Recent findings suggest that brief dialectical behavior therapy (DBT) for borderline personality disorder is effective for reducing self-harm, but it remains unknown which patients are likely to improve in brief v. 12 months of DBT. Research is needed to identify patient characteristics that moderate outcomes. Here, we characterized changes in cognition across brief DBT (DBT-6) v. a standard 12-month course (DBT-12) and examined whether cognition predicted self-harm outcomes in each arm.

In this secondary analysis of 240 participants in the FASTER study (NCT02387736), cognitive measures were administered at pre-treatment, after 6 months, and at 12 months. Self-harm was assessed from pre-treatment to 2-year follow-up. Multilevel models characterized changes in cognition across treatment. Generalized estimating equations examined whether pre-treatment cognitive performance predicted self-harm outcomes in each arm.

Cognitive performance improved in both arms after 6 months of treatment, with no between-arm differences at 12-months. Pre-treatment inhibitory control was associated with different self-harm outcomes in DBT-6 v. DBT-12. For participants with average inhibitory control, self-harm outcomes were significantly better when assigned to DBT-12, relative to DBT-6, at 9–18 months after initiating treatment. In contrast, participants with poor inhibitory control showed better self-harm outcomes when assigned to brief DBT-6 v. DBT-12, at 12–24 months after initiating treatment.

This work represents an initial step toward an improved understanding of patient profiles that are best suited to briefer v. standard 12 months of DBT, but observed effects should be replicated in a waitlist-controlled study to confirm that they were treatment-specific.

The COVID-19 pandemic disrupted many areas of life, including culturally accepted practices at end-of-life care, funeral rites, and access to social, community, and professional support. This survey investigated the mental health outcomes of Australians bereaved during this time to determine how these factors might have impacted bereavement outcomes.

An online survey indexing pandemic and bereavement experiences, levels of grief, depression, anxiety, and health, work, and social impairment. Latent class analysis (LCA) was used to identify groups of individuals who shared similar symptom patterns. Multinomial regressions identified pandemic-related, loss-related, and sociodemographic correlates of class membership.

1911 Australian adults completed the survey. The LCA identified four classes: low symptoms (46.8%), grief (17.3%), depression/anxiety (17.7%), and grief/depression/anxiety (18.2%). The latter group reported the highest levels of health, work, and social impairment. The death of a child or partner and an inability to care for the deceased due to COVID-19 public health measures were correlated with grief symptoms (with or without depression and anxiety). Preparedness for the person's death and levels of pandemic-related loneliness and social isolation differentiated all four classes. Unemployment was associated with depression/anxiety (with or without grief).

COVID-19 had profound impacts for the way we lived and died, with effects that are likely to ricochet through society into the foreseeable future. These lessons learned must inform policymakers and healthcare professionals to improve bereavement care and ensure preparedness during and following future predicted pandemics to prevent negative impacts.

Obsessive–compulsive disorder (OCD) is thought to arise from dysconnectivity among interlinked brain regions resulting in a wide spectrum of clinical manifestations. Cortical gyrification, a key morphological feature of human cerebral cortex, has been considered associated with developmental connectivity in early life. Monitoring cortical gyrification alterations may provide new insights into the developmental pathogenesis of OCD.

Sixty-two medication-naive patients with OCD and 59 healthy controls (HCs) were included in this study. Local gyrification index (LGI) was extracted from T1-weighted MRI data to identify the gyrification changes in OCD. Total distortion (splay, bend, or twist of fibers) was calculated using diffusion-weighted MRI data to examine the changes in white matter microstructure in patients with OCD.

Compared with HCs, patients with OCD showed significantly increased LGI in bilateral medial frontal gyrus and the right precuneus, where the mean LGI was positively correlated with anxiety score. Patients with OCD also showed significantly decreased total distortion in the body, genu, and splenium of the corpus callosum (CC), where the average distortion was negatively correlated with anxiety scores. Intriguingly, the mean LGI of the affected cortical regions was significantly correlated with the mean distortion of the affected white matter tracts in patients with OCD.

We demonstrated associations among increased LGI, aberrant white matter geometry, and higher anxiety in patients with OCD. Our findings indicate that developmental dysconnectivity-driven alterations in cortical folding are one of the neural substrates underlying the clinical manifestations of OCD.

Remitted psychotic depression (MDDPsy) has heterogeneity of outcome. The study's aims were to identify subgroups of persons with remitted MDDPsy with distinct trajectories of depression severity during continuation treatment and to detect predictors of membership to the worsening trajectory.

One hundred and twenty-six persons aged 18–85 years participated in a 36-week randomized placebo-controlled trial (RCT) that examined the clinical effects of continuing olanzapine once an episode of MDDPsy had remitted with sertraline plus olanzapine. Latent class mixed modeling was used to identify subgroups of participants with distinct trajectories of depression severity during the RCT. Machine learning was used to predict membership to the trajectories based on participant pre-trajectory characteristics.

Seventy-one (56.3%) participants belonged to a subgroup with a stable trajectory of depression scores and 55 (43.7%) belonged to a subgroup with a worsening trajectory. A random forest model with high prediction accuracy (AUC of 0.812) found that the strongest predictors of membership to the worsening subgroup were residual depression symptoms at onset of remission, followed by anxiety score at RCT baseline and age of onset of the first lifetime depressive episode. In a logistic regression model that examined depression score at onset of remission as the only predictor variable, the AUC (0.778) was close to that of the machine learning model.

Residual depression at onset of remission has high accuracy in predicting membership to worsening outcome of remitted MDDPsy. Research is needed to determine how best to optimize the outcome of psychotic MDDPsy with residual symptoms.

Electroconvulsive therapy (ECT) is effective for treatment-resistant depression and leads to short-term structural brain changes and decreases in the inflammatory response. However, little is known about how brain structure and inflammation relate to the heterogeneity of treatment response in the months following an index ECT course.

A naturalistic six-month study following an index ECT course included 20 subjects with treatment-resistant depression. Upon conclusion of the index ECT course and again after six months, structural magnetic resonance imaging scans and peripheral inflammation measures [interleukin-6 (IL-6), IL-8, tumor necrosis factor (TNF-α), and C-reactive protein] were obtained. Voxel-based morphometry processed with the CAT-12 Toolbox was used to estimate changes in gray matter volume.

Between the end of the index ECT course and the end of follow-up, we found four clusters of significant decreases in gray matter volume (p < 0.01, FWE) and no regions of increased volume. Decreased HAM-D scores were significantly related only to reduced IL-8 level. Decreased volume in one cluster, which included the right insula and Brodmann's Area 22, was related to increased HAM-D scores over six months. IL-8 levels did not mediate or moderate the relationship between volumetric change and depression.

Six months after an index ECT course, multiple regions of decreased gray matter volume were observed in a naturalistic setting. The independent relations between brain volume and inflammation to depressive symptoms suggest novel explanations of the heterogeneity of longer-term ECT treatment response.

Psychiatric disorders and homelessness are related, but temporal associations are unclear. We aimed to explore the overlap between hospital-based psychiatric disorders and sheltered homelessness.

This population-based cohort study was conducted using the Danish registers e.g., the Danish Homeless Register and the Danish National Patient Register. The study cohort included all individuals aged 15 years or older, living in Denmark at least one day during 2002–2021 (born 1984–2006). First psychiatric diagnosis was used to define psychiatric disorder and first homeless shelter contact to define homelessness. Adjusted incidence rate ratios (IRRs) and cumulative incidences were estimated.

Among 1 530 325 individuals accounting for 16 787 562 person-years at risk aged 15–38 years, 11 433 (0.8%) had at least one homeless shelter contact. Among 1 406 410 individuals accounting for 14 131 060 person-years at risk, 210 730 had at least one psychiatric disorder. People with any psychiatric disorder had increased risk of sheltered homelessness relative to individuals with no psychiatric disorder [IRR 9.2, 95% confidence interval (CI) 8.8–9.6]. Ten years after first psychiatric disorder, 3.0% (95% CI 2.9–3.1) had at least one homeless shelter contact. Individuals experiencing homelessness had increased risk of any psychiatric disorder compared to individuals with no homeless shelter contact (IRR 7.0, 95% CI 6.7–7.4). Ten years after first homeless shelter contact, 47.1% (45.3–48.0) had received a hospital-based psychiatric diagnosis.

Strong bidirectional associations between psychiatric disorders and homelessness were identified. Health and social care professionals should be aware of and address these high risks of accumulated psychiatric and social problems.

This paper investigates whether age of onset of depression, duration of the last episode, number of episodes, and residual symptoms of depression and anxiety are associated with depression relapse in primary care patients who have been on long–term maintenance antidepressant treatment and no longer meet ICD10 criteria for depression.

An observational cohort using data from ANTLER (N = 478), a double-blind placebo-controlled trial. The primary outcome was time to relapse using the retrospective CIS-R. Participants were followed for 12 months.

Primary outcome was available for 468 participants. Time to relapse in those with more than five previous episodes of depression was shorter, hazard ratio (HR) 1.84 (95% confidence interval [CI] 1.23–2.75) compared to people with two episodes; HR 1.57 (95% CI 1.01–2.43) after adjustment. The residual symptoms of depression at baseline were also associated with increased relapse: HR 1.05 (95% CI 1.01–1.09) and HR 1.06 (95% CI 1.01–1.12) in the adjusted model. There was evidence of reduced rate of relapse in older age of onset group: HR 0.86 (95% CI 0.78–0.95); HR attenuated after adjustment HR 0.91 (95% CI 0.81–1.02). There was no evidence of an association between duration of the current episode and residual anxiety symptoms with relapse.

The number of previous episodes and residual symptoms of depression were associated with increased likelihood of relapse. These factors could inform joint decision making when patients are considering tapering off maintenance antidepressant treatment or considering other treatments to prevent relapse.

With efforts increasing worldwide to understand and treat paranoia, there is a pressing need for cross-culturally valid assessments of paranoid beliefs. The recently developed Revised Green et al., Paranoid Thoughts Scale (R-GPTS) constitutes an easy to administer self-report assessment of mild ideas of reference and more severe persecutory thoughts. Moreover, it comes with clinical cut-offs for increased usability in research and clinical practice. With multiple translations of the R-GPTS already available and in use, a formal test of its measurement invariance is now needed.

Using data from a multinational cross-sectional online survey in the UK, USA, Australia, Germany, and Hong Kong (N = 2510), we performed confirmatory factory analyses on the R-GPTS and tested for measurement invariance across sites.

We found sufficient fit for the two-factor structure (ideas of reference, persecutory thoughts) of the R-GPTS across cultures. Measurement invariance was found for the persecutory thoughts subscale, indicating that it does measure the same construct across the tested samples in the same way. For ideas of reference, we found no scalar invariance, which was traced back to (mostly higher) item intercepts in the Hong Kong sample.

We found sufficient invariance for the persecutory thoughts scale, which is of substantial practical importance, as it is used for the screening of clinical paranoia. A direct comparison of the ideas of reference sum-scores between cultures, however, may lead to an over-estimation of these milder forms of paranoia in some (non-western) cultures.

Everyday affective fluctuations are more extreme and more frequent in adolescence compared to any other time in development. Successful regulation of these affective experiences is important for good mental health and has been proposed to depend on affective control. The present study examined whether improving affective control through a computerised affective control training app (AffeCT) would benefit adolescent mental health.

One-hundred and ninety-nine participants (11–19 years) were assigned to complete 2 weeks of AffeCT or placebo training on an app. Affective control (i.e. affective inhibition, affective updating and affective shifting), mental health and emotion regulation were assessed at pre- and post-training. Mental health and emotion regulation were assessed again one month and one year later.

Compared with the placebo group, the AffeCT group showed significantly greater improvements in affective control on the trained measure. AffeCT did not, relative to placebo, lead to better performance on untrained measures of affective control. Pre- to post-training change in affective control covaried with pre- to post-training change in mental health problems in the AffeCT but not the placebo group. These mental health benefits of AffeCT were only observed immediately following training and did not extend to 1 month or year post-training.

In conclusion, the study provides preliminary evidence that AffeCT may confer short-term preventative benefits for adolescent mental health.

Cognitive distancing is an emotion regulation strategy commonly used in psychological treatment of various mental health disorders, but its therapeutic mechanisms are unknown.

935 participants completed an online reinforcement learning task involving choices between pairs of symbols with differing reward contingencies. Half (49.1%) of the sample was randomised to a cognitive self-distancing intervention and were trained to regulate or ‘take a step back’ from their emotional response to feedback throughout. Established computational (Q-learning) models were then fit to individuals' choices to derive reinforcement learning parameters capturing clarity of choice values (inverse temperature) and their sensitivity to positive and negative feedback (learning rates).

Cognitive distancing improved task performance, including when participants were later tested on novel combinations of symbols without feedback. Group differences in computational model-derived parameters revealed that cognitive distancing resulted in clearer representations of option values (estimated 0.17 higher inverse temperatures). Simultaneously, distancing caused increased sensitivity to negative feedback (estimated 19% higher loss learning rates). Exploratory analyses suggested this resulted from an evolving shift in strategy by distanced participants: initially, choices were more determined by expected value differences between symbols, but as the task progressed, they became more sensitive to negative feedback, with evidence for a difference strongest by the end of training.

Adaptive effects on the computations that underlie learning from reward and loss may explain the therapeutic benefits of cognitive distancing. Over time and with practice, cognitive distancing may improve symptoms of mental health disorders by promoting more effective engagement with negative information.

Early-life stressful experiences are associated with increased risk of adverse psychological outcomes in later life. However, much less is known about associations between early-life positive experiences, such as participation in cognitively stimulating activities, and late-life mental health. We investigated whether greater engagement in cognitively stimulating activities in early life is associated with lower risk of depression and anxiety in late life.

We surveyed former participants of the St. Louis Baby Tooth study, between 22 June 2021 and 25 March 2022 to collect information on participants' current depression/anxiety symptoms and their early-life activities (N = 2187 responded). A composite activity score was created to represent the early-life activity level by averaging the frequency of self-reported participation in common cognitively stimulating activities in participants' early life (age 6, 12, 18), each rated on a 1 (least frequent) to 5 (most frequent) point scale. Depression/anxiety symptoms were measured by Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder Screener (GAD-7). We used logistic regressions to estimate odds ratios (OR) and 95% confidence intervals (CI) of outcome risk associated with frequency of early-life activity.

Each one-point increase in the early-life composite cognitive activity score was associated with an OR of 0.54 (95% CI 0.38–0.77) for late-life depression and an OR of 0.94 (95% CI 0.61–1.43) for late-life anxiety, adjusting for age, sex, race, parental education, childhood family structure, and socioeconomic status.

More frequent participation in cognitively stimulating activities during early life was associated with reduced risk of late-life depression.

To clarify, in a national sample, associations between risk for seven psychiatric and substance use disorders and five key transitions in Sweden's public educational system.

Swedish-born individuals (1972–1995, N = 1 997 910) were followed through 12-31-2018, at mean age 34.9. We predicted, from these educational transitions, risk for major depression (MD), obsessive-compulsive disorder (OCD), bipolar disorder (BD), schizophrenia (SZ), anorexia nervosa (AN), alcohol use disorder (AUD), and drug use disorder (DUD), assessed from Swedish national registers, by Cox regression, censoring individuals with onsets ⩽17. We also predicted risk from the deviation of grades from family-genetic expectations (deviation 1) and from changes in grades from ages 16 to 19 (deviation 2).

We observed four major risk patterns across transitions in our disorders: (i) MD and BD, (ii) OCD and SZ, (iii) AUD and DUD, and (iv) AN. Failing early educational transitions had the greatest impact on risk for OCD and SZ while for other disorders, not progressing from basic to upper high school had the largest effect. Completing vocational v. college-prep upper high school was strongly associated with risk for AUD and DUD, had little relation with MD, OCD, BD, and SZ risk, and was protective for AN. Deviation 1 predicted risk most strongly for SZ, AN, and MD. Deviation 2 predicted risk most strongly for SZ, AUD, and DUD.

The pattern of educational transitions and within family and within person development deviations are strongly and relatively specifically associated with future risk for seven psychiatric and substance-use disorders.

Childhood trauma (CT) has been cross-sectionally associated with metabolic syndrome (MetS), a group of biological risk factors for cardiometabolic disease. Longitudinal studies, while rare, would clarify the development of cardiometabolic dysregulations over time. Therefore, we longitudinally investigated the association of CT with the 9-year course of MetS components.

Participants (N = 2958) from the Netherlands Study of Depression and Anxiety were assessed four times across 9 years. The CT interview retrospectively assessed childhood emotional neglect and physical, emotional, and sexual abuse. Metabolic outcomes encompassed continuous MetS components (waist circumference, triglycerides, high-density lipoprotein [HDL] cholesterol, blood pressure [BP], and glucose) and count of clinically elevated MetS components. Mixed-effects models estimated sociodemographic- and lifestyle-adjusted longitudinal associations of CT with metabolic outcomes over time. Time interactions evaluated change in these associations.

CT was reported by 49% of participants. CT was consistently associated with increased waist (b = 0.32, s.e. = 0.10, p = 0.001), glucose (b = 0.02, s.e. = 0.01, p < 0.001), and count of MetS components (b = 0.04, s.e. = 0.01, p < 0.001); and decreased HDL cholesterol (b = −0.01, s.e.<0.01, p = .020) and systolic BP (b = −0.33, s.e. = 0.13, p = 0.010). These associations were mainly driven by severe CT and unaffected by lifestyle. Only systolic BP showed a CT-by-time interaction, where CT was associated with lower systolic BP initially and with higher systolic BP at the last follow-up.

Over time, adults with CT have overall persistent poorer metabolic outcomes than their non-maltreated peers. Individuals with CT have an increased risk for cardiometabolic disease and may benefit from monitoring and early interventions targeting metabolism.

There are phenomenological similarities between social anxiety disorder (SAD) and posttraumatic stress disorder, such as a provoking aversive event, posttraumatic stress symptoms (e.g. intrusions) in response to these events and deficient (context-dependent) fear conditioning processes. This study investigated the neural correlates of context-dependent extinction recall and fear renewal in SAD, specifically in patients with intrusions in response to an etiologically relevant aversive social event.

During functional magnetic resonance imaging a two-day context-dependent fear conditioning paradigm was conducted in 54 patients with SAD and 54 healthy controls (HC). This included fear acquisition (context A) and extinction learning (context B) on one day, and extinction recall (context B) as well as fear renewal (contexts C and A) one day later. The main outcome measures were blood oxygen level-dependent responses in regions of interest and skin conductance responses.

Patients with SAD showed reduced differential conditioned amygdala activation during extinction recall in the safe extinction context and during fear renewal in the acquisition context compared to HC. Patients with clinically relevant intrusions moreover exhibited hypoactivation of the ventromedial prefrontal cortex (vmPFC) during extinction learning, extinction recall, and fear renewal in a novel context, while amygdala activation more strongly decreased during extinction learning and increased during fear renewal in the acquisition context compared with patients without intrusions.

Our study provides first evidence that intrusions in SAD are associated with similar deficits in context-dependent regulation of conditioned fear via the vmPFC as previously demonstrated in posttraumatic stress disorder.

Although risk markers for depressive disorders (DD) are dynamic, especially during adolescence, few studies have examined how change in risk levels during adolescence predict DD onset during transition to adulthood. We compared two competing hypotheses of the dynamic effects of risk. The risk escalation hypothesis posits that worsening of risk predicts DD onset beyond risk level. The chronic risk hypothesis posits that persistently elevated risk level, rather than risk change, predicts DD onset.

Our sample included 393 girls (baseline age 13.5–15.5 years) from the adolescent development of emotions and personality traits project. Participants underwent five diagnostic interviews and assessments of risk markers for DD at 9-month intervals and were re-interviewed at a 6-year follow-up. We focused on 17 well-established risk markers. For each risk marker, we examined the prospective effects of risk level and change on first DD onset at wave six, estimated by growth curve modeling using data from the first five waves.

For 13 of the 17 depression risk markers, elevated levels of risk during adolescence, but not change in risk, predicted first DD onset during transition to adulthood, supporting the chronic risk hypothesis. Minimal evidence was found for the risk escalation hypothesis.

Participants who had a first DD onset during transition to adulthood have exhibited elevated levels of risk throughout adolescence. Researchers and practitioners should administer multiple assessments and focus on persistently elevated levels of risk to identify individuals who are most likely to develop DD and to provide targeted DD prevention.

Bipolar disorder (BD) is an overarching diagnostic class defined by the presence of at least one prior manic episode (BD I) or both a prior hypomanic episode and a prior depressive episode (BD II). Traditionally, BD II has been conceptualized as a less severe presentation of BD I, however, extant literature to investigate this claim has been mixed.

We apply genomic structural equation modeling (Genomic SEM) to investigate divergent genetic pathways across BD's two major subtypes using the most recent GWAS summary statistics from the PGC. We begin by identifying divergences in genetic correlations across 98 external traits using a Bonferroni-corrected threshold. We also use a theoretically informed follow-up model to examine the extent to which the genetic variance in each subtype is explained by schizophrenia and major depression. Lastly, transcriptome-wide SEM (T-SEM) was used to identify neuronal gene expression patterns associated with BD subtypes.

BD II was characterized by significantly larger genetic overlap across non-psychiatric medical and internalizing traits (e.g. heart disease, neuroticism, insomnia), while stronger associations for BD I were absent. Consistent with these findings, follow-up modeling revealed a substantial major depression component for BD II. T-SEM results revealed 35 unique genes associated with shared risk across BD subtypes.

Divergent patterns of genetic relationships across external traits provide support for the distinction of the bipolar subtypes. However, our results also challenge the illness severity conceptualization of BD given stronger genetic overlap across BD II and a range of clinically relevant traits and disorders.

Screen time in infancy is linked to changes in social-emotional development but the pathway underlying this association remains unknown. We aim to provide mechanistic insights into this association using brain network topology and to examine the potential role of parent–child reading in mitigating the effects of screen time.

We examined the association of screen time on brain network topology using linear regression analysis and tested if the network topology mediated the association between screen time and later socio-emotional competence. Lastly, we tested if parent–child reading time was a moderator of the link between screen time and brain network topology.

Infant screen time was significantly associated with the emotion processing-cognitive control network integration (p = 0.005). This network integration also significantly mediated the association between screen time and both measures of socio-emotional competence (BRIEF-2 Emotion Regulation Index, p = 0.04; SEARS total score, p = 0.04). Parent–child reading time significantly moderated the association between screen time and emotion processing-cognitive control network integration (β = −0.640, p = 0.005).

Our study identified emotion processing-cognitive control network integration as a plausible biological pathway linking screen time in infancy and later socio-emotional competence. We also provided novel evidence for the role of parent–child reading in moderating the association between screen time and topological brain restructuring in early childhood.

Several hypotheses may explain the association between substance use, posttraumatic stress disorder (PTSD), and depression. However, few studies have utilized a large multisite dataset to understand this complex relationship. Our study assessed the relationship between alcohol and cannabis use trajectories and PTSD and depression symptoms across 3 months in recently trauma-exposed civilians.

In total, 1618 (1037 female) participants provided self-report data on past 30-day alcohol and cannabis use and PTSD and depression symptoms during their emergency department (baseline) visit. We reassessed participant's substance use and clinical symptoms 2, 8, and 12 weeks posttrauma. Latent class mixture modeling determined alcohol and cannabis use trajectories in the sample. Changes in PTSD and depression symptoms were assessed across alcohol and cannabis use trajectories via a mixed-model repeated-measures analysis of variance.

Three trajectory classes (low, high, increasing use) provided the best model fit for alcohol and cannabis use. The low alcohol use class exhibited lower PTSD symptoms at baseline than the high use class; the low cannabis use class exhibited lower PTSD and depression symptoms at baseline than the high and increasing use classes; these symptoms greatly increased at week 8 and declined at week 12. Participants who already use alcohol and cannabis exhibited greater PTSD and depression symptoms at baseline that increased at week 8 with a decrease in symptoms at week 12.

Our findings suggest that alcohol and cannabis use trajectories are associated with the intensity of posttrauma psychopathology. These findings could potentially inform the timing of therapeutic strategies.

This systematic review and individual participant data meta-analysis (IPDMA) examined the overall effectiveness of eye movement desensitization and reprocessing (EMDR) in reducing posttraumatic stress disorder (PTSD) symptoms, achieving response and remission, and reducing treatment dropout among adults with PTSD compared to other psychological treatments. Additionally, we examined available participant-level moderators of the efficacy of EMDR.

This study included randomized controlled trials. Eligible studies were identified by a systematic search in PubMed, Embase, PsyclNFO, PTSDpubs, and CENTRAL. The target population was adults with above-threshold baseline PTSD symptoms. Trials were eligible if at least 70% of study participants had been diagnosed with PTSD using a structured clinical interview. Primary outcomes included PTSD symptom severity, treatment response, and PTSD remission. Treatment dropout was a secondary outcome. The systematic search retrieved 15 eligible randomized controlled trials (RCTs); 8 of these 15 were able to be included in this IPDMA (346 patients). Comparator treatments included relaxation therapy, emotional freedom technique, trauma-focused cognitive behavioral psychotherapies, and REM-desensitization.

One-stage IPDMA found no significant difference between EMDR and other psychological treatments in reducing PTSD symptom severity (β = −0.24), achieving response (β = 0.86), attaining remission (β = 1.05), or reducing treatment dropout rates (β = −0.25). Moderator analyses found unemployed participants receiving EMDR had higher PTSD symptom severity at the post-test, and males were more likely to drop out of EMDR treatment than females.

The current study found no significant difference between EMDR and other psychological treatments. We found some indication of the moderating effects of gender and employment status.

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.