Recent theories have implicated inflammatory biology in the development of psychopathology and maladaptive behaviors in adolescence, including suicidal thoughts and behaviors (STB). Examining specific biological markers related to inflammation is thus warranted to better understand risk for STB in adolescents, for whom suicide is a leading cause of death.

Participants were 211 adolescent females (ages 9–14 years; Mage = 11.8 years, SD = 1.8 years) at increased risk for STB. This study examined the prospective association between basal levels of inflammatory gene expression (average of 15 proinflammatory mRNA transcripts) and subsequent risk for suicidal ideation and suicidal behavior over a 12-month follow-up period.

Controlling for past levels of STB, greater proinflammatory gene expression was associated with prospective risk for STB in these youth. Similar effects were observed for CD14 mRNA level, a marker of monocyte abundance within the blood sample. Sensitivity analyses controlling for other relevant covariates, including history of trauma, depressive symptoms, and STB prior to data collection, yielded similar patterns of results.

Upregulated inflammatory signaling in the immune system is prospectively associated with STB among at-risk adolescent females, even after controlling for history of trauma, depressive symptoms, and STB prior to data collection. Additional research is needed to identify the sources of inflammatory up-regulation in adolescents (e.g., stress psychobiology, physiological development, microbial exposures) and strategies for mitigating such effects to reduce STB.

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.

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.

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 χ 21 = 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.

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.

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.

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.

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.

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.

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.

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.

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.

Predictive risk algorithms embedded into universal screening, coupled with telehealth intervention, offer significant potential as a suicide prevention approach for students.

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).

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.

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.

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.

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.

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.

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.

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.

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.

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).

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).

NSSI is common among first-year college students and is a behavioral marker of various common mental disorders.

Non-suicidal self-injury (NSSI) prospectively predicts suicidal thoughts and behaviors in civilian populations. Despite high rates of suicide among US military members, little is known about the prevalence and course of NSSI, or how NSSI relates to suicidal thoughts and behaviors, in military personnel.

We conducted secondary analyses of two representative surveys of active-duty soldiers (N = 21 449) and newly enlisted soldiers (N = 38 507) from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).

The lifetime prevalence of NSSI is 6.3% (1.2% 12-month prevalence) in active-duty soldiers and 7.9% (1.3% 12-month prevalence) in new soldiers. Demographic risk factors for lifetime NSSI include female sex, younger age, non-Hispanic white ethnicity, never having married, and lower educational attainment. The association of NSSI with temporally primary internalizing and externalizing disorders varies by service history (new v. active-duty soldiers) and gender (men v. women). In both active-duty and new soldiers, NSSI is associated with increased odds of subsequent onset of suicidal ideation [adjusted odds ratio (OR) = 1.66–1.81] and suicide attempts (adjusted OR = 2.02–2.43), although not with the transition from ideation to attempt (adjusted OR = 0.92–1.36). Soldiers with a history of NSSI are more likely to have made multiple suicide attempts, compared with soldiers without NSSI.

NSSI is prevalent among US Army soldiers and is associated with significantly increased odds of later suicidal thoughts and behaviors, even after NSSI has resolved. Suicide risk assessments in military populations should screen for history of NSSI.

Investigations of drinking behavior across military deployment cycles are scarce, and few prospective studies have examined risk factors for post-deployment alcohol misuse.

Prevalence of alcohol misuse was estimated among 4645 US Army soldiers who participated in a longitudinal survey. Assessment occurred 1–2 months before soldiers deployed to Afghanistan in 2012 (T0), upon their return to the USA (T1), 3 months later (T2), and 9 months later (T3). Weights-adjusted logistic regression was used to evaluate associations of hypothesized risk factors with post-deployment incidence and persistence of heavy drinking (HD) (consuming 5 + alcoholic drinks at least 1–2×/week) and alcohol or substance use disorder (AUD/SUD).

Prevalence of past-month HD at T0, T2, and T3 was 23.3% (s.e. = 0.7%), 26.1% (s.e. = 0.8%), and 22.3% (s.e. = 0.7%); corresponding estimates for any binge drinking (BD) were 52.5% (s.e. = 1.0%), 52.5% (s.e. = 1.0%), and 41.3% (s.e. = 0.9%). Greater personal life stress during deployment (e.g., relationship, family, or financial problems) – but not combat stress – was associated with new onset of HD at T2 [per standard score increase: adjusted odds ratio (AOR) = 1.20, 95% CI 1.06–1.35, p = 0.003]; incidence of AUD/SUD at T2 (AOR = 1.54, 95% CI 1.25–1.89, p < 0.0005); and persistence of AUD/SUD at T2 and T3 (AOR = 1.30, 95% CI 1.08–1.56, p = 0.005). Any BD pre-deployment was associated with post-deployment onset of HD (AOR = 3.21, 95% CI 2.57–4.02, p < 0.0005) and AUD/SUD (AOR = 1.85, 95% CI 1.27–2.70, p = 0.001).

Alcohol misuse is common during the months preceding and following deployment. Timely intervention aimed at alleviating/managing personal stressors or curbing risky drinking might reduce risk of alcohol-related problems post-deployment.