Examining unique and prospective relationships among self-injurious thoughts and behaviors and posttraumatic stress disorder: a network analysis in two trauma-exposed samples.

BACKGROUND: As self-injurious thoughts and behaviors (SITB) remain a pressing public health concern, research continues to focus on risk factors, such as posttraumatic stress disorder (PTSD). Network analysis provides a novel approach to examining the PTSD-SITB relationship. This study utilized the network approach to elucidate how individual PTSD symptoms may drive and maintain SITB. METHODS: We estimated cross-sectional networks in two samples of trauma-exposed adults (Sample 1: N = 349 adults; Sample 2: N = 1307 Veterans) to identify PTSD symptoms that may act as bridges to SITB. Additionally, we conducted a cross-lagged panel network in Sample 2 to further clarify the temporal relationship between PTSD symptoms and SITB during a 2-year follow-up. Finally, in both samples, we conducted logistic regressions to examine the utility of PTSD symptoms in prospectively predicting SITB, over a 15-day period (Sample 1) and over a 2-year period (Sample 2), allowing us to examine both short- and long-term prediction. RESULTS: Two PTSD symptoms (i.e. negative beliefs and risky behaviors) emerged as highly influential on SITB in both cross-sectional networks. In the cross-lagged panel network, distorted blame emerged as highly influential on SITB over time. Finally, risky behaviors, unwanted memories, and psychological distress served as the strongest predictors of SITB across the two samples. CONCLUSIONS: Overall, our results suggest that treatments targeting negative beliefs and risky behaviors may prevent SITB in community and Veteran populations, whereas treatments targeting distorted blame and unwanted memories may help reduce SITB for individuals with a history of combat trauma.

User Experience Affects Dropout from Internet-Delivered Dialectical Behavior Therapy.

Background: The emergence of computerized treatment may help reduce the gap between mental health treatment needs and accessibility, but unfortunately, dropout from these interventions is often high. Introduction: To increase the effectiveness of computerized interventions and reduce dropout, particularly among high-risk and clinically complex populations, better understanding of how usable and acceptable (i.e., user experience) these interventions are, informed by human computer interaction research, is needed. This study examines user experience of internet-delivered dialectical behavior therapy (iDBT). The major aim is to explore whether treatment dropout was affected by the complexity of population and/or user experience. Methods: Secondary analyses were conducted using data from a randomized controlled trial that evaluated iDBT in a sample of 59 suicidal and heavy episodic drinkers. Multivariate logistic regression and chi-square tests were performed to examine the roles of clinical characteristics and user experience in differentiating dropouts and nondropouts. Results: The only significant pretreatment predictor of dropout was the presence of a barrier, with technological and unknown barriers being most strongly associated with dropping. No clinical characteristics emerged as significant predictors of dropout. Discussion: The current results highlight technological problems as a possible barrier to adherence to computerized interventions. Future research would profit from increased integration of human-computer interaction to identify and solve user experience problems.

Developing an optimal short-form of the PTSD Checklist for DSM-5 (PCL-5).

BACKGROUND: Although several short-forms of the posttraumatic stress disorder (PTSD) Checklist (PCL) exist, all were developed using heuristic methods. This report presents the results of analyses designed to create an optimal short-form PCL for DSM-5 (PCL-5) using both machine learning and conventional scale development methods. METHODS: The short-form scales were developed using independent datasets collected by the Army Study to Assess Risk and Resilience among Service members. We began by using a training dataset (n = 8,917) to fit short-form scales with between 1 and 8 items using different statistical methods (exploratory factor analysis, stepwise logistic regression, and a new machine learning method to find an optimal integer-scored short-form scale) to predict dichotomous PTSD diagnoses determined using the full PCL-5. A smaller subset of best short-form scales was then evaluated in an independent validation sample (n = 11,728) to select one optimal short-form scale based on multiple operating characteristics (area under curve [AUC], calibration, sensitivity, specificity, net benefit). RESULTS: Inspection of AUCs in the training sample and replication in the validation sample led to a focus on 4-item integer-scored short-form scales selected with stepwise regression. Brier scores in the validation sample showed that a number of these scales had comparable calibration (0.015-0.032) and AUC (0.984-0.994), but that one had consistently highest net benefit across a plausible range of decision thresholds. CONCLUSIONS: The recommended 4-item integer-scored short-form PCL-5 generates diagnoses that closely parallel those of the full PCL-5, making it well-suited for screening.

Transition to suicide attempt from recent suicide ideation in U.S. Army soldiers: Results from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).

BACKGROUND: Most people with suicide ideation (SI) do not attempt suicide (SA). Understanding the transition from current/recent SI to SA is important for mental health care. Our objective was to identify characteristics that differentiate SA from 30-day SI among representative U.S. Army soldiers. METHODS: Using a unique case-control design, soldiers recently hospitalized for SA (n = 132) and representative soldiers from the same four communities (n = 10,193) were administered the same questionnaire. We systematically identified variables that differentiated suicide attempters from the total population, then examined whether those same variables differentiated all 30-day ideators (n = 257) from the total population and attempters from nonattempting 30-day ideators. RESULTS: In univariable analyses, 20 of 23 predictors were associated with SA in the total population (0.05 level). The best multivariable model included eight significant predictors: interpersonal violence, relationship problems, major depressive disorder, posttraumatic stress disorder (PTSD), and substance use disorder (all having positive associations), as well as past 12-month combat trauma, intermittent explosive disorder (IED), and any college education (all having negative associations). Six of these differentiated 30-day ideators from the population. Three differentiated attempters from ideators: past 30-day PTSD (OR = 6.7 [95% CI = 1.1-39.4]), past 30-day IED (OR = 0.2 [95% CI = 0.1-0.5]), and any college education (OR = 0.1 [95% CI = 0.0-0.6]). The 5% of ideators with highest predicted risk in this final model included 20.9% of attempters, a four-fold concentration of risk. CONCLUSIONS: Prospective army research examining transition from SI to SA should consider PTSD, IED, and education. Combat exposure did not differentiate attempters from ideators. Many SA risk factors in the Army population are actually risk factors for SI.

Traumatic Event Exposure, Posttraumatic Stress Disorder, and Sleep Disturbances in a National Sample of U.S. Adults.

Posttraumatic stress disorder (PTSD) is a highly prevalent, debilitating disorder found to develop after exposure to a potentially traumatic event (PTE). Individuals with PTSD often report sleep disturbances, specifically nightmares and insomnia, which are listed within the criteria for PTSD. This research examined prevalence of insomnia and nightmares within a national sample of 2,647 adults (data weighted by age and sex to correct for differences in sample distribution) who had been exposed to one or more PTEs. Prevalence of self-reported sleep disturbance, sleep disturbances by PTE type, and gender differences were examined. All participants completed a self-administered, structured online interview that assessed exposure to stressful events and PTSD symptoms. Among individuals who met DSM-5 criteria for PTSD, a large majority (more than 92%) reported at least one sleep disturbance. Insomnia was relatively more prevalent than PTE-related nightmares among individuals with PTSD and among all PTE-exposed individuals. A higher number of PTEs experienced significantly increased the likelihood of both trauma-related nightmares and insomnia, McFadden's pseudo R2 = .07, p < .001. Women exposed to PTEs were more likely to endorse experience of insomnia, χ2 (1, N = 2,647) = 99.13, p < .001, φ = .194, and nightmares compared to men, χ2 (1, N = 2,648) = 82.98, p < .001, φ = .177, but this gender difference was not significant among individuals with PTSD, ps = .130 and .050, respectively. Differences in sleep disturbance prevalence by PTE type were also examined. Implications for treatment and intervention and future directions are discussed.

Spanish Abstracts by Asociación Chilena de Estrés Traumático (ACET) Exposición a eventos traumáticos, trastorno de estrés postraumático y trastornos del sueño en una muestra nacional de adultos EXPOSICION AL TRAUMA, TEPT Y SUEÑO El trastorno de estrés postraumático (TEPT) es un trastorno altamente prevalente y debilitante que se desarrolla después de la exposición a un evento potencialmente traumático (EPT). Los individuos con TEPT a menudo reportan alteraciones del sueño, específicamente pesadillas e insomnio, que se enumeran dentro de los criterios para el TEPT. Esta investigación examinó la prevalencia de insomnio y pesadillas en una muestra nacional de 2647 adultos (datos ponderados por edad y sexo para corregir las diferencias en la distribución de la muestra) quienes habían sido expuestos a uno o más EPTs. Se examinó la prevalencia de trastornos del sueño autoinformados, los trastornos del sueño por tipo de EPT y las diferencias de género. Todos los participantes completaron una entrevista estructurada auto-administrada online, que evaluó la exposición a eventos estresantes y los síntomas de TEPT. Entre las personas que cumplieron con los criterios del DSM-5 para el TEPT, una gran mayoría (más de 92%) reportó al menos una alteración del sueño. El insomnio fue relativamente más prevalente que las pesadillas relacionadas con EPT entre individuos con TEPT y entre todos los individuos expuestos a EPT. Un mayor número de los que experimentaron EPT aumentó significativamente la probabilidad de ambos, pesadillas relacionadas a trauma e insomnio, pseudo R2 de McFadden = .07, p <.001. Las mujeres expuestas a los EPT fueron más propensas a respaldar la experiencia de insomnio, χ2 (1, N = 2647) = 99.13, p <.001, φ = .194, y pesadillas en comparación con los hombres, χ2 (1, N = 2648) = 82.98, p <.001, φ = .177, pero esta diferencia de género no fue significativa entre los individuos con TEPT, ps = .130 y .050, respectivamente. También se examinaron las diferencias en la prevalencia de trastornos del sueño por tipo de EPT. Se discuten las implicaciones para el tratamiento y la intervención y las direcciones futuras.

Suicidality in adolescents and adults with binge-eating disorder: Results from the national comorbidity survey replication and adolescent supplement.

OBJECTIVE: The relation between binge-eating disorder (BED) and suicidality (i.e., suicide ideation, plan, and/or attempt) has not been studied extensively, and it is unknown whether BED is uniquely associated with suicidality when adjusting for comorbid psychopathology. Moreover, the course of suicidality in BED has not been determined and it is unknown whether BED precedes suicidality or vice versa. METHOD: A total of 10,123 adolescents and 2,980 adults from two nationally representative surveys were administered diagnostic interviews assessing psychopathology and suicidality, as well the retrospectively reported ages of onset. RESULTS: Among adults and adolescents, BED was associated with elevated odds of suicide ideation, plan, and attempt at a univariate level, but BED was not associated with elevated odds of suicidality when adjusting for comorbid psychopathology. Kaplan-Meier estimates of temporal patterns displayed that most adolescents experienced suicidality onset following BED onset, whereas most adults experienced suicidality onset prior to BED onset. DISCUSSION: BED, comorbid disorders, and suicidality share common factors and interrelations, and individuals with BED and comorbid disorders may be at particularly high risk for suicidal outcomes. The presence of BED in adolescence may serve as a marker for more severe symptomatology that precedes the occurrence of suicidality. Research is needed to understand how eating disorder symptoms, comorbid symptoms, and suicidality affect one another over time. © 2016 Wiley Periodicals, Inc. (Int J Eat Disord 2017; 50:40-49).

Intervening on high-risk responses during ecological momentary assessment of suicidal thoughts: Is there an effect on study data?

Ecological momentary assessment (EMA) is increasingly used to study suicidal thoughts and behaviors (STBs). There is a potential ethical obligation for researchers to intervene when receiving information about suicidal thoughts in real time. A possible concern, however, is that intervening when receiving responses that indicate high risk for suicide during EMA research may impact how participants respond to questions about suicidal thoughts and thus affect the validity and integrity of collected data. We leveraged data from a study of adults and adolescents (N = 434) recruited during a hospital visit for STBs to examine whether monitoring and intervening on high-risk responses affects subsequent participant responding. Overall, we found mixed support for the notion that intervening on high-risk responses influences participants' ratings. Although we observed some evidence of discontinuity in subsequent responses at the threshold used to trigger response-contingent interventions, it was not clear that such discontinuity was caused by the interventions; lower subsequent responses could be due to effective intervention, participant desire to not be contacted again, or regression to the mean. Importantly, the likelihood of completing surveys did not change from before to after response-contingent intervention. Adolescents were significantly more likely than adults, however, to change their initial suicidal intent ratings from above to below the high-risk threshold after viewing automated response-contingent pop-up messages. Studies explicitly designed to assess the potential impact of intervening on high-risk responses in real-time monitoring research are needed, as this will inform effective, scalable strategies for intervening during moments of high suicide risk. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Perspectives of suicide loss survivors: Qualitative analysis of data from a psychological autopsy study of U.S. Army soldiers.

INTRODUCTION: Suicide loss survivors can provide information not otherwise available about the circumstances preceding a suicide. In this study, we analyzed interview data from suicide loss survivors collected as part of a psychological autopsy study of U.S. Army soldiers. METHODS: Next-of-kin (NOK) (n = 61) and Army supervisors (SUP) (n = 107) of suicide decedents (n = 135) who had died in the last 2-3 months answered open-ended questions about suicide risk factors, ideas for improving suicide prevention, and the impact of the suicide. Responses were coded using conventional content analysis methods to identify common themes. RESULTS: Many NOK (30%) and SUP (50%) did not observe any signs of risk preceding the soldier's suicide. The most common idea regarding suicide prevention from SUP was that the suicide was inevitable, whereas NOK were more likely to emphasize the importance of increasing mental health treatment and reducing stigma. Both NOK and SUP reported negative effects of the suicide, but SUP reported some positive effects (e.g., increased unit connectedness). CONCLUSIONS: Results underscore the challenges of using informants to identify soldiers at high risk of suicide, given many respondents did not observe any warning signs. Findings also highlight attitudinal barriers present in the military that, if targeted, may increase soldiers' help-seeking and willingness to disclose their risk.

Heterogeneity in suicide risk: Evidence from personalized dynamic models.

Most theories of suicide propose within-person changes in psychological states cause suicidal thoughts/behaviors; however, most studies use between-person analyses. Thus, there are little empirical data exploring current theories in the way they are hypothesized to occur. We used a form of statistical modeling called group iterative multiple model estimation (GIMME) to explore one theory of suicide: The Interpersonal Theory of Suicide (IPTS). GIMME estimates personalized statistical models for each individual and associations shared across individuals. Data were from a real-time monitoring study of individuals with a history of suicidal thoughts/behavior (adult sample: participants = 111, observations = 25,242; adolescent sample: participants = 145, observations = 26,182). Across both samples, none of theorized IPTS effects (i.e., contemporaneous effect from hopeless to suicidal thinking) were shared at the group level. There was significant heterogeneity in the personalized models, suggesting there are different pathways through which different people come to experience suicidal thoughts/behaviors. These findings highlight the complexity of suicide risk and the need for more personalized approaches to assessment and prediction.

Recent Stressful Experiences and Suicide Risk: Implications for Suicide Prevention and Intervention in U.S. Army Soldiers.

Objectives: To identify the extent to which the presence of recent stressful events are risk factors for suicide among active-duty soldiers as reported by informants. Methods: Next-of-kin (NOK) and supervisors (SUP) of active duty soldiers (n = 135) who died by suicide and two groups of living controls: propensity-matched (n = 128) and soldiers who reported suicidal ideation in the past year, but did not die (SI) (n = 108) provided data via structured interviews from the Study to Assess Risk and Resilience in Servicemembers (Army STARRS). Multivariate logistic regression analyses were used to create a risk score for suicide. Results: The odds of suicide increased significantly for soldiers experiencing relationship problems, military punishment, and perceived failure or humiliation in the month prior to death. Suicide risk models with these risk factors predicted suicide death among those who reported SI in the past year (OR = 5.9, [95% CI = 1.5, 24.0] χ 2 = 6.24, p = 0.0125, AUC, 0.73 (0.7, 0.8) NOK) and (OR = 8.6, [95% CI = 1.4, 51.5] χ 2 = 5.49, p = 0.0191, AUC, 0.78 (0.7, 0.8); SUP) suggesting the combination of these recent stressors may contribute to the transition from ideation to action. Conclusions: Our findings suggest for the first time recent stressors distinguished suicide ideating controls from suicide decedents in the month prior to death as reported by informants. Implications for preventive intervention efforts for clinicians, supervisors and family members in identifying the transition from ideation to action are discussed.

Increased severity of mental health symptoms among adolescent inpatients during COVID-19.

OBJECTIVE: Prior research suggests that the COVID-19 pandemic has been detrimental to adolescent mental health. However, no research has examined whether the pandemic is associated with increased symptom severity among high-risk youth, such as those hospitalized for a psychiatric crisis. METHOD: Over a four-year period, upon admission to an adolescent psychiatric inpatient unit, youth completed measures of depression (Center for Epidemiologic Studies Depression Scale), feeling like a burden and lack of belongingness (Interpersonal Needs Questionnaire), trauma-related symptoms (Child Trauma Screen), suicidal thoughts and behaviors (Self-Injurious Thoughts and Behaviors Interview Self-Report Version). We compared the severity of these symptoms for patients admitted during the pandemic to the severity for patients admitted to the same unit in the three years before the pandemic. RESULTS: Across most symptoms, youth hospitalized during the pandemic reported increased severity compared to those hospitalized before the pandemic. CONCLUSIONS: Adolescents requiring psychiatric hospitalization during the pandemic reported increased symptom severity compared to adolescents hospitalized on the same inpatient unit in the three years prior to the pandemic.

Implementing Machine Learning Models for Suicide Risk Prediction in Clinical Practice: Focus Group Study With Hospital Providers.

BACKGROUND: Interest in developing machine learning models that use electronic health record data to predict patients' risk of suicidal behavior has recently proliferated. However, whether and how such models might be implemented and useful in clinical practice remain unknown. To ultimately make automated suicide risk-prediction models useful in practice, and thus better prevent patient suicides, it is critical to partner with key stakeholders, including the frontline providers who will be using such tools, at each stage of the implementation process. OBJECTIVE: The aim of this focus group study is to inform ongoing and future efforts to deploy suicide risk-prediction models in clinical practice. The specific goals are to better understand hospital providers' current practices for assessing and managing suicide risk; determine providers' perspectives on using automated suicide risk-prediction models in practice; and identify barriers, facilitators, recommendations, and factors to consider. METHODS: We conducted 10 two-hour focus groups with a total of 40 providers from psychiatry, internal medicine and primary care, emergency medicine, and obstetrics and gynecology departments within an urban academic medical center. Audio recordings of open-ended group discussions were transcribed and coded for relevant and recurrent themes by 2 independent study staff members. All coded text was reviewed and discrepancies were resolved in consensus meetings with doctoral-level staff. RESULTS: Although most providers reported using standardized suicide risk assessment tools in their clinical practices, existing tools were commonly described as unhelpful and providers indicated dissatisfaction with current suicide risk assessment methods. Overall, providers' general attitudes toward the practical use of automated suicide risk-prediction models and corresponding clinical decision support tools were positive. Providers were especially interested in the potential to identify high-risk patients who might be missed by traditional screening methods. Some expressed skepticism about the potential usefulness of these models in routine care; specific barriers included concerns about liability, alert fatigue, and increased demand on the health care system. Key facilitators included presenting specific patient-level features contributing to risk scores, emphasizing changes in risk over time, and developing systematic clinical workflows and provider training. Participants also recommended considering risk-prediction windows, timing of alerts, who will have access to model predictions, and variability across treatment settings. CONCLUSIONS: Providers were dissatisfied with current suicide risk assessment methods and were open to the use of a machine learning-based risk-prediction system to inform clinical decision-making. They also raised multiple concerns about potential barriers to the usefulness of this approach and suggested several possible facilitators. Future efforts in this area will benefit from incorporating systematic qualitative feedback from providers, patients, administrators, and payers on the use of these new approaches in routine care, especially given the complex, sensitive, and unfortunately still stigmatized nature of suicide risk.

A Longitudinal Examination of Interpersonal Violence Exposure, Concern for Loved Ones During a Disaster, and Web-Based Intervention Effects on Posttraumatic Stress Disorder Among Adolescent Victims of the Spring 2011 Tornadoes.

Natural disasters are common and devastating, and can affect the mental health of adolescents. It is also common for adolescents to have histories of interpersonal violence (IPV). The current study was a secondary data analysis of a larger randomized clinical trial and examined the moderating effect of IPV history and concern for loved ones during a disaster on treatment condition effects on posttraumatic stress disorder (PTSD) symptoms over time among disaster-exposed adolescents. Participants (n = 979) were recruited postdisaster to participate in a randomized clinical trial examining the efficacy of a web-based intervention, Bounce Back Now (BBN), on mental health symptoms at 4 and 12 months postintervention. It was found that adolescents with an IPV history and who had caregivers that were concerned for loved ones during a disaster had more PTSD symptoms at baseline than those without such histories. Furthermore, caregiver concern for loved ones during a disaster moderated the effect of BBN on PTSD symptoms over time. Specifically, the BBN condition was most effective for adolescents who had caregivers who were concerned for loved ones during the disaster in reductions of PTSD symptoms over time. The current study provides further evidence for the use of technology-based interventions for individuals as a means to address mental health symptoms after a traumatic event, especially among those with more severe traumatic experiences.

It's quality and quantity: the effect of the amount of comments on online suicidal posts.

Every day, individuals post suicide notes on social media asking for support, resources, and reasons to live. Some posts receive few comments while others receive many. While prior studies have analyzed whether specific responses are more or less helpful, it is not clear if the quantity of comments received is beneficial in reducing symptoms or in keeping the user engaged with the platform and hence with life. In the present study, we create a large dataset of users' first r/SuicideWatch (SW) posts from Reddit (N=21,274), collect the comments as well as the user's subsequent posts (N=1,615,699) to determine whether they post in SW again in the future. We use propensity score stratification, a causal inference method for observational data, and estimate whether the amount of comments -as a measure of social support- increases or decreases the likelihood of posting again on SW. One hypothesis is that receiving more comments may decrease the likelihood of the user posting in SW in the future, either by reducing symptoms or because comments from untrained peers may be harmful. On the contrary, we find that receiving more comments increases the likelihood a user will post in SW again. We discuss how receiving more comments is helpful, not by permanently relieving symptoms since users make another SW post and their second posts have similar mentions of suicidal ideation, but rather by reinforcing users to seek support and remain engaged with the platform. Furthermore, since receiving only 1 comment -the most common case- decreases the likelihood of posting again by 14% on average depending on the time window, it is important to develop systems that encourage more commenting.

Fear of sleep and sleep quality mediate the relationship between trauma exposure and suicide attempt in adolescents.

Prior work has established bivariate associations between suicidal thoughts and behaviors, trauma exposure and sleep disturbance broadly. Specifically, this study tested whether fear of sleep and sleep quality mediated the association between trauma exposure and suicide attempt. Participants (N = 100) were adolescents admitted to an inpatient psychiatric program for suicidality. Trauma exposure history was retrieved from admission notes and participants completed self-report surveys assessing sleep quality, fear of sleep and number of suicide attempts within the previous month. Structural equation modelling was used to investigate the relationships between childhood trauma, fear of sleep, sleep quality, and suicide attempt. Path analysis was used to investigate the indirect effects from trauma exposure to suicide attempt through fear of sleep, and sleep quality. Path analysis revealed a significant indirect effect from trauma exposure to suicide attempt through fear of sleep and sleep quality. Our findings suggest that a significant portion of the association between trauma exposure and suicide attempts in adolescence may be explained by the negative impact of trauma exposure on sleep. Fear of sleep may increase the risk of a suicide attempt by negatively impacting sleep quality. Future studies should investigate whether interventions targeting sleep and fear of sleep reduce the association between trauma and suicide attempt.

A secondary analysis of a brief video intervention on suicidal ideation among recent rape victims.

Although rape has been linked to risk for suicidal ideation and attempts, there are scant data on the efficacy of brief interventions to reduce suicidality among recent rape victims. This secondary analysis of a randomized controlled trial investigated whether a video intervention delivered in the emergency department (ED), cortisol measured at the ED, and prior rape history predicted postrape suicidal ideation independently or in combination with the other predictors. Participants were 235 women aged 15-71 years who presented to the ED for a sexual assault medical forensic examination and were randomly assigned to either receive a video intervention that addressed avoidance and promoted healthy coping strategies or standard care prior to the examination. Participants also provided a blood sample for cortisol and completed at least one of three follow-ups at 6 weeks, 3 months, or 6 months postrape. The intervention conferred protection against suicidal ideation among women with elevated cortisol and a prior rape; however, it did not reduce risk for women without a prior rape, particularly those with elevated cortisol. It may be important to consider the influence of prior rape and neuroendocrine reactivity in developing treatments to address suicidal ideation among rape victims. More specifically, there appears to be value in screening victims for prior rape and administering this brief intervention to reduce suicidal ideation; however, other avenues should be explored for victims without a prior rape history. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Accuracy Requirements for Cost-effective Suicide Risk Prediction Among Primary Care Patients in the US.

Importance: Several statistical models for predicting suicide risk have been developed, but how accurate such models must be to warrant implementation in clinical practice is not known. Objective: To identify threshold values of sensitivity, specificity, and positive predictive value that a suicide risk prediction method must attain to cost-effectively target a suicide risk reduction intervention to high-risk individuals. Design, Setting, and Participants: This economic evaluation incorporated published data on suicide epidemiology, the health care and societal costs of suicide, and the costs and efficacy of suicide risk reduction interventions into a novel decision analytic model. The model projected suicide-related health economic outcomes over a lifetime horizon among a population of US adults with a primary care physician. Data analysis was performed from September 19, 2019, to July 5, 2020. Interventions: Two possible interventions were delivered to individuals at high predicted risk: active contact and follow-up (ACF; relative risk of suicide attempt, 0.83; annual health care cost, $96) and cognitive behavioral therapy (CBT; relative risk of suicide attempt, 0.47; annual health care cost, $1088). Main Outcomes and Measures: Fatal and nonfatal suicide attempts, quality-adjusted life-years (QALYs), health care sector costs and societal costs (in 2016 US dollars), and incremental cost-effectiveness ratios (ICERs) (with ICERs ≤$150 000 per QALY designated cost-effective). Results: With a specificity of 95% and a sensitivity of 25%, primary care-based suicide risk prediction could reduce suicide death rates by 0.5 per 100 000 person-years (if used to target ACF) or 1.6 per 100 000 person-years (if used to target CBT) from a baseline of 15.3 per 100 000 person-years. To be cost-effective from a health care sector perspective at a specificity of 95%, a risk prediction method would need to have a sensitivity of 17.0% or greater (95% CI, 7.4%-37.3%) if used to target ACF and 35.7% or greater (95% CI, 23.1%-60.3%) if used to target CBT. To achieve cost-effectiveness, ACF required positive predictive values of 0.8% for predicting suicide attempt and 0.07% for predicting suicide death; CBT required values of 1.7% for suicide attempt and 0.2% for suicide death. Conclusions and Relevance: These findings suggest that with sufficient accuracy, statistical suicide risk prediction models can provide good health economic value in the US. Several existing suicide risk prediction models exceed the accuracy thresholds identified in this analysis and thus may warrant pilot implementation in US health care systems.

Social closeness and support are associated with lower risk of suicide among U.S. Army soldiers.

OBJECTIVE: We tested the aspects of social support, unit cohesion, and religiosity hypothesized to be protective factors for suicide among U.S. service members. METHODS: This case-control study compared U.S. Army soldiers who died by suicide while on active duty (n = 135) to controls of two types: those propensity score-matched on known sociodemographic risk factors (n = 128); and those controls who had thought about, but not died by, suicide in the past year (n = 108). Data included structured interviews of next of kin (NOK) and Army supervisors (SUP) for each case and control soldier. Logistic regression analyses were used to examine predictors of suicide. RESULTS: Perceived social closeness and seeking help from others were associated with decreased odds of suicide, as reported by SUP (OR = 0.2 [95% CI = 0.1, 0.5]) and NOK (OR = 0.4 [95% CI = 0.2, 0.8]). Novel reports by SUP informants of high levels of unit cohesion/morale decreased odds of suicide (OR = 0.1 [95% CI = 0.0, 0.2]). Contrary to study hypotheses, no religious affiliation was associated with lower odds of suicide (OR = 0.3 [95% CI = 0.2, 0.6]). CONCLUSIONS: Perceived social closeness and unit/group cohesion are associated with lower odds of suicide. These results point toward social intervention strategies as testable components of suicide prevention programs.

Can passive measurement of physiological distress help better predict suicidal thinking?

There has been growing interest in using wearable physiological monitors to passively detect the signals of distress (i.e., increases in autonomic arousal measured through increased electrodermal activity [EDA]) that may be imminently associated with suicidal thoughts. Before using these monitors in advanced applications such as creating suicide risk detection algorithms or just-in-time interventions, several preliminary questions must be answered. Specifically, we lack information about whether: (1) EDA concurrently and prospectively predicts suicidal thinking and (2) data on EDA adds to the ability to predict the presence and severity of suicidal thinking over and above self-reports of emotional distress. Participants were suicidal psychiatric inpatients (n = 25, 56% female, M age = 33.48 years) who completed six daily assessments of negative affect and suicidal thinking duration of their psychiatric inpatient stay and 28 days post-discharge, and wore on their wrist a physiological monitor (Empatica Embrace) that passively detects autonomic activity. We found that physiological data alone both concurrently and prospectively predicted periods of suicidal thinking, but models with physiological data alone had the poorest fit. Adding physiological data to self-report models improved fit when the outcome variable was severity of suicidal thinking, but worsened model fit when the outcome was presence of suicidal thinking. When predicting severity of suicidal thinking, physiological data improved model fit more for models with non-overlapping self-report data (i.e., low arousal negative affect) than for overlapping self-report data (i.e., high arousal negative affect). These findings suggest that physiological data, under certain contexts (e.g., when combined with self-report data), may be useful in better predicting-and ultimately, preventing-acute increases in suicide risk. However, some cautious optimism is warranted since physiological data do not always improve our ability to predict suicidal thinking.

Increase in Suicidal Thinking During COVID-19.

There is concern that the COVID-19 pandemic may cause increased risk of suicide. In the current study, we tested whether suicidal thinking has increased during the COVID-19 pandemic and whether such thinking was predicted by increased feelings of social isolation. In a sample of 55 individuals recently hospitalized for suicidal thinking or behaviors and participating in a 6-month intensive longitudinal smartphone monitoring study, we examined suicidal thinking and isolation before and after the COVID-19 pandemic was declared a national emergency in the United States. We found that suicidal thinking increased significantly among adults (odds ratio [OR] = 4.01, 95% confidence interval [CI] = [3.28, 4.90], p < .001) but not adolescents (OR = 0.84, 95% CI = [0.69, 1.01], p = .07) during the onset of the COVID-19 pandemic. Increased feelings of isolation predicted suicidal thinking during the pandemic phase. Given the importance of social distancing policies, these findings support the need for digital outreach and treatment.