Comparative effectiveness of remote digital gamified and group CBT skills training interventions for anxiety and depression among college students: Results of a three-arm randomised controlled trial.

Digital interventions can enhance access to healthcare in under-resourced settings. However, guided digital interventions may be costly for low- and middle-income countries, despite their effectiveness. In this randomised control trial, we evaluated the effectiveness of two digital interventions designed to address this issue: (1) a Cognitive Behavioral Therapy Skills Training (CST) intervention that increased scalability by using remote online group administration; and (2) the SuperBetter gamified self-guided CBT skills training app, which uses other participants rather than paid staff as guides. The study was implemented among anxious and/or depressed South African undergraduates (n = 371) randomised with equal allocation to Remote Group CST, SuperBetter, or a MoodFlow mood monitoring control. Symptoms were assessed with the Generalized Anxiety Disorder-7 (GAD-7) and the Patient Health Questionnaire-9 (PHQ-9). Intention-to-treat analysis found effect sizes at the high end of prior digital intervention trials, including significantly higher adjusted risk differences (ARD; primary outcome) in joint anxiety/depression remission at 3-months and 6-months for Remote Group CST (ARD = 23.3-18.9%, p = 0.001-0.035) and SuperBetter (ARD = 12.7-22.2%, p = 0.047-0.006) than MoodFlow and mean combined PHQ-9/GAD-7 scores (secondary outcome) significantly lower for Remote Group CST and SuperBetter than MoodFlow. These results illustrate how innovative delivery methods can increase the scalability of standard one-on-one guided digital interventions. PREREGISTRATION INTERNATIONAL STANDARD RANDOMISED CONTROLLED TRIAL NUMBER (ISRTCN) SUBMISSION #: 47,089,643.

Predicting Suicide Among US Veterans Using Natural Language Processing-enriched Social and Behavioral Determinants of Health.

Despite recognizing the critical association between social and behavioral determinants of health (SBDH) and suicide risk, SBDHs from unstructured electronic health record (EHR) notes for suicide predictive modeling remain underutilized. This study investigates the impact of SBDH, identified from both structured and unstructured data utilizing a natural language processing (NLP) system, on suicide prediction within 7, 30, 90, and 180 days of discharge. Using EHR data of 2,987,006 Veterans between October 1, 2009, and September 30, 2015, from the US Veterans Health Administration (VHA), we designed a case-control study that demonstrates that incorporating structured and NLP-extracted SBDH significantly enhances the performance of three architecturally distinct suicide predictive models - elastic-net logistic regression, random forest (RF), and multilayer perceptron. For example, RF achieved notable improvements in suicide prediction within 180 days of discharge, with an increase in the area under the receiver operating characteristic curve from 83.57-84.25% (95% CI = 0.63%-0.98%, p-val < 0.001) and the area under the precision recall curve from 57.38-59.87% (95% CI = 3.86%-4.82%, p-val < 0.001) after integrating NLP-extracted SBDH. These findings underscore the potential of NLP-extracted SBDH in enhancing suicide prediction across various prediction timeframes, offering valuable insights for healthcare practitioners and policymakers.

Twelve-month prevalence, persistence, severity, and treatment of mood and anxiety disorders in Qatar's national mental health study.

OBJECTIVES: To estimate 12-month prevalence, persistence, severity, and treatment of mental disorders and socio-demographic correlates in Qatar. METHODS: We conducted the first national population-based telephone survey of Arab adults between 2019 and 2022 using the Composite International Diagnostic Interview and estimated 12-month DSM-5 mood and anxiety disorders and their persistence (the proportion of lifetime cases who continue to meet 12-month criteria). RESULTS: The 12-month prevalence of any disorder was 21.1% (10.4% mild, 38.7% moderate, and 50.9% severe) and was associated with: younger age, female, previously married, and with persistence of any disorder. Persistence was 74.7% (64.0% mood and 75.6% anxiety) and was significantly associated with secondary education or lower. Minimally adequate treatment received among those with any 12-month mental disorder was 10.6% (74.6% in healthcare and 64.6% non-healthcare sectors). Severity and the number of disorders significantly associated with each other and with treatment received (χ2 = 7.24, p = 0.027) including adequate treatment within the mental health specialty sector (χ2 = 21.42, p < 0.001). CONCLUSIONS: Multimorbidity and sociodemographics were associated with 12-month mental disorder. Treatment adequacy in Qatar are comparable to high-income countries. Low treatment contact indicate need for population-wide mental health literacy programes in addition to more accessible and effective mental health services.

Lifetime prevalence, risk, and treatment of mood and anxiety disorders in Qatar's national mental health study.

OBJECTIVES: To estimate lifetime prevalence, risk, and treatment for mental disorders and their correlates in Qatar's general population for the first time. METHODS: We conducted a national phone survey of 5,195 Qatari and Arab residents in Qatar (2019-2022) using the Composite International Diagnostic Interview Version 3.3 and estimated lifetime mood and anxiety defined diagnoses. Survival-based discrete time models, lifetime morbid risk, and treatment projections were estimated. RESULTS: Lifetime prevalence of any disorder was 28.0% and was associated with younger cohorts, females, and migrants, but lower formal education. Treatment contact in the year of disorder onset were 13.5%. The median delay in receiving treatment was 5 years (IQR = 2-13). Lifetime treatment among those with a lifetime disorder were 59.9% for non-healthcare and 63.5% for healthcare; it was 68.1% for any anxiety and 80.1% for any mood disorder after 50 years of onset. Younger cohorts and later age of onset were significantly predictors of treatment. CONCLUSIONS: Lifetime prevalence of mental disorders in Qatar is comparable to other countries. Treatment is significantly delayed and delivered largely in non-healthcare sectors thus the need for increased literacy of mental illness to reduce stigma and improve earlier help-seeking in healthcare settings.

Clinical reappraisal of the composite international diagnostic interview version 3.3 in Qatar's National Mental Health Study.

OBJECTIVES: Lifetime DSM-5 diagnoses generated by the lay-administered Composite International Diagnostic Interview for DSM-5 (CIDI) in the World Mental Health Qatar (WMHQ) study were compared to diagnoses based on blinded clinician-administered reappraisal interviews. METHODS: Telephone follow-up interviews used the non-patient edition of the Structured Clinician Interview for DSM-5 (SCID) oversampling respondents who screened positive for five diagnoses in the CIDI: major depressive episode, mania/hypomania, panic disorder, generalized anxiety disorder, and obsessive-compulsive disorder. Concordance was also examined for a diagnoses of post-traumatic stress disorder based on a short-form versus full version of the PTSD Checklist for DSM-5 (PCL-5). RESULTS: Initial CIDI prevalence estimates differed significantly from the SCID for most diagnoses ( χ 1 2 ${\chi }_{1}^{2}$  = 6.6-31.4, p = 0.010 < 0.001), but recalibration reduced most of these differences and led to consistent increases in individual-level concordance (AU-ROC) from 0.53-0.76 to 0.67-0.81. Recalibration of the short-form PCL-5 removed an initially significant difference in PTSD prevalence with the full PCL-5 (from χ 1 2 ${\chi }_{1}^{2}$  = 610.5, p < 0.001 to χ 1 2 ${\chi }_{1}^{2}$  = 2.5, p = 0.110) while also increasing AU-ROC from 0.76 to 0.81. CONCLUSIONS: Recalibration resulted in valid diagnoses of common mental disorders in the Qatar National Mental Health Survey, but with inflated prevalence estimates for some disorders that need to be considered when interpreting results.

Can the potential benefit of individualizing treatment be assessed using trial summary statistics alone?

Individualizing treatment assignment can improve outcomes for diseases with patient-to-patient variability in comparative treatment effects. When a clinical trial demonstrates that some patients improve on treatment while others do not, it is tempting to assume that treatment effect heterogeneity exists. However, if outcome variability is mainly driven by factors other than variability in the treatment effect, investigating the extent to which covariate data can predict differential treatment response is a potential waste of resources. Motivated by recent meta-analyses assessing the potential of individualizing treatment for major depressive disorder using only summary statistics, we provide a method that uses summary statistics widely available in published clinical trial results to bound the benefit of optimally assigning treatment to each patient. We also offer alternate bounds for settings in which trial results are stratified by another covariate. Our upper bounds can be especially informative when they are small, as there is then little benefit to collecting additional covariate data. We demonstrate our approach using summary statistics from a depression treatment trial. Our methods are implemented in the rct2otrbounds R package, which is available at https://github.com/ngalanter/rct2otrbounds.

Sex differences in response inhibition-related neural predictors of PTSD in recent trauma-exposed civilians.

BACKGROUND: Females are more likely to develop posttraumatic stress disorder (PTSD) than males. Impaired inhibition has been identified as mechanism for PTSD development, but studies on the potential sex differences of this neurobiological mechanism and how it relates to PTSD severity and progression are sparse. Here we examined sex differences in neural activation during response inhibition and PTSD following recent trauma. METHODS: Participants (N= 205, 138 female sex assigned at birth) were recruited from emergency departments within 72 hours of a traumatic event. PTSD symptoms were assessed 2-weeks and 6-months post-trauma. A Go/NoGo task was performed 2-weeks post-trauma in a 3T MRI scanner to measure neural activity during response inhibition in the ventromedial prefrontal cortex (vmPFC), right inferior frontal gyrus (rIFG), and the bilateral hippocampus. General Linear models were used to examine the interaction effect of sex on the relationship between our regions of interest (ROIs) and the whole brain, and PTSD symptoms at 6-months, and symptom progression between 2-weeks and 6-months. RESULTS: Lower response-inhibition-related vmPFC activation 2-weeks post-trauma predicted more PTSD symptoms at 6-months in females but not in males, while greater response-inhibition-related rIFG activation predicted lower PTSD symptom progression in males but not females. Whole brain interaction effects were observed in the medial temporal gyrus and left precentral gyrus. CONCLUSIONS: There are sex differences in the relationship between inhibition-related brain activation and PTSD symptom severity and progression. These findings suggest that sex differences should be assessed in future PTSD studies and reveal potential targets for sex-specific interventions.

The epidemiology of obsessive-compulsive disorder in the Kingdom of Saudi Arabia: Data from the Saudi National Mental Health Survey.

AIMS: There is ongoing debate about the extent to which the epidemiology of OCD is similar across the world, given the lack of nationally representative data from key regions like the Middle East and North Africa. Using the nationally representative dataset from the Saudi National Mental Health Survey (SNMHS), we aimed to delineate the epidemiological profile of OCD in the Saudi population. METHODS: A subsample of 1981 participants from the SNMHS was assessed. Prevalence estimates and correlates of OCD were determined using logistic regressions and cross tabulations. RESULTS: The lifetime, 12-month, and 30-day prevalence estimates for OCD were 4.2%, 1.8%, and 1.6%, respectively, with hoarding being the most common symptom dimension. The mean age-of-onset of OCD was 16.8 years. In over two-thirds of respondents with lifetime (72.2%) or 12-month (71.2%), OCD was accompanied by comorbid mental disorder, particularly impulse control, anxiety, and mood disorders. Among individuals with 12-month OCD, 77.5% reported severe impairment, and only 9.2% received treatment. CONCLUSIONS: In Saudi Arabia, OCD is a prevalent and persistent condition, characterized by early onset, high odds of mental comorbidity, and significant associated impairment. These findings emphasize the universality of OCD epidemiology and the need for improved diagnosis and treatment globally.

Effectiveness of the Minder Mobile Mental Health and Substance Use Intervention for University Students: Randomized Controlled Trial.

BACKGROUND: University attendance represents a transition period for students that often coincides with the emergence of mental health and substance use challenges. Digital interventions have been identified as a promising means of supporting students due to their scalability, adaptability, and acceptability. Minder is a mental health and substance use mobile app that was codeveloped with university students. OBJECTIVE: This study aims to examine the effectiveness of the Minder mobile app in improving mental health and substance use outcomes in a general population of university students. METHODS: A 2-arm, parallel-assignment, single-blinded, 30-day randomized controlled trial was used to evaluate Minder using intention-to-treat analysis. In total, 1489 participants were recruited and randomly assigned to the intervention (n=743, 49.9%) or waitlist control (n=746, 50.1%) condition. The Minder app delivers evidence-based content through an automated chatbot and connects participants with services and university social groups. Participants are also assigned a trained peer coach to support them. The primary outcomes were measured through in-app self-assessments and included changes in general anxiety symptomology, depressive symptomology, and alcohol consumption risk measured using the 7-item General Anxiety Disorder scale, 9-item Patient Health Questionnaire, and US Alcohol Use Disorders Identification Test-Consumption Scale, respectively, from baseline to 30-day follow-up. Secondary outcomes included measures related to changes in the frequency of substance use (cannabis, alcohol, opioids, and nonmedical stimulants) and mental well-being. Generalized linear mixed-effects models were used to examine each outcome. RESULTS: In total, 79.3% (589/743) of participants in the intervention group and 83% (619/746) of participants in the control group completed the follow-up survey. The intervention group had significantly greater average reductions in anxiety symptoms measured using the 7-item General Anxiety Disorder scale (adjusted group mean difference=-0.85, 95% CI -1.27 to -0.42; P<.001; Cohen d=-0.17) and depressive symptoms measured using the 9-item Patient Health Questionnaire (adjusted group mean difference=-0.63, 95% CI -1.08 to -0.17; P=.007; Cohen d=-0.11). A reduction in the US Alcohol Use Disorders Identification Test-Consumption Scale score among intervention participants was also observed, but it was not significant (P=.23). Statistically significant differences in favor of the intervention group were found for mental well-being and reductions in the frequency of cannabis use and typical number of drinks consumed. A total of 77.1% (573/743) of participants in the intervention group accessed at least 1 app component during the study period. CONCLUSIONS: In a general population sample of university students, the Minder app was effective in reducing symptoms of anxiety and depression, with provisional support for increasing mental well-being and reducing the frequency of cannabis and alcohol use. These findings highlight the potential ability of e-tools focused on prevention and early intervention to be integrated into existing university systems to support students' needs. TRIAL REGISTRATION: ClinicalTrials.gov NCT05606601; https://clinicaltrials.gov/ct2/show/NCT05606601. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/49364.

Factors associated with satisfaction and perceived helpfulness of mental healthcare: a World Mental Health Surveys report.

BACKGROUND: Mental health service providers are increasingly interested in patient perspectives. We examined rates and predictors of patient-reported satisfaction and perceived helpfulness in a cross-national general population survey of adults with 12-month DSM-IV disorders who saw a provider for help with their mental health. METHODS: Data were obtained from epidemiological surveys in the World Mental Health Survey Initiative. Respondents were asked about satisfaction with treatments received from up to 11 different types of providers (very satisfied, satisfied, neither satisfied nor dissatisfied, somewhat dissatisfied, very dissatisfied) and helpfulness of the provider (a lot, some, a little, not at all). We modelled predictors of satisfaction and helpfulness using a dataset of patient-provider observations (n = 5,248). RESULTS: Most treatment was provided by general medical providers (37.4%), psychiatrists (18.4%) and psychologists (12.7%). Most patients were satisfied or very satisfied (65.9-87.5%, across provider) and helped a lot or some (64.4-90.3%). Spiritual advisors and healers were most often rated satisfactory and helpful. Social workers in human services settings were rated lowest on both dimensions. Patients also reported comparatively low satisfaction with general medical doctors and psychiatrists/psychologists and found general medical doctors less helpful than other providers. Men and students reported lower levels of satisfaction than women and nonstudents. Respondents with high education reported higher satisfaction and helpfulness than those with lower education. Type of mental disorder was unrelated to satisfaction but in some cases (depression, bipolar spectrum disorder, social phobia) was associated with low perceived helpfulness. Insurance was unrelated to either satisfaction or perceived helpfulness but in some cases was associated with elevated perceived helpfulness for a given level of satisfaction. CONCLUSIONS: Satisfaction with and perceived helpfulness of treatment varied as a function of type of provider, service setting, mental status, and socio-demographic variables. Invariably, caution is needed in combining data from multiple countries where there are cultural and service delivery variations. Even so, our findings underscore the utility of patient perspectives in treatment evaluation and may also be relevant in efforts to match patients to treatments.

Developing an individualized treatment rule for Veterans with major depressive disorder using electronic health records.

Efforts to develop an individualized treatment rule (ITR) to optimize major depressive disorder (MDD) treatment with antidepressant medication (ADM), psychotherapy, or combined ADM-psychotherapy have been hampered by small samples, small predictor sets, and suboptimal analysis methods. Analyses of large administrative databases designed to approximate experiments followed iteratively by pragmatic trials hold promise for resolving these problems. The current report presents a proof-of-concept study using electronic health records (EHR) of n = 43,470 outpatients beginning MDD treatment in Veterans Health Administration Primary Care Mental Health Integration (PC-MHI) clinics, which offer access not only to ADMs but also psychotherapy and combined ADM-psychotherapy. EHR and geospatial databases were used to generate an extensive baseline predictor set (5,865 variables). The outcome was a composite measure of at least one serious negative event (suicide attempt, psychiatric emergency department visit, psychiatric hospitalization, suicide death) over the next 12 months. Best-practices methods were used to adjust for nonrandom treatment assignment and to estimate a preliminary ITR in a 70% training sample and to evaluate the ITR in the 30% test sample. Statistically significant aggregate variation was found in overall probability of the outcome related to baseline predictors (AU-ROC = 0.68, S.E. = 0.01), with test sample outcome prevalence of 32.6% among the 5% of patients having highest predicted risk compared to 7.1% in the remainder of the test sample. The ITR found that psychotherapy-only was the optimal treatment for 56.0% of patients (roughly 20% lower risk of the outcome than if receiving one of the other treatments) and that treatment type was unrelated to outcome risk among other patients. Change in aggregate treatment costs of implementing this ITR would be negligible, as 16.1% fewer patients would be prescribed ADMs and 2.9% more would receive psychotherapy. A pragmatic trial would be needed to confirm the accuracy of the ITR.

Health service and psychotropic medication use for mental health conditions among healthcare workers active during the Spain Covid-19 Pandemic - A prospective cohort study using web-based surveys.

Little is known about healthcare workers' (HCW) use of healthcare services for mental disorders. This study presents data from a 16-month prospective cohort study of Spanish HCW (n = 4,809), recruited shortly after the COVID-19 pandemic onset, and assessed at four timepoints using web-based surveys. Use of health services among HCW with mental health conditions (i.e., those having a positive screen for mental disorders and/or suicidal thoughts and behaviours [STB]) was initially low (i.e., 18.2 %) but increased to 29.6 % at 16-month follow-up. Service use was positively associated with pre-pandemic mental health treatment (OR=1.99), a positive screen for major depressive disorder (OR=1.50), panic attacks (OR=1.74), suicidal thoughts and behaviours (OR=1.22), and experiencing severe role impairment (OR=1.33), and negatively associated with being female (OR = 0.69) and a higher daily number of work hours (OR=0.95). Around 30 % of HCW with mental health conditions used anxiolytics (benzodiazepines), especially medical doctors. Four out of ten HCW (39.0 %) with mental health conditions indicated a need for (additional) help, with most important barriers for service use being too ashamed, long waiting lists, and professional treatment not being available. Our findings delineate a clear mental health treatment gap among Spanish HCW.

Suicidal ideation risk among LGB Spanish university students: The role of childhood and adolescence adversities and mental disorders.

BACKGROUND: Childhood/adolescence adversities and mental disorders are higher among LGB youths. AIMS: To evaluate the role of childhood maltreatment, bullying, and mental disorders on the association between sexual orientation and suicidal ideation (SI); and the role of mental disorders on the association between sexual orientation discrimination and SI. METHODS: Baseline and 12-month follow-up online surveys of Spanish first-year university students (18-24-year-olds). Multivariable logistic regression models assessed the effects of childhood/adolescence adversities and mental disorders in the relationship between sexual orientation, discrimination and SI. RESULTS: A total of 1224 students were included (16.4 % LGBs). Risk factors of lifetime SI were sexual orientation (OR 2.4), any bullying (OR 2.4), any childhood maltreatment (OR 4.0), and any mental disorders (OR 3.8). Final model Area Under the Curve (AUC) 0.78. Among homosexual and bisexual students, discrimination showed increased risk of 12-month SI (OR 2.2), but this effect was no longer statistically significant when any 12-month mental disorder was added (OR 7.8). Final model AUC 0.72. LIMITATIONS: Sample of interest was relatively small. But it was similar to comparable studies and statistical adjustments have been performed. Assessment of mental disorders and SI was not based on clinical assessment. However, validated scales showing good diagnostic agreement with clinical judgement were used. CONCLUSIONS: Childhood/adolescence adversities and mental disorders interact in the association between sexual orientation and SI. Mental disorders may mediate the association between sexual orientation discrimination and SI. Further research using larger samples and causal modelling approach assessing the mediators of SI risk among LGBs is needed.

Polygenic risk for suicide attempt is associated with lifetime suicide attempt in US soldiers independent of parental risk.

BACKGROUND: Suicide is a leading cause of death worldwide. Whereas some studies have suggested that a direct measure of common genetic liability for suicide attempts (SA), captured by a polygenic risk score for SA (SA-PRS), explains risk independent of parental history, further confirmation would be useful. Even more unsettled is the extent to which SA-PRS is associated with lifetime non-suicidal self-injury (NSSI). METHODS: We used summary statistics from the largest available GWAS study of SA to generate SA-PRS for two non-overlapping cohorts of soldiers of European ancestry. These were tested in multivariable models that included parental major depressive disorder (MDD) and parental SA. RESULTS: In the first cohort, 417 (6.3 %) of 6573 soldiers reported lifetime SA and 1195 (18.2 %) reported lifetime NSSI. In a multivariable model that included parental history of MDD and parental history of SA, SA-PRS remained significantly associated with lifetime SA [aOR = 1.26, 95%CI:1.13-1.39, p < 0.001] per standardized unit SA-PRS]. In the second cohort, 204 (4.2 %) of 4900 soldiers reported lifetime SA, and 299 (6.1 %) reported lifetime NSSI. In a multivariable model that included parental history of MDD and parental history of SA, SA-PRS remained significantly associated with lifetime SA [aOR = 1.20, 95%CI:1.04-1.38, p = 0.014]. A combined analysis of both cohorts yielded similar results. In neither cohort or in the combined analysis was SA-PRS significantly associated with NSSI. CONCLUSIONS: PRS for SA conveys information about likelihood of lifetime SA (but not NSSI, demonstrating specificity), independent of self-reported parental history of MDD and parental history of SA. LIMITATIONS: At present, the magnitude of effects is small and would not be immediately useful for clinical decision-making or risk-stratified prevention initiatives, but this may be expected to improve with further iterations. Also critical will be the extension of these findings to more diverse populations.

Toward personalized care for insomnia in the US Army: a machine learning model to predict response to cognitive behavioral therapy for insomnia.

STUDY OBJECTIVES: The standard of care for military personnel with insomnia is cognitive behavioral therapy for insomnia (CBT-I). However, only a minority seeking insomnia treatment receive CBT-I, and little reliable guidance exists to identify those most likely to respond. As a step toward personalized care, we present results of a machine learning (ML) model to predict CBT-I response. METHODS: Administrative data were examined for n=1,449 nondeployed US Army soldiers treated for insomnia with CBT-I who had moderate-severe baseline Insomnia Severity Index (ISI) scores and completed one or more follow-up ISIs 6-12 weeks after baseline. An ensemble ML model was developed in a 70% training sample to predict clinically significant ISI improvement (reduction of at least two standard deviations on the baseline ISI distribution). Predictors included a wide range of military administrative and baseline clinical variables. Model accuracy was evaluated in the remaining 30% test sample. RESULTS: 19.8% of patients had clinically significant ISI improvement. Model AU-ROC (SE) was 0.60 (0.03). The 20% of test sample patients with highest probabilities of improvement were twice as likely to have clinically significant improvement as the remaining 80% (36.5% versus 15.7%; χ21=9.2, p=.002). Nearly 85% of prediction accuracy was due to ten variables, the most important of which were baseline insomnia severity and baseline suicidal ideation. CONCLUSIONS: Pending replication, the model could be used as part of a patient-centered decision-making process for insomnia treatment. Parallel models will be needed for alternative treatments before such a system is of optimal value.

Predicting Homelessness Among Transitioning U.S. Army Soldiers.

INTRODUCTION: This study develops a practical method to triage Army transitioning service members (TSMs) at highest risk of homelessness to target a preventive intervention. METHODS: The sample included 4,790 soldiers from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS) who participated in 1 of 3 Army STARRS 2011-2014 baseline surveys followed by the third wave of the STARRS-LS online panel surveys (2020-2022). Two machine learning models were trained: a Stage-1 model that used administrative predictors and geospatial data available for all TSMs at discharge to identify high-risk TSMs for initial outreach; and a Stage-2 model estimated in the high-risk subsample that used self-reported survey data to help determine highest risk based on additional information collected from high-risk TSMs once they are contacted. The outcome in both models was homelessness within 12 months after leaving active service. RESULTS: Twelve-month prevalence of post-transition homelessness was 5.0% (SE=0.5). The Stage-1 model identified 30% of high-risk TSMs who accounted for 52% of homelessness. The Stage-2 model identified 10% of all TSMs (i.e., 33% of high-risk TSMs) who accounted for 35% of all homelessness (i.e., 63% of the homeless among high-risk TSMs). CONCLUSIONS: Machine learning can help target outreach and assessment of TSMs for homeless prevention interventions.

Multi-ancestry genome-wide association study of major depression aids locus discovery, fine mapping, gene prioritization and causal inference.

Most genome-wide association studies (GWAS) of major depression (MD) have been conducted in samples of European ancestry. Here we report a multi-ancestry GWAS of MD, adding data from 21 cohorts with 88,316 MD cases and 902,757 controls to previously reported data. This analysis used a range of measures to define MD and included samples of African (36% of effective sample size), East Asian (26%) and South Asian (6%) ancestry and Hispanic/Latin American participants (32%). The multi-ancestry GWAS identified 53 significantly associated novel loci. For loci from GWAS in European ancestry samples, fewer than expected were transferable to other ancestry groups. Fine mapping benefited from additional sample diversity. A transcriptome-wide association study identified 205 significantly associated novel genes. These findings suggest that, for MD, increasing ancestral and global diversity in genetic studies may be particularly important to ensure discovery of core genes and inform about transferability of findings.

Sociodemographic Correlates of Mental Health Treatment Seeking Among College Students: A Systematic Review and Meta-Analysis.

OBJECTIVE: College students have high rates of mental health problems and low rates of treatment. Although sociodemographic disparities in student mental health treatment seeking have been reported, findings have not been synthesized and quantified. The extent to which differences in perceived need for treatment contribute to overall disparities remains unclear. METHODS: A systematic search of PubMed, PsycInfo, and Embase was conducted. Studies published between 2007 and 2022 were included if they reported treatment rates among college students with mental health problems, stratified by sex, gender, race-ethnicity, sexual orientation, student type, student year, or student status. Random-effects models were used to calculate pooled prevalence ratios (PRs) of having a perceived need for treatment and of receiving treatment for each sociodemographic subgroup. RESULTS: Twenty-one studies qualified for inclusion. Among students experiencing mental health problems, consistent and significant sociodemographic differences were identified in perceived need for treatment and treatment receipt. Students from racial-ethnic minority groups (in particular, Asian students [PR=0.49]) and international students (PR=0.63) reported lower rates of treatment receipt than White students and domestic students, respectively. Students identifying as female (sex) or as women (gender) (combined PR=1.33) reported higher rates of treatment receipt than students identifying as male or as men. Differences in perceived need appeared to contribute to some disparities; in particular, students identifying as male or as men reported considerably lower rates of perceived need than students identifying as female or as women. CONCLUSIONS: Findings highlight the need for policy makers to address barriers throughout the treatment-seeking pathway and to tailor efforts to student subgroups to reduce treatment disparities.

Estimated Average Treatment Effect of Psychiatric Hospitalization in Patients With Suicidal Behaviors: A Precision Treatment Analysis.

Importance: Psychiatric hospitalization is the standard of care for patients presenting to an emergency department (ED) or urgent care (UC) with high suicide risk. However, the effect of hospitalization in reducing subsequent suicidal behaviors is poorly understood and likely heterogeneous. Objectives: To estimate the association of psychiatric hospitalization with subsequent suicidal behaviors using observational data and develop a preliminary predictive analytics individualized treatment rule accounting for heterogeneity in this association across patients. Design, Setting, and Participants: A machine learning analysis of retrospective data was conducted. All veterans presenting with suicidal ideation (SI) or suicide attempt (SA) from January 1, 2010, to December 31, 2015, were included. Data were analyzed from September 1, 2022, to March 10, 2023. Subgroups were defined by primary psychiatric diagnosis (nonaffective psychosis, bipolar disorder, major depressive disorder, and other) and suicidality (SI only, SA in past 2-7 days, and SA in past day). Models were trained in 70.0% of the training samples and tested in the remaining 30.0%. Exposures: Psychiatric hospitalization vs nonhospitalization. Main Outcomes and Measures: Fatal and nonfatal SAs within 12 months of ED/UC visits were identified in administrative records and the National Death Index. Baseline covariates were drawn from electronic health records and geospatial databases. Results: Of 196 610 visits (90.3% men; median [IQR] age, 53 [41-59] years), 71.5% resulted in hospitalization. The 12-month SA risk was 11.9% with hospitalization and 12.0% with nonhospitalization (difference, -0.1%; 95% CI, -0.4% to 0.2%). In patients with SI only or SA in the past 2 to 7 days, most hospitalization was not associated with subsequent SAs. For patients with SA in the past day, hospitalization was associated with risk reductions ranging from -6.9% to -9.6% across diagnoses. Accounting for heterogeneity, hospitalization was associated with reduced risk of subsequent SAs in 28.1% of the patients and increased risk in 24.0%. An individualized treatment rule based on these associations may reduce SAs by 16.0% and hospitalizations by 13.0% compared with current rates. Conclusions and Relevance: The findings of this study suggest that psychiatric hospitalization is associated with reduced average SA risk in the immediate aftermath of an SA but not after other recent SAs or SI only. Substantial heterogeneity exists in these associations across patients. An individualized treatment rule accounting for this heterogeneity could both reduce SAs and avert hospitalizations.