Jenny Retzler
Using drift diffusion modeling to understand inattentive behavior in preterm and term-born children.
Retzler, Jenny; Retzler, Chris; Groom, Madeleine; Johnson, Samantha; Cragg, Lucy
Authors
Chris Retzler
Professor MADDIE GROOM maddie.groom@nottingham.ac.uk
PROFESSOR OF NEURODEVELOPMENTAL CONDITIONS
Samantha Johnson
Professor LUCY CRAGG lucy.cragg@nottingham.ac.uk
PROFESSOR OF DEVELOPMENTAL PSYCHOLOGY
Abstract
Objective: Children born very preterm are at increased risk of inattention, but it remains unclear whether the underlying processes are the same as in their term-born peers. Drift diffusion modelling (DDM) may better characterise the cognitive processes underlying inattention than standard reaction time (RT) measures. This study used DDM to compare the processes related to inattentive behaviour in preterm and term-born children.
Method: Performance on a cued continuous performance task was compared between 33 children born very preterm (VP; ≤32 weeks’ gestation) and 32 term-born peers (≥37 weeks’ gestation), aged 8-11 years. Both groups included children with a wide spectrum of parent-rated inattention (above average attention to severe inattention). Performance was defined using standard measures (RT, RT variability and accuracy) and modelled using a DDM. A hierarchical regression assessed the extent to which standard or DDM measures explained variance in parent-rated inattention and whether these relationships differed between VP and term-born children.
Results: There were no group differences in performance on standard or DDM measures of task performance. Parent-rated inattention correlated significantly with hit rate, RT variability, and drift rate (a DDM estimate of processing efficiency) in one or both groups. Regression analysis revealed that drift rate was the best predictor of parent-rated inattention. This relationship did not differ significantly between groups.
Conclusions: Findings suggest that less efficient information processing is a common mechanism underlying inattention in both VP and term-born children. This study demonstrates the benefits of using DDM to better characterise atypical cognitive processing in clinical samples.
Citation
Retzler, J., Retzler, C., Groom, M., Johnson, S., & Cragg, L. (2020). Using drift diffusion modeling to understand inattentive behavior in preterm and term-born children. Neuropsychology, 34(1), 77-87. https://doi.org/10.1037/neu0000590
Journal Article Type | Article |
---|---|
Acceptance Date | Jun 24, 2019 |
Online Publication Date | Oct 3, 2019 |
Publication Date | Jan 1, 2020 |
Deposit Date | Jun 28, 2019 |
Publicly Available Date | Jun 28, 2019 |
Journal | Neuropsychology |
Print ISSN | 0894-4105 |
Electronic ISSN | 1931-1559 |
Publisher | American Psychological Association |
Peer Reviewed | Peer Reviewed |
Volume | 34 |
Issue | 1 |
Pages | 77-87 |
DOI | https://doi.org/10.1037/neu0000590 |
Keywords | Attention; Very preterm; Drift diffusion model; Information processing |
Public URL | https://nottingham-repository.worktribe.com/output/2237345 |
Publisher URL | https://psycnet.apa.org/fulltext/2019-58357-001.html |
Additional Information | ©American Psychological Association, [2019]. This paper is not the copy of record and may not exactly replicate the authoritative document published in the APA journal. Please do not copy or cite without author's permission. The final article is available, upon publication, at: http://dx.doi.org/10.1037/neu0000590 |
Contract Date | Jun 28, 2019 |
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