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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.

OBJECTIVES Caregiver engagement during acute inpatient hospitalizations has been demonstrated to provide developmental and behavioral benefits for children, decrease readmissions and length of stay, and improve caregiver confidence. Caregiver engagement has been examined in acute care settings; however, there is a gap in information regarding caregiver engagement in a pediatric post-acute care hospital (pPACH). The objective of this study was to explore caregiver engagement in a pPACH. PATIENTS AND METHODS All patients, birth to 23 years of age, in the medical service of an independent pPACH in the Northeastern United States, January 1, 2013, through December 31, 2017, were identified. Retrospective review of electronic health records for patient demographics and caregiver engagement, identified as visit(s) and telephone call(s), was conducted. Descriptive statistics and logistic regression were used to distinguish differences and measure associations of caregiver visits and calls between demographic groups. RESULTS The primary mode of caregiver engagement for pPACH patients (n = 614) was by visits, whereas caregiver calls were less frequent. Multivariable logistic regression analysis identified significantly greater odds of caregiver visits among patients ages 1 to 17 years, with private payer, and having a single admission, whereas lower odds of visits were identified among those CONCLUSIONS Patients who were infants, had ≥2 admissions, had CPS involvement, and were covered under public payer experienced lower caregiver visit rates. Strategies are needed to further identify and address barriers to caregiver engagement.

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.

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.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.Across most symptoms, youth hospitalized during the pandemic reported increased severity compared to those hospitalized before the pandemic.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.

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.

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 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).

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.

The Death/Suicide Implicit Association Test (IAT) is effective at detecting and prospectively predicting suicidal thoughts and behaviors. However, traditional IAT scoring procedures used in all prior studies (i.e., D-scores) provide an aggregate score that is inherently relative, obfuscating the separate associations (i.e., “Me = Death/Suicide,” “Me = Life”) that might be most relevant for understanding suicide-related implicit cognition. Here, we decompose the D-scores and validate a new analytic technique called the Decomposed D-scores (“DD-scores”) that creates separate scores for each category (“Me,” “Not Me”) in the IAT. Across large online volunteer samples (N > 12,000), results consistently showed that a weakened association between “Me = Life” is more strongly predictive of having a history of suicidal attempts than is a stronger association between “Me = Death/Suicide.” These findings replicated across three different versions of the IAT and were observed when calculated using both reaction times and error rates. However, among those who previously attempted suicide, a strengthened association between “Me = Death” is more strongly predictive of the recency of a suicide attempt. These results suggest that decomposing traditional IAT D-scores can offer new insights into the mental associations that may underlie clinical phenomena and may help to improve the prediction, and ultimately the prevention, of these clinical outcomes.

Despite significant advances in early-intervention services for psychosis, delays in identifying patients continue to impede the delivery of prompt and effective treatments. We sought to develop and preliminarily validate a self-administered psychosis implicit association task (P-IAT) as a screening and diagnostic support tool for identifying individuals with psychotic illness in community settings. The P-IAT is a response latency task, designed to measure the extent to which individuals implicitly associate psychosis-related terms with the "self." The P-IAT was administered to 57 participants across 3 groups: healthy controls (N=19), inpatients hospitalized with active psychosis (N=19), and outpatients with psychotic disorders (N=19). Mean D-scores (the output of the task) differed significantly between the illness groups and healthy controls (Mann-Whitney U=138, p.001). A receiver operating curve was plotted to assess the performance of D-scores in predicting a psychosis diagnosis, yielding an area under the curve of 0.81. When participant D-scores exceeded -0.24, the test achieved a specificity of 100% (sensitivity: 47%), with all 18 participants scoring above this threshold belonging to the illness groups. The discriminant performance of the P-IAT suggests its potential to augment existing screening instruments and inform referral decision making, particularly in settings with limited access to specialist providers.

Key Points Question What is the best method to predict which patients presenting to the emergency department will make a suicide attempt within 1 and 6 months after the visit? Findings This prognostic study of 1818 patients found that prediction of suicide attempts in the 1 month and 6 months after a patient visited an emergency department was significantly improved using machine learning models applied to data from a brief patient self-report scale, especially when supplemented with data from patients’ electronic health records and/or clinicians’ assessments. Meaning This study suggests that clinicians can improve their ability to identify patients at high risk of suicide by using data from a brief patient self-report scale and electronic health records., Importance Half of the people who die by suicide make a health care visit within 1 month of their death. However, clinicians lack the tools to identify these patients. Objective To predict suicide attempts within 1 and 6 months of presentation at an emergency department (ED) for psychiatric problems. Design, Setting, and Participants This prognostic study assessed the 1-month and 6-month risk of suicide attempts among 1818 patients presenting to an ED between February 4, 2015, and March 13, 2017, with psychiatric problems. Data analysis was performed from May 1, 2020, to November 19, 2021. Main Outcomes and Measures Suicide attempts 1 and 6 months after presentation to the ED were defined by combining data from electronic health records (EHRs) with patient 1-month (n = 1102) and 6-month (n = 1220) follow-up surveys. Ensemble machine learning was used to develop predictive models and a risk score for suicide. Results A total of 1818 patients participated in this study (1016 men [55.9%]; median age, 33 years [IQR, 24-46 years]; 266 Hispanic patients [14.6%]; 1221 non-Hispanic White patients [67.2%], 142 non-Hispanic Black patients [7.8%], 64 non-Hispanic Asian patients [3.5%], and 125 non-Hispanic patients of other race and ethnicity [6.9%]). A total of 137 of 1102 patients (12.9%; weighted prevalence) attempted suicide within 1 month, and a total of 268 of 1220 patients (22.0%; weighted prevalence) attempted suicide within 6 months. Clinicians’ assessment alone was little better than chance at predicting suicide attempts, with externally validated area under the receiver operating characteristic curve (AUC) of 0.67 for the 1-month model and 0.60 for the 6-month model. Prediction accuracy was slightly higher for models based on EHR data (1-month model: AUC, 0.71; 6 month model: AUC, 0.65) and was best using patient self-reports (1-month model: AUC, 0.76; 6-month model: AUC, 0.77), especially when patient self-reports were combined with EHR and/or clinician data (1-month model: AUC, 0.77; and 6 month model: AUC, 0.79). A model that used only 20 patient self-report questions and an EHR-based risk score performed similarly well (1-month model: AUC, 0.77; 6 month model: AUC, 0.78). In the best 1-month model, 30.7% (positive predicted value) of the patients classified as having highest risk (top 25% of the sample) made a suicide attempt within 1 month of their ED visit, accounting for 64.8% (sensitivity) of all 1-month attempts. In the best 6-month model, 46.0% (positive predicted value) of the patients classified at highest risk made a suicide attempt within 6 months of their ED visit, accounting for 50.2% (sensitivity) of all 6-month attempts. Conclusions and Relevance This prognostic study suggests that the ability to identify patients at high risk of suicide attempt after an ED visit for psychiatric problems improved using a combination of patient self-reports and EHR data., This prognostic study assesses methods of identifying patients at high risk of suicide attempts within 1 and 6 months after patients presented at an emergency department for psychiatric problems using clinician assessments, a brief patient self-report scale, and electronic health records.

SummaryResearchers, clinicians and patients are increasingly using real-time monitoring methods to understand and predict suicidal thoughts and behaviours. These methods involve frequently assessing suicidal thoughts, but it is not known whether asking about suicide repeatedly is iatrogenic. We tested two questions about this approach: (a) does repeatedly assessing suicidal thinking over short periods of time increase suicidal thinking, and (b) is more frequent assessment of suicidal thinking associated with more severe suicidal thinking? In a real-time monitoring study (n = 101 participants, n = 12 793 surveys), we found no evidence to support the notion that repeated assessment of suicidal thoughts is iatrogenic.

Behavioral measures are increasingly used to assess suicidal thoughts and behaviors. Some measures, such as the Suicide Stroop Task, have yielded mixed findings in the literature. An understudied feature of these behavioral measures has been their psychometric properties, which may affect the probability of detecting significant effects and reproducibility. In the largest investigation of its kind, we tested the internal consistency and concurrent validity of the Suicide Stroop Task in its current form, drawing from seven separate studies (N = 875 participants, 64% female, aged 12 to 81 years). Results indicated that the most common Suicide Stroop scoring approach, interference scores, yielded unacceptably low internal consistency (rs = -.09-.13) and failed to demonstrate concurrent validity. Internal consistency coefficients for mean reaction times (RTs) to each stimulus type ranged from rs = .93-.94. All scoring approaches for suicide-related interference demonstrated poor classification accuracy (AUCs = .52-.56) indicating that scores performed near chance in their ability to classify suicide attempters from nonattempters. In the case of mean RTs, we did not find evidence for concurrent validity despite our excellent reliability findings, highlighting that reliability does not guarantee a measure is clinically useful. These results are discussed in the context of the wider implications for testing and reporting psychometric properties of behavioral measures in mental health research. ispartof: Psychological Assessment vol:31 issue:8 pages:1052-1061 ispartof: location:United States status: published

Background Human decision making exhibits a mixture of model-based and model-free control. Recent evidence indicates that arbitration between these two modes of control (“metacontrol”) is based on their relative costs and benefits. While model-based control may increase accuracy, it requires greater computational resources, so people invoke model-based control only when potential rewards exceed those of model-free control. We used a sequential decision task, while concurrently manipulating performance incentives, to ask if symptoms and traits of psychopathology decrease or increase model-based control in response to incentives. Methods We recruited a nonpatient population of 839 online participants using Amazon Mechanical Turk who completed transdiagnostic self-report measures encompassing symptoms, traits, and factors. We fit a dual-controller reinforcement learning model and obtained a computational measure of model-based control separately for small incentives and large incentives. Results None of the constructs were related to a failure of large incentives to boost model-based control. In fact, for the sensation seeking trait and anxious-depression factor, higher scores were associated with a larger incentive effect, whereby greater levels of these constructs were associated with larger increases in model-based control. Many constructs showed decreases in model-based control as a function of severity, but a social withdrawal factor was positively correlated; alcohol use and social anxiety were unrelated to model-based control. Conclusions Our results demonstrate that model-based control can reliably be improved independent of construct severity for most measures. This suggests that incentives may be a useful intervention for boosting model-based control across a range of symptom and trait severity.

Contains fulltext : 201988.pdf (Publisher’s version ) (Closed access) Suicide is a leading cause of death worldwide. Despite decades of clinical and theoretical accounts that suggest that suicidal thoughts and behaviors are efforts to escape painful emotions, little prior research has examined decision making involved in escaping aversive states. We compared the performance of 85 suicidal participants to 44 nonsuicidal psychiatric patients on a novel reinforcement learning task with choices to make either active (i.e., "go") or passive responses (i.e., "no-go") to either escape or avoid an aversive stimulus. We used a computational cognitive model to isolate decision-making biases. We hypothesized that suicidal participants would exhibit a relatively elevated bias for making active responses to escape an aversive state and would show worse performance when escape required a passive response (i.e., "doing nothing" to escape). Our hypotheses were supported: The computational model revealed that suicidal participants exhibited a higher bias for an active response to escape compared with nonsuicidal psychiatric controls, suggesting that this finding was not just the result of the presence of psychopathology. The bias parameter also accounted for unique variance in predicting group status among several constructs previously related to suicidal thoughts and behaviors. This study provides a new method for testing escape decision making and does so using a computational cognitive model, allowing us to precisely index processes underlying suicidal and related behaviors. Future research examining escape decision making from a computational perspective could help link neural processes or environmental stressors to suicidal thoughts or behaviors. 13 p.

OBJECTIVE: Prior research indicates that adults’ implicit identification with death can be used to predict suicidal thoughts and behaviors (STBs) in the community. However, no studies have examined whether this effect is found among adolescents—a group for whom suicide is the 2(nd) leading cause of death. The current study tested the utility of implicit identification with death, using a Death Implicit Association Test (Death IAT), for detecting and predicting STBs in adolescents. METHOD: Participants were 141 adolescents aged 12–19 years (81.6% female; 74.5% White) with a current psychiatric disorder and/or currently receiving outpatient psychiatric treatment. All participants completed the Death IAT and self-report measures of STBs at baseline, as well as self-report measures of STBs at 6-month and 1-year follow-ups. RESULTS: At baseline, stronger implicit identification with death (higher Death IAT score) was related to greater suicide ideation (SI) frequency, severity, and duration, but did not differ based on suicide attempt history. Prospectively, higher Death IAT scores predicted any occurrence (but not frequency) of SI over the subsequent year, but not when controlling for prior SI. Death IAT scores were higher among adolescents with prior attempts who reattempted suicide over the follow-up. Examination of stimuli-level results suggested that Death IAT differences may be driven by responses on trials with specific words, including “Suicide” and “Die”. CONCLUSIONS: Implicit identification with death may be a useful behavioral indicator of suicide risk in adolescents. Preliminary findings suggest that the Death IAT may aid in predicting STBs among youth receiving outpatient treatment.

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.

Researchers, clinicians, and patients are increasingly using real-time monitoring methods to understand and predict suicidal thoughts and behaviors. These methods involve frequently assessing suicidal thoughts, but it is unknown if asking about suicide repeatedly is iatrogenic. We tested two questions about this approach: (1) does repeatedly assessing suicidal thinking over short periods of time increase suicidal thinking? (2) is more frequent assessment of suicidal thinking associated with more severe suicidal thinking? In a real-time monitoring study (N = 81, number of surveys = 9,819), we found no evidence to support the notion that repeated assessment of suicidal thoughts is iatrogenic.

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.

The Self-Injurious Thoughts and Behaviors Interview (SITBI) is a widely used measure of the presence, frequency, and characteristics of suicide and self-harming thoughts and behaviors. In response to advances in the conceptualization of these outcomes, and the potential for online data collection, we created a revised version of the SITBI (SITBI-R) and tested its psychometric properties via in-person interview and online self-report formats. Across two studies, the SITBI-R demonstrated strong psychometric properties for both assessment formats. In Study 1, outcomes measured via the SITBI-R showed convergent validity with those assessed with the Columbia Suicide Severity Rating Scale, another interview assessing suicidal thoughts and behaviors. The SITBI-R also showed strong alternate-forms reliability across nearly all outcomes assessed via both assessment formats. In Study 2, the SITBI-R showed strong test-retest reliability via the online assessment format. Across both studies, reliability was strongest for more recent outcomes (e.g., past year vs. lifetime) and for more commonly assessed outcomes of suicidal thoughts, plans, and attempts than for other, less commonly assessed behaviors (e.g., suicide gestures, interrupted suicide attempts, and aborted suicide attempts). The results of these two studies suggest that the SITBI-R provides reliable and valid measurement of key self-injurious outcomes both in person and online. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Suicide is a leading cause of death worldwide and perhaps the most puzzling and devastating of all human behaviors. Suicide research has primarily been guided by verbal theories containing vague constructs and poorly specified relationships. We propose two fundamental changes required to move toward a mechanistic understanding of suicide. First, we must formalize theories of suicide, expressing them as mathematical or computational models. Second, we must conduct rigorous descriptive research, prioritizing direct observation and precise measurement of suicidal thoughts and behaviors and of the factors posited to cause them. Together, theory formalization and rigorous descriptive research will facilitate abductive theory construction and strong theory testing, thereby improving the understanding and prevention of suicide and related behaviors.

Persistent suicide ideation (SI) is known to be a risk factor for subsequent suicidal behaviors. Reducing SI persistence among people with a history of SI consequently might be a useful target for preventive intervention; however, basic information is lacking about patterns and predictors of SI persistence. We report preliminary retrospective data on annual SI persistence in a representative sample of 3,501 U.S. Army soldiers with lifetime SI from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS). Reports about age-of-onset and number of years with SI were used to estimate two definitions of persistence: persistence beyond year-of-onset and proportional annual persistence (i.e., percentage of years with SI since year-of-onset). Results revealed that for 47.8% of respondents with lifetime SI, their SI did not persist beyond the year-of-onset. For the 52.2% whose SI did persist beyond the year-of-onset, the median (interquartile range) proportional annual persistence was 33% (17-67%). Significant predictors of increased persistence were different for respondents with preenlistment SI onset (prior histories of attention-deficit/hyperactivity disorder [ADHD], bipolar disorder, and panic disorder) and postenlistment SI onset (male, combat support military occupation specialty, prior histories of ADHD, panic disorder, and posttraumatic stress disorder). These predictors of persistence are different from the predictors of SI onset, suggesting that secondary preventive interventions to reduce SI persistence may need to focus on different factors than primary preventive interventions to reduce SI onset. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Prior research has shown that most known risk factors for suicide attempts in the general population actually predict suicide ideation rather than attempts among ideators. Yet clinical interest in predicting suicide attempts often involves the evaluation of risk among patients with ideation. We examined a number of characteristics of suicidal thoughts hypothesized to predict incident attempts in a retrospective analysis of lifetime ideators (N = 3,916) drawn from a large (N = 29,982), representative sample of United States Army soldiers. The most powerful predictors of first nonfatal lifetime suicide attempt in a multivariate model controlling for previously known predictors (e.g., demographics, mental disorders) were: recent onset of ideation, presence and recent onset of a suicide plan, low controllability of suicidal thoughts, extreme risk-taking or "tempting fate," and failure to answer questions about the characteristics of one's suicidal thoughts. A predictive model using these risk factors had strong accuracy (area under the curve [AUC] = .93), with 66.2% of all incident suicide attempts occurring among the 5% of soldiers with highest composite predicted risk. This high concentration of risk in this retrospective study suggests that a useful clinical decision support model could be constructed from prospective data to identify those with highest risk of subsequent suicide attempt. (PsycINFO Database Record

The current report presents data on lifetime prevalence of suicide ideation and nonfatal attempts as reported by the large representative sample of U.S. Army soldiers who participated in the Consolidated All Army Survey (AAS) of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS; n=29,982). We also examine associations of key Army career characteristics with these outcomes. Prevalence estimates for lifetime suicidal ideation are 12.7% among men and 20.1% among women, and for lifetime suicide attempts are 2.5% and 5.1%, respectively. Retrospective age-of-onset reports suggest that 53.4%–70.0% of these outcomes had pre-enlistment onsets. Results revealed that, for both men and women, being in the Regular Army, compared with being in the National Guard or Army Reserve, and being in an enlisted-rank, compared with being an officer, is associated with increased risk of suicidal behaviors and that this elevated risk is present both before and after joining the Army.

BACKGROUND: Although child maltreatment is a well documented risk factor for suicidal behavior, little is known about whether the timing of child maltreatment differentially associates with risk of suicidal ideation, suicide plans, or suicide attempts. The goal of this study was to examine whether a first exposure to physical or sexual abuse during specific developmental periods significantly elevated risk for suicidal behavior in adolescents. METHODS: Data came from the National Comorbidity Survey Adolescent Supplement, a population-based sample of US adolescents aged 13-18 years old (n = 9,272). Using discrete time survival analysis, we assessed the association between timing of first abuse (early childhood: ages 0-5; middle childhood: ages 6-10; adolescence: ages 11-18) and suicidal ideation, plans, and attempts. RESULTS: Exposure to either physical or sexual abuse increased the odds of reporting suicidal ideation (odds ratio [OR] = 5.06 and OR = 3.56, respectively), plans (OR = 3.63 and OR = 3.58, respectively), and attempts (OR = 5.80 and OR = 4.21, respectively), even after controlling for sociodemographic covariates and psychiatric disorders. However, the timing of physical and sexual abuse exposure was unassociated with suicidal behavior (all P values >.05). CONCLUSIONS: Exposure to child maltreatment is strongly associated with the risk for adolescent suicidal behaviors, though this association did not vary based on the timing of first exposure. These findings suggest that prevention efforts should be implemented throughout early development and target all children, regardless of when they were first exposed.© 2017 Wiley Periodicals, Inc. Language: en

The application of digital technology to psychiatry research is rapidly leading to new discoveries and capabilities in the field of mobile health. However, the increase in opportunities to passively collect vast amounts of detailed information on study participants coupled with advances in statistical techniques that enable machine learning models to process such information has raised novel ethical dilemmas regarding researchers' duties to: (i) monitor adverse events and intervene accordingly; (ii) obtain fully informed, voluntary consent; (iii) protect the privacy of participants; and (iv) increase the transparency of powerful, machine learning models to ensure they can be applied ethically and fairly in psychiatric care. This review highlights emerging ethical challenges and unresolved ethical questions in mobile health research and provides recommendations on how mobile health researchers can address these issues in practice. Ultimately, the hope is that this review will facilitate continued discussion on how to achieve best practice in mobile health research within psychiatry.L'application des technologies numériques à la recherche psychiatrique entraîne rapidement de nouvelles découvertes et capacités en matière de santé mobile. Cependant, la multiplication des opportunités de recueillir passivement d'immenses quantités d'informations détaillées sur les participants aux études combinée aux progrès des techniques statistiques permettant aux modèles d'apprentissage automatique de traiter de telles informations a soulevé de nouveaux dilemmes éthiques concernant l'obligation des chercheurs: (i) de surveiller les effets indésirables et d'intervenir en conséquence; (ii) d'obtenir un consentement pleinement éclairé et volontaire; (iii) de protéger la vie privée des participants; et enfin, (iv) d'améliorer la transparence des puissants modèles d'apprentissage automatique afin de garantir une application éthique et impartiale dans le domaine des soins psychiatriques. Ce rapport identifie les défis qui en découlent ainsi que les questions éthiques non résolues en matière de santé mobile. Il formule également des recommandations sur la façon dont les chercheurs en santé mobile peuvent résoudre ces problèmes dans la pratique. À terme, nous espérons que ce rapport favorisera la poursuite des discussions portant sur les moyens de définir des méthodes de recherche adéquates pour la santé mobile en psychiatrie.La aplicación de la tecnología digital a la investigación en psiquiatría está conduciendo rápidamente a descubrimientos y capacidades nuevas en el ámbito de la salud móvil. No obstante, el incremento de las oportunidades para recopilar pasivamente grandes volúmenes de información detallada sobre los participantes en los estudios, junto con los avances en las técnicas de estadística que permiten a los modelos de aprendizaje automático procesar tal información, ha planteado nuevos dilemas éticos relativos a los deberes de los investigadores: (i) hacer un seguimiento de los eventos adversos e intervenir en consecuencia; (ii) obtener un consentimiento voluntario plenamente informado; (iii) proteger la privacidad de los participantes; y (iv) aumentar la transparencia de los modelos potentes de aprendizaje automático para asegurar que puedan aplicarse de manera ética y justa en la atención psiquiátrica. En este análisis se destacan tanto los desafíos éticos nuevos como las cuestiones éticas aún sin resolver en la investigación sobre la salud móvil y se formulan recomendaciones sobre cómo los investigadores de la salud móvil pueden abordar dichas cuestiones en la práctica. En última instancia, se espera que este análisis facilite un debate continuo sobre cómo lograr las mejores prácticas en la investigación de la salud móvil dentro de la psiquiatría.يؤدي تطبيق التكنولوجيا الرقمية على أبحاث الطب النفسي إلى اكتشافات وقدرات جديدة، بشكل سريع، في مجال الصحة عبر الهاتف المحمول. ومع ذلك، فإن زيادة فرص جمع كميات هائلة من المعلومات التفصيلية بشكل سلبي عن المشاركين في الدراسة، إلى جانب التطورات في التقنيات الإحصائية التي تسمح لنماذج التعلم الآلي بمعالجة هذه المعلومات، قد أدت لإثارة معضلات أخلاقية غير مسبوقة تتعلق بواجبات الباحثين من أجل القيام بما يلي: (1) مراقبة الأحداث السلبية والتدخل وفقًا لذلك؛ و(2) الحصول على موافقة طوعية واعية بالكامل؛ و(3) حماية خصوصية المشاركين؛ و(4) زيادة شفافية نماذج التعلم الآلي القوية وذلك لضمان إمكانية تطبيقها بشكل أخلاقي وعادل في الرعاية النفسية. تسلط هذه المراجعة الضوء على التحديات الأخلاقية الناشئة، والمعضلات الأخلاقية غير المحسومة في أبحاث الصحة عبر الهاتف المحمول، وتقدم توصيات حول كيف يمكن للباحثين، في مجال الصحة عبر الهاتف المحمول، معالجة هذه القضايا في الممارسة العملية. وفي النهاية، نأمل أن تؤدي هذه المراجعة إلى تسهيل النقاش المستمر حول كيفية تحقيق أفضل الممارسات في أبحاث الصحة عبر الهاتف المحمول في مجال الطب النفسي.数字技术在精神病学研究中的应用正迅速带来移动医疗领域的新发现和新功能。然而，研究参与者被收集大量详细信息的机率增加，以及统计技术的进步，使机器学习模型能够处理此类信息，这就产生了关于研究人员职责的新型伦理困境：（i） 监测不良事件并进行相应的干预；（ii） 取得完全知情自愿的同意；（iii） 保护参与者的隐私；以及（iv） 提高强大的机器学习模型的透明度，以确保它们能够在精神病学保健中得到合乎道德和公平的应用。这篇文章强调了移动医疗研究中新出现的伦理挑战和未解决的伦理问题，并就移动医疗研究人员如何在实践中解决这些问题提出了建议。最终，我们希望这篇综述将有助于继续讨论如何实现移动医疗研究在精神病学中的最佳实践。.Использование цифровых технологий для проведения исследований в психиатрии способствует новым открытиям и появлению новых возможностей в сфере мобильного здравоохранения. Однако расширение возможностей пассивного сбора большого количества подробной информации об участниках исследования в сочетании с совершенствованием методов статистической обработки информации, позволяющих использовать модели машинного обучения для обработки такой информации, породило принципиально новые этические дилеммы в отношении таких обязанностей исследователей, как: (i) отслеживание нежелательных явлений и принятие соответствующих мер, (ii) получение полностью информированного добровольного согласия, (iii) защита конфиденциальности участников и (iv) повышение прозрачности мощных моделей машинного обучения, чтобы гарантировать их справедливое и этичное применение для оказания психиатрической помощи. В данном обзоре освещены возникающие этические проблемы и нерешенные этические вопросы исследований в области мобильного здравоохранения, а также содержатся практические рекомендации по их решению для исследователей в области мобильного здравоохранения. В конечном счете этот обзор должен посодействовать обсуждению вопроса применения наиболее совершенных практических методов для проведения исследований в психиатрии в рамках мобильного здравоохранения.

The interpersonal theory of suicide (IPTS) has been widely studied in adults, but not adolescent populations at acute risk for suicide. Accordingly, this study aimed to evaluate IPTS clinical utility in a high-risk sample of suicidal adolescent inpatients. We assessed whether constructs of the IPTS (1) are associated with suicidal thoughts and behaviors (STBs) on admission to a psychiatric hospitalization, and (2) prospectively predict suicide attempt (SA) or psychiatric rehospitalization 90 days after discharge. On admission, adolescent patients self-reported recent STBs, perceived burdensomeness (PB), thwarted belongingness (TB), and depression. Parents reported their child's rehospitalization and suicide attempts 90 days after discharge. Generalized linear regression modelling was used to determine how key constructs of the IPTS are associated with STBs prior to admission and whether they prospectively predict SA or rehospitalization 90 days after discharge. IPTS constructs did not predict rehospitalization or SA within 90 days of discharge. Although PB and TB interacted to associate with prehospitalization SI frequency, and PB, TB and NSSI interacted to associate with prehospitalization SA, the nature of these interactions were not as the IPTS predicts. IPTS constructs are relevant proximal predictors of prehospitalization STB in adolescents, but may operate differently than in adults.

Background Wearable physiological monitoring devices enable the continuous measurement of human behavior and psychophysiology in the real world. Although such monitors are promising, their availability does not guarantee that participants will continuously wear and interact with them, especially during times of psychological distress. Objective This study aimed to evaluate the feasibility and acceptability of using a wearable behavioral and physiological monitor, the Empatica E4, to continuously assess a group of suicidal adolescent inpatients. Methods Participants (n=50 adolescent inpatients) were asked to wear an Empatica E4 on their wrist for the duration of their inpatient stay. In addition to assessing behavioral metadata (eg, hours worn per day), we also used qualitative interviews and self-report measures to assess participants’ experience of wearing the monitor. Results Results supported the feasibility and acceptability of this approach. Participants wore the monitor for an average of 18 hours a day and reported that despite sometimes finding the monitor uncomfortable, they did not mind wearing it. Many of the participants noted that the part of the study they enjoyed most was contributing to scientific understanding, especially if it could help people similar to them in the future. Conclusions These findings provide promising support for using wearable monitors in clinical samples in future studies, especially if participants are invested in being part of a research study.

BACKGROUND Wearable physiological monitoring devices enable the continuous measurement of human behavior and psychophysiology in the real world. Although such monitors are promising, their availability does not guarantee that participants will continuously wear and interact with them, especially during times of psychological distress. OBJECTIVE This study aimed to evaluate the feasibility and acceptability of using a wearable behavioral and physiological monitor, the Empatica E4, to continuously assess a group of suicidal adolescent inpatients. METHODS Participants (n=50 adolescent inpatients) were asked to wear an Empatica E4 on their wrist for the duration of their inpatient stay. In addition to assessing behavioral metadata (eg, hours worn per day), we also used qualitative interviews and self-report measures to assess participants’ experience of wearing the monitor. RESULTS Results supported the feasibility and acceptability of this approach. Participants wore the monitor for an average of 18 hours a day and reported that despite sometimes finding the monitor uncomfortable, they did not mind wearing it. Many of the participants noted that the part of the study they enjoyed most was contributing to scientific understanding, especially if it could help people similar to them in the future. CONCLUSIONS These findings provide promising support for using wearable monitors in clinical samples in future studies, especially if participants are invested in being part of a research study.

Background Wearable physiological monitoring devices enable the continuous measurement of human behavior and psychophysiology in the real world. Although such monitors are promising, their availability does not guarantee that participants will continuously wear and interact with them, especially during times of psychological distress. Objective This study aimed to evaluate the feasibility and acceptability of using a wearable behavioral and physiological monitor, the Empatica E4, to continuously assess a group of suicidal adolescent inpatients. Methods Participants (n=50 adolescent inpatients) were asked to wear an Empatica E4 on their wrist for the duration of their inpatient stay. In addition to assessing behavioral metadata (eg, hours worn per day), we also used qualitative interviews and self-report measures to assess participants' experience of wearing the monitor. Results Results supported the feasibility and acceptability of this approach. Participants wore the monitor for an average of 18 hours a day and reported that despite sometimes finding the monitor uncomfortable, they did not mind wearing it. Many of the participants noted that the part of the study they enjoyed most was contributing to scientific understanding, especially if it could help people similar to them in the future. Conclusions These findings provide promising support for using wearable monitors in clinical samples in future studies, especially if participants are invested in being part of a research study.

The law of least mental effort states that, everything else being equal, the brain tries to minimize mental effort expenditure during task performance by avoiding decisions that require greater cognitive demands. Prior studies have shown associations between disruptions in effort expenditure and specific psychiatric illnesses (e.g., schizophrenia and depression) or clinically-related symptoms and traits (e.g., anhedonia and apathy), yet no research has explored this issue transdiagnostically. Specifically, this research has largely focused on a single diagnostic category, symptom, or trait. However, abnormalities in effort expression could be related to several different psychiatrically-relevant constructs that cut across diagnostic boundaries. Therefore, we examined the relationship between avoidance of mental effort and a diverse set of clinically-related symptoms and traits, and transdiagnostic latent factors in a large sample (n = 811). Only lack of perseverance, a dimension of impulsiveness, was associated with increased avoidance of mental effort. In contrast, several constructs were associated with less mental effort avoidance, including positive urgency, distress intolerance, obsessive-compulsive symptoms, disordered eating, and a factor consisting of compulsive behavior and intrusive thoughts. These findings demonstrate that deviations from normative effort expenditure are associated with a number of constructs that are common to several forms of psychiatric illness.

Key Points Question Can prediction of suicide attempts after psychiatric hospitalization be improved using frequent assessments of the level and variability of an individual’s suicidal thoughts? Findings In this prognostic study of 83 adult psychiatric inpatients, prediction of posthospital suicide attempts was fair when using only baseline data, improved in a model using mean level of suicidal thinking during hospitalization, and improved further in a model including dynamic features of suicidal thoughts. Meaning These findings suggest that data on real-time, dynamic changes in suicidal thoughts could improve prediction of suicide attempts during the high-risk period following psychiatric hospitalization., This prognostic study tests whether modeling dynamic changes in real-time suicidal thoughts during psychiatric hospitalization can improve predictions of postdischarge suicide attempts vs using only baseline data or using the mean level of real-time suicidal thoughts during hospitalization., Importance The weeks following discharge from psychiatric hospitalization are the highest-risk period for suicide attempts. Real-time monitoring of suicidal thoughts via smartphone prompts may be more indicative of short-term risk than a single, cross-sectional assessment. Objective To test whether modeling dynamic changes in real-time suicidal thoughts during psychiatric hospitalization can improve predictions of postdischarge suicide attempts vs using only baseline (ie, admission) data or using the mean level of real-time suicidal thoughts during hospitalization. Design, Setting, and Participants In this prognostic study, 83 adults recruited from the inpatient psychiatric unit at Massachusetts General Hospital completed ecological momentary assessment surveys of suicidal thinking 4 to 6 times per day during hospitalization as well as brief follow-up surveys assessing suicide attempts at 2 and 4 weeks after discharge. Participants completed at least 3 real-time monitoring surveys. Inclusion criteria included hospitalization for suicidal thoughts and/or behaviors and English fluency. Data were collected from January 2016 to December 2018 and analyzed from January to December 2020. Main Outcomes and Measures The primary outcome was suicide attempt in the month after discharge. Results Of 83 participants (mean [SD] age, 38.4 [13.6] years; 43 [51.8%] male participants; 69 [83.1%] White individuals), 9 (10.8%) made a suicide attempt in the month after discharge. Mean cross-validated AUC for elastic net models revealed predictive accuracy was fair for the model using baseline data (area under the curve [AUC], 0.71; first to third quartile, 0.55-0.88), good for the model using the mean level of real-time suicidal thoughts during hospitalization (AUC, 0.81; first to third quartile, 0.67-0.91), and best for the model using dynamic changes in real-time suicidal thoughts during hospitalization (AUC, 0.89; first to third quartile, 0.81-0.97); this pattern of results held for other classification metrics (eg, accuracy, positive predictive value, Brier score) and when using different cross-validation procedures. Features assessing rapid fluctuations in suicidal thinking emerged as the strongest predictors of posthospital suicide attempts. A final set of models incorporating percentage missingness further improved both the mean (mean AUC, 0.93; first to third quartile, 0.90-1.00) and dynamic feature (mean AUC, 0.93; first to third quartile, 0.88-1.00) models. Conclusions and Relevance In this study, collecting real-time data about suicidal thinking during the course of hospitalization significantly improved short-term prediction of posthospitalization suicide attempts. Models including dynamic changes in suicidal thinking over time yielded the best prediction; features that captured rapid changes in suicidal thoughts were particularly strong predictors. Survey noncompletion also emerged as an important predictor of posthospitalization suicide attempts.

Self-injurious behaviors (SIBs) are leading causes of death and injury. Unfortunately, disagreement regarding whether and how to classify suicidal and nonsuicidal SIBs has contributed to their misclassification, likely hindering clinical care and impeding scientific progress. The present study utilized a data-driven approach to facilitate classification and measurement of three forms of SIBs, with a particular focus on one with scant clinical and scientific attention: nonsuicidal overdoses (i.e. intentional overdoses where the person states that they had no intention of dying from the overdose). Results from this study demonstrated that nonsuicidal overdoses were similar to suicide attempts in terms of age of onset, and similar to nonsuicidal self-injury (NSSI) in terms of suicidal thoughts and desire to die when engaging in these behaviors. Nonsuicidal overdoses were unique from NSSI and suicide attempts in terms of the reported likelihood of dying from the behavior. The present study highlighted that current definitions for nonsuicidal behaviors (including requirements that the person has zero intent to die) may not accurately represent people's intent when engaging in these behaviors. Additionally, the present study highlighted that empirical analysis of SIBs can provide important insights for classification of SIBs.

To die by suicide, one must think about suicide, make a plan, and then carry it out. Prior research has examined the presence and predictors of these outcomes; however, virtually no studies have characterized how these steps unfold along the pathway to suicide. A novel instrument was administered to 30 recent suicide attempters. Results revealed that although the median onset for suicidal ideation occurs 1 to 5 years prior to attempting, the median for 6 of the 10 steps measured was within 6 hours of attempting. Overall, 86.5% of proximal planning steps took place within 1 week of attempting and 66.6% occurred within 12 hours.

Assessing suicidal thoughts and behaviors is difficult because at-risk individuals often fail to provide honest or accurate accounts of their suicidal thoughts or intentions. Research has shown that the Death Implicit Association Test (D-IAT), a behavioral test that measures implicit (i.e., outside of conscious control) associations between oneself and death concepts, can differentiate among people with different suicidal histories, such as those with different severity or recency of suicidal behaviors. We report here on the development and evaluation of a shorter and simpler version of the D-IAT called the Death Brief Implicit Association Test (D-BIAT). We recruited large (ns > 1,500) samples of participants to complete the original D-IAT and shorter D-BIAT via a public web-based platform and evaluated different scoring approaches, assessed the reliability and validity of the D-BIAT and compared it with the D-IAT. We found that the D-BIAT was reliable, provided significant group differences with effect sizes on par with the D-IAT, as well as similarly sized classification metrics (i.e., receiver operator characteristics). Although the D-IAT was nonsignificantly better on most outcomes, the D-BIAT is 1-1[1/2] minutes shorter and provided larger effect sizes for distinguishing between past year and lifetime attempters. Thus, there is a trade-off between administration time and improved outcomes associated with increased data. The D-BIAT should be considered for use where time or participant burden needs to be minimized, such as in clinical settings. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Objective For over 100 years impulsiveness has been cited as a key factor in why some people that think about killing themselves go on to attempt suicide. Yet prior studies are limited by not using experimental groups that can test this hypothesis and by treating impulsiveness as a unidimensional construct. To overcome these limitations, we compared suicide ideators and suicide attempters on several dimensions of impulsiveness. Method In Study 1 we compared inpatient suicide attempters who made an attempt within the prior two weeks (n = 30), current inpatient suicide ideators (n = 31), and community controls (n = 34) on several dimensions of impulsiveness using self-report and behavioral measures. In Study 2 (n = 346), we compared three similar groups based on lifetime and past year suicidal behaviors on several of the measures in Study 1. Results In Study 1, we found only that negative urgency was clearly elevated among attempters compared with ideators. In Study 2, there were no significant differences on any impulsiveness constructs, including negative urgency. Conclusions Results from the two studies suggest that attempters may not have significantly elevated trait impulsiveness, compared to ideators; however, attempters may have higher impulsiveness when in a negative state.

Using self-harm Implicit Association Tests (IATs), we sought to test whether (1) suicidal adolescents show implicit identification with self-harm and whether (2) IATs are reliable and sensitive to psychiatric change and (3) predict future suicide attempts. We administered 6 self-harm IATs to 71 adolescents from a psychiatric inpatient unit and assessed suicidal behaviors at admission, discharge and 3 months after discharge. Results were in the expected direction for each IAT but not statistically significant. After aggregating trials across IATs, suicide attempters showed increased implicit identification with self-harm, compared with non-suicidal controls. IATs showed good reliability and sensitivity to psychiatric change but did not prospectively predict suicide attempts. Adolescent suicide attempters may have stronger implicit associations with self-harm than non-suicidal controls.

Background Theoretical work and clinical observation suggest that many patients experience relief from negative affect after thinking about suicide, which may increase the likelihood of future suicidal thoughts. Accordingly, our objective was to examine whether the occurrence of suicidal thinking was followed by decreased negative affect and increased positive affect. Methods Participants were 43 adults who attempted suicide at least once in the past year (78% female, 78% White, M age = 23.28 years, SD age = 4.38 years) who completed 28 days of smartphone-based real-time monitoring, where they were signaled four times/day to report on current affect and whether they were having suicidal thoughts. Participants could initiate a survey whenever they had a suicidal thought. Results First, we examined changes in affect that occurred when suicidal thinking at the current time (T) but not at T + 1 (approximately 4–8 h later). Negative affect decreased and positive affect increased when participants went from a period when they were experiencing suicidal thoughts to a period where they were not. Second, to assess the time course of changes in affect, we examined changes in affect before and after participant-initiated reports of suicidal thinking. Positive affect increased and sadness decreased. Limitations Given its preliminary nature, the study has some limitations including insufficient power to expand beyond a 4–8 h timespan. Conclusions Findings provide preliminary evidence that suicidal thinking leads to shifts in affect. These shifts in affect may be reinforcing, helping to explain (in part) why suicidal thinking is so persistent for some patients.

Self-injurious thoughts and behaviors (SITBs), including nonsuicidal self-injury, suicidal thoughts, suicide attempts, and suicide death exhibit substantial sex differences. Across most countries, men die by suicide more frequently than women; yet, women think about and attempt suicide more frequently than men. Research on sex differences in nonsuicidal self-injury is less developed; however, nonsuicidal self-injury is historically understood as a primarily female phenomenon. This review describes current research on sex differences across SITBs with a focus on factors that moderate these effects, such as age, race, geographic region, and time. Additionally, this review describes factors that may help to explain why sex differences across SITBs exist, including differences in culture, access to lethal suicide methods, rates of mental illness, and utilization of health care. The role of gender, and particularly non-binary gender, is also discussed. Current understanding of these sex differences is described with an eye toward future research on this topic.

Here we report on associations of retrospectively-reported temporally prior mental disorders and Army career characteristics with subsequent first onset of suicidal behaviors in a large, representative sample of U.S. Army soldiers who participated in the Consolidated All Army Survey (AAS) of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS; n=29,982). Results reveal that among men and women, all self-reported lifetime disorders measured (some assessed with screening scales) are associated with subsequent onset of suicide ideation. Among men, three disorders characterized by agitation and impulsiveness (intermittent explosive disorder, panic disorder, and substance disorders) predict the transition from suicide ideation to attempt. For both men and women, being in the Regular Army (vs. National Guard or Army Reserve) and being junior-rank enlisted (vs. being an officer) predict suicide attempts in the total sample. For men, a history of deployment and junior rank are predictors of suicide attempts after adjusting for pre-enlistment disorders but not accounting for pre- and post-enlistment disorders, suggesting that post-enlistment disorders account for some of the increased suicide risk among these career characteristics. Overall, these results highlight associations between mental disorders and suicidal behaviors, but underscore limitations predicting which people with ideation attempt suicide.

Decades of research suggest that social support is an important factor in predicting suicide risk and resilience. However, no studies have examined dynamic fluctuations in day-by-day levels of perceived social support. We examined such fluctuations over 28 days among a sample of 53 adults who attempted suicide in the past year (992 total observations). Variability in social support was analyzed with between-person intraclass correlations and root mean square of successive differences. Multi-level models were conducted to determine the association between social support and suicidal ideation. Results revealed that social support varies considerably from day to day with 45% of social support ratings differing by at least one standard deviation from the prior assessment. Social support is inversely associated with same-day and next-day suicidal ideation, but not with next-day suicidal ideation after adjusting for same-day suicidal ideation (i.e., not with daily changes in suicidal ideation). These results suggest that social support is a time-varying protective factor for suicidal ideation.

The network approach to psychopathology conceptualizes mental disorders as networks of mutually reinforcing nodes (i.e., symptoms). Researchers adopting this approach have suggested that network topology can be used to identify influential nodes, with nodes central to the network having the greatest influence on the development and maintenance of the disorder. However, because commonly used centrality indices do not distinguish between positive and negative edges, they may not adequately assess the nature and strength of a node's influence within the network. To address this limitation, we developed 2 indices of a node's expected influence (EI) that account for the presence of negative edges. To evaluate centrality and EI indices, we simulated single-node interventions on randomly generated networks. In networks with exclusively positive edges, centrality and EI were both strongly associated with observed node influence. In networks with negative edges, EI was more strongly associated with observed influence than was centrality. We then used data from a longitudinal study of bereavement to examine the association between (a) a node's centrality and EI in the complicated grief (CG) network and (b) the strength of association between change in that node and change in the remainder of the CG network from 6- to 18-months postloss. Centrality and EI were both correlated with the strength of the association between node change and network change. Together, these findings suggest high-EI nodes, such as emotional pain and feelings of emptiness, may be especially important to the etiology and treatment of CG. (PsycINFO Database Record

A functional neuroimaging study examined the long-term neural correlates of early adverse rearing conditions in humans as they relate to socio-emotional development. Previously institutionalized (PI) children and a same-aged comparison group were scanned using functional magnetic resonance imaging (fMRI) while performing an Emotional Face Go/Nogo task. PI children showed heightened activity of the amygdala, a region that supports emotional learning and reactivity to emotional stimuli, and corresponding decreases in cortical regions that support perceptual and cognitive functions. Amygdala activity was associated with decreased eye-contact as measured by eye-tracking methods and during a live dyadic interaction. The association between early rearing environment and subsequent eye-contact was mediated by amygdala activity. These data support the hypothesis that early adversity alters human brain development in a way that can persist into childhood, and they offer insight into the socio-emotional disturbances in human behavior following early adversity.

Early adversity, for example poor caregiving, can have profound effects on emotional development. Orphanage rearing, even in the best circumstances, lies outside of the bounds of a species-typical caregiving environment. The long-term effects of this early adversity on the neurobiological development associated with socio-emotional behaviors are not well understood. Seventy-eight children, who include those who have experienced orphanage care and a comparison group, were assessed. Magnetic resonance imaging (MRI) was used to measure volumes of whole brain and limbic structures (e.g. amygdala, hippocampus). Emotion regulation was assessed with an emotional go-nogo paradigm, and anxiety and internalizing behaviors were assessed using the Screen for Child Anxiety Related Emotional Disorders, the Child Behavior Checklist, and a structured clinical interview. Late adoption was associated with larger corrected amygdala volumes, poorer emotion regulation, and increased anxiety. Although more than 50% of the children who experienced orphanage rearing met criteria for a psychiatric disorder, with a third having an anxiety disorder, the group differences observed in amygdala volume were not driven by the presence of an anxiety disorder. The findings are consistent with previous reports describing negative effects of prolonged orphanage care on emotional behavior and with animal models that show long-term changes in the amygdala and emotional behavior following early postnatal stress. These changes in limbic circuitry may underlie residual emotional and social problems experienced by children who have been internationally adopted.