Cognition varies across the calendar year in multiple large-scale datasets
Abstract
Children’s cognitive abilities vary across short and long timescales, from circadian fluctuations to year-by-year developmental changes. “Summer slide” refers to seasonal variation in academic performance, characterized by decreased performance following an extended school vacation. However, it remains unclear whether this effect generalizes across varied assessments and the extent of this effect across sociodemographic groups has been debated. Though seasonal variation in cognitive performance is often attributed to “forgetting” of learned material, no large-scale studies have systematically investigated seasonal variation in general cognitive skills (e.g., executive functioning) on standardized laboratory-based assessments in school-age youth compared to adults. Across four datasets with geographic, demographic, mental health, and measurement variation (total n = 23,251), we quantify cyclical, seasonal variation in children’s cognitive performance using generalized additive models with cyclic cubic splines. In school-age children but not young adults, we found consistent cognitive performance minima following school vacation (July–September in the United States; November–January in Singapore) across nearly all cognitive domains investigated. These results demonstrate a generalizable small-magnitude effect of lower cognitive performance aligning with school vacation even after adjusting for socioeconomic status or ADHD diagnosis. We contextualize summer cognitive minima relative to environmental and developmental effects, noting that the largest effect size is still seven times smaller than effects of the socioeconomic environment on cognition, and provide recommendations for future data collection and analysis of behavior across the calendar year.
Article Details
Journal Info
Proceedings of the National Academy of Sciences
National Academy of Sciences
Authors (18)
Arielle S. Keller
Department of Psychological Sciences, University of Connecticut
Alisha Shetty
Department of Psychiatry, University of Pennsylvania
Ran Barzilay
Department of Psychiatry, University of Pennsylvania
Monica E. Calkins
Department of Psychiatry, University of Pennsylvania
Yap-Seng Chong
Institute for Human Development and Potential, Agency for Science, Technology and Research
Niyati Dave
Department of Psychological Sciences, University of Connecticut
Damien A. Fair
Department of Pediatrics, University of Minnesota
Peter D. Gluckman
Institute for Human Development and Potential, Agency for Science, Technology and Research
Raquel E. Gur
Department of Psychiatry, University of Pennsylvania
Ruben C. Gur
Department of Psychiatry, University of Pennsylvania
Allyson P. Mackey
Department of Psychology, University of Pennsylvania
Michael J. Meaney
Institute for Human Development and Potential, Agency for Science, Technology and Research
Lucille A. Moore
Masonic Institute for the Developing Brain, University of Minnesota
Tyler M. Moore
Department of Psychiatry, University of Pennsylvania
Theodore D. Satterthwaite
Department of Psychiatry, University of Pennsylvania
Ai Peng Tan
Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore
Brenden Tervo-Clemmens
Institute of Child Development, University of Minnesota
Bart S. Larsen
Department of Pediatrics, University of Minnesota