ObjectiveThere has been widespread concern that so-called lockdown measures, including social distancing and school closures, could negatively impact children’s mental health. However, there has been little direct evidence of any association due to the paucity of longitudinal studies reporting mental health before and during the lockdown. This present study provides the first longitudinal examination of changes in childhood mental health, a key component of an urgently needed evidence base that can inform policy and practice surrounding the continuing response to the COVID-19 pandemic.MethodsMental health assessments on 168 children (aged 7.6–11.6 years) were taken before and during the UK lockdown (April–June 2020). Assessments included self-reports, caregiver reports, and teacher reports. Mean mental health scores before and during the UK lockdown were compared using mixed linear models.ResultsA significant increase in depression symptoms during the UK lockdown was observed, as measured by the Revised Child Anxiety and Depression Scale (RCADS) short form. CIs suggest a medium-to-large effect size. There were no significant changes in the RCADS anxiety subscale and Strengths and Difficulties Questionnaire emotional problems subscale.ConclusionsDuring the UK lockdown, children’s depression symptoms have increased substantially, relative to before lockdown. The scale of this effect has direct relevance for the continuation of different elements of lockdown policy, such as complete or partial school closures. This early evidence for the direct impact of lockdown must now be combined with larger scale epidemiological studies that establish which children are most at risk and tracks their future recovery.
The formation of large-scale brain networks, and their continual refinement, represent crucial developmental processes that can drive individual differences in cognition and which are associated with multiple neurodevelopmental conditions. But how does this organization arise, and what mechanisms drive diversity in organization? We use generative network modeling to provide a computational framework for understanding neurodevelopmental diversity. Within this framework macroscopic brain organization, complete with spatial embedding of its organization, is an emergent property of a generative wiring equation that optimizes its connectivity by renegotiating its biological costs and topological values continuously over time. The rules that govern these iterative wiring properties are controlled by a set of tightly framed parameters, with subtle differences in these parameters steering network growth towards different neurodiverse outcomes. Regional expression of genes associated with the simulations converge on biological processes and cellular components predominantly involved in synaptic signaling, neuronal projection, catabolic intracellular processes and protein transport. Together, this provides a unifying computational framework for conceptualizing the mechanisms and diversity in neurodevelopment, capable of integrating different levels of analysis—from genes to cognition.
In response to the COVID-19 epidemic, the United Kingdom Government implemented a national “lockdown” involving school closures and social distancing. Little is known about the impact of these policies on children’s mental health. This is in part due to the paucity of recent pre-lockdown baseline data. We report results from a cohort of children living in East of England. This cohort had recently been assessed via combination of parent-, teacher- and self-reports of mental health, and have been followed up with a parent-reported survey during lockdown. We found a medium-to-large increase in depression symptoms during lockdown, and smaller, non-significant changes in SDQ Emotional Problems and anxiety symptoms.
A child’s socio-economic status has been independently associated with poorer educational outcomes, slower cognitive development, and mental ill-health. However, while these factors clearly do not operate in a vacuum, testing all within a single study is challenging, and their interrelations thus remain largely unclear. We aimed to close this knowledge gap by developing a comprehensive tablet-based assessment of developmental variables in a sample of 519 children aged 7-9 years. We employed clustering algorithms to show that children do not group into discrete phenotypes. We then cast the broad range of measured variables as a network to explore the psychological architecture of cognitive, educational, mental health, and several environmental factors. Educational outcomes (reading and maths fluency) were directly related to cognition (short-term memory, number sense, and processing speed). By contrast, mental health (anxiety and depression symptoms) and attitudes (conscientious, grit, and growth mindset) showed indirect relationships with school outcomes by moderating cognition. Finally, socio-economic factors (neighbourhood deprivation and family affluence) related directly to educational outcomes, cognition, mental health, and even grit. In sum, cognition is the central cog through which mental health and attitude relate to educational outcomes. However, socio-economic status acts as the great unequaliser through its direct relations with all developmental outcomes.
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