Abstract In recent years, there has been a growing interest in understanding the relationship between sleep and suicide. Although sleep disturbances are commonly cited as critical risk factors for suicidal thoughts and behaviours, it is unclear to what degree sleep disturbances confer risk for suicide. The aim of this meta-analysis was to clarify the extent to which sleep disturbances serve as risk factors (i.e., longitudinal correlates) for suicidal thoughts and behaviours. Our analyses included 156 total effects drawn from 42 studies published between 1982 and 2019. We used a random effects model to analyse the overall effects of sleep disturbances on suicidal ideation, attempts, and death. We additionally explored potential moderators of these associations. Our results indicated that sleep disturbances are statistically significant, yet weak, risk factors for suicidal thoughts and behaviours. The strongest associations were found for insomnia, which significantly predicted suicide ideation (OR 2.10 [95% CI 1.83–2.41]), and nightmares, which significantly predicted suicide attempt (OR 1.81 [95% CI 1.12–2.92]). Given the low base rate of suicidal behaviours, our findings raise questions about the practicality of relying on sleep disturbances as warning signs for imminent suicide risk. Future research is necessary to uncover the causal mechanisms underlying the relationship between sleep disturbances and suicide.
For decades, our ability to predict suicidal thoughts and behaviors (STBs) has been at near-chance levels. The objective of this study was to advance prediction by addressing two major methodological constraints pervasive in past research: (a) the reliance on long follow-ups and (b) the application of simple conceptualizations of risk. Participants were 1,021 high-risk suicidal and/or self-injuring individuals recruited worldwide. Assessments occurred at baseline and 3, 14, and 28 days after baseline using a range of implicit and self-report measures. Retention was high across all time points (> 90%). Risk algorithms were derived and compared with univariate analyses at each follow-up. Results indicated that short-term prediction alone did not improve prediction for attempts, even using commonly cited “warning signs”; however, a small set of factors did provide fair-to-good short-term prediction of ideation. Machine learning produced considerable improvements for both outcomes across follow-ups. Results underscore the importance of complexity in the conceptualization of STBs.
Emerging evidence indicates that agitation is an ominous precursor to imminent death by suicide, yet measures of it are few, and to our knowledge, no self-report measure of agitation exists. To fill this gap, we have developed the Brief Agitation Measure (BAM), which is designed as a brief measure to assess agitation. In this article, we provide preliminary evidence from 2 studies examining the reliability and validity of the BAM in an undergraduate sample as well as a clinical sample. We close with a discussion of the limitations of the studies and implications of our findings.
Importance Suicide remains an ongoing concern in the US military. Statistical models have not been broadly disseminated for US Navy service members. Objective To externally validate and update a statistical suicide risk model initially developed in a civilian setting with an emphasis on primary care. Design, Setting, and Participants This retrospective cohort study used data collected from 2007 through 2017 among active-duty US Navy service members. The external civilian model was applied to every visit at Naval Medical Center Portsmouth (NMCP), its NMCP Naval Branch Health Clinics (NBHCs), and TRICARE Prime Clinics (TPCs) that fall within the NMCP area. The model was retrained and recalibrated using visits to NBHCs and TPCs and updated using Department of Defense (DoD)–specific billing codes and demographic characteristics, including expanded race and ethnicity categories. Domain and temporal analyses were performed with bootstrap validation. Data analysis was performed from September 2020 to December 2022. Exposure Visit to US NMCP. Main Outcomes and Measures Recorded suicidal behavior on the day of or within 30 days of a visit. Performance was assessed using area under the receiver operating curve (AUROC), area under the precision recall curve (AUPRC), Brier score, and Spiegelhalter z -test statistic. Results Of the 260 583 service members, 6529 (2.5%) had a recorded suicidal behavior, 206 412 (79.2%) were male; 104 835 (40.2%) were aged 20 to 24 years; and 9458 (3.6%) were Asian, 56 715 (21.8%) were Black or African American, and 158 277 (60.7%) were White. Applying the civilian-trained model resulted in an AUROC of 0.77 (95% CI, 0.74-0.79) and an AUPRC of 0.004 (95% CI, 0.003-0.005) at NBHCs with poor calibration (Spiegelhalter P < .001). Retraining the algorithm improved AUROC to 0.92 (95% CI, 0.91-0.93) and AUPRC to 0.66 (95% CI, 0.63-0.68). Number needed to screen in the top risk tiers was 366 for the external model and 200 for the retrained model; the lower number indicates better performance. Domain validation showed AUROC of 0.90 (95% CI, 0.90-0.91) and AUPRC of 0.01 (95% CI, 0.01-0.01), and temporal validation showed AUROC of 0.75 (95% CI, 0.72-0.78) and AUPRC of 0.003 (95% CI, 0.003-0.005). Conclusions and Relevance In this cohort study of active-duty Navy service members, a civilian suicide attempt risk model was externally validated. Retraining and updating with DoD-specific variables improved performance. Domain and temporal validation results were similar to external validation, suggesting that implementing an external model in US Navy primary care clinics may bypass the need for costly internal development and expedite the automation of suicide prevention in these clinics.
Self-injurious thoughts and behaviors (SITBs) are major public health concerns impacting a wide range of individuals and communities. Despite major efforts to develop and refine treatments to reduce SITBs, the efficacy of SITB interventions remains unclear. To provide a comprehensive summary of SITB treatment efficacy, we conducted a meta-analysis of published randomized controlled trials (RCTs) that have attempted to reduce SITBs. A total of 591 published articles from 1,125 unique RCTs with 3,458 effect sizes from the past 50 years were included. The random-effects meta-analysis yielded surprising findings: The overall intervention effects were small across all SITB outcomes; despite a near-exponential increase in the number of RCTs across five decades, intervention efficacy has not improved; all SITB interventions produced similarly small effects, and no intervention appeared significantly and consistently stronger than others; the overall small intervention effects were largely maintained at follow-up assessments; efficacy was similar across age groups, though effects were slightly weaker for child/adolescent populations and few studies focused on older adults; and major sample and study characteristics (e.g., control group type, treatment target, sample size, intervention length) did not consistently moderate treatment efficacy. This meta-analysis suggests that fundamental changes are needed to facilitate progress in SITB intervention efficacy. In particular, powerful interventions target the necessary causes of pathology, but little is known about SITB causes (vs. SITB correlates and risk factors). The field would accordingly benefit from the prioritization of research that aims to identify and target common necessary causes of SITBs. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
