Background: Most mental health difficulties have their onset during childhood and adolescence. Many children who suffer from one mental health issue also suffer from at least one comorbid disorder. Autoregressive latent trajectory models with structured residuals (ALT-SR) and multilevel graphical vector autoregression (GVAR) are recent complementary approaches that can help provide new insights into the reciprocal relationships between multiple mental health domains and advance the understanding of the development of comorbidities.Methods: This study uses ALT-SR and multilevel GVAR models to analyse the temporal, contemporaneous and between-person relationships between emotional problems, peer problems, conduct problems, hyperactivity/inattention and prosociality as measured by the parent-reported Strengths and Difficulties Questionnaire (SDQ) in 17,478 children taking part in the UK Millennium Cohort Study at ages 3, 5, 7, 11, 14 and 17 years. Results: Results from both the ALT-SR model and the multilevel GVAR model highlight that children’s strengths and difficulties in different domains of psychosocial functioning dynamically influence each other over- and within-time. The ALT-SR model highlighted that hyperactivity/inattention plays a central role in affecting other domains over developmental time while the GVAR model highlighted comparably strong bidirectional relationships between conduct problems and prosociality as well as between emotional problems and peer problems. Both models suggest that most domains are also related to each other over shorter timescales.Conclusion: This study highlights that mental health difficulties influence one another dynamically over time. As illustrated in the domains of the SDQ, these dynamic changes can be modelled using the complementary techniques of ALT-SR or GVAR models, each offering different insights into the nature of comorbidity.
Changes in the understory diversity of secondary Pinus tabulaeformis forests are the result of stand density and soil properties
