Heterogeneity in suicide risk: Evidence from personalized dynamic models.

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

Do people know how suicidal they will be? Understanding suicidal prospection.

INTRODUCTION: Little research has been done on how people mentally simulate future suicidal thoughts and urges, a process we term suicidal prospection. METHODS: Participants were 94 adults with recent suicidal thoughts. Participants completed a 42-day real-time monitoring study and then a follow-up survey 28 days later. Each night, participants provided predictions for the severity of their suicidal thoughts the next day and ratings of the severity of suicidal thoughts over the past day. We measured three aspects of suicidal prospection: predicted levels of desire to kill self, urge to kill self, and intent to kill self. We generated prediction errors by subtracting participants' predictions of the severity of their suicidal thoughts from their experienced severity. RESULTS: Participants tended to overestimate (although the average magnitude was small and the modal error was zero) the severity of their future suicidal thoughts. The best fitting models suggested that participants used both their current suicidal thinking and previous predictions of their suicidal thinking to generate predictions of their future suicidal thinking. Finally, the average severity of predicted future suicidal thoughts predicted the number of days participants thought about suicide during the follow-up period. CONCLUSIONS: This study highlights prospection as a psychological process to better understand suicidal thoughts and behaviors.

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

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

Suicidal thinking as affect regulation.

Nine percent of people worldwide report thinking about suicide at some point during their lives. A fundamental question we currently lack a clear answer to is: why do suicidal thoughts persist over time? One possibility is that suicidal thoughts serve adaptive functions for people who experience them. We tested whether suicidal thinking may serve as a form of affect regulation. In a real-time monitoring study among adults with recent suicidal thoughts (N = 105), we found that participants often endorsed using suicidal thinking as a form of affect regulation. The occurrence of suicidal thinking was followed by decreased negative affect. However, when assessing the direction of the relationship between suicidal thinking and negative affect, we also found positive bidirectional associations between them. Finally, using suicidal thinking as a form of affect regulation predicted the frequency and severity of suicidal thinking at later time points. These findings may help explain the persistence of suicidal thoughts. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Mapping the timescale of suicidal thinking.

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.

Examining tradeoffs between cognitive effort and relief among adults with self-injurious behavior.

BACKGROUND: 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. METHOD: 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. RESULTS: 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. LIMITATIONS: 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. CONCLUSIONS: 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 classification of suicide gestures: Examining the validity, measurement, and level of intent of a controversial construct.

INTRODUCTION: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Real-time digital monitoring of a suicide attempt by a hospital patient.

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.

Caregiver Engagement During Pediatric Post-Acute Care Hospitalization.

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 <1 year or ≥18 years, with ≥2 pPACH admissions, public insurance, Child Protective Services (CPS) involvement, and African American/Black, other, and unknown race/ethnicities. 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.

Validation of a novel Psychosis-Implicit Association Test (P-IAT) as a diagnostic support tool.

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.

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

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

Social Support and Nonsuicidal Self-injury among adolescent Psychiatric Inpatients.

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.

Examining implicit positive affect toward suicide among suicidal and nonsuicidal adults and adolescents.

OBJECTIVE: The purpose of this study was to examine implicit affect toward suicide (i.e., how good/bad suicide is perceived). Some people might be more likely to think about/choose suicide because they perceive it as a good option (to gain relief) relative to available alternatives. METHOD: Implicit affect toward suicide among adults (N = 72) and adolescents (N = 174) with and without suicidal thoughts was examined using first-person (FP) perspective suicide pictures in the affect misattribution procedure (AMP). RESULTS: Suicidal adults' implicit positive affect toward suicide was associated with STB variables, such as explicit valence (r = 0.34) and arousal (r = 0.44) ratings of suicide pictures, and implicit affect differentiated groups above and beyond explicit valence ratings. Contrary to our hypothesis, suicidal participants did not display higher implicit positive affect toward suicide than nonsuicidal participants. However, suicidal participants displayed consistent implicit affect toward different suicide pictures, whereas nonsuicidal participants evaluated some pictures as more pleasant than others (ORs = 1.92-2.27). CONCLUSIONS: Implicit affect toward suicide may relate to STB, but stimuli characteristics (e.g., color) likely influence the accuracy of assessment with the AMP and should be a focus of future research involving this and other implicit measures.

Effect of frequent assessment of suicidal thinking on its incidence and severity: high-resolution real-time monitoring study.

Researchers, 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.

Prediction of Suicide Attempts Using Clinician Assessment, Patient Self-report, 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.

Consensus Statement on Ethical & Safety Practices for Conducting Digital Monitoring Studies with People at Risk of Suicide and Related Behaviors.

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.

A Pilot Study Using Frequent Inpatient Assessments of Suicidal Thinking to Predict Short-Term Postdischarge Suicidal Behavior.

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.

Inconsistencies in self-reports of suicidal ideation and attempts across assessment methods.

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).

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

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

Do Patterns and Types of Negative Affect During Hospitalization Predict Short-Term Post-Discharge Suicidal Thoughts and Behaviors?

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 four 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.