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| Content Provider | Springer Nature : BioMed Central |
|---|---|
| Author | Coolen, Ilse E. J. I. van Langen, Jordy Hofman, Sophie van Aagten, Fréderique E. Schaaf, Jessica V. Michel, Lea Aristodemou, Michael Judd, Nicholas van Hout, Aran T. B. Meeussen, Emma Kievit, Rogier A. |
| Abstract | Background Children’s cognitive performance fluctuates across multiple timescales. However, fluctuations have often been neglected in favour of research into average cognitive performance, limiting the unique insights into cognitive abilities and development that cognitive variability may afford. Preliminary evidence suggests that greater variability is associated with increased symptoms of neurodevelopmental disorders, and differences in behavioural and neural functioning. The relative dearth of empirical work on variability, historically limited due to a lack of suitable data and quantitative methodology, has left crucial questions unanswered, which the CODEC (COgnitive Dynamics in Early Childhood) study aims to address. Method The CODEC cohort is an accelerated 3-year longitudinal study which encompasses 600 7-to-10-year-old children. Each year includes a ‘burst’ week (3 times per day, 5 days per week) of cognitive measurements on five cognitive domains (reasoning, working memory, processing speed, vocabulary, exploration), conducted both in classrooms and at home through experience sampling assessments. We also measure academic outcomes and external factors hypothesised to predict cognitive variability, including sleep, mood, motivation and background noise. A subset of 200 children (CODEC-MRI) are invited for two deep phenotyping sessions (in year 1 and year 3 of the study), including structural and functional magnetic resonance imaging, eye-tracking, parental measurements and questionnaire-based demographic and psychosocial measures. We will quantify developmental differences and changes in variability using Dynamic Structural Equation Modelling, allowing us to simultaneously capture variability and the multilevel structure of trials nested in sessions, days, children and classrooms. Discussion CODEC’s unique design allows us to measure variability across a range of different cognitive domains, ages, and temporal resolutions. The deep-phenotyping arm allows us to test hypotheses concerning variability, including the role of mind wandering, strategy exploration, mood, sleep, and brain structure. Due to CODEC’s longitudinal nature, we are able to quantify which measures of variability at baseline predict long-term outcomes. In summary, the CODEC study is a unique longitudinal study combining experience sampling, an accelerated longitudinal ‘burst’ design, deep phenotyping, and cutting-edge statistical methodologies to better understand the nature, causes, and consequences of cognitive variability in children. Trial registration ClinicalTrials.gov - NCT06330090 |
| Related Links | https://bmcpsychology.biomedcentral.com/counter/pdf/10.1186/s40359-024-01904-5.pdf |
| Ending Page | 26 |
| Page Count | 26 |
| Starting Page | 1 |
| File Format | HTM / HTML |
| ISSN | 20507283 |
| DOI | 10.1186/s40359-024-01904-5 |
| Journal | BMC Psychology |
| Issue Number | 1 |
| Volume Number | 12 |
| Language | English |
| Publisher | BioMed Central |
| Publisher Date | 2024-07-26 |
| Access Restriction | Open |
| Subject Keyword | Psychology Research Clinical Psychology Cognitive Psychology Intra-individual variability Cognitive development Fluctuations DSEM Longitudinal |
| Content Type | Text |
| Resource Type | Article |
| Subject | Medicine Psychology |
| Journal Impact Factor | 2.7/2023 |
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