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People engage in nonsuicidal self-injury (NSSI) to reduce negative affect, but it is not clear why they engage in this harmful type of behavior instead of using healthier strategies. The primary goal of this study was to evaluate whether people choose NSSI to reduce negative affect because they perceive it to be less cognitively costly than other available strategies.In experiment one, 43 adults completed a novel, relief-based effort discounting task designed to index preferences about exerting cognitive effort to achieve relief. In experiment two, 149 adults, 52 % with a history of NSSI, completed our effort discounting task.Our main results suggest that people will accept less relief from an aversive experience if doing so requires expending less effort, i.e. they demonstrate effort discounting in the context of decisions about relief. We also found and that effort discounting is stronger among those with a history of NSSI, but this association became nonsignificant when simultaneously accounting for other conditions associated with aberrant effort tradeoffs.The use of a control group without NSSI or other potentially harmful relief-seeking behaviors limits our ability to draw specific conclusions about NSSI. The ecological validity of our task was limited by a modestly effective affect manipulation, and because participants made hypothetical choices.This study demonstrates that preferences about exerting cognitive effort may be a barrier to using healthier affect regulation strategies. Further, the preference not to exert cognitive effort, though present in NSSI, is likely not unique to NSSI. Instead, effort discounting may be a transdiagnostic mechanism promoting an array of harmful relief-seeking behaviors.

The inclusion of suicide gestures in modern nomenclatures for self-injurious thoughts and behaviors (SITB) is contentious due to their history of pejorative connotations and inconsistent operationalization and measurement. Here we sought to investigate the extent to which participants who endorse this behavior on a standardized SITB measure: (1) describe their behavior in a way that is consistent with contemporary definitions for suicide gestures; (2) accurately classify their behavior when presented with multiple SITB response options; and (3) consistently report their level of intent to die across survey items.Participants were 83 adults from a community-based sample who endorsed lifetime suicide gesture(s) in an online survey containing self-report measures assessing their prior SITB engagement, followed by open-ended questions eliciting narrative descriptions of their behaviors.Approximately 13% of participants who endorsed lifetime suicide gestures provided narrative descriptions that met criteria for the behavior, and around one-third consistently reported zero intent to die in their explicit ratings. Additionally, some participants reported non-zero intent to die from behaviors without direct potential for physical injury.Overall, this study highlights substantial issues with the validity of current approaches to measuring suicide gestures. Implications for the classification of suicide gestures in clinical and research settings are discussed.

The ILHBN is funded by the National Institutes of Health to collaboratively study the interactive dynamics of behavior, health, and the environment using Intensive Longitudinal Data (ILD) to (a) understand and intervene on behavior and health and (b) develop new analytic methods to innovate behavioral theories and interventions. The heterogenous study designs, populations, and measurement protocols adopted by the seven studies within the ILHBN created practical challenges, but also unprecedented opportunities to capitalize on data harmonization to provide comparable views of data from different studies, enhance the quality and utility of expensive and hard-won ILD, and amplify scientific yield. The purpose of this article is to provide a brief report of the challenges, opportunities, and solutions from some of the ILHBN's cross-study data harmonization efforts. We review the process through which harmonization challenges and opportunities motivated the development of tools and collection of metadata within the ILHBN. A variety of strategies have been adopted within the ILHBN to facilitate harmonization of ecological momentary assessment, location, accelerometer, and participant engagement data while preserving theory-driven heterogeneity and data privacy considerations. Several tools have been developed by the ILHBN to resolve challenges in integrating ILD across multiple data streams and time scales both within and across studies. Harmonization of distinct longitudinal measures, measurement tools, and sampling rates across studies is challenging, but also opens up new opportunities to address cross-cutting scientific themes of interest.Health behavior changes, such as prevention of suicidal thoughts and behaviors, smoking, drug use, and alcohol use; and the promotion of mental health, sleep, and physical activities, and decreases in sedentary behavior, are difficult to sustain. The ILHBN is a cooperative agreement network funded jointly by seven participating units within the National Institutes of Health to collaboratively study how factors that occur in individuals’ everyday life and in their natural environment influence the success of positive health behavior changes. This article discusses how information collected using smartphones, wearables, and other devices can provide helpful active and passive reflections of the participants’ extent of risk and resources at the moment for an extended period of time. However, successful engagement and retention of participants also require tailored adaptations of study designs, measurement tools, measurement intervals, study span, and device choices that create hurdles in integrating (harmonizing) data from multiple studies. We describe some of the challenges, opportunities, and solutions that emerged from harmonizing intensive longitudinal data under heterogeneous study and participant characteristics within the ILHBN, and share some tools and recommendations to facilitate future data harmonization efforts.

Background Although non-suicidal self-injury (NSSI) is known typically to begin in adolescence, longitudinal information is lacking about patterns, predictors, and clinical outcomes of NSSI persistence among emerging adults. The present study was designed to (1) estimate NSSI persistence during the college period, (2) identify risk factors and high-risk students for NSSI persistence patterns, and (3) evaluate the association with future mental disorders and suicidal thoughts and behaviors (STB). Methods Using prospective cohorts from the Leuven College Surveys (n = 5915), part of the World Mental Health International College Student Initiative, web-based surveys assessed mental health and psychosocial problems at college entrance and three annual follow-up assessments. Results Approximately one in five (20.4%) students reported lifetime NSSI at college entrance. NSSI persistence was estimated at 56.4%, with 15.6% reporting a high-frequency repetitive pattern (≥five times yearly). Many hypothesized risk factors were associated with repetitive NSSI persistence, with the most potent effects observed for pre-college NSSI characteristics. Multivariate models suggest that an intervention focusing on the 10–20% at the highest predicted risk could effectively reach 34.9–56.7% of students with high-frequency repetitive NSSI persistence (PPV = 81.8–93.4, AUC = 0.88–0.91). Repetitive NSSI persistence during the first two college years predicted 12-month mental disorders, role impairment, and STB during the third college year, including suicide attempts. Conclusions Most emerging adults with a history of NSSI report persistent self-injury during their college years. Web-based screening may be a promising approach for detecting students at risk for a highly persistent NSSI pattern characterized by subsequent adverse outcomes.

Background Personality traits (e.g. neuroticism) and the social environment predict risk for internalizing disorders and suicidal behavior. Studying these characteristics together and prospectively within a population confronted with high stressor exposure (e.g. U.S. Army soldiers) has not been done, yet could uncover unique and interactive predictive effects that may inform prevention and early intervention efforts. Methods Five broad personality traits and social network size were assessed via self-administered questionnaires among experienced soldiers preparing for deployment (N = 4645) and new soldiers reporting for basic training (N = 6216). Predictive models examined associations of baseline personality and social network variables with recent distress disorders or suicidal behaviors assessed 3- and 9-months post-deployment and approximately 5 years following enlistment. Results Among the personality traits, elevated neuroticism was consistently associated with increased mental health risk following deployment. Small social networks were also associated with increased mental health risk following deployment, beyond the variance accounted for by personality. Limited support was found for social network size moderating the association between personality and mental health outcomes. Small social networks also predicted distress disorders and suicidal behavior 5 years following enlistment, whereas unique effects of personality traits on these more distal outcomes were rare. Conclusions Heightened neuroticism and small social networks predict a greater risk for negative mental health sequelae, especially following deployment. Social ties may mitigate adverse impacts of personality traits on psychopathology in some contexts. Early identification and targeted intervention for these distinct, modifiable factors may decrease the risk of distress disorders and suicidal behavior.

Suicide is a major public health concern in the United States, but few effective and scalable interventions exist to help those with suicidal thoughts. We hypothesized that reading first-person narratives about working through suicidal thoughts would reduce the desire to die among adults and that this effect would be mediated by increased perceived shared experience and optimism.Using a randomized waitlist-controlled trial, we tested the effect of digital narrative-based bibliotherapy among 528 adults visiting a social media platform dedicated to providing mental health support. Participants were randomized to either a treatment condition (n = 266), in which they read one suicide narrative per day for 14 days or to a waitlist control condition (n = 262). The primary outcome was a measure of desire to die assessed daily for the 14-day trial period and at 2-week follow-up.Participants in the treatment condition reported lower desire to die than participants in the control condition during the 14-day trial period (β = -0.26, p = .001) and at 2-week follow-up (t = -2.82, p = .005). Increased perceived shared experience (indirect effect b = -0.55, p.001) and optimism (indirect effect b = -0.85, p.001) mediated the effect of treatment on desire to die.Digital narrative-based bibliotherapy may be an effective intervention for those at risk for suicide, and may work in part by increasing feelings of perceived shared experience and optimism. Future research is needed to test the generalizability of these results to other platforms, groups, and conditions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Purpose: To investigate the associations of childhood adversities (CAs) with lifetime onset and transitions across suicidal thoughts and behaviors (STB) among incoming college students. Methods: Web-based self-report surveys administered to 20,842 incoming college students from nine countries (response rate 45.6%) assessed lifetime suicidal ideation, plans and attempts along with seven CAs: parental psychopathology, three types of abuse (emotional, physical, sexual), neglect, bully victimization, and dating violence. Logistic regression estimated individual- and population-level associations using CA operationalizations for type, number, severity, and frequency. Results: Associations of CAs with lifetime ideation and the transition from ideation to plan were best explained by the exact number of CA types (OR range 1.32–52.30 for exactly two to seven CAs). Associations of CAs with a transition to attempts were best explained by the frequency of specific CA types (scaled 0–4). Attempts among ideators with a plan were significantly associated with all seven CAs (OR range 1.16–1.59) and associations remained significant in adjusted analyses with the frequency of sexual abuse (OR = 1.42), dating violence (OR = 1.29), physical abuse (OR = 1.17) and bully victimization (OR = 1.17). Attempts among ideators without plan were significantly associated with frequency of emotional abuse (OR = 1.29) and bully victimization (OR = 1.36), in both unadjusted and adjusted analyses. Population attributable risk simulations found 63% of ideation and 30–47% of STB transitions associated with CAs. Conclusion: Early-life adversities represent a potentially important driver in explaining lifetime STB among incoming college students. Comprehensive intervention strategies that prevent or reduce the negative effects of CAs may reduce subsequent onset of STB.

The first year of college may carry especially high risk for onset of alcohol use disorders. We assessed the one-year incidence of alcohol use disorders (AUD) among incoming first-year students, predictors of AUD-incidence, prediction accuracy and population impact. A prospective cohort study of first-year college students (baseline: N = 5843; response rate = 51.8%; 1-year follow-up: n = 1959; conditional response rate = 41.6%) at a large university in Belgium was conducted. AUD were evaluated with the AUDIT and baseline predictors with the Composite International Diagnostic Interview Screening Scales (CIDI-SC). The one-year incidence of AUD was 3.9% (SE = 0.4). The most important individual-level baseline predictors of AUD incidence were being male (OR = 1.53; 95% CI = 1.12-2.10), a break-up with a romantic partner (OR = 1.67; 95% CI = 1.08-2.59), hazardous drinking (OR = 3.36; 95% CI = 1.31-8.63), and alcohol use characteristics at baseline (ORs between 1.29 and 1.38). Multivariate cross-validated prediction (cross-validated AUC = 0.887) shows that 55.5% of incident AUD cases occurred among the 10% of students at highest predicted risk (20.1% predicted incidence in this highest-risk subgroup). Four out of five students with incident AUD would hypothetically be preventable if baseline hazardous drinking was to be eliminated along with a reduction of one standard deviation in alcohol use characteristics scores, and another 15.0% would potentially be preventable if all 12-month stressful events were eliminated. Screening at college entrance is a promising strategy to identify students at risk of transitioning to more problematic drinking and AUD, thus improving the development and deployment of targeted preventive interventions. ispartof: European Child & Adolescent Psychiatry vol:31 issue:7 ispartof: location:Germany status: Published online

This study aims to identify the timescale of suicidal thinking, leveraging real-time monitoring data and a number of different analytic approaches. Participants were 105 adults with past week suicidal thoughts who completed a 42-d real-time monitoring study (total number of observations = 20,255). Participants completed two forms of real-time assessments: traditional real-time assessments (spaced hours apart each day) and high-frequency assessments (spaced 10 min apart over 1 h). We found that suicidal thinking changes rapidly. Both descriptive statistics and Markov-switching models indicated that elevated states of suicidal thinking lasted on average 1 to 3 h. Individuals exhibited heterogeneity in how often and for how long they reported elevated suicidal thinking, and our analyses suggest that different aspects of suicidal thinking operated on different timescales. Continuous-time autoregressive models suggest that current suicidal intent is predictive of future intent levels for 2 to 3 h, while current suicidal desire is predictive of future suicidal desire levels for 20 h. Multiple models found that elevated suicidal intent has on average shorter duration than elevated suicidal desire. Finally, inferences about the within-person dynamics of suicidal thinking on the basis of statistical modeling were shown to depend on the frequency at which data was sampled. For example, traditional real-time assessments estimated the duration of severe suicidal states of suicidal desire as 9.5 h, whereas the high-frequency assessments shifted the estimated duration to 1.4 h.

BackgroundAlthough non-suicidal self-injury (NSSI) is an issue of major concern to colleges worldwide, we lack detailed information about the epidemiology of NSSI among college students. The objectives of this study were to present the first cross-national data on the prevalence of NSSI and NSSI disorder among first-year college students and its association with mental disorders.MethodsData come from a survey of the entering class in 24 colleges across nine countries participating in the World Mental Health International College Student (WMH-ICS) initiative assessed in web-based self-report surveys (20 842 first-year students). Using retrospective age-of-onset reports, we investigated time-ordered associations between NSSI and Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-IV) mood (major depressive and bipolar disorder), anxiety (generalized anxiety and panic disorder), and substance use disorders (alcohol and drug use disorder).ResultsNSSI lifetime and 12-month prevalence were 17.7% and 8.4%. A positive screen of 12-month DSM-5 NSSI disorder was 2.3%. Of those with lifetime NSSI, 59.6% met the criteria for at least one mental disorder. Temporally primary lifetime mental disorders predicted subsequent onset of NSSI [median odds ratio (OR) 2.4], but these primary lifetime disorders did not consistently predict 12-month NSSI among respondents with lifetime NSSI. Conversely, even after controlling for pre-existing mental disorders, NSSI consistently predicted later onset of mental disorders (median OR 1.8) as well as 12-month persistence of mental disorders among students with a generalized anxiety disorder (OR 1.6) and bipolar disorder (OR 4.6).ConclusionsNSSI is common among first-year college students and is a behavioral marker of various common mental disorders.

Emotion reactivity (ER) and distress intolerance (DI) may be associated with increased suicide attempt (SA) risk among U.S. Army soldiers.In this case-control study, 74 soldiers recently hospitalized for SA (cases) were compared with 133 control soldiers from the same Army installations selected based on either propensity score matching (n = 103) or reported 12-month suicide ideation (SI) (n = 30). Controls were weighted to represent the total Army population at the study sites and the subpopulation of 12-month ideators. Participants completed questionnaires assessing ER, DI, and other psychosocial variables. Logistic regression analyses examined whether ER and DI differentiated SA cases from the general population and from 12-month ideators before and after controlling for additional important risk factors (sociodemographic characteristics, stressors, mental disorders).In univariate analyses, ER differentiated SA cases from both the general population (OR = 2.5[95%CI = 1.7-3.6]) and soldiers with 12-month SI (OR = 2.5[95%CI = 1.3-4.6]). DI also differentiated cases from the general population (OR = 2.9[95%CI = 2.0-4.1]) and 12-month ideators (OR = 1.9[95%CI = 1.1-3.5]). These associations persisted after controlling for sociodemographic variables, stressors, and mental disorders.Findings provide evidence that higher ER and DI are associated with increased risk of SA among soldiers, even after adjusting for known risk factors. Prospective research with larger samples is needed.

Objective Suicide is one of the leading causes of death worldwide, yet clinicians find it difficult to reliably identify individuals at high risk for suicide. Algorithmic approaches for suicide risk detection have been developed in recent years, mostly based on data from electronic health records (EHRs). Significant room for improvement remains in the way these models take advantage of temporal information to improve predictions. Materials and Methods We propose a temporally enhanced variant of the random forest (RF) model—Omni-Temporal Balanced Random Forests (OT-BRFs)—that incorporates temporal information in every tree within the forest. We develop and validate this model using longitudinal EHRs and clinician notes from the Mass General Brigham Health System recorded between 1998 and 2018, and compare its performance to a baseline Naive Bayes Classifier and 2 standard versions of balanced RFs. Results Temporal variables were found to be associated with suicide risk: Elevated suicide risk was observed in individuals with a higher total number of visits as well as those with a low rate of visits over time, while lower suicide risk was observed in individuals with a longer period of EHR coverage. RF models were more accurate than Naive Bayesian classifiers at predicting suicide risk in advance (area under the receiver operating curve = 0.824 vs. 0.754, respectively). The proposed OT-BRF model performed best among all RF approaches, yielding a sensitivity of 0.339 at 95% specificity, compared to 0.290 and 0.286 for the other 2 RF models. Temporal variables were assigned high importance by the models that incorporated them. Discussion We demonstrate that temporal variables have an important role to play in suicide risk detection and that requiring their inclusion in all RF trees leads to increased predictive performance. Integrating temporal information into risk prediction models helps the models interpret patient data in temporal context, improving predictive performance.

Background Suicidal and nonsuicidal self-injurious thoughts and behaviors (SITBs) are major health concerns among military veterans yet little is known about the temporal relations among these outcomes. This study examined the temporal relations between suicidal and nonsuicidal SITBs among higher-risk veterans. Specifically, we identified when SITBs emerged and evaluated the role of nonsuicidal self-injury (NSSI) in the medical lethality of suicide attempts (SA), relative risk, and survival time of suicidal SITBs (i.e., suicide ideation [SI], suicide plan, SA). Method Cross-sectional data were collected from two samples examining suicide risk among veterans receiving inpatient psychiatric care (n = 157) and community-residing veterans with current depression and/or past month SI (n = 200). Participants completed an interview to assess SITBs. Results SITBs emerged between ages 14-28 years with behaviors emerging, on average, earlier among inpatient veterans. The time lag between SITBs was not significantly different between groups. Inpatient veterans had a significantly shorter time lag from SI to SA. NSSI history predicted an increase in relative risk for all suicidal SITBs and shorter survival time. There was no association between NSSI history and medical lethality of the most serious SA for both groups. Limitations Limitations included use of cross-sectional, retrospective self-report with age-of-onset endorsed in years and not all SITBs were assessed (e.g., passive SI). Conclusions Veterans with a NSSI history are at high risk for suicidal SITBs and have a shorter survival time. Results showed thoughts (i.e., NSSI thoughts, SI) emerged before behavior (i.e., NSSI, SA) and NSSI emerged before SA.

Restrictive eating is common and associated with negative psychological outcomes across the life span and eating disorder (ED) severity levels. Little is known about functional processes that maintain restriction, especially outside of narrow diagnostic categories (e.g., anorexia nervosa). Here, we extend research on operant four-function models (identifying automatic negative, automatic positive, social negative, and social positive reinforcement functions) that have previously been applied to nonsuicidal self-injury (NSSI), binge eating, and purging to restricting. We assessed restrictive eating functions in three samples: clinically heterogeneous adolescents (Study 1: N = 457), transdiagnostic adults (Study 2: N = 145), and adults with acute or recently weight-restored anorexia nervosa (Study 3: N = 45). Study 1 indicated the four-function model was a good fit for restricting (root mean square error of approximation [RMSEA] = .06, Tucker-Lewis index [TLI] = .88). This factor structure replicated in Study 2 (comparative fit index [CFI] = .97, RMSEA = .07, TLI = .97, standardized root mean square residual [SRMR] = .09). Unlike NSSI, binge eating, and purging, which have been found to primarily serve automatic negative reinforcement functions, all three present studies found automatic positive reinforcement was most highly endorsed (by up to 85% of participants). In Studies 1 and 3, automatic functions were associated with poorer emotion regulation (ps < .05). In Study 1, social functions were associated with less social support (ps < .001). Across studies, automatic functions were associated with greater restriction ps < .05). Functions varied slightly by ED diagnosis. Across ED presentation, severity, and developmental stage, restrictive eating may be largely maintained by automatic positive reinforcement, with some variability across presentations. Continued examination of restrictive eating functions will establish processes that maintain restriction, allowing more precise treatment targeting for these problematic behaviors. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

We still have little understanding of short-term predictors of suicidal thoughts and behaviors (STBs). Prior research links increased negative affect to STBs, but the vast majority of earlier work is limited by measuring negative affect at one time point and aiming to predict STBs months or years in the future. Recently, intensive longitudinal studies have shown that negative affect is associated with suicidal thoughts over relatively short, clinically useful time periods; however, the specific patterns and types of negative affect that predict STBs remain unclear. Using ecological momentary assessment (EMA) data from psychiatric inpatients hospitalized for suicide risk (n = 83), this study sought to test whether the patterns (means and variability) of two types of negative affect (anxiety/agitation and shame/self-hatred, which were derived from a larger EMA battery) during hospitalization predict STBs in the 4 weeks after discharge: an extremely high-risk time for suicidal behavior. The mean—but not the variability—of both anxiety/agitation and shame/self-hatred during hospitalization predicted the number of days with suicidal thoughts after discharge. The mean and the variability of shame/self-hatred—but not anxiety/agitation—predicted post-discharge suicide attempt. We discuss implications for assessment and treatment of suicidal individuals and propose key directions for future research. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s42761-021-00058-6.

Adolescent risk for self-injurious thoughts and behaviors (STBs) involves disturbance across multiple systems (e.g., affective valence, arousal regulatory, cognitive and social processes). However, research integrating information across these systems is lacking. Utilizing a multiple-levels-of-analysis approach, this person-centered study identified psychobiological stress response profiles and linked them to cognitive processes, interpersonal behaviors, and STBs. At baseline, adolescent girls (N = 241, Mage = 14.68 years, Range = 12–17) at risk for STBs completed the Trier Social Stress Test (TSST), questionnaires, and STB interviews. Positive affect (PA), negative affect (NA), and salivary cortisol (SC) were assessed before and after the TSST. STBs were assessed again during 3, 6, and 9 month follow-up interviews. Multitrajectory modeling of girls’ PA, NA, and SC revealed four profiles, which were compared on cognitive and behavioral correlates as well as STB outcomes. Relative to normative, girls in the affective distress, hyperresponsive, and hyporesponsive subgroups were more likely to report negative cognitive style (all three groups) and excessive reassurance seeking (hyporesponsive only) at baseline, as well as nonsuicidal self-injury (all three groups) and suicidal ideation and attempt (hyporesponsive only) at follow-up. Girls’ close friendship characteristics moderated several profile–STB links. A synthesis of the findings is presented alongside implications for person-centered tailoring of intervention efforts.

Objective: Digital monitoring technologies (e.g., smart-phones and wearable devices) provide unprecedented opportunities to study potentially harmful behaviors such as suicide, violence, and alcohol/substance use in real-time. The use of these new technologies has the potential to significantly advance the understanding, prediction, and prevention of these behaviors. However, such technologies also introduce myriad ethical and safety concerns, such as deciding when and how to intervene if a participant’s responses indicate elevated risk during the study? Methods: We used a modified Delphi process to develop a consensus among a diverse panel of experts on the ethical and safety practices for conducting digital monitoring studies with those at risk for suicide and related behaviors. Twenty-four experts including scientists, clinicians, ethicists, legal experts, and those with lived experience provided input into an iterative, multi-stage survey, and discussion process. Results: Consensus was reached on multiple aspects of such studies, including: inclusion criteria, informed consent elements, technical and safety procedures, data review practices during the study, responding to various levels of participant risk in real-time, and data and safety monitoring. Conclusions: This consensus statement provides guidance for researchers, funding agencies, and institutional review boards regarding expert views on current best practices for conducting digital monitoring studies with those at risk for suicide—with relevance to the study of a range of other potentially harmful behaviors (e.g., alcohol/substance use and violence). This statement also highlights areas in which more data are needed before consensus can be reached regarding best ethical and safety practices for digital monitoring studies.

Suicide is among the most devastating problems facing clinicians, who currently have limited tools to predict and prevent suicidal behavior. Here we report on real-time, continuous smartphone and sensor data collected before, during, and after a suicide attempt made by a patient during a psychiatric inpatient hospitalization. We observed elevated and persistent sympathetic nervous system arousal and suicidal thinking leading up to the suicide attempt. This case provides the highest resolution data to date on the psychological, psychophysiological, and behavioral markers of imminent suicidal behavior and highlights new directions for prediction and prevention efforts.

Suicide is among the leading causes of death in the US and worldwide. Devastatingly, it disproportionately affects youth, making it a leading contributor to years of life lost as well. Whereas the US federal government has prioritized the study and prevention of other causes of death, causing mortality rates from them to drop precipitously (e.g., cancer, heart disease, HIV/AIDS), this is not true of suicide. Funding for suicide prevention research is less than one-third of that allocated to other leading causes of death, and as a result the US suicide rate now is virtually identical to what it was 100 years ago. This situation is alarming and requires immediate action.

Suicide researchers commonly use a variety of assessment methods (e.g., surveys and interviews) to enroll participants into studies and assign them to study conditions. However, prior studies suggest that different assessment methods and items may yield different responses from participants. This study examines potential inconsistencies in participants' reports of suicidal ideation (SI) and suicide attempt (SA) across commonly used assessment methods: phone screen interview, in-person interview, self-report survey, and confidential exit survey. To test the reliability of the effects, we replicated the study across two samples. In both samples, we observed a notable degree of inconsistent reporting. Importantly, the highest endorsement rates for SI/SA were on a confidential exit survey. Follow-up assessments and analyses did not provide strong support for the roles of purposeful inaccuracy, random responding, or differences in participant experiences/conceptualizations of SI. Although the reasons for such inconsistencies remain inconclusive, results suggest that classification of suicidal/control participants that uses multiple items to capture a single construct, that uses a Graded Scale to capture a broad spectrum of thoughts and behaviors, and that takes into account consistency of responding across such items may provide clearer and more homogenous groups and is recommended for future study. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

ImportanceThe months after psychiatric hospital discharge are a time of high risk for suicide. Intensive postdischarge case management, although potentially effective in suicide prevention, is likely to be cost-effective only if targeted at high-risk patients. A previously developed machine learning (ML) model showed that postdischarge suicides can be predicted from electronic health records and geospatial data, but it is unknown if prediction could be improved by adding additional information.ObjectiveTo determine whether model prediction could be improved by adding information extracted from clinical notes and public records.Design, Setting, and ParticipantsModels were trained to predict suicides in the 12 months after Veterans Health Administration (VHA) short-term (less than 365 days) psychiatric hospitalizations between the beginning of 2010 and September 1, 2012 (299 050 hospitalizations, with 916 hospitalizations followed within 12 months by suicides) and tested in the hospitalizations from September 2, 2012, to December 31, 2013 (149 738 hospitalizations, with 393 hospitalizations followed within 12 months by suicides). Validation focused on net benefit across a range of plausible decision thresholds. Predictor importance was assessed with Shapley additive explanations (SHAP) values. Data were analyzed from January to August 2022.Main Outcomes and MeasuresSuicides were defined by the National Death Index. Base model predictors included VHA electronic health records and patient residential data. The expanded predictors came from natural language processing (NLP) of clinical notes and a social determinants of health (SDOH) public records database.ResultsThe model included 448 788 unique hospitalizations. Net benefit over risk horizons between 3 and 12 months was generally highest for the model that included both NLP and SDOH predictors (area under the receiver operating characteristic curve range, 0.747-0.780; area under the precision recall curve relative to the suicide rate range, 3.87-5.75). NLP and SDOH predictors also had the highest predictor class-level SHAP values (proportional SHAP = 64.0% and 49.3%, respectively), although the single highest positive variable-level SHAP value was for a count of medications classified by the US Food and Drug Administration as increasing suicide risk prescribed the year before hospitalization (proportional SHAP = 15.0%).Conclusions and RelevanceIn this study, clinical notes and public records were found to improve ML model prediction of suicide after psychiatric hospitalization. The model had positive net benefit over 3-month to 12-month risk horizons for plausible decision thresholds. Although caution is needed in inferring causality based on predictor importance, several key predictors have potential intervention implications that should be investigated in future studies.

Stressful life events are a common antecedent of suicidal thoughts. However, not all stressful events lead to increased suicidal thinking, even among those who frequently have suicidal thoughts. In this study, we examined whether the ways that individuals regulate their emotions moderates the association between stressful events and suicidal thinking. Building on prior research we hypothesized that cognitive reappraisal is associated with a weaker relationship between stress and same-day suicidal thoughts, and that expressive suppression is associated with a stronger relationship between stress and suicidal thoughts. We used a daily diary method to collect self-reports of stressful events and suicidal thoughts over a 28-day period. At baseline, we assessed participants’ tendency to use cognitive reappraisal and expressive suppression. Consistent with our first hypothesis, we found that at higher levels of reappraisal, there was a weaker relationship between stress and suicidal thoughts. Contrary to our second hypothesis, we found that at higher levels of expressive suppression there was also a weaker relationship between stress and suicidal thoughts. In contrast to laboratory-based findings suggesting that expressive suppression has negative psychological effects, these preliminary daily diary results suggest that expressive suppression could be an effective short-term emotion regulation strategy among individuals considering suicide.

(248 words) Introduction There is public concern about potential associations between adolescent social media/smartphone use and risk for suicide. However, no prior studies leverage qualitative methods to explore the experiences of adolescents currently at-risk for suicide. Methods This study examined social technology use from the perspectives of adolescents (n = 30; Mage = 16.1 years) currently hospitalized for a recent suicide attempt or severe ideation. We conducted in-depth interviews and coded transcripts using thematic analysis. We had three research questions: What (1) negative and (2) positive experiences do suicidal adolescents report related to their use of social media/smartphones? (3) How do adolescents describe their disconnection from these technologies use during inpatient hospitalization and views on a subsequent return to digital connectivity after discharge? Results and conclusions Results reveal both positive and negative social technology uses, with most participants reporting mixed (positive and negative) experiences. Negatives/risks included trouble regulating use, stress related to social media metrics, encounters with “triggering” content, hostility and meanness, self-denigrating comparisons, and burdensome friendship expectations. Positives/benefits included social connection, social support, affect-enhancing content, shared interests, and resources for mental health and coping. Overall, the documented risks and benefits of social technology use correspond with established (offline) risk and protective factors for suicidal thoughts and behaviors. Participants generally valued the break from social technologies during hospitalization, and also viewed them as integral to social re-entry and identified related concerns. Future studies should test well-being focused ‘digital hygiene’ interventions for maximizing potential benefits and minimizing potential harms of social technologies for at-risk adolescents.

Cross-sectional studies and prospective studies with long follow-up periods (e.g., years) have shown that lower levels of social support are associated with nonsuicidal self-injury (NSSI) among adolescents. This study examined how short-term changes in social support may contribute to NSSI behavior and whether different sources of support (e.g., friends, family members) provide differential protective effects against NSSI. We examined fluctuations in NSSI and social support perceived from multiple sources among a sample of 118 high-risk adolescents hospitalized for serious self-harm risk. Participants provided daily reports of social support and any self-injurious behavior for the duration of their inpatient treatment (721 total observations, average observations per participant = 6.11). Multi-level models were used to assess variability in social support and how these fluctuations relate to whether or not an individual engages in NSSI. Over one-third of participants reported engaging in NSSI at least once during inpatient hospitalization and self-reported social support varied within person across sources of support (ICC range = 0.68-0.81). Support perceived from family members and inpatient unit staff was inversely associated with NSSI, but no relationship was found between NSSI and support from other patients on the unit or friends outside of the unit. These findings suggest that the protective effects of social support for NSSI vary over short periods of time and that support perceived from adults is particularly relevant among this high-risk clinical sample. This study represents an important step in identifying risk factors to improve the detection and prevention of NSSI among adolescent inpatients.