Around the world, people living in objectively difficult circumstances who experience symptoms of generalized anxiety disorder (GAD) do not qualify for a diagnosis because their worry is not ‘excessive’ relative to the context. We carried out the first large-scale, cross-national study to explore the implications of removing this excessiveness requirement.

Data come from the World Health Organization World Mental Health Survey Initiative. A total of 133 614 adults from 12 surveys in Low- or Middle-Income Countries (LMICs) and 16 surveys in High-Income Countries (HICs) were assessed with the Composite International Diagnostic Interview. Non-excessive worriers meeting all other DSM-5 criteria for GAD were compared to respondents meeting all criteria for GAD, and to respondents without GAD, on clinically-relevant correlates.

Removing the excessiveness requirement increases the global lifetime prevalence of GAD from 2.6% to 4.0%, with larger increases in LMICs than HICs. Non-excessive and excessive GAD cases worry about many of the same things, although non-excessive cases worry more about health/welfare of loved ones, and less about personal or non-specific concerns, than excessive cases. Non-excessive cases closely resemble excessive cases in socio-demographic characteristics, family history of GAD, and risk of temporally secondary comorbidity and suicidality. Although non-excessive cases are less severe on average, they report impairment comparable to excessive cases and often seek treatment for GAD symptoms.

Individuals with non-excessive worry who meet all other DSM-5 criteria for GAD are clinically significant cases. Eliminating the excessiveness requirement would lead to a more defensible GAD diagnosis.

Functional connectivity of the default mode network (DMN) during rest has been shown to be different among adults with Mild Cognitive Impairment (MCI) relative to aged-matched individuals without MCI and is predictive of transition to dementia. Post-traumatic stress disorder (PTSD) is also associated with aberrant connectivity of the DMN. Prior work from this group has demonstrated a higher rate of MCI and PTSD among World Trade Center (WTC) responders relative to the general population. The current study sought to investigate the main and interactive effects of MCI and PTSD on DMN functioning. Based on prior work, we hypothesized that MCI, but not PTSD, would predict aberrant connectivity in the DMN.

99 WTC responders aged 44–65 stratified by MCI status (yes/no) and PTSD status (yes/no) and matched for age in years, sex (male vs. female), race (white, black, and other), and educational attainment (high school or less, some college / technical school, and university degree), and occupation on September 11, 2001 (law enforcement vs. other) underwent fMRI using a 3T Siemens Biograph MR scanner. A single 10-minute continuous functional MR sequence was acquired while participants were at rest with their eyes open. Group-level analyses were conducted using SPM-12, with correction for multiple comparisons using AFNI's 3dClustSim. Based on this threshold, the number of comparisons in our imaging volume, and the smoothness of our imaging data as measured by 3dFWHMx-acf, a minimum cluster size of 1134 voxels was required to have a corrected p . .05 with 2-sided thresholding. Spherical 3 mm seeds were placed in the dorsal (4, -50, 26) and ventral (4, -60, 46) posterior cingulate cortex (PCC).

Individuals with PTSD demonstrated significantly less connectivity of the dorsal posterior cingulate cortex (PCC) with medial insula (T = 5.21), subthalamic nucleus (T = 4.66), and postcentral gyrus (T = 3.81). There was no difference found in this study for connectivity between groups stratified by MCI status. There were no significant results for the ventral PCC seed.

Contrary to hypotheses that were driven by a study of cortical thickness in WTC responders, the impact of PTSD appears to outweigh the impact of MCI on dorsal DMN connectivity among WTC responders stratified by PTSD and MCI status. This study is limited by several issues, including low number of female and minority participants, relatively small group cell sizes (n = 23–27 per cell), a brief resting state sequence (10 minutes), and lack of a non-WTC control group. Importantly, responders are a unique population so generalizability to other populations may be limited. Individuals in the current study are now being followed longitudinally to relate baseline resting state functional connectivity with cognitive changes and changes in connectivity over a four-year period.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Oral histories from 9/11 responders to the World Trade Center (WTC) attacks provide rich narratives about distress and resilience. Artificial Intelligence (AI) models promise to detect psychopathology in natural language, but they have been evaluated primarily in non-clinical settings using social media. This study sought to test the ability of AI-based language assessments to predict PTSD symptom trajectories among responders.

Participants were 124 responders whose health was monitored at the Stony Brook WTC Health and Wellness Program who completed oral history interviews about their initial WTC experiences. PTSD symptom severity was measured longitudinally using the PTSD Checklist (PCL) for up to 7 years post-interview. AI-based indicators were computed for depression, anxiety, neuroticism, and extraversion along with dictionary-based measures of linguistic and interpersonal style. Linear regression and multilevel models estimated associations of AI indicators with concurrent and subsequent PTSD symptom severity (significance adjusted by false discovery rate).

Cross-sectionally, greater depressive language (β = 0.32; p = 0.049) and first-person singular usage (β = 0.31; p = 0.049) were associated with increased symptom severity. Longitudinally, anxious language predicted future worsening in PCL scores (β = 0.30; p = 0.049), whereas first-person plural usage (β = −0.36; p = 0.014) and longer words usage (β = −0.35; p = 0.014) predicted improvement.

This is the first study to demonstrate the value of AI in understanding PTSD in a vulnerable population. Future studies should extend this application to other trauma exposures and to other demographic groups, especially under-represented minorities.

Life events (LEs) are a risk factor for first onset and relapse of psychotic disorders. However, the impact of LEs on specific symptoms – namely reality distortion, disorganization, negative symptoms, depression, and mania – remains unclear. Moreover, the differential effects of negative v. positive LEs are poorly understood.

The present study utilizes an epidemiologic cohort of patients (N = 428) ascertained at first-admission for psychosis and followed for a decade thereafter. Symptoms were assessed at 6-, 24-, 48-, and 120-month follow-ups.

We examined symptom change within-person and found that negative events in the previous 6 months predicted an increase in reality distortion (β = 0.07), disorganized (β = 0.07), manic (β = 0.08), and depressive symptoms (β = 0.06), and a decrease in negative symptoms (β = −0.08). Conversely, positive LEs predicted fewer reality distortion (β = −0.04), disorganized (β = −0.04), and negative (β = −0.13) symptoms, and were unrelated to mood symptoms. A between-person approach to the same hypotheses confirmed that negative LEs predicted change in all symptoms, while positive LEs predicted change only in negative symptoms. In contrast, symptoms rarely predicted future LEs.

These findings confirm that LEs have an effect on symptoms, and thus contribute to the burden of psychotic disorders. That LEs increase positive symptoms and decrease negative symptoms suggest at least two different mechanisms underlying the relationship between LEs and symptoms. Our findings underscore the need for increased symptom monitoring following negative LEs, as symptoms may worsen during that time.

Genetics hold promise of predicting long-term post-traumatic stress disorder (PTSD) outcomes following trauma. The aim of the current study was to test whether six hypothesized polygenic risk scores (PRSs) developed to capture genetic vulnerability to psychiatric conditions prospectively predict PTSD onset, severity, and 18-year course after trauma exposure.

Participants were 1490 responders to the World Trade Center (WTC) disaster (mean age at 9/11 = 38.81 years, s.d. = 8.20; 93.5% male; 23.8% lifetime WTC-related PTSD diagnosis). Prospective longitudinal data on WTC-related PTSD symptoms were obtained from electronic medical records and modelled as PTSD trajectories using growth mixture model analysis. Independent regression models tested whether six hypothesized psychiatric PRSs (PTSD-PRS, Re-experiencing-PRS, Generalized Anxiety-PRS, Schizophrenia-PRS, Depression-PRS, and Neuroticism-PRS) are predictive of WTC-PTSD outcomes: lifetime diagnoses, average symptom severity, and 18-year symptom trajectory. All analyses were adjusted for population stratification, 9/11 exposure severity, and multiple testing.

Depression-PRS predicted PTSD diagnostic status (OR 1.37, CI 1.17–1.61, adjusted p = 0.001). All PRSs, except PTSD-PRS, significantly predicted average PTSD symptoms (β = 0.06–0.10, adjusted p < 0.05). Re-experiencing-PRS, Generalized Anxiety-PRS and Schizophrenia-PRS predicted the high severity PTSD trajectory class (ORs 1.21–1.28, adjusted p < 0.05). Finally, PRSs prediction was independent of 9/11 exposure severity and jointly accounted for 3.7 times more variance in PTSD symptoms than the exposure severity.

Psychiatric PRSs prospectively predicted WTC-related PTSD lifetime diagnosis, average symptom severity, and 18-year trajectory in responders to 9/11 disaster. Jointly, PRSs were more predictive of subsequent PTSD than the exposure severity. In the future, PRSs may help identify at-risk responders who might benefit from targeted prevention approaches.

There is a substantial proportion of patients who drop out of treatment before they receive minimally adequate care. They tend to have worse health outcomes than those who complete treatment. Our main goal is to describe the frequency and determinants of dropout from treatment for mental disorders in low-, middle-, and high-income countries.

Respondents from 13 low- or middle-income countries (N = 60 224) and 15 in high-income countries (N = 77 303) were screened for mental and substance use disorders. Cross-tabulations were used to examine the distribution of treatment and dropout rates for those who screened positive. The timing of dropout was examined using Kaplan–Meier curves. Predictors of dropout were examined with survival analysis using a logistic link function.

Dropout rates are high, both in high-income (30%) and low/middle-income (45%) countries. Dropout mostly occurs during the first two visits. It is higher in general medical rather than in specialist settings (nearly 60% v. 20% in lower income settings). It is also higher for mild and moderate than for severe presentations. The lack of financial protection for mental health services is associated with overall increased dropout from care.

Extending financial protection and coverage for mental disorders may reduce dropout. Efficiency can be improved by managing the milder clinical presentations at the entry point to the mental health system, providing adequate training, support and specialist supervision for non-specialists, and streamlining referral to psychiatrists for more severe cases.

Performance monitoring entails rapid error detection to maintain task performance. Impaired performance monitoring is a candidate pathophysiological process in psychotic disorders, which may explain the broader deficit in executive function and its known associations with negative symptoms and poor functioning. The current study models cross-sectional pathways bridging neurophysiological measures of performance monitoring with executive function, symptoms, and functioning.

Data were from the 20-year assessment of the Suffolk County Mental Health Project. Individuals with psychotic disorders (N = 181) were originally recruited from inpatient psychiatric facilities. Data were also collected from a geographically and demographically matched group with no psychosis history (N = 242). Neural measures were the error-related negativity (ERN) and error positivity (Pe). Structural equation modeling tested mediation pathways.

Blunted ERN and Pe in the clinical cohort related to impaired executive function (r = 0.26–0.35), negative symptom severity (r = 0.17–0.25), and poor real-world functioning (r = 0.17–0.19). Associations with executive function were consistent across groups. Multiple potential pathways were identified in the clinical cohort: reduced ERN to inexpressivity was mediated by executive function (β = 0.10); reduced Pe to global functioning was mediated by executive function and avolition (β = 0.10).

This supports a transdiagnostic model of psychotic disorders by which poor performance monitoring contributes to impaired executive function, which contributes to negative symptoms and poor real-world functioning. If supported by future longitudinal research, these pathways could inform the development of targeted interventions to address cognitive and functional deficits that are central to psychotic disorders.