidal ideation that could prove useful in both clinical and research settings.

Recent anti-infective exposure as a risk factor for first episode of suicidal thoughts and/or behaviors in pediatric patients

Objectives

We conducted a retrospective cohort study of medical records from a large, Maryland, U.S.-based cohort of pediatric primary care patients for potential associations between antibacterial, antifungal and antiviral prescriptions and subsequent suicidal thoughts and/or behaviors.

Methods

Using first suicide-related diagnosis as the outcome and prior prescription of antibacterial, antifungal, and/or antiviral use as the exposure, we employed a series of multivariate Cox proportional hazards models. These models examined the hazard of developing newly recognized suicidal thoughts and/or behaviors, controlling for age, sex, race, insurance, number of encounters during the study period, prior mood disorder diagnosis and number of chronic health conditions. We constructed the same series of models stratified by the groups with and without a prior recorded mental or behavioral health diagnosis (MBHD).

Results

Suicidal thoughts and/or behaviors were associated with the previous prescription of an antibacterial, antifungal and/or antiviral medication (HR 1.31, 95 %-CI 1.05-1.64) as well as the total number of such medications prescribed (HR 1.04, 95 %-CI 1.01-1.08), with the strongest relationship among patients with three or more medications (HR 1.44, 95 %-CI 1.06-1.96). Among individual medications, the strongest association was with antibacterial medication (HR 1.28, 95 %-CI 1.03-1.60). Correlations were strongest among the subgroup of patients with no previous (MBHD).

Interpretation

Infections treated with antimicrobial medications were associated with increased risks of a suicide-related diagnosis among patients who had not had a previous mental or behavioral health diagnosis. This group should be considered for increased levels of vigilance as well as interventions directed at suicide screening and prevention.

Funding

National Institutes of Health, Stanley Medical Research Institute.

Racial and Gender Disparities in Suicide and Mental Health Care Utilization in a Pediatric Primary Care Setting

PURPOSE

We examined racial and gender disparities in the underrecognition of mental health disorders in adolescents and young adults as defined by a suicide-related diagnosis without a previous mental or behavioral health diagnosis.

METHODS

We employed a series of adjusted mixed multilevel logistic regression models to determine the odds of specific mental health diagnoses (anxiety, depression, and suicide-related) in a large, U.S. pediatric ambulatory care group (ages 8-20 years) using Electronic Medical Record Data.

RESULTS

Using the reference group of White males, White females had 17% increased odds of having a suicide-related diagnosis (odds ratio (OR) 1.17, 95% confidence intervals (CI) 1.03, 1.34) and Black females had 48% increased odds of suicide-related diagnosis (OR 1.48, 95% CI 1.28, 1.71). Conversely, White females had 75% increased odds of recorded anxiety (OR 1.75, 95% CI 1.62, 1.89), Black males had 62% decreased odds of anxiety (OR 0.38, 95% CI 0.33, 0.42), and Black females had 33% decreased odds of anxiety (OR 0.67, 95% CI 0.60, 0.74). White females had 81% increased odds of having recorded depression (OR 1.81, 95% CI 1.62, 2.04) and Black females had 80% increased odds of underrecognized need for mental or behavioral health diagnosis services (OR 1.80, 95% CI 1.53, 2.13) as defined by a suicide-related diagnosis without a previous mental health diagnosis.

DISCUSSION

Black adolescents and young adult patients are either not accessing or identified as needing mental health services at the same rates as their White peers, and Black females are experiencing the most underrecognition of need for mental health services.

Suicide Among Monotheistic Religions: Between Sacrifice, Honour and Power

This article discusses the problem of suicide in monotheistic religions (Judaism, Christianity and Islam), focusing on their early existence and considering the original contribution of Christianity. The first part presents the main theses of E. Durkheim on altruistic suicide and the concept of honour. This provides an opportunity to examine the problem of suicide in monotheistic religions from a more comprehensive perspective and recognise a certain specificity of suicide that was absent in altrusitic suicide. The analysis of the problem in relation to the concept of honour is also a valuable starting point for complementary psychological theories. The second part of the article is a more detailed discussion of suicide in Judaism, Christianity and Islam. The results provide a better understanding of the origins and nature of suicide in monotheistic religions whilst opening up a discussion on the possibility of suicide prevention.

Preventing Suicide: Time to Mobilize the Physical Therapist Workforce

Each year, approximately 700,000 people, including 46,000 Americans, die by suicide; however, many more people experience suicidal thoughts and behaviors. Historically, the prevention of suicide has largely been the domain of mental health professionals working within specialist mental health care settings. An issue with this approach is that many individuals who experience suicidal ideation never disclose these thoughts to a mental health professional. The nonprofessional and paraprofessional mental health movement aims to bring suicide prevention to the people who need it, rather than wait for them to seek help. The nonprofessional and paraprofessional mental health movement does so by upskilling people who are not recognized as mental health professionals but may have contact with people experiencing suicidal thoughts and behaviors. In this Perspective, we argue that physical therapists are well-positioned to engage in suicide prevention. For example, physical therapists working in pain management are likely to frequently encounter clients experiencing suicidal thoughts and behaviors. Physical therapy is also viewed as a physical health profession, meaning that they may have contact with a broad range of populations at high risk of suicide who may be difficult to reach through traditional channels (eg, men from rural communities). Physical therapists will require training on how to provide crisis support, including how to link clients with appropriate mental health services. However, given the size of the physical therapist workforce globally, the impact of mobilizing the physical therapist workforce could be significant.

Are false positives in suicide classification models a risk group? Evidence for "true alarms" in a population-representative longitudinal study of Norwegian adolescents

Introduction

False positives in retrospective binary suicide attempt classification models are commonly attributed to sheer classification error. However, when machine learning suicide attempt classification models are trained with a multitude of psycho-socio-environmental factors and achieve high accuracy in suicide risk assessment, false positives may turn out to be at high risk of developing suicidal behavior or attempting suicide in the future. Thus, they may be better viewed as "true alarms," relevant for a suicide prevention program. In this study, using large population-based longitudinal dataset, we examine three hypotheses: (1) false positives, compared to the true negatives, are at higher risk of suicide attempt in future, (2) the suicide attempts risk for the false positives increase as a function of increase in specificity threshold; and (3) as specificity increases, the severity of risk factors between false positives and true positives becomes more similar.

Methods

Utilizing the Gradient Boosting algorithm, we used a sample of 11,369 Norwegian adolescents, assessed at two timepoints (1992 and 1994), to classify suicide attempters at the first time point. We then assessed the relative risk of suicide attempt at the second time point for false positives in comparison to true negatives, and in relation to the level of specificity.

Results

We found that false positives were at significantly higher risk of attempting suicide compared to true negatives. When selecting a higher classification risk threshold by gradually increasing the specificity cutoff from 60% to 97.5%, the relative suicide attempt risk of the false positive group increased, ranging from minimum of 2.96 to 7.22 times. As the risk threshold increased, the severity of various mental health indicators became significantly more comparable between false positives and true positives.

Conclusion

We argue that the performance evaluation of machine learning suicide classification models should take the clinical relevance into account, rather than focusing solely on classification error metrics. As shown here, the so-called false positives represent a truly at-risk group that should be included in suicide prevention programs. Hence, these findings should be taken into consideration when interpreting machine learning suicide classification models as well as planning future suicide prevention interventions for adolescents.

One-Week Suicide Risk Prediction Using Real-Time Smartphone Monitoring: Prospective Cohort Study

BACKGROUND

Suicide is a major global public health issue that is becoming increasingly common despite preventive efforts. Though current methods for predicting suicide risk are not sufficiently accurate, technological advances provide invaluable tools with which we may evolve toward a personalized, predictive approach.

OBJECTIVE

We aim to predict the short-term (1-week) risk of suicide by identifying changes in behavioral patterns characterized through real-time smartphone monitoring in a cohort of patients with suicidal ideation.

METHODS

We recruited 225 patients between February 2018 and March 2020 with a history of suicidal thoughts and behavior as part of the multicenter SmartCrisis study. Throughout 6 months of follow-up, we collected information on the risk of suicide or mental health crises. All participants underwent voluntary passive monitoring using data generated by their own smartphones, including distance walked and steps taken, time spent at home, and app usage. The algorithm constructs daily activity profiles for each patient according to these data and detects changes in the distribution of these profiles over time. Such changes are considered critical periods, and their relationship with suicide-risk events was tested.

RESULTS

During follow-up, 18 (8%) participants attempted suicide, and 14 (6.2%) presented to the emergency department for psychiatric care. The behavioral changes identified by the algorithm predicted suicide risk in a time frame of 1 week with an area under the curve of 0.78, indicating good accuracy.

CONCLUSIONS

We describe an innovative method to identify mental health crises based on passively collected information from patients' smartphones. This technology could be applied to homogeneous groups of patients to identify different types of crises.

Validation of the German Version of the P4 Suicidality Tool

For general practitioners (GPs), it may be challenging to assess suicidal ideation (SI) in patients. Although promising instruments exist for the use in primary care, only a few have been validated in German. The objectives of this study were to examine the validity of the brief P4 screener for assessing SI in a cross-sectional study including outpatients. Inclusion criteria were a PHQ-9 score ≥ 10 or an affirmative answer to its SI item. Construct validity of the P4 was examined by comparison with the four-item Suicide Behaviors Questionnaire-Revised (SBQ-R), the PHQ-9 (convergent), and the positive mental health (PMH) scale (divergent). The study sample included 223 patients (mean age 47.61 ± 15 years; 61.9% women) from 20 primary care practices (104 patients) and 10 psychiatric/psychotherapeutic clinics (119 patients). The first three items of the P4 correlate positively with most of the four items of the reference standard SBQ-R (convergent validity); the fourth item of the P4 (preventive factors) correlates significantly with the PMH scale. The most common preventive factor (67%) is family or friends. The German P4 screener can be used to assess SI in outpatient care. It explores preventive or protective factors of suicide, which may support the GP's decision on treatment. We recommend a further clinical interview for patients flagged by P4 assessment in order to more formally assess suicidal risk.

Circadian Activity Rhythms and Psychopathology in Major Depressive Episodes

BACKGROUND

Identifying suicidal risk based on clinical assessment is challenging. Suicidal ideation fluctuates, can be downplayed or denied, and seems stigmatizing if divulged. In contrast, vitality is foundational to subjectivity in being immediately conscious before reflection. Including its assessment may improve detection of suicidal risk compared to relying on suicidal ideation alone. We hypothesized that objective motility measures would be associated with vitality and enhance assessment of suicidal risk.

METHODS

We evaluated 83 adult-psychiatric outpatients with a DSM-5 bipolar (BD) or major depressive disorder (MDD): BD-I (n = 48), BD-II (20), and MDD (15) during a major depressive episode. They were actigraphically monitored continuously over 3 weekdays and self-rated their subjective states at regular intervals. We applied cosinor analysis to actigraphic data and analyzed associations of subjective psychopathology measures with circadian activity parameters.

RESULTS

Actigraphic circadian mesor, amplitude, day- and nighttime activity were lower with BD versus MDD. Self-rated vitality (wish-to-live) was significantly lower, self-rated suicidality (wish-to-die) was higher, and their difference was lower, with BD versus MDD. There were no other significant diagnostic differences in actigraphic sleep parameters or in self-rated depression, dysphoria, or anxiety. By linear regression, the difference between vitality and passive suicidal ideation was strongly positively correlated with mesor (p < 0.0001), daytime activity (p < 0.0001), and amplitude (p = 0.001).

CONCLUSIONS

Higher circadian activity measures reflected enhanced levels of subjective vitality and were associated with lesser suicidal ideation. Current suicidal-risk assessment might usefully include monitoring of motility and vitality in addition to examining negative affects and suicidal thinking.

Predictive modelling of deliberate self-harm and suicide attempts in young people accessing primary care: a machine learning analysis of a longitudinal study

PURPOSE

Machine learning (ML) has shown promise in modelling future self-harm but is yet to be applied to key questions facing clinical services. In a cohort of young people accessing primary mental health care, this study aimed to establish (1) the performance of models predicting deliberate self-harm (DSH) compared to suicide attempt (SA), (2) the performance of models predicting new-onset or repeat behaviour, and (3) the relative importance of factors predicting these outcomes.

METHODS

802 young people aged 12-25 years attending primary mental health services had detailed social and clinical assessments at baseline and 509 completed 12-month follow-up. Four ML algorithms, as well as logistic regression, were applied to build four distinct models.

RESULTS

The mean performance of models predicting SA (AUC: 0.82) performed better than the models predicting DSH (AUC: 0.72), with mean positive predictive values (PPV) approximately twice that of the prevalence (SA prevalence 14%, PPV: 0.32, DSH prevalence 22%, PPV: 0.40). All ML models outperformed standard logistic regression. The most frequently selected variable in both models was a history of DSH via cutting.

CONCLUSION

History of DSH and clinical symptoms of common mental disorders, rather than social and demographic factors, were the most important variables in modelling future behaviour. The performance of models predicting outcomes in key sub-cohorts, those with new-onset or repetition of DSH or SA during follow-up, was poor. These findings may indicate that the performance of models of future DSH or SA may depend on knowledge of the individual's recent history of either behaviour.

Assessment of suicide risk in mental health practice: shifting from prediction to therapeutic assessment, formulation, and risk management

Suicide prevention in psychiatric practice has been dominated by efforts to predict risk of suicide in individual patients. However, traditional risk prediction measures have been shown repeatedly in studies from high income countries to be ineffective. Several factors might contribute to clinicians' preoccupation with risk prediction, which can have negative effects on patient care and also on clinicians where prediction is seen as failing. The model of therapeutic risk assessment, formulation, and management we outline in this article regards all patients with mental health problems as potentially at increased risk of suicide. It is aimed at reducing risk through use of a person-centred approach. We describe how a move towards therapeutic risk assessment, formulation, and risk management, including collaborative safety planning, could help clinicians develop a more tailored approach to managing risk for all patients, incorporating potentially therapeutic effects as well as helping to identify other risk reduction interventions. Such an approach could lead to enhanced patient safety and quality of care, which is more acceptable to patients.

Early Intervention for Personality Disorder

Both the DSM-5 Section III Alternative Model for Personality Disorders and the ICD-11 have introduced a genuinely developmental approach to personality disorder. Among young people with personality disorder, compelling evidence demonstrates a high burden of disease, substantial morbidity, and premature mortality, as well as response to treatment. Yet, early diagnosis and treatment for the disorder have struggled to emerge from its identity as a controversial diagnosis to a mainstream focus for mental health services. Key reasons for this include stigma and discrimination, lack of knowledge about and failure to identify personality disorder among young people, along with the belief that personality disorder must always be addressed through lengthy and specialized individual psychotherapy programs. In fact, evidence suggests that early intervention for personality disorder should be a focus for all mental health clinicians who see young people and is feasible by using widely available clinical skills.

Suicide Risk Assessments: A Scientific and Ethical Critique

There are widely held premises that suicide is almost exclusively the result of mental illness and there is "strong evidence for successfully detecting and managing suicidality in healthcare" (Hogan and Grumet, 2016). In this context, 'zero-suicide' policies have emerged, and suicide risk assessment tools have become a normative component of psychiatric practice. This essay discusses how suicide evolved from a moral to a medical problem and how, in an effort to reduce suicide, a paternalistic healthcare response emerged to predict those at high risk. The evidence for the premises is critiqued and shown to be problematic; and it is found that strong paternalistic interventions are being used more often than acknowledged. Using a Principles approach, the ethics of overriding autonomy in suicide prevention is considered. Ethical concerns are identified with the current approach which are potentially amplified by the use of these risk assessments. Furthermore, it is identified that the widespread use of risk assessments in health settings is equivalent to screening without regard to the ethical principles of screening. The essay concludes that this is unethical; that we should abandon the use of standardized suicide risk assessments and 'zero-suicide' policy; and that this may improve outcomes.

Identifying Youth at Risk for Suicidal Thoughts and Behaviors Using the "p" factor in Primary Care: An Exploratory Study

Suicide is a major, preventable public health problem. The general factor of psychopathology ("p" factor) might help improve detection and prediction of individuals at risk for suicide. This cross-sectional proof-of-concept study tests whether the p-factor score is associated with suicidal thoughts and behaviors (STB) better than a depression scale alone. Youth (N = 841; mean age 18.02, SD = 3.36) in primary care were universally screened using the Behavioral Health Screen (BHS). Factor analysis and ROC results showed the BHS assesses the p-factor, and the p-factor score demonstrates higher classification accuracy of several types of STB than a depression scale. The p-factor could help clinicians in the identification of youths with STB.

[Suicide prevention: How to act?]

Although being complex, suicide is a phenomenon considered as preventable, and its prevention has been made as a public health priority. Some interventions to prevent suicide have been evaluated, such as the education of the healthcare workers, especially in the suicidal assessment (suicidal risk and suicidal emergency/dangerousness), the diagnosis and management of common mental disorders, the care provided after a suicide attempt, the restriction access to common means of suicide, the use of websites to educate the public, or the appropriate reports of suicide in media. Other interventions, even not rigorously evaluated, are implemented in France as in many parts of the world. It is the case of interventions among identified high-risk groups. To be efficient, prevention programs should simultaneously include different strategies targeting several known risk factors for suicide. Clinicians play a crucial role in the suicide prevention strategies.

Exploring the Risk of Suicide in Real Time on Spanish Twitter: Observational Study

Background

Social media is now a common context wherein people express their feelings in real time. These platforms are increasingly showing their potential to detect the mental health status of the population. Suicide prevention is a global health priority and efforts toward early detection are starting to develop, although there is a need for more robust research.

Objective

We aimed to explore the emotional content of Twitter posts in Spanish and their relationships with severity of the risk of suicide at the time of writing the tweet.

Methods

Tweets containing a specific lexicon relating to suicide were filtered through Twitter's public application programming interface. Expert psychologists were trained to independently evaluate these tweets. Each tweet was evaluated by 3 experts. Tweets were filtered by experts according to their relevance to the risk of suicide. In the tweets, the experts evaluated: (1) the severity of the general risk of suicide and the risk of suicide at the time of writing the tweet (2) the emotional valence and intensity of 5 basic emotions; (3) relevant personality traits; and (4) other relevant risk variables such as helplessness, desire to escape, perceived social support, and intensity of suicidal ideation. Correlation and multivariate analyses were performed.

Results

Of 2509 tweets, 8.61% (n=216) were considered to indicate suicidality by most experts. Severity of the risk of suicide at the time was correlated with sadness (ρ=0.266; P<.001), joy (ρ=–0.234; P=.001), general risk (ρ=0.908; P<.001), and intensity of suicidal ideation (ρ=0.766; P<.001). The severity of risk at the time of the tweet was significantly higher in people who expressed feelings of defeat and rejection (P=.003), a desire to escape (P<.001), a lack of social support (P=.03), helplessness (P=.001), and daily recurrent thoughts (P=.007). In the multivariate analysis, the intensity of suicide ideation was a predictor for the severity of suicidal risk at the time (β=0.311; P=.001), as well as being a predictor for fear (β=–0.009; P=.01) and emotional valence (β=0.007; P=.009). The model explained 75% of the variance.

Conclusions

These findings suggest that it is possible to identify emotional content and other risk factors in suicidal tweets with a Spanish sample. Emotional analysis and, in particular, the detection of emotional variations may be key for real-time suicide prevention through social media.

Hospital staff at most psychiatric clinics in Stockholm experience that patients who self-harm have too long hospital stays, with ensuing detrimental effects

BACKGROUND

Previous research on patients who self-harm has indicated potential negative effects from long hospital stays. Yet, such care has been reported to occur regularly. We conducted this questionnaire study to investigate how hospital staff, who treat self-harming patients, experience the relation between lengths of stay and self-harm behaviour, and the motives for non-beneficial hospital stays.

METHODS

The respondents of the questionnaire were nurses and mental health workers employed at public inpatient wards in Stockholm, treating patients who self-harm. The questionnaire contained questions with fixed answers and room for comments. A total of 304 questionnaires were distributed to 13 wards at five clinics, and the response rate was 63%. The data were analysed with descriptive statistics and qualitative descriptive content analysis.

RESULTS

The results show that most staff experienced that more than a week's stay either increased (57%) or had no effect (33%) on self-harm behaviour. Most respondents at most clinics considered the stays to be too long at their wards, and that the stays could be reduced. The respondents recognized several reasons for non-beneficial hospital stays, like fear of suicidal behaviour and doctors' fear of complaints. Patients appearing as demanding or fragile were thought to be given more care than others. The respondents' comments confirmed the majority's experience of detrimental effects from longer hospital stays.

CONCLUSIONS

A majority of the health care staff experienced that patients who self-harm often receive too long hospital stays, with detrimental effects, and they had experienced several non-medical reasons for such care.

Catalytic Reaction Model of Suicide

Suicide is a devastating outcome of unresolved issues that affect mental health, general wellbeing and socioeconomic stress. The biology of suicidal behavior is still poorly understood, although progress has been made. Suicidal behavior runs in families and genetic studies have provided initial glimpses into potential genes that contribute to suicide risk. Here, we attempt to unify the biology and behavioral dimensions into a model that can guide research in this area. The proposed model envisions suicidal behavior as a catalytic reaction that may result in suicide depending on the conditions, analogously to enzyme catalysis of chemical reactions. A wide array of substrates or reactants, such as hopelessness, depression, debilitating illnesses and diminished motivation can mobilize suicidal thoughts and behaviors (STBs), which can then catalyze the final step/act of suicide. Here, we focus on three biological substrates in particular: threat assessment, motivation to engage in life and impulsivity. Genetic risk factors can affect each of these processes and tilt the balance toward suicidal behavior when existential crises (real or perceived) emerge such as loss of a loved one, sudden changes in social status or serious health issues. Although suicide is a uniquely human behavior, many of the fundamental biological processes are evolutionarily conserved. Insights from animal models may help to shape our understanding of suicidal behavior in man. By examining counterparts of the major biological processes in other organisms, new ideas about the role of genetic risk factors may emerge along with possible therapeutic interventions or preventive measures.

[Suicides in the German prison system: frequency, risk factors, and prevention]

Gefangene haben ein hohes Suizidrisiko und die höchsten Suizidraten sind bei Untersuchungsgefangenen zu verzeichnen. Suizid ist die häufigste singuläre Todesursache in deutschen Gefängnissen. In diesem narrativen Übersichtsbeitrag werden zunächst die Gefängnispopulation und ihre allgemeine Gesundheitsversorgung beschrieben, wobei insbesondere auf psychiatrische und Substanzkonsumstörungen eingegangen wird. Der Hauptteil widmet sich der Prävalenz, den Ursachen und Risikofaktoren von Gefängnissuizid. Maßnahmen zur Suizidprävention werden dargestellt.

Der Anteil von Männern unter Gefangenen in Deutschland ist mit 94 % (2020) wie in allen Teilen der Welt sehr hoch. Die meisten Gefangenen sind jungen oder mittleren Alters. Die durchschnittlichen jährlichen Suizidraten bei Männern und Frauen in deutschen Gefängnissen entsprechen mit 105,8/100.000 bzw. 54,7/100.000 denen der meisten Länder in der Europäischen Union (Vollerhebung 2000–2011). Die Suizidraten bei männlichen deutschen Gefangenen sind in den Jahren 2000–2013 unabhängig vom Alter kontinuierlich zurückgegangen. Bei weiblichen Gefangenen stiegen sie dagegen an, wobei die Ursachen hierfür nicht bekannt sind. Es gibt Hinweise darauf, dass psychiatrische Erkrankungen nicht erkannt worden waren.

Wichtige suizidpräventive Maßnahmen sind die Unterbringung in Gemeinschaft und die Vermeidung von Isolation, beispielsweise durch das Angebot von Arbeit. Zudem stehen validierte deutschsprachige Screeninginstrumente zur Verfügung, um ein Suizidrisiko frühzeitig zu erkennen. Für eine wirksame Gefängnissuizidprävention bedarf es der Identifikation von Hochrisikopersonen, des Angebots geeigneter suizidpräventiver Maßnahmen sowie der Entwicklung teambezogener Maßnahmen beim Gefängnispersonal.

Barbiturate-related hospitalisations, drug treatment episodes, and deaths in Australia, 2000-2018

OBJECTIVES

To determine the characteristics and population rates of barbiturate-related hospitalisations, treatment episodes, and deaths in Australia, 2000-2018.

DESIGN, SETTING

Analysis of national data on barbiturate-related hospitalisations (National Hospital Morbidity Database, 1999-2000 to 2017-18), drug treatment episodes (Alcohol and Other Drug Treatment Services National Minimum Data Set, 2002-03 to 2017-18), and deaths (National Coronial Information System, 2000-01 to 2016-17).

MAIN OUTCOME MEASURES

Population rates directly age-standardised to the 2001 Australian standard population; average annual percentage change (AAPC) in rates estimated by Joinpoint regression.

RESULTS

We identified 1250 barbiturate-related hospitalisations (791 cases of deliberate self-harm [63%]), 993 drug treatment episodes (195 cases with barbiturates as the principal drug of concern [20%]), and 511 deaths during the respective analysis periods. The barbiturate-related hospitalisation rate declined from 0.56 in 1999-2000 to 0.14 per 100 000 population in 2017-18 (AAPC, -6.0%; 95% CI, -7.2% to -4.8%); the declines in hospitalisations related to accidental poisoning (AAPC, -5.8%; 95% CI, -9.1% to -2.4%) and intentional self-harm (AAPC, -5.6%; 95% CI, -6.9% to -4.2%) were each statistically significant. Despite a drop from 0.67 in 2002-03 to 0.23 per 100 000 in 2003-04, the drug treatment episode rate did not decline significantly (AAPC, -6.7%; 95% CI, -16% to +4.0%). The population rate of barbiturate-related deaths increased from 0.07 in 2000-01 to 0.19 per 100 000 population in 2016-17 (AAPC, +9.3%; 95% CI, +6.2-12%); the rate of intentional self-harm deaths increased (AAPC, +11%; 95% CI, +7.4-15%), but not that of accidental deaths (AAPC, -0.3%; 95% CI, -4.1% to +3.8%).

CONCLUSIONS

While prescribing and community use of barbiturates has declined, the population rate of intentional self-harm using barbiturates has increased. The major harm associated with these drugs is now suicide.

Do implicit measures improve suicide risk prediction? An 18-month prospective study using different tasks

BACKGROUND

There is accumulating evidence that implicit measures improve the prediction of suicidality within a 6-month follow-up period in psychiatric populations. Building upon these results, we set out to expand the follow-up period and to investigate various implicit methods.

METHODS

Seventy-nine inpatients completed the Beck Scale for Suicidal Ideation (BSS) and a range of implicit measures: three implicit association tests (IATs: Death; Self-harm-Me/Others; Self-Harm-Good/Bad) and a subliminal priming task (with separate scores for negative and positive adjectives, each indicating the association between the primes "dying" and "growing"). After 18 months, we reached n = 52 patients and reassessed suicidal ideation, plans, and attempts.

RESULTS

In a hierarchical regression, the five implicit task indices were entered after the patient's age, gender, and BSS score at baseline. The implicit scores improved prediction of BSS scores after 18 months compared to prediction based on age, gender, and BSS score at baseline alone. However, none of the implicit measures was associated with suicide plans or attempts during the follow-up period.

CONCLUSION

Results suggest that implicit measures can be a useful assessment tool for the prediction of suicidal ideation, even beyond the BSS. However, long-term prediction of suicide plans or attempts using implicit measures seems limited.

Gatekeeper training for friends and family of individuals at risk of suicide: A systematic review

AIMS

Gatekeeper training (GKT) is an important suicide prevention strategy. Studies have evaluated the effectiveness of GKT in different populations, often neglecting family and friends who play a vital role in caring for people with suicide risk. This review evaluated GKT programs targeting family and friends to determine their effectiveness in this specific population.

METHODS

Academic databases were searched for studies on GKT programs. Programs involving family and friends caring for people with suicide risk were assessed for any impact on knowledge, self-efficacy, attitudes, and suicide prevention skills.

RESULTS

Seventeen studies were reviewed. GKT showed significant gains on outcomes of interest. Three studies targeted family and friends, with one involving them in program creation and conduction and another adjusting the program after their input.

CONCLUSIONS

GKT programs have potentially positive effects on family and friends caring for people with suicide risk. Few programs address the specific needs of this group, and programs adapted specifically for them are scarce. Future program development recommendations are discussed.

Is suicidal behaviour a stronger predictor of later suicide than suicidal ideation? A systematic review and meta-analysis

OBJECTIVE

Suicidal ideation and suicidal behaviour are both regarded as important risk factors for suicide, but it is usually believed that suicidal ideation is less strongly linked to suicide than suicidal behaviours. In this study, we assessed and compared the strengths of the associations that suicidal ideation and suicidal behaviour have with later suicide using meta-analysis of primary studies reporting both these independent variables and the dependent variable of suicide.

METHODS

A total of 51 English language publications describing cohort or controlled studies that reported on both the association between suicidal ideation and suicide and the association between suicidal behaviours and suicide were located using searches for titles in PubMed containing variants of the word suicide (suicid*). Suicides were considered to include reported suicides and open verdicts from mortality registers. The strengths of the two associations were examined in separate random effects meta-analyses and were then compared using mixed effects meta-regression. Subgroups were examined according to study characteristics including the definitions of suicidal ideation or behaviour used, setting (psychiatric or non-psychiatric), diagnostic mix of the study population, study design (cohort or control) and study quality.

RESULTS

Suicidal ideation (odds ratio = 3.11, 95% confidence interval = 2.51, 3.86) and suicidal behaviours (odds ratio = 4.09, 95% confidence interval = 3.05, 5.49) were both significantly associated with suicide but there was no significant difference in the strengths of association (p = 0.14). Nor were there significant differences in the strengths of the two associations in multiple subgroup analyses.

CONCLUSION

Suicidal ideation and suicidal behaviour are both moderately associated with suicide. Existing data cannot conclusively demonstrate that suicidal behaviours are more strongly associated with suicide than suicidal ideation. Clinicians should not strongly prioritise suicidal behaviour over suicidal ideation when considering suicide risk.

Accuracy of individual and combined risk-scale items in the prediction of repetition of self-harm: multicentre prospective cohort study

BACKGROUND

Individuals attending emergency departments following self-harm have increased risks of future self-harm. Despite the common use of risk scales in self-harm assessment, there is growing evidence that combinations of risk factors do not accurately identify those at greatest risk of further self-harm and suicide.

AIMS

To evaluate and compare predictive accuracy in prediction of repeat self-harm from clinician and patient ratings of risk, individual risk-scale items and a scale constructed with top-performing items.

METHOD

We conducted secondary analysis of data from a five-hospital multicentre prospective cohort study of participants referred to psychiatric liaison services following self-harm. We tested predictive utility of items from five risk scales: Manchester Self-Harm Rule, ReACT Self-Harm Rule, SAD PERSONS, Modified SAD PERSONS, Barratt Impulsiveness Scale and clinician and patient risk estimates. Area under the curve (AUC), sensitivity, specificity, predictive values and likelihood ratios were used to evaluate predictive accuracy, with sensitivity analyses using classification-tree regression.

RESULTS

A total of 483 self-harm episodes were included, and 145 (30%) were followed by a repeat presentation within 6 months. AUC of individual items ranged from 0.43-0.65. Combining best performing items resulted in an AUC of 0.56. Some individual items outperformed the scale they originated from; no items were superior to clinician or patient risk estimations.

CONCLUSIONS

No individual or combination of items outperformed patients' or clinicians' ratings. This suggests there are limitations to combining risk factors to predict risk of self-harm repetition. Risk scales should have little role in the management of people who have self-harmed.

Detection of Suicidality Among Opioid Users on Reddit: Machine Learning-Based Approach

BACKGROUND

In recent years, both suicide and overdose rates have been increasing. Many individuals who struggle with opioid use disorder are prone to suicidal ideation; this may often result in overdose. However, these fatal overdoses are difficult to classify as intentional or unintentional. Intentional overdose is difficult to detect, partially due to the lack of predictors and social stigmas that push individuals away from seeking help. These individuals may instead use web-based means to articulate their concerns.

OBJECTIVE

This study aimed to extract posts of suicidality among opioid users on Reddit using machine learning methods. The performance of the models is derivative of the data purity, and the results will help us to better understand the rationale of these users, providing new insights into individuals who are part of the opioid epidemic.

METHODS

Reddit posts between June 2017 and June 2018 were collected from r/suicidewatch, r/depression, a set of opioid-related subreddits, and a control subreddit set. We first classified suicidal versus nonsuicidal languages and then classified users with opioid usage versus those without opioid usage. Several traditional baselines and neural network (NN) text classifiers were trained using subreddit names as the labels and combinations of semantic inputs. We then attempted to extract out-of-sample data belonging to the intersection of suicide ideation and opioid abuse. Amazon Mechanical Turk was used to provide labels for the out-of-sample data.

RESULTS

Classification results were at least 90% across all models for at least one combination of input; the best classifier was convolutional neural network, which obtained an F1 score of 96.6%. When predicting out-of-sample data for posts containing both suicidal ideation and signs of opioid addiction, NN classifiers produced more false positives and traditional methods produced more false negatives, which is less desirable for predicting suicidal sentiments.

CONCLUSIONS

Opioid abuse is linked to the risk of unintentional overdose and suicide risk. Social media platforms such as Reddit contain metadata that can aid machine learning and provide information at a personal level that cannot be obtained elsewhere. We demonstrate that it is possible to use NNs as a tool to predict an out-of-sample target with a model built from data sets labeled by characteristics we wish to distinguish in the out-of-sample target.

The Relationship between Suicide and Oxidative Stress in a Group of Psychiatric Inpatients

Diagnosis of suicide risk is a clinical challenge requiring an interdisciplinary therapeutic approach. Except for psychological explanation of the suicidal mechanism, there is evidence that it is associated with brain chemistry disturbances as oxidative stress. The objective of this study was to explore the role of oxidative stress components in suicidality comparing subjects at different stages of suicide. The study included psychiatric inpatients aged 18–64 (n = 48) with different psychiatric diagnoses. Blood specimens were collected from subjects and tested for oxidative stress biomarkers: superoxide dismutase (SOD), dityrozine (DT), oxidative stress index (OSI), glutathione peroxidase (GPx), total antioxidant capacity (TAC trolox), ferric reducing ability of plasma (FRAP), total oxidant status (TOS), catalase (CAT), advanced glycoxidation end products (AGE), NADPH oxidase (NOX), and advanced oxidation protein products (AOPP). The Columbia Severity Suicide Scale (C-SSRS) was used for suicidality assessment. Subjects with a history of suicide ideations over the last three months had significantly higher levels of NOX, AOPP, and OSI. There was no significant relationship to any oxidative stress component levels either with a history of suicide behaviors or with suicide attempts over the last three months. The levels of NOX and AOPP were both positively correlated to the intensity of suicidal thoughts. Moreover, there was a positive correlation between a number of suicide attempts during a lifetime with AGE and DT and negative with CAT. Similarly, the subjects with a history of suicide attempts had significantly higher AGE and DT levels and lower CAT values. The study confirmed that oxidative stress plays an important role in the pathophysiology of suicide and specific oxidative stress measures vary in suicidal and non-suicidal psychiatric inpatients.

What would cardiology do? Lessons from other medical specialties should help guide suicide prevention research

Suicide is among the most important causes of mortality in medicine as it is the most common cause of death due to illness from the teenage years into middle age. Yet our approach to mental health research aimed at suicide prevention has often diverged from accepted practices in other areas of medicine. This includes the exclusion of those at highest risk of suicide from clinical trials and the recent emphasis on prediction. In this Viewpoint, we propose that comparing our approach to that of other medical specialties would help us to avoid strategic errors and discuss the implications for the field of suicide prevention.

Predicting suicide: A comparison between clinical suicide risk assessment and the Suicide Intent Scale

BACKGROUND

How suicide risk should be assessed is under discussion with arguments for both actuarial and clinical approaches. The aim of the present study was to compare the predictive accuracy of a clinical suicide risk assessment to that of the Suicide Intent Scale (SIS) in predicting suicide within one year of an episode of self-harm with or without suicidal intent.

METHODS

Prospective clinical study of 479 persons assessed in a psychiatric emergency department after an episode of self-harm. The clinical risk assessment and the SIS rating were made independently of each other. Suicides within one year were identified in the National Cause of Death Register. Receiver operating characteristic (ROC) curves were constructed, optimal cut-offs were identified and accuracy statistics were calculated.

RESULTS

Of 479 participants, 329 (68.7%) were women. The age range was 18-95 years. During one-year follow up, 14 participants died by suicide. The area under the curve (AUC) for the clinical risk assessment and the SIS score were very similar, as were the accuracy statistic measures at the optimal cut-offs of the respective methods. The positive predictive value (PPV) of each assessment method was 6%.

LIMITATIONS

The clinical suicide risk assessment is not standardized. The number of suicides is small, not allowing for stratification by e.g. gender or diagnosis.

CONCLUSION

Predictive accuracy was similar for a clinical risk assessment and the SIS, and insufficient to guide treatment allocation.

The Study of Motivation in the Suicidal Process: The Motivational Interview for Suicidality

Introduction: Suicide is the outcome of a process starting with the experiences of an unbearable pain or hopelessness, passing from suicidal ideation and planning, to possible para-suicidal behaviors or actual attempts. Recent studies have evidenced the necessity to integrate approaches based on the identification of psychopathological diagnoses and other variables as possible predictors of suicidal conduct with a more clinically based approach. A clinical assessment is needed that focuses on the patients' mental state with respect to thoughts concerning death and suicide. In particular, a qualitative assessment of motivations underlying the suicidal process could represent an effective guide for clinicians engaged in the difficult field of preventing adolescents' suicidal gestures. Most instruments investigating the suicidal motivation are self-report measures, possibly resulting in a lack of sufficiently valid assessment of this area. In the present work, we present the Motivational Interview for Suicidality in Adolescence (MIS-A) aiming at identifying the motivational areas sustaining suicidal ideation and gestures in this phase of development. Materials and Methods: The identification of the different areas derives from a thorough review of the empirical literature subsequently vetted by expert clinicians who selected specific reasons behind suicidal ideation and gesture. Result: The MIS is a semi-structured clinician-report interview. The interview is composed of seven areas and 14 sub-areas, evaluated on a four-point Likert scale: illness motivated attempts area, chronic presence of internal pessimistic criticism area, sense of defeat and entrapment area, relational area, external motivated crisis area, extreme and unusual cases area, and lack of control area. Conclusions: The path followed in the creation of the MIS reflects both an empirically orientated and a clinically informed approach. Creating this MIS is the first step within a wider research project that will allow one to test the reliability of the instrument.

How accurate are suicide risk prediction models? Asking the right questions for clinical practice

Prediction models assist in stratifying and quantifying an individual's risk of developing a particular adverse outcome, and are widely used in cardiovascular and cancer medicine. Whether these approaches are accurate in predicting self-harm and suicide has been questioned. We searched for systematic reviews in the suicide risk assessment field, and identified three recent reviews that have examined current tools and models derived using machine learning approaches. In this clinical review, we present a critical appraisal of these reviews, and highlight three major limitations that are shared between them. First, structured tools are not compared with unstructured assessments routine in clinical practice. Second, they do not sufficiently consider a range of performance measures, including negative predictive value and calibration. Third, the potential role of these models as clinical adjuncts is not taken into consideration. We conclude by presenting the view that the current role of prediction models for self-harm and suicide is currently not known, and discuss some methodological issues and implications of some machine learning and other analytic techniques for clinical utility.