Towards indicated prevention of psychosis: using probabilistic assessments of transition risk in psychosis prodrome.

The concept of indicated prevention has proliferated in psychiatry, and accumulating evidence suggests that it may indeed be possible to prevent or delay the onset of a first episode of psychosis though adequate interventions in individuals deemed at clinical high risk (CHR) for such an event. One challenge undermining these efforts is the relatively poor predictive accuracy of clinical assessments used in practice for CHR individuals, often leading to diagnostic and therapeutic uncertainty reflected in clinical guidelines promoting a 'watch and wait' approach to CHR patients. Using data from published studies, and employing predictive models based on the odds-ratio form of Bayes' rule, we simulated scenarios where clinical interview, neurocognitive testing, structural magnetic resonance imaging and electrophysiology are part of the initial assessment process of a CHR individual (extended diagnostic approach). Our findings indicate that for most at-risk patients, at least three of these assessments are necessary to arrive at a clinically meaningful differentiation into high- intermediate-, and low-risk groups. In particular, patients with equivocal results in the initial assessments require additional diagnostic testing to produce an accurate risk profile forming part of the comprehensive initial assessment. The findings may inform future research into reliable identification and personalized therapeutic targeting of CHR patients, to prevent transition to full-blown psychosis.

Long-term recreational exercise patterns in adolescents and young adults: Trajectory predictors and associations with health, mental-health, and educational outcomes.

Individual and societal factors influencing the formation of long-term recreational exercise habits during the transition from adolescence to young adulthood are not well explored. Using data from the Longitudinal Survey of Australian Youth (LSAY), a population-representative cohort study of Young People followed from age 15 to 25, we aimed to (1) model longitudinal recreational exercise trajectories from age 16 to 24, (2) examine predictors at age 15 of entering these trajectories, and (3) explore the association between the trajectories and health, mental health and educational achievement outcomes measured at the final study wave (age 25). Self-reported recreational exercise frequency data from 9353 LSAY participants were analysed using group-based trajectory modelling. We modelled the evolution of two patterns of recreational exercise behaviour: daily exercise, as per public health guidelines (Model 1); and at least once weekly exercise (Model 2). Model 1 trajectories were guideline-adherent exercisers (17.9% of the sample), never guideline exercisers (27.5%), guideline drop-outs (15.2%) and towards guideline (39.4%); Model 2 trajectories were weekly exercise (69.5% of the sample), decreasing (17.4%), increasing (4.8%), and infrequent (8.3%). For both models, at age 15, trajectory membership was predicted by gender, self-efficacy, time spent participating in sport, time spent watching TV, parental socioeconomic status, and academic literacy. At age 25, people in the guideline-adherent exerciser trajectory (model 1) reported better general health relative to other trajectories, Those in the weekly exerciser trajectory (model 2) had better general health and reduced rates of psychological distress, were happier with life and were more optimistic for the future relative to participants in less than weekly trajectory groups. Exercise-promoting interventions for Young People should specifically address the needs of females, people with low self-efficacy, reluctant exercisers, higher academic achievers, and those experiencing socioeconomic disadvantage.

Multifactorial structure of cognitive assessment tests in the UK Biobank: A combined exploratory factor and structural equation modeling analyses.

Introduction: The UK Biobank cognitive assessment data has been a significant resource for researchers looking to investigate predictors and modifiers of cognitive abilities and associated health outcomes in the general population. Given the diverse nature of this data, researchers use different approaches - from the use of a single test to composing the general intelligence score, g, across the tests. We argue that both approaches are suboptimal - one being too specific and the other one too general - and suggest a novel multifactorial solution to represent cognitive abilities. Methods: Using a combined Exploratory Factor (EFA) and Exploratory Structural Equation Modeling Analyses (ESEM) we developed a three-factor model to characterize an underlying structure of nine cognitive tests selected from the UK Biobank using a Cattell-Horn-Carroll framework. We first estimated a series of probable factor solutions using the maximum likelihood method of extraction. The best solution for the EFA-defined factor structure was then tested using the ESEM approach with the aim of confirming or disconfirming the decisions made. Results: We determined that a three-factor model fits the UK Biobank cognitive assessment data best. Two of the three factors can be assigned to fluid reasoning (Gf) with a clear distinction between visuospatial reasoning and verbal-analytical reasoning. The third factor was identified as a processing speed (Gs) factor. Discussion: This study characterizes cognitive assessment data in the UK Biobank and delivers an alternative view on its underlying structure, suggesting that the three factor model provides a more granular solution than g that can further be applied to study different facets of cognitive functioning in relation to health outcomes and to further progress examination of its biological underpinnings.