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.

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, , 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.

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).