Explore the vast range of titles available.

Understanding whether and how the schizophrenia polygenic risk score (SZ PRS) predicts course of illness could improve diagnosis and prognostication in psychotic disorders. We tested whether the SZ PRS predicts symptoms, cognition, illness severity, and diagnostic changes over the 20 years following first admission. The Suffolk County Mental Health Project is an inception cohort study of first-admission patients with psychosis. Patients were assessed six times over 20 years, and 249 provided DNA. Geographically- and demographically-matched never psychotic adults were recruited at year 20, and 205 provided DNA. Symptoms were rated using the Schedule for the Assessment of Positive Symptoms and Schedule for the Assessment of Negative Symptoms. Cognition was evaluated with a comprehensive neuropsychological battery. Illness severity and diagnosis were determined by consensus of study psychiatrists. SZ PRS was significantly higher in first-admission than never psychotic groups. Within the psychosis cohort, the SZ PRS predicted more severe negative symptoms (β = 0.21), greater illness severity (β = 0.28), and worse cognition (β = −0.35), across the follow-up. The SZ PRS was the strongest predictor of diagnostic shifts from affective to non-affective psychosis over the 20 years (AUC = 0.62). The SZ PRS predicts persistent differences in cognition and negative symptoms. The SZ PRS also predicts who among those who appear to have a mood disorder with psychosis at first admission will ultimately be diagnosed with a schizophrenia spectrum disorder. These findings show potential for the SZ PRS to become a tool for diagnosis and treatment planning.

ObjectivesThis scoping review aims to facilitate psychometric developments in the field of digital media usage and well-being in young people by (1) identifying core concepts in the area of “screen time” and digital media use in children, adolescents, and young adults, (2) synthesising existing research paradigms and measurement tools that quantify these dimensions, and (3) highlighting important areas of need to guide future measure development.DesignA scoping review of 140 sources (126 database, 14 grey literature) published between 2014 and 2019 yielded 162 measurement tools across a range of domains, users, and cultures. Database sources from Ovid MEDLINE, PsycINFO and Scopus were extracted, in addition to grey literature obtained from knowledge experts and organisations relevant to digital media use in children. To be included, the source had to: (1) be an empirical investigation or present original research, (2) investigate a sample/target population that included children or young persons between the ages of 0 and 25 years of age, and (3) include at least one assessment method for measuring digital media use. Reviews, editorials, letters, comments and animal model studies were all excluded.MeasuresBasic information, level of risk of bias, study setting, paradigm, data type, digital media type, device, usage characteristics, applications or websites, sample characteristics, recruitment methods, measurement tool information, reliability and validity.ResultsSignificant variability in nomenclature surrounding problematic use and criteria for identifying clinical impairment was discovered. Moreover, there was a paucity of measures in key domains, including tools for young children, whole families, disadvantaged groups, and for certain patterns and types of usage.ConclusionThis knowledge synthesis exercise highlights the need for the widespread development and implementation of comprehensive, multi-method, multilevel, and multi-informant measurement suites.

Patients with schizophrenia have a high prevalence of cigarette smoking and respond poorly to conventional treatments, highlighting the need for new therapies. We conducted a mechanistic, proof-of-concept study using bilateral deep repetitive transcranial magnetic stimulation (dTMS) of insular and prefrontal cortices at high frequency, using the specialized H4 coil. Feasibility of dTMS was tested for disruption of tobacco self-administration, insula target engagement, and insula circuit modulation, all of which were a priori outcomes of interest. Twenty patients completed the study, consisting of weekday dTMS sessions (randomization to active dTMS or sham; double-blind; 10 patients per group), a laboratory tobacco self-administration paradigm (pre/post assessments), and multimodal imaging (three MRI total sessions). Results showed that participants assigned to active dTMS were slower to initiate smoking their first cigarette compared with sham, consistent with smoking disruption. The imaging analyses did not reveal significant Time × Group interactions, but effects were in the anticipated directions. In arterial spin labeling analyses testing for target engagement, an overall decrease in insula blood flow, measured during a post-treatment MRI versus baseline, was numerically more pronounced in the active dTMS group than sham. In fMRI analyses, resting-state connectivity between the insula and default mode network showed a numerically greater change from baseline in the active dTMS group than sham, consistent with a functional change to insula circuits. Exploratory analyses further suggested a therapeutic effect of dTMS on symptoms of psychosis. These initial observations pave the way for future confirmatory studies of dTMS in smoking patients with schizophrenia.

IntroductionResearch on the relationship between digital media exposure and child development is complex, inconsistent and fraught with debate. A highlighted area of inadequacy surrounds the methodological limitations of measuring digital media use for both researchers and clinicians, alike. This protocol aims to (1) identify core concepts in the area of screen time and digital media use in children and adolescents (2) map existing research paradigms and screening/measurement tools that serve to underpin and operationalise core concepts and (3) provide an initial step in integrating these findings into a consolidated screening toolkit. It is expected this enterprise will help advance research and clinical evaluation in fields concerned with digital media use, namely medicine, child development and the social sciences.Methods and analysisThe planned scoping review will search relevant electronic databases, including Ovid MEDLINE, PsycINFO and Scopus, in addition to grey literature. All empirical investigations and presentation of original research will be considered, and measurement/screening tools for digital media usage in children and adolescents will be identified and reported on. Two reviewers will pilot test the screening criteria, and data extraction forms prior to independently screening all relevant literature and extracting the data. A three-stage synthesis process will be used to map the existent measurement and screening tools for digital media usage in children and adolescents.Ethics and disseminationThere are no ethical considerations for this scoping review. Plans for dissemination include publication in a top-tier, open-access journal, public presentations and conference proceedings. Presentation of the full scoping review has been accepted to the American Academy of Child & Adolescent Psychiatry 66th Annual Meeting.

The associations among normal personality and many mental disorders are well established, but it remains unclear whether and how symptoms of schizophrenia and schizotypal traits align with the personality taxonomy. This study examined the joint factor structure of normal personality, schizotypy, and schizophrenia symptoms in people with psychotic disorders (n = 288) and never-psychotic adults (n = 257) in the Suffolk County Mental Health Project. First, we evaluated the structure of schizotypal (positive schizotypy, negative schizotypy, and mistrust) and normal traits. In both the psychotic-disorder and never-psychotic groups, the best-fitting model had 5 factors: neuroticism, extraversion, conscientiousness, agreeableness, and psychoticism. The schizotypy traits were placed on different dimensions: negative schizotypy went on (low) extraversion, whereas positive schizotypy and mistrust went on psychoticism. Next, we added symptoms to the model. Numerous alternatives were compared, and the 5-factor model remained best-fitting. Reality distortion (hallucinations and delusions) and disorganization symptoms were placed on psychoticism, and negative symptoms were placed on extraversion. Models that separated symptom dimensions from trait dimensions did not fit well, arguing that taxonomies of symptoms and traits are aligned. This is the first study to show that symptoms of psychosis, schizotypy, and normal personality reflect the same underlying dimensions. Specifically, (low) extraversion, negative schizotypy, and negative symptoms form one spectrum, whereas psychoticism, positive schizotypy, and positive and disorganized symptoms form another. This framework helps to understand the heterogeneity of psychosis and comorbidity patterns found in psychotic disorders. It also underscores the importance of traits to understanding these disorders.

The late positive potential (LPP) is an event-related potential component that is sensitive to the motivational salience of stimuli. Children with a parental history of depression, an indicator of risk, have been found to exhibit an attenuated LPP to emotional stimuli. Research on depressive and anxiety disorders has organized these conditions into two empirical classes: distress and fear disorders. The present study examined whether parental history of distress and fear disorders was associated with the LPP to emotional stimuli in a large sample of adolescent girls. The sample of 550 girls (ages 13.5-15.5 years) with no lifetime history of depression completed an emotional picture-viewing task and the LPP was measured in response to neutral, pleasant and unpleasant pictures. Parental lifetime history of psychopathology was determined via a semi-structured diagnostic interview with a biological parent, and confirmatory factor analysis was used to model distress and fear dimensions. Parental distress risk was associated with an attenuated LPP to all stimuli. In contrast, parental fear risk was associated with an enhanced LPP to unpleasant pictures but was unrelated to the LPP to neutral and pleasant pictures. Furthermore, these results were independent of the adolescent girls' current depression and anxiety symptoms and pubertal status. The present study demonstrates that familial risk for distress and fear disorders may have unique profiles in terms of electrocortical measures of emotional information processing. This study is also one of the first to investigate emotional/motivational processes underlying the distress and fear disorder dimensions.

Individual differences in neuroticism, extraversion, and conscientiousness are associated with, and may predict onset of, internalizing disorders. These general traits can be parsed into facets, but there is a surprising paucity of research on facet risk for internalizing disorders. We examined general traits and facets of neuroticism, extraversion, and conscientiousness in predicting first onsets of depressive and anxiety disorders. A community sample of 550 adolescent females completed general and facet-level personality measures and diagnostic interviews. Interviews were re-administered 18 months later. First onsets of depressive disorders were predicted by neuroticism, extraversion, and conscientiousness. Facets predicting first onset of depression included depressivity (neuroticism facet) and lower positive emotionality and sociability (extraversion facets). First onsets of generalized anxiety disorder (GAD) were predicted by neuroticism, and particularly the facet of anxiousness. First onsets of social phobia were predicted at the facet level by anxiousness. First onsets of specific phobia were predicted by neuroticism, low conscientiousness, and all neuroticism facets. In multivariate analyses, first onsets of depression were uniquely predicted by depressivity, and onsets of GAD and social phobia were uniquely predicted by anxiousness over and above the general trait of neuroticism. General traits predict first onsets of depressive and anxiety disorders. In addition, more specific associations are evident at the facet level. Facets can refine our understanding of the links between personality and psychopathology risk, and provide finer-grained targets for personality-informed interventions.

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.

Classic conceptual frameworks explaining the relationship of personality traits to depression include the precursor and predisposition models. The former hypothesizes that depression is predicted by traits alone whereas the latter hypothesizes that stress, together with personality, predicts depression. Dynamic vulnerability models (DVM) expand on these perspectives by incorporating fluctuations in personality over time. The stress generation model provides an alternative view, positing that depression generates stress, creating a self-perpetuating cycle. However, these conceptual models are rarely directly compared. We tested these models, focusing on neuroticism and stressful life events that the participant may have contributed to, using path analysis in a sample of 550 never-depressed, adolescent females assessed five times over 3 years. A dynamic precursor model with stress generation was best supported. For the precursor component, neuroticism predicted subsequent depression across four assessment intervals. For the dynamic trait component, stressful life events predicted subsequent neuroticism at three of four intervals. Finally, in line with stress generation, depression consistently predicted subsequent stressful life events, and life events then predicted depression. Finding support for the DVM is noteworthy, as this is the first comprehensive test of this model. Moreover, results supported integrating stress generation with trait vulnerability. Continued use of integrated approaches and refining the statistical implementation of these theories is necessary to advance understanding of the development of depression.

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 ( = 181) were originally recruited from inpatient psychiatric facilities. Data were also collected from a geographically and demographically matched group with no psychosis history ( = 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 ( = 0.26-0.35), negative symptom severity ( = 0.17-0.25), and poor real-world functioning ( = 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 ( = 0.10); reduced Pe to global functioning was mediated by executive function and avolition ( = 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.