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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.

Cognitive impairments in psychosis negatively impact functional recovery and quality of life. Existing interventions for improving cognitive impairment in recent-onset psychosis show inconsistent treatment efficacy, small effects, suboptimal engagement and limited generalizability to daily life functioning. In this perspective we explore how digital technology has the potential to address these limitations in order to improve cognitive and functional outcomes in recent-onset psychosis. Computer programs can be used for standardized, automated delivery of cognitive remediation training. Virtual reality provides the opportunity for learning and practicing cognitive skills in real-world scenarios within a virtual environment. Smartphone apps could be used for notification reminders for everyday tasks to compensate for cognitive difficulties. Internet-based technologies can offer psychoeducation and training materials for enhancing cognitive skills. Early findings indicate some forms of digital interventions for cognitive enhancement can be effective, with well-established evidence for human-supported computer-based cognitive remediation in recent-onset psychosis. Emerging evidence regarding virtual reality is favorable for improving social cognition. Overall, blending digital interventions with human support improves engagement and effectiveness. Despite the potential of digital interventions for enhancing cognition in recent-onset psychosis, few studies have been conducted to date. Implementation challenges affecting application of digital technologies for cognitive impairment in recent-onset psychosis are sustained engagement, clinical integration, and lack of quality in the commercial marketplace. Future opportunities lie in including motivational frameworks and behavioral change interventions, increasing service engagement in young people and lived experience involvement in digital intervention development.

Recent life events have been implicated in the onset and progression of psychosis. However, psychological processes that account for the association are yet to be fully understood. Using a network approach, we aimed to identify pathways linking recent life events and symptoms observed in psychosis. Based on previous literature, we hypothesized that general symptoms would mediate between recent life events and psychotic symptoms. We analyzed baseline data of patients at clinical high risk for psychosis and with recent-onset psychosis (n = 547) from the Personalised Prognostic Tools for Early Psychosis Management (PRONIA) study. In a network analysis, we modeled links between the burden of recent life events and all individual symptoms of the Positive and Negative Syndrome Scale before and after controlling for childhood trauma. To investigate the longitudinal associations between burden of recent life events and symptoms, we analyzed multiwave panel data from seven timepoints up to month 18. Corroborating our hypothesis, burden of recent life events was connected to positive and negative symptoms through general psychopathology, specifically depression, guilt feelings, anxiety and tension, even after controlling for childhood trauma. Longitudinal modeling indicated that on average, burden of recent life events preceded general psychopathology in the individual. In line with the theory of an affective pathway to psychosis, recent life events may lead to psychotic symptoms via heightened emotional distress. Life events may be one driving force of unspecific, general psychopathology described as characteristic of early phases of the psychosis spectrum, offering promising avenues for interventions.

Depression frequently occurs in first-episode psychosis (FEP) and predicts longer-term negative outcomes. It is possible that this depression is seen primarily in a distinct subgroup, which if identified could allow targeted treatments. We hypothesize that patients with recent-onset psychosis (ROP) and comorbid depression would be identifiable by symptoms and neuroanatomical features similar to those seen in recent-onset depression (ROD). Data were extracted from the multisite PRONIA study: 154 ROP patients (FEP within 3 months of treatment onset), of whom 83 were depressed (ROP+D) and 71 who were not depressed (ROP−D), 146 ROD patients, and 265 healthy controls (HC). Analyses included a (1) principal component analysis that established the similar symptom structure of depression in ROD and ROP+D, (2) supervised machine learning (ML) classification with repeated nested cross-validation based on depressive symptoms separating ROD vs ROP+D, which achieved a balanced accuracy (BAC) of 51%, and (3) neuroanatomical ML-based classification, using regions of interest generated from ROD subjects, which identified BAC of 50% (no better than chance) for separation of ROP+D vs ROP−D. We conclude that depression at a symptom level is broadly similar with or without psychosis status in recent-onset disorders; however, this is not driven by a separable depressed subgroup in FEP. Depression may be intrinsic to early stages of psychotic disorder, and thus treating depression could produce widespread benefit.

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.

Background Resilience provides a new understanding of the highly variable trajectories of mental illness, and has consistently been linked with improved mental health outcomes. Resilience is largely defined as the presence of additional factors which overcome a specific risk for mental illness, leading to ultimately more positive outcomes than expected given said risk. Previous research in the area has focused on identifying psychological factors which may be associated with resilience. Moving forwards, it is essential that researchers investigate how resilience may function in different domains. The aim for the present research was to conduct a preliminary investigation into the possible role of neuropsychological performance in resilience using data from the PRONIA study. Methods Participants were individuals aged 15–40 who were recruited into the PRONIA study. Total scores for the Resilience Scale for Adults (RSA), assessing self-report psychological resilience, were available for 587 participants. The sample included individuals with first-episode psychosis (N=113), first-episode depression (N=118), individuals at ultra-high risk for psychosis (N=109), and healthy controls (N=247). Participants also completed a comprehensive neuropsychological test battery which assessed performance in the following domains: IQ, executive functioning (EF), processing speed (PS), sustained attention, working memory, visual memory, social cognition, motivational salience, and verbal learning and memory. Results A stepwise multiple linear regression was used to identify which of the neuropsychological domains would best predict RSA total score. The final model significantly predicted RSA total score, explaining 4% of the variance in these scores, F(2, 512) = 12.37, p < 0.001. The model indicated that higher RSA total was associated with PS (β=3.35, p=.032) and EF (β=4.15, p=0.046). EF provided the highest relative contribution in the model, with every 1 point increase resulting in 4.15 standard deviation increase in RSA total. Discussion The present results suggest that neuropsychological performance has a small, but significant relationship with psychological resilience. The two neuropsychological domains which best predicted this outcome were PS and EF. Resilience has been argued to be a highly dynamic process, by which individuals must utilise assets and resources to their benefit. Furthermore, the effectiveness of such factors will vary across time and circumstance, adding to the flexibility required to navigate this process. These results support this conceptualisation of resilience, as EF is thought to involve the organisation and execution of complex thoughts and behaviour. Processing speed has also been found to affect other cognitive functions such as reasoning. These neuropsychological processes may aid an individual’s ability to utilise protective factors to their benefit during a period of adversity or risk. These results are preliminary, and future research should look to replicate and extend this research to form a multi-modal model of resilience. A deeper understanding of the mechanisms underlying this process can then inform future intervention strategies.

The study investigated the processes underlying the retrieval of action information about functional object pairs, focusing on the contribution of procedural and semantic knowledge. We further assessed whether the retrieval of action knowledge is affected by task demands and age. The contribution of procedural knowledge was examined by the way objects were selected, specifically whether active objects were selected before passive objects. The contribution of semantic knowledge was examined by manipulating the relation between targets and distracters. A touchscreen-based search task was used testing young, middle-aged, and elderly participants. Participants had to select by touching two targets among distracters using two search tasks. In an explicit action search task, participants had to select two objects which afforded a mutual action (e.g., functional pair: hammer-nail). Implicit affordance perception was tested using a visual color-matching search task; participants had to select two objects with the same colored frame. In both tasks, half of the colored targets also afforded an action. Overall, middle-aged participants performed better than young and elderly participants, specifically in the action task. Across participants in the action task, accuracy was increased when the distracters were semantically unrelated to the functional pair, while the opposite pattern was observed in the color task. This effect was enhanced with increased age. In the action task all participants utilized procedural knowledge, i.e., selected the active object before the passive object. This result supports the dual-route account from vision to action. Semantic knowledge contributed to both the action and the color task, but procedural knowledge associated with the direct route was primarily retrieved when the task was action-relevant. Across the adulthood lifespan, the data show inverted U-shaped effects of age on the retrieval of action knowledge. Age also linearly increased the involvement of the indirect (semantic) route and the integration of information of the direct and the indirect routes in selection processes.