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Suicide disproportionately affects the military and veteran population, yet the task of identifying those at an increased risk of suicidal behavior remains challenging. In the face of this complex issue, novel machine learning methods have been applied to study the relationship between suicide and potential risk factors, but are often not generalizable to new and unseen samples. Herein, we examine the problem of prediction on unknown environments, commonly known as environment-wise domain adaptation, as it relates to the prediction of suicidal beliefs, measured with items from the Suicide Cognitions Scale (SCS). We adapt several recently invariance-based models trained using a sample consisting of people without any prior suicidal ideation (SI) to the prediction of suicidal beliefs of those with prior SI. In addition, we examine the possible causal relations regarding the SCS. Using a prospective sample of 2744 primary care patients with 17 risk and protective factors, we show that, to some extent, these methods are able to generalize to a new environment, namely, a sample with prior SI. Additionally, our results indicate suicidal ideation and suicidal behavior are likely to be causal children of SCS.

The majority of Veterans who died by suicide in 2021 had not recently used Veterans Health Administration (VA) services. A public health approach to Veteran suicide prevention has been prioritized as part of the VA National Strategy for Preventing Veteran Suicide. Aligned with this approach, VA’s Patient Safety Center of Inquiry—Suicide Prevention Collaborative piloted a Veteran suicide prevention learning collaborative with both clinical and non-clinical community agencies that serve Veterans. The VA COmmunity LeArning CollaboraTive (CO-ACT) uses a quality improvement framework and facilitative process to support community organizational implementation of evidence-based and best practice suicide prevention strategies to achieve this goal. This paper details the structure of CO-ACT and processes by which it is implemented. This includes the CO-ACT toolkit, an organizational self-assessment, a summary of recommendations, creation of a blueprint for change, selection of suicide prevention program components, and an action plan to guide organizations in implementing suicide prevention practices. CO-ACT pilot outcomes are reported in a previous publication.

Despite decades of research, the direct causes of suicide remain unknown. Some researchers have proposed that suicide is sufficiently complex that no single variable or set of variables can be determined causal. The invariance-based causal prediction (ICP) is a contemporary data analytic method developed to identify the direct causal relationships, but the method has not yet been applied to suicide. In this study, we used ICP to identify the variables that were most directly related to the emergence of suicidal behavior in a prospective sample of 2,744 primary care patients. Fifty-eight (2.1%) participants reported suicidal behavior during the following year. Of 18 predictors tested, shame was most likely to be directly causal only under the least restrictive conditions. No single variable or set of variables was identified. Results support the indeterminacy hypothesis that suicide is caused by many combinations of factors, none of which are necessary for suicide to occur.

The last several decades have witnessed growing and converging evidence from randomized controlled trials (RCT’s) that an identifiable set of simple clinical management strategies are effective for those at risk for suicidal thinking and/or suicide attempts. The current article offers a brief review of clinical strategies supported by RCT’s targeting suicidality as “commonalities of treatments that work” and related recommendations for use in the delivery of care for suicidal individuals in generic fashion, regardless of any particular treatment, theoretical orientation, or intervention perspective. The article includes eight recommendations that can be easily adapted across the full range of clinical contexts, institutional settings, and delivery systems, recommendations that help frame a broader clinical narrative for suicide prevention. Recommendations cut across five identifiable domains or clinical strategies for the delivery of care: (1) informed consent discussion that identifies risks of opting out of care and emphasizes the importance of shared responsibility and a collaborative process, (2) an explanatory model that emphasizes the importance of individual self-management skills and targeting the causes of suicide rather than describing suicidality as a function of mental illness, (3) the importance of proactively identifying barriers to care and engaging in targeted problem-solving to facilitate treatment adherence, (4) a proactive and specific plan for management of future suicidal episodes, and (5) reinforcing the importance of taking steps to safeguard lethal means and facilitate safe storage of firearms.

BackgroundAssessing for and identifying those at imminent risk for suicide continues to present challenges, especially as many who die do not interact with specialty mental health treatment preceding suicide. Suicide-specific interventions in healthcare settings have been found to improve suicide-related outcomes, yet little is known about the confluence of behavioral, cognitive, emotional, and physiological indicators of emotional distress as they correspond to other key risk characteristics and high-risk groups like gun owners.AimThe purpose of this content analysis was to examine self-identified warning signs of distress between gun owners and non-owners through crisis response planning (CRP).MethodsParticipants completed a collaborative CRP. Warning signs were categorized as being either behavioral, cognitive, emotional, or physiological in nature. Bivariate logistic regression models were used to examine associations between firearm ownership and variables of interest. Participants were evenly split between men (n = 44) and women (n = 44) and were predominantly white (67.1%) with a mean age of 35.9 (SD = 13.6).ResultsEmotional warning signs of distress (68.2%) were reported slightly more often than behavioral (65.9%) followed by physiological (52.3%), and cognitive (46.6%). Firearm owners were significantly more likely to be male (OR = 2.5, 95%CI [1.07–6.0]). All participants were about a fourth as likely to report both a behavioral and physiological warning sign concurrently (OR = 0.26, 95% CI [0.09–0.67]).ConclusionSimilarities and departures in warning signs of emotional distress may inform future research exploring both self-reported warning signs and related self-management strategies identified through suicide-specific interventions, particularly among high-risk groups such as gun owners.

Research in clinical suicidology continues to rapidly expand, much of it with implications for day-to-day clinical practice. Clinicians routinely wrestle with how best to integrate recent advances into practice and how to do so in efficient and effective fashion. This article identifies five critical domains of recent research findings and offers examples of simple questions that can easily be integrated into a clinician's existing suicide risk assessment interview and related protocol helping inform the risk formulation process.

The study explored the development of the Brief Suicide Cognitions Scale (B-SCS), a simple and brief measure of suicide risk. The B-SCS provides a brief measure that captures critical aspects of suicide risk embedded in core beliefs about the self as unlovable, one's emotional experience as unbearable, and life problems as unsolvable (i.e., the suicidal belief system), resulting in chronic or enduring suicide risk and heightened vulnerability for acute episodes secondary to internal and external triggers. Data were analyzed from three diverse samples, including a student sample (N = 349), an inpatient psychiatric sample (N = 160), and a sample of emergency department (ED) patients presenting secondary to a suicidal crisis (N = 94). Those in the student and inpatient samples completed additional symptom measures (hopelessness, anxiety, depression) and the ED sample provided 6-month follow-up data for suicide attempts. Reliability (internal consistency, test-retest), concurrent validity, construct (divergent, convergent) validity, factorial, incremental, and predictive validity were evaluated, along with calculation of predictive value of negative and positive tests, sensitivity, and specificity estimates. The B-SCS demonstrated good reliability and validity, a unidimensional factor structure across samples, along with good predictive validity and value in real-world clinical settings. The B-SCS is a brief, reliable and valid measure of suicide risk, with good ability to identify those with enduring risk for subsequent suicide attempts. The B-SCS offers a unique contribution to understanding and assessing the nature of suicide risk over time targeting the suicidal belief system, with easy application across inpatient and outpatient clinical settings, and good predictive value.