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"Psychotic-Like Experiences" (PLEs) are common in the general population. While they are usually transient and resolve spontaneously, they can be distressing and signify increased risk for later psychosis or other psychopathology. It is important to investigate factors associated with PLEs which could be targeted to reduce their prevalence and impact. Males and females are known to experience PLEs differently, but any gender differences in the relationships between PLEs and other, potentially targetable, factors are currently unknown. 302 adolescents (175 females, mean age = 16.03, SD = 0.75; 127 males, mean age = 16.09, SD = 0.74) from secondary schools in the West Midlands region of the UK completed baseline self-report measures of positive PLEs, measured by the Community Assessment of Psychic Experiences (CAPE-P), and several potentially related factors including: cannabis use, perceived stress, anxiety, depression, and daily hassles. PLEs were common in this sample, with 67.5% of individuals experiencing at least one CAPE-P item 'often' or 'almost always'. Females reported significantly higher levels of PLEs, and associated distress, than males. Anxiety, depressive, and stress symptoms were similarly associated with PLEs in both genders. However, there was a significant interaction of gender and daily hassles in the association with PLEs. In summary, there were significant gender differences in the experience of PLEs in this sample. Although daily hassles were more common in females, they had a significantly stronger association with PLEs in males. Thus, addressing "daily life stress" in adolescents may require tailoring towards the more emotional perception of stress in females, and towards everyday life hassles in males.

Background Childhood trauma (CT) is a major yet elusive psychiatric risk factor, whose multidimensional conceptualization and heterogeneous effects on brain morphology might demand advanced mathematical modeling. Therefore, we present an unsupervised machine learning approach to characterize the clinical and neuroanatomical complexity of CT in a larger, transdiagnostic context. Methods We used a multicenter European cohort of 1076 female and male individuals (discovery: n = 649; replication: n = 427) comprising young, minimally medicated patients with clinical high-risk states for psychosis; patients with recent-onset depression or psychosis; and healthy volunteers. We employed multivariate sparse partial least squares analysis to detect parsimonious associations between combinations of items from the Childhood Trauma Questionnaire and gray matter volume and tested their generalizability via nested cross-validation as well as via external validation. We investigated the associations of these CT signatures with state (functioning, depressivity, quality of life), trait (personality), and sociodemographic levels. Results We discovered signatures of age-dependent sexual abuse and sex-dependent physical and sexual abuse, as well as emotional trauma, which projected onto gray matter volume patterns in prefronto-cerebellar, limbic, and sensory networks. These signatures were associated with predominantly impaired clinical state- and trait-level phenotypes, while pointing toward an interaction between sexual abuse, age, urbanicity, and education. We validated the clinical profiles for all three CT signatures in the replication sample. Conclusions Our results suggest distinct multilayered associations between partially age- and sex-dependent patterns of CT, distributed neuroanatomical networks, and clinical profiles. Hence, our study highlights how machine learning approaches can shape future, more fine-grained CT research.

BACKGROUND Identifying neurobiologically based transdiagnostic categories of depression and psychosis may elucidate heterogeneity and provide better candidates for predictive modeling. We aimed to identify clusters across patients with recent-onset depression (ROD) and recent-onset psychosis (ROP) based on structural neuroimaging data. We hypothesized that these transdiagnostic clusters would identify patients with poor outcome and allow more accurate prediction of symptomatic remission than traditional diagnostic structures. METHODS HYDRA (Heterogeneity through Discriminant Analysis) was trained on whole-brain volumetric measures from 577 participants from the discovery sample of the multisite PRONIA study to identify neurobiologically driven clusters, which were then externally validated in the PRONIA replication sample (n = 404) and three datasets of chronic samples (Centre for Biomedical Research Excellence, n = 146; Mind Clinical Imaging Consortium, n = 202; Munich, n = 470). RESULTS The optimal clustering solution was two transdiagnostic clusters (cluster 1: n = 153, 67 ROP, 86 ROD; cluster 2: n = 149, 88 ROP, 61 ROD; adjusted Rand index = 0.618). The two clusters contained both patients with ROP and patients with ROD. One cluster had widespread gray matter volume deficits and more positive, negative, and functional deficits (impaired cluster), and one cluster revealed a more preserved neuroanatomical signature and more core depressive symptomatology (preserved cluster). The clustering solution was internally and externally validated and assessed for clinical utility in predicting 9-month symptomatic remission, outperforming traditional diagnostic structures. CONCLUSIONS We identified two transdiagnostic neuroanatomically informed clusters that are clinically and biologically distinct, challenging current diagnostic boundaries in recent-onset mental health disorders. These results may aid understanding of the etiology of poor outcome patients transdiagnostically and improve development of stratified treatments.

Background Bullying as a specific subtype of adverse life events is a major risk factor for poor mental health. Although many questionnaires on bullying are available, so far none covers bullying retrospectively throughout school and working life. To close this gap, the Bullying Scale for Adults (BSA) was designed. Methods Based on data of 622 participants from five European countries collected in the prospective multicenter Personalized Prognostic Tools for Early Psychosis Management (PRONIA) study, we investigated whether the BSA is a reliable and valid measurement for bullying and whether there is a difference across different diagnostic groups of early mental disorders (recent onset depressive/ psychotic patients, patients at clinical high-risk of psychosis) and healthy controls. Results Bullying experiences were significantly less frequent in healthy controls than in patient groups, with no significant differences between the three clinical groups. The BSA exhibited a high item scale discrimination (r > .3) and very good internal consistency (Cronbach's α = .93). Four factors were identified: 1. Sexual harassment, 2. Emotional Abuse, 3. Physical Abuse, 4. Problems at school. The highly significant correlation between bullying, and childhood adversities and trauma (r = .645, p Discussion The BSA is the first validated questionnaire that, in retrospective, reliably records various aspects of bullying (incl. its consequences) not only throughout childhood but also working life. It can be used to assess bullying as a transdiagnostic risk factor of mental disorders in different mental disorders, esp. psychosis and depression.

Aim Resilience is rapidly gaining momentum in mental health literature. It provides a new understanding of the highly variable trajectories of mental illness, and has consistently been linked with improved mental health outcomes. The present review aims to clarify the definition of resilience and to discuss new directions for the field. Methods After discussing the definition of resilience, this narrative review synthesizes evidence that identifies the specific protective factors involved in this process. This review also addresses the mechanisms that underlie resilience. Results Recent literature has clarified the three core components of resilience, which are the presence of an adversity or specific risk for mental illness; the influence of protective factors that supersede this risk; and finally, a subsequently more positive outcome than expected. Now that these are largely agreed upon, the field should move on to addressing other topics. Resilience is a dynamic process by which individuals utilize protective factors and resources to their benefit. It can vary within one individual across time and circumstance. It can also refer to good functional outcomes in the context of diagnosable illness. While previous research has focused on psychological resilience, it is essential that resilience is conceptualized across modalities. Conclusions The field should move towards the development of a multimodal model of resilience. Researchers should now focus on producing empirical research which clarifies the specific protective factors and mechanisms of the process, aligning with the core concepts of resilience. This growing, more homogeneous evidence base, can then inform new intervention strategies.