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- W2890923791 abstract "Aim Research has shown that Latent Class Growth Modelling (LCGM) techniques can be applied to discover heterogeneous trajectories of autistic traits (ATs) within diagnosed samples. However, no studies have yet applied LCGM to general population participants. This study aimed to use LCGM to examine latent trajectories of ATs in a large, general population cohort. Methods Growth Mixture Modelling (GMM) was applied to Social and Communication Difficulties Checklist (Skuse et al, 2005) scores at ages 7, 10, 13 and 16. Data were from 9,744 participants in the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Sex, IQ and general difficulties were investigated in relation to latent classes. Results Six latent classes of ATs over time were observed, characterised by persistent high, persistent low, early increasing, later increasing, high decreasing and moderate decreasing trajectories. Females were overrepresented in the later developing trajectory. General difficulties followed similar growth patterns to ATs within groups. Conclusions A six-class model characterised development of ATs. Evidence was found to support the observation that girls display symptoms later than boys and are likely to be under-diagnosed. Further characterising latent trajectory classes of ATs in the general population could improve understanding of aetiology, genetics and treatment." @default.
- W2890923791 created "2018-09-27" @default.
- W2890923791 creator A5059063373 @default.
- W2890923791 date "2017-09-26" @default.
- W2890923791 modified "2023-09-24" @default.
- W2890923791 title "Latent Trajectories of Autistic Traits in the General Population" @default.
- W2890923791 hasPublicationYear "2017" @default.
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