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.

Linguistic measures of psychological distance track symptom levels and treatment outcomes in a large set of psychotherapy transcripts.

SignificanceUsing language to "distance" ourselves from distressing situations (i.e., by talking less about ourselves and the present moment) can help us manage emotions. Here, we translate this basic research to discover that such "linguistic distancing" is a replicable measure of mental health in a large set of therapy transcripts (N = 6,229). Additionally, clustering techniques showed that language alone could identify participants who differed on both symptom severity and treatment outcomes. These findings lay the foundation for 1) tools that can rapidly identify people in need of psychological services based on language alone and 2) linguistic interventions that can improve mental health.

Development and evaluation of a predictive algorithm and telehealth intervention to reduce suicidal behavior among university students.

BACKGROUND: Suicidal behaviors are prevalent among college students; however, students remain reluctant to seek support. We developed a predictive algorithm to identify students at risk of suicidal behavior and used telehealth to reduce subsequent risk. METHODS: Data come from several waves of a prospective cohort study (2016-2022) of college students (n = 5454). All first-year students were invited to participate as volunteers. (Response rates range: 16.00-19.93%). A stepped-care approach was implemented: (i) all students received a comprehensive list of services; (ii) those reporting past 12-month suicidal ideation were directed to a safety planning application; (iii) those identified as high risk of suicidal behavior by the algorithm or reporting 12-month suicide attempt were contacted via telephone within 24-h of survey completion. Intervention focused on support/safety-planning, and referral to services for this high-risk group. RESULTS: 5454 students ranging in age from 17-36 (s.d. = 5.346) participated; 65% female. The algorithm identified 77% of students reporting subsequent suicidal behavior in the top 15% of predicted probabilities (Sensitivity = 26.26 [95% CI 17.93-36.07]; Specificity = 97.46 [95% CI 96.21-98.38], PPV = 53.06 [95% CI 40.16-65.56]; AUC range: 0.895 [95% CIs 0.872-0.917] to 0.966 [95% CIs 0.939-0.994]). High-risk students in the Intervention Cohort showed a 41.7% reduction in probability of suicidal behavior at 12-month follow-up compared to high-risk students in the Control Cohort. CONCLUSIONS: Predictive risk algorithms embedded into universal screening, coupled with telehealth intervention, offer significant potential as a suicide prevention approach for students.

Undetected suicide attempts among U.S. soldiers: results from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).

BACKGROUND: While previous studies have reported high rates of documented suicide attempts (SAs) in the U.S. Army, the extent to which soldiers make SAs that are not identified in the healthcare system is unknown. Understanding undetected suicidal behavior is important in broadening prevention and intervention efforts. METHODS: Representative survey of U.S. Regular Army enlisted soldiers (n = 24 475). Reported SAs during service were compared with SAs documented in administrative medical records. Logistic regression analyses examined sociodemographic characteristics differentiating soldiers with an undetected SA v. documented SA. Among those with an undetected SA, chi-square tests examined characteristics associated with receiving a mental health diagnosis (MH-Dx) prior to SA. Discrete-time survival analysis estimated risk of undetected SA by time in service. RESULTS: Prevalence of undetected SA (unweighted n = 259) was 1.3%. Annual incidence was 255.6 per 100 000 soldiers, suggesting one in three SAs are undetected. In multivariable analysis, rank ⩾E5 (OR = 3.1[95%CI 1.6-5.7]) was associated with increased odds of undetected v. documented SA. Females were more likely to have a MH-Dx prior to their undetected SA (Rao-Scott χ21 = 6.1, p = .01). Over one-fifth of undetected SAs resulted in at least moderate injury. Risk of undetected SA was greater during the first four years of service. CONCLUSIONS: Findings suggest that substantially more soldiers make SAs than indicated by estimates based on documented attempts. A sizable minority of undetected SAs result in significant injury. Soldiers reporting an undetected SA tend to be higher ranking than those with documented SAs. Undetected SAs require additional approaches to identifying individuals at risk.

Detecting suicide risk among U.S. servicemembers and veterans: a deep learning approach using social media data.

BACKGROUND: Military Servicemembers and Veterans are at elevated risk for suicide, but rarely self-identify to their leaders or clinicians regarding their experience of suicidal thoughts. We developed an algorithm to identify posts containing suicide-related content on a military-specific social media platform. METHODS: Publicly-shared social media posts (n = 8449) from a military-specific social media platform were reviewed and labeled by our team for the presence/absence of suicidal thoughts and behaviors and used to train several machine learning models to identify such posts. RESULTS: The best performing model was a deep learning (RoBERTa) model that incorporated post text and metadata and detected the presence of suicidal posts with relatively high sensitivity (0.85), specificity (0.96), precision (0.64), F1 score (0.73), and an area under the precision-recall curve of 0.84. Compared to non-suicidal posts, suicidal posts were more likely to contain explicit mentions of suicide, descriptions of risk factors (e.g. depression, PTSD) and help-seeking, and first-person singular pronouns. CONCLUSIONS: Our results demonstrate the feasibility and potential promise of using social media posts to identify at-risk Servicemembers and Veterans. Future work will use this approach to deliver targeted interventions to social media users at risk for suicide.

Knowledge About the Source of Emotion Predicts Emotion-Regulation Attempts, Strategies, and Perceived Emotion-Regulation Success.

People's ability to regulate emotions is crucial to healthy emotional functioning. One overlooked aspect in emotion-regulation research is that knowledge about the source of emotions can vary across situations and individuals, which could impact people's ability to regulate emotion. Using ecological momentary assessments (N = 396; 7 days; 5,466 observations), we measured adults' degree of knowledge about the source of their negative emotions. We used language processing to show that higher reported knowledge led to more concrete written descriptions of the source. We found that higher knowledge of the source predicted more emotion-regulation attempts; increased the use of emotion-regulation strategies that target the source (cognitive reappraisal, situation modification) versus strategies that do not (distraction, emotional eating); predicted greater perceived success in regulating emotions; and greater well-being. These patterns were evident both within and between persons. Our findings suggest that pinpointing the source of emotions might play an important role in emotion regulation.

Social network size and personality traits independently and prospectively predict distress disorders and suicidal behavior in U.S. Army soldiers.

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

A longitudinal investigation of non-suicidal self-injury persistence patterns, risk factors, and clinical outcomes during the college period.

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

Non-suicidal self-injury among first-year college students and its association with mental disorders: results from the World Mental Health International College Student (WMH-ICS) initiative.

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

Body dissatisfaction, ideals, and identity in the development of disordered eating among adolescent ballet dancers.

OBJECTIVE: Little is known about how female adolescent ballet dancers-a group at high-risk for the development of body dissatisfaction and eating disorders-construct body ideals, and how their social identities interact with body ideals to confer risk for disordered eating. Using a novel body figure behavioral task, this study investigated (1) whether degree of body dissatisfaction corresponded to severity of disordered eating thoughts and behaviors, and (2) how ballet identity corresponded with ideal body figure size among adolescent ballet dancers. METHODS: Participants were 188 female ballet dancers ages 13-18 years who completed self-report measures of study constructs and the behavioral task. RESULTS: Linear regression models indicated that more severe body dissatisfaction was positively associated with increased disordered eating thoughts and behaviors (p < .19), except for muscle building (p = .32). We also found that identifying more strongly as a ballet dancer was correlated with having a smaller ideal body size (p = .017). CONCLUSION: Findings from this study suggest desire to achieve smaller body sizes is correlated with more severe disordered eating endorsement and stronger ballet identity. Instructors and clinicians may consider assessing the extent to which individuals identify as a ballet dancer as a risk factor for disordered eating and encourage adolescent dancers to build and nurture other identities beyond ballet. PUBLIC SIGNIFICANCE: Eating disorders are debilitating conditions that can lead to malnutrition, social isolation, and even premature death. Though disordered eating thoughts and behaviors can affect anyone, adolescents in physically demanding and body image-driven activities including ballet dance are particularly vulnerable. Investigating how factors like body dissatisfaction and strength of identity are associated with disordered eating among high-risk groups is crucial for developing effective prevention and intervention methods that minimize harm.

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.

Adolescent girls' stress responses as prospective predictors of self-injurious thoughts and behaviors: A person-centered, multilevel study.

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

Childhood adversities and suicidal thoughts and behaviors among first-year college students: results from the WMH-ICS initiative.

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

Exploring joint HPA-inflammatory stress response profiles in adolescent girls: Implications for developmental models of neuroendocrine dysregulation.

Prior research has struggled to differentiate cortisol stress response patterns reflective of well-regulated versus dysregulated hypothalamic-pituitary-adrenal (HPA) axis function among adolescents. Here, we show how exploring profiles of joint HPA-inflammatory stress responsivity, and linking those profiles to pubertal development and peer stress exposure may aid such distinction. Adolescent girls (N = 157, Mage  = 14.72 years, SD = 1.38) at risk for psychopathology completed assessments of salivary cortisol and pro-inflammatory cytokines (i.e., tumor necrosis factor-α, interleukin-1ß, and interleukin-6) prior to and following the Trier Social Stress Test. Adolescents, a close friend, and a caregiver completed questionnaire measures of peer stress and pubertal status. Multitrajectory modeling of adolescents' cortisol and cytokine levels revealed three profiles: low cortisol response-stably low cytokine (n = 75), high cortisol response-stably moderate cytokine (n = 47), and low cortisol response-stably high cytokine (n = 35). Relative to low cortisol response-stably low cytokine, adolescents exhibiting the high cortisol response-stably moderate cytokine profile were more advanced in their pubertal development, but presented with similarly low levels of peer stress exposure. Despite showing cortisol responses that were indistinguishable from low cortisol response-stably low cytokine, adolescents exhibiting the low cortisol response-stably high cytokine profile were more pubertally advanced, but also more likely to have experienced chronic peer strain (self-report) and relational peer victimization (close friend-report). These findings thus illustrate the potential value of taking a multisystem approach to studying adolescent stress responsivity and underscore the importance of considering developmental and social factors when interpreting cortisol stress response patterns. Ultimately, such work may help inform developmental models of neuroendocrine dysregulation and related risk for psychopathology.

Invited Commentary: New Directions in Machine Learning Analyses of Administrative Data to Prevent Suicide-Related Behaviors.

This issue contains a thoughtful report by Gradus et al. (Am J Epidemiol. 2021;190(12):2517-2527) on a machine learning analysis of administrative variables to predict suicide attempts over 2 decades throughout Denmark. This is one of numerous recent studies that document strong concentration of risk of suicide-related behaviors among patients with high scores on machine learning models. The clear exposition of Gradus et al. provides an opportunity to review major challenges in developing, interpreting, and using such models: defining appropriate controls and time horizons, selecting comprehensive predictors, dealing with imbalanced outcomes, choosing classifiers, tuning hyperparameters, evaluating predictor variable importance, and evaluating operating characteristics. We close by calling for machine-learning research into suicide-related behaviors to move beyond merely demonstrating significant prediction-this is by now well-established-and to focus instead on using such models to target specific preventive interventions and to develop individualized treatment rules that can be used to help guide clinical decisions to address the growing problems of suicide attempts, suicide deaths, and other injuries and deaths in the same spectrum.

Mental Disorders, Gun Ownership, and Gun Carrying Among Soldiers After Leaving the Army, 2016-2019.

Objectives. To examine associations of current mental and substance use disorders with self-reported gun ownership and carrying among recently separated US Army soldiers. Veterans have high rates of both gun ownership and mental disorders, the conjunction of which might contribute to the high suicide rate in this group. Methods. Cross-sectional survey data were collected in 2018-2019 from 5682 recently separated personnel who took part in the Army Study to Assess Risk and Resilience in Servicemembers. Validated measures assessed recent mood, anxiety, substance use, and externalizing disorders. Logistic regression models examined associations of sociodemographic characteristics, service characteristics, and mental disorders with gun ownership and carrying. Results. Of the participants, 50% reported gun ownership. About half of owners reported carrying some or most of the time. Mental disorders were not associated significantly with gun ownership. However, among gun owners, major depressive disorder, panic disorder, posttraumatic stress disorder, and intermittent explosive disorder were associated with significantly elevated odds of carrying at least some of the time. Conclusions. Mental disorders are not associated with gun ownership among recently separated Army personnel, but some mental disorders are associated with carrying among gun owners. (Am J Public Health. 2021;111(10):1855-1864. https://doi.org/10.2105/AJPH.2021.306420).

Racism and Poverty are Barriers to the Treatment of Youth Mental Health Concerns.

OBJECTIVE: Traditional studies of treatment moderators have focused largely on psychological factors such as clinical severity. Racial and economic inequity exert large effects on youth mental health, on treatment efficacy, and on the likelihood of receiving treatment altogether. Yet, these factors are studied less often by clinical psychological scientists. METHOD: We conducted a narrative review of literature on racial and economic inequities and their impact on youth mental health. RESULTS: First, systemic problems such as racism and poverty increase the risk of developing complex health issues and decrease the likelihood of benefiting from treatment. Second, attitudinal barriers, such as mistrust associated with treatments provided by researchers and government agencies, decrease the likelihood that minoritized groups will engage with or benefit from evidence-based treatments. Third, minoritized and underserved communities are especially unlikely to receive evidence-based treatment. CONCLUSION: Clinical psychological science has unique insights that can help address systemic inequities that can decrease treatment efficacy for youth mental health treatment. Psychological scientists can help eliminate disparities in accessing evidence-based treatment and help end violent policies in underserved minoritized communities by at the very least (1) building and supporting scalable community-based treatments as well as (2) publicly advocating for an end to violent policies that impose negative social costs.

Positive and negative uses of social media among adolescents hospitalized for suicidal behavior.

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

The pain of grief: Exploring the concept of psychological pain and its relation to complicated grief, depression, and risk for suicide in bereaved adults.

OBJECTIVE: Emotional or psychological pain is a core symptom of complicated grief (CG), yet its correlates are largely unexamined among bereaved individuals. METHOD: Bereaved adults (N = 135) completed self-reports regarding psychological pain, CG, depression, and suicidality. We assessed correlations among these variables and tested whether psychological pain was elevated among individuals with CG and individuals with current or past suicidal thoughts and behaviors. Using logistic regression, we also assessed psychological pain, depression, and CG symptom severity as predictors of suicide risk. RESULTS: Psychological pain was strongly associated with both CG and depression severity and was elevated among subjects reporting current or past suicidality. CG and depression were not statistically significant predictors of suicidal ideation after accounting for the effects of psychological pain. CONCLUSIONS: Psychological pain is strongly associated with bereavement-related psychopathology and warrants further investigation in studies examining the nature and treatment of CG.