Developmental complexity, structural simplicity: a longitudinal, multi-method investigation of internalising and externalising symptoms in young people

This research involves a series of studies investigating various aspects of the development of mental disorder during late childhood and early adolescence (8-14 years) in a large nationwide longitudinal study in England. The first two studies examine the clinical validity and survey format equivalence of a child self-report measure of mental health, the Me and My School questionnaire, measuring symptoms in the two key domains of child psychopathology: internalising and externalising. The next two studies investigate the complexity of individuals’ symptom development by examining the developmental trajectories of internalising and externalising symptoms using latent class growth analysis, a method that allows the estimation of different person-centred trajectories of symptom development. Subsequently, the studies investigate the socio-demographic correlates (including gender, socio-economic status, ethnicity and age) of individuals with different trajectories. This is followed by examining the impact of these different types of trajectories on another key domain of child functioning: educational attainment. The fifth study focuses on the co-development of symptoms in the internalising and externalising domains in late childhood and early adolescence, trying to uncover patterns in their association and development over time in these two developmental periods. The last study, based on the results of the previous studies, aims to investigate the underlying structure of child psychopathology. Using hierarchical bi-factor analysis, the study explores the possibility of a general propensity for psychopathology that not only is a better predictor of future psychopathology but can lead to better models of specific disorders as well. The thesis contributes to increasing the understanding of complexities in symptom development and proposes a simpler structural model underlying symptoms. The analytic approach used highlights the value of modern data analytic techniques in increasing our understanding of the development of psychopathology