Abstract
Childhood adversity can lead to cognitive deficits or enhancements, depending on many factors. Though progress has been made, two challenges prevent us from integrating and better understanding these patterns. First, studies commonly use and interpret raw performance differences, such as response times, which conflate different stages of cognitive processing. Second, most studies either isolate or aggregate abilities, obscuring the degree to which individual differences reflect task-general (shared) or task-specific (unique) processes. We addressed these challenges using Drift Diffusion Modeling (DDM) and structural equation modeling (SEM). Leveraging a large, representative sample of 9–10 year-olds from the Adolescent Brain Cognitive Development (ABCD) study, we examined how two forms of adversity—material deprivation and household threat—were associated with performance on tasks measuring processing speed, inhibition, attention shifting, and mental rotation. Using DDM, we decomposed performance on each task into three distinct stages of processing: speed of information uptake, response caution, and stimulus encoding/response execution. Using SEM, we isolated task-general and task-specific variances in each processing stage and estimated their associations with the two forms of adversity. Youth with more exposure to household threat (but not material deprivation) showed slower task-general processing speed, but showed intact task-specific abilities. In addition, youth with more exposure to household threat tended to respond more cautiously in general. These findings suggest that traditional assessments might overestimate the extent to which childhood adversity reduces specific abilities. By combining DDM and SEM approaches, we can develop a more nuanced understanding of how adversity affects different aspects of youth's cognitive performance. Research Highlight: To understand how childhood adversity shapes cognitive abilities, the field needs analytical approaches that can jointly document and explain patterns of lowered and enhanced performance. Using Drift Diffusion Modeling and Structural Equation Modeling, we analyzed associations between adversity and processing speed, inhibition, attention shifting, and mental rotation. Household threat, but not material deprivation, was mostly associated with slower task-general processing speed and more response caution. In contrast, task-specific abilities were largely intact. Researchers might overestimate the impact of childhood adversity on specific abilities and underestimate the impact on general processing speed and response caution using traditional measures.
Original language | English |
---|---|
Article number | e13478 |
Number of pages | 17 |
Journal | Developmental Science |
Volume | 27 |
Issue number | 4 |
Early online date | 6 Feb 2024 |
DOIs | |
Publication status | Published - Jul 2024 |
Bibliographical note
Publisher Copyright:© 2024 The Authors. Developmental Science published by John Wiley & Sons Ltd.
Funding
Data used in the preparation of this article were obtained from the Adolescent Brain Cognitive Development (ABCD) Study ( https://abcdstudy.org ), held in the NIMH Data Archive (NDA). This is a multisite, longitudinal study designed to recruit more than 10,000 children age 9–10 and follow them over 10 years into early adulthood. The ABCD Study is supported by the National Institutes of Health and additional federal partners under award numbers U01DA041048, U01DA050989, U01DA051016, U01DA041022, U01DA051018, U01DA051037, U01DA050987, U01DA041174, U01DA041106, U01DA041117, U01DA041028, U01DA041134, U01DA050988, U01DA051039, U01DA041156, U01DA041025, U01DA041120, U01DA051038, U01DA041148, U01DA041093, U01DA041089, U24DA041123, U24DA041147. A full list of supporters is available at https://abcdstudy.org/federal‐partners.html . A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/consortium_members/ . ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in the analysis or writing of this report. This manuscript reflects the views of the authors and may not reflect the opinions or views of the NIH or ABCD consortium investigators. The ABCD data repository grows and changes over time. The ABCD data used in this report came from Data Release 4.0 (DOI: https://doi.org/10.15154/1523041 ). WEF's contributions have been supported by the Dutch Research Council (V1.Vidi.195.130) and the James S. McDonnell Foundation (https://doi.org/10.37717/220020502) MLD was supported by the National Institute of Child Health and Human Development (NICHD) (1F32HD112065‐01).
Funders | Funder number |
---|---|
National Institutes of Health | U01DA051039, U01DA051016, U01DA051038, U01DA051018, U01DA051037, U01DA041106, U01DA041117, U01DA041028, U01DA041148, U24DA041147, U01DA041048, U01DA041025, U24DA041123, U01DA041134, U01DA041156, U01DA041089, U01DA041022, U01DA041120, U01DA041174, U01DA050987, U01DA050988, U01DA050989, U01DA041093 |
National Institutes of Health | |
James S. McDonnell Foundation | |
Nederlandse Organisatie voor Wetenschappelijk Onderzoek | V1.Vidi.195.130 |
Nederlandse Organisatie voor Wetenschappelijk Onderzoek |
Keywords
- Adolecent Brain Cognitive Development (ABCD) Study
- Adversity
- Cognitive deficits
- Cognitive enhancements
- Drift Diffusion Modeling