Person:

Kleiman, Evan

Suicidal thoughts and behaviors are highly prevalent public health problems with devastating consequences. There is an urgent need to improve our understanding of risk factors for suicide to identify effective intervention targets. The aim of this meta-analysis was to examine the magnitude and clinical utility of anxiety and its disorders as risk factors for suicide ideation, attempts, and deaths. We conducted a literature search through December 2014; of the 65 articles meeting our inclusion criteria, we extracted 180 cases in which an anxiety-specific variable was used to longitudinally predict a suicide-related outcome. Results indicated that anxiety is a statistically significant, yet weak, predictor of suicide ideation (OR=1.49, 95% CI: 1.18, 1.88) and attempts (OR=1.64, 95% CI: 1.47, 1.83), but not deaths (OR=1.01, 95% CI: 0.87, 1.18). The strongest associations were observed for PTSD. Estimates were reduced after accounting for publication bias, and diagnostic accuracy analyses indicated acceptable specificity but poor sensitivity. Overall, the extant literature suggests that anxiety and its disorders, at least when these constructs are measured in isolation and as trait-like constructs, are relatively weak predictors of suicidal thoughts and behaviors over long follow-up periods. Implications for future research priorities are discussed.

Background

A history of self-injurious thoughts and behaviors (SITBs) is consistently cited as one of the strongest predictors of future suicidal behavior. However, stark discrepancies in the literature raise questions about the true magnitude of these associations. The objective of this study is to examine the magnitude and clinical utility of the associations between SITBs and subsequent suicide ideation, attempts, and death.

Method

We searched PubMed, PsycInfo, and Google Scholar for papers published through December 2014. Inclusion required that studies include at least one longitudinal analysis predicting suicide ideation, attempts, or death using any SITB variable. We identified 2179 longitudinal studies; 172 met inclusion criteria.

Results

The most common outcome was suicide attempt (47.80%), followed by death (40.50%) and ideation (11.60%). Median follow-up was 52 months (mean = 82.52, s.d. = 102.29). Overall prediction was weak, with weighted mean odds ratios (ORs) of 2.07 [95% confidence interval (CI) 1.76–2.43] for ideation, 2.14 (95% CI 2.00–2.30) for attempts, and 1.54 (95% CI 1.39–1.71) for death. Adjusting for publication bias further reduced estimates. Diagnostic accuracy analyses indicated acceptable specificity (86–87%) and poor sensitivity (10–26%), with areas under the curve marginally above chance (0.60–0.62). Most risk factors generated OR estimates of <2.0 and no risk factor exceeded 4.5. Effects were consistent regardless of sample severity, sample age groups, or follow-up length.

Conclusions

Prior SITBs confer risk for later suicidal thoughts and behaviors. However, they only provide a marginal improvement in diagnostic accuracy above chance. Addressing gaps in study design, assessment, and underlying mechanisms may prove useful in improving prediction and prevention of suicidal thoughts and behaviors.

Nonsuicidal self-injury (NSSI) is a prevalent and dangerous phenomenon associated with many negative outcomes, including future suicidal behaviors. Research on these behaviors has primarily focused on correlates; however, an emerging body of research has focused on NSSI risk factors. To provide a summary of current knowledge about NSSI risk factors, we conducted a meta-analysis of published, prospective studies longitudinally predicting NSSI. This included 20 published reports across 5078 unique participants. Results from a random-effects model demonstrated significant, albeit weak, overall prediction of NSSI (OR = 1.59; 95% CI: 1.50 to 1.69). Among specific NSSI risk factors, prior history of NSSI, cluster b, and hopelessness yielded the strongest effects (ORs > 3.0); all remaining risk factor categories produced ORs near or below 2.0. NSSI measurement, sample type, sample age, and prediction case measurement type (i.e., binary versus continuous) moderated these effects. Additionally, results highlighted several limitations of the existing literature, including idiosyncratic NSSI measurement and few studies among samples with NSSI histories. These findings indicate that few strong NSSI risk factors have been identified, and suggest a need for examination of novel risk factors, standardized NSSI measure ment, and study samples with a history of NSSI.

Suicide is a leading cause of death worldwide. Prior research has focused primarily on sociodemographic and psychiatric risk factors with little improvement in the prediction or prevention of suicidal behavior over time. The Research Domain Criteria (RDoC) may be an especially useful framework for advancing research in this area. This paper provides a brief and broad overview of research on suicidal behavior relating to each of the RDoC domains—highlighting the RDoC construct(s) where research has focused, construct(s) where research is lacking, and suggestions for future research directions. We also discuss major challenges for suicide research within the RDoC framework, including the intersection of RDoC domains, interaction of domains with the environment, incorporation of developmental stage, integration of distal and proximal processes, and inclusion of suicide-specific constructs. We conclude by underscoring important considerations for future research aimed at using the RDoC framework to study suicidal behavior and other forms of psychopathology.

The impact of suicide is undeniable. In the United States alone, over 40,000 people died by suicide in 2012 (Centers for Disease Control and Prevention [CDC], 2013). Moreover, it is estimated that 10 times as many people make medically serious suicide attempts every year, resulting in a cost to the medical system in excess of $150 million. A large body of research on suicide risk has been amassed with the implicit goal of reducing suicide’s impact. This goal has yet to be achieved. Since 1990, suicide rates have generally stayed the same (Kessler, Berglund, Borges, Nock, & Wang, 2005). The lack of progress in reducing suicide’s impact may be a result of limits to what we can learn from the majority of previous research, which has often relied upon bivariate and sometimes atheoretical models. Indeed, there has recently been a push to move beyond main effect models to more complex theoretically informed models of suicide risk that involve mediators and moderators (Glenn & Nock, 2014; O’Connor & Nock, 2014). Main effect models can only identify which factors are associated with suicide risk. Moderation and mediation models, however, help us understand the conditions under which suicide risk is enhanced or diminished as well as the mechanisms of how suicide risk is generated. The articles in this special issue of the International Journal of Cognitive Therapy address this need for a movement beyond main effects by answering three overarching questions: (1) What are the moderators that might increase or decrease risk for suicide?, (2) What are the mediators between suicide risk and suicide-related outcomes?, and (3) How can we better integrate theory into our empirical investigations?

Background: To examine whether there are subtypes of suicidal thinking using real-time digital monitoring, which allows for the measurement of such thoughts with greater temporal granularity than ever before possible.

Methods: We used smartphone-based real-time monitoring to assess suicidal thoughts four times per day in two samples: Adults who attempted suicide in the past year recruited from online forums (n = 51 participants with a total of 2,889 responses, surveyed over 28 days; ages ranged from 18 – 38 years) and psychiatric inpatients with recent suicidal ideation or attempts (n = 32 participants with a total of 640 responses, surveyed over the duration of inpatient treatment [mean stay = 8.79 days], ages ranged 23 – 68 years). Latent profile analyses were used to identify distinct phenotypes of suicidal thinking based on the frequency, intensity, and variability of such thoughts.

Results: Across both samples, five distinct phenotypes of suicidal thinking emerged that differed primarily on the intensity and variability of suicidal thoughts. Participants whose profile was characterized by more severe, persistent suicidal thoughts (i.e., higher mean and lower variability around the mean) were most likely to have made a recent suicide attempt.

Conclusions: Suicidal thinking has historically been studied as a homogeneous construct, but using newly available monitoring technology we discovered five profiles of suicidal thinking. Key questions for future research include how these phenotypes prospectively relate to future suicidal behaviors, and whether they represent remain stable or trait-like over longer periods.

Background: Suicide is a leading cause of death and a complex clinical outcome. Here we summarize the current state of research pertaining to suicidal thoughts and behaviors in youth. We review their definitions/measurement and phenomenology, epidemiology, potential etiological mechanisms, and psychological treatment and prevention efforts. Results: We identify key patterns and gaps in knowledge that should guide future work. Regarding epidemiology, the prevalence of suicidal thoughts and behaviors among youth varies across countries and sociodemographic populations. Despite this, studies are rarely conducted cross-nationally and do not uniformly account for high-risk populations. Regarding etiology, the majority of risk factors have been identified within the realm of environmental and psychological factors (notably negative affect-related processes), and most frequently using self-report measures. Little research has spanned across additional units of analyses including behavior, physiology, molecules, cells, and genes. Finally, there has been growing evidence in support of select psychotherapeutic treatment and prevention strategies, and preliminary evidence for computerized interventions that are rarely tested among youth. Conclusions: There is much work to be done to better understand suicidal thoughts and behaviors among youth. We strongly encourage future research to: (a) continue improving the conceptualization and operationalization of suicidal thoughts and behaviors; (b) improve etiological understanding by focusing on individual (preferably malleable) mechanisms; (c) improve etiological understanding also by integrating findings across multiple units of analyses and developing short-term prediction models; (d) demonstrate greater developmental sensitivity overall; and (e) account for diverse high-risk populations via sampling and reporting of sample characteristics. These serve as initial steps to improve the scientific approach, knowledge base, and ultimately prevention of suicidal thoughts and behaviors among youth.