Individuals withADHDoften exhibit differences inworking memory functions, which are crucial for holding and manipulating information in the short term.
These differences can significantly impact various cognitive processes, including mathematical abilities.
Working memory is essential for math tasks such as mental arithmetic, problem-solving, and understanding complex mathematical concepts.
By studying math ability in individuals with ADHD, researchers can better understand the cognitive mechanisms underlying their academic challenges and develop more targeted interventions.
Key Points
Rationale
Attention Deficit Hyperactivity Disorder (ADHD) affects 1-2% of children, with an additional 5% experiencing subthreshold symptoms (Czamara et al., 2013; Hong et al., 2014).
Children with ADHD often struggle with math (Capano et al., 2008; DuPaul et al., 2013), but the relationship between ADHD and math performance is not consistent across studies (Capodieci & Martinussen, 2017).
This variability may be due to differences in underlying cognitive abilities (Geary et al., 2007; Kofler et al., 2017).
Executive functions(EF) have been implicated in both ADHD symptoms and math abilities (Biederman et al., 2004; Cragg et al., 2017).
However, there is marked heterogeneity in EF performance among individuals with ADHD (Coghill et al., 2014; Kofler et al., 2019).
This study aimed to explore whether cognitive function, particularly EF profiles, better predicted math performance than ADHD diagnosis in children referred for ADHD assessment.
The research took a transdiagnostic approach, reflecting the common co-occurrences in neurodivergent children, which is often overlooked in ADHD studies (Goulardins et al., 2015).
By using an undiagnosed sample on an ADHD referral pathway, the study ensured participants were drug-naïve and allowed for direct comparison between those who did and did not receive a diagnosis.
Method
Procedure
The study employed across-sectional design. Participants completed a comprehensive battery of cognitive assessments, including tests of executive functions, intelligence, and math skills.
Parents completed questionnaires about their child’s ADHD symptoms and co-occurring difficulties.
Sample
44 drug-naïve children (70% boys) aged 6-12 years (M = 101.34 months, SD = 19.39) were recruited from a clinical ADHD referral waiting list at an NHS Child and Adolescent Mental Health Service in Scotland.
All children scored high on ADHD symptom scales. After clinical evaluation, 24 children received an ADHD diagnosis, 15 did not, and 5 were awaiting confirmation.
Measures
Statistical measures
The study used two main analytical approaches:
Results
Hypothesis 1:Cognitive function will better predict math performance than ADHD diagnosis.
Result:Supported. The diagnostic approach (ADHD vs. subclinical ADHD) did not differentiate cognitive functioning or math outcomes. In contrast, data-driven EF clusters showed significant differences in math performance.
Hypothesis 2:Data-driven EF clusters will show distinct profiles in math performance.
Result:Supported. Three EF clusters were identified:
Hypothesis 3:EF clusters will not differ significantly in ADHD symptoms or co-occurring disorders.
Result:Supported. No significant differences were found between clusters in ADHD symptoms or co-occurring disorder symptoms.
Insight
This study provides compelling evidence that cognitive profiles, particularly executive function patterns, are more informative than diagnostic categories in predicting math performance among children referred for ADHD assessment.
The identification of three distinct EF clusters (Low Working Memory, Low Visuospatial EF, and Relatively Intact EF) highlights the cognitive heterogeneity within ADHD and its impact on academic outcomes.
This suggests that interventions targeting working memory could be particularly beneficial for improving math performance in this population.
The study also underscores the limitations of categorical diagnostic approaches in understanding academic difficulties in ADHD.
The lack of significant differences between children diagnosed with ADHD and those with subclinical symptoms in terms of cognitive functioning and math outcomes challenges the utility of strict diagnostic cutoffs in educational contexts.
Future research could explore the stability of these EF clusters over time and investigate whether targeted interventions based on a child’s EF profile lead to improved academic outcomes.
Additionally, examining how these cognitive profiles relate to other academic domains beyond math could provide a more comprehensive understanding of learning difficulties in ADHD.
Strengths
This study had several methodological strengths, including:
Limitations
This study also had several methodological limitations, including:
These limitations restrict the generalizability of the findings and highlight the need for larger, longitudinal studies to confirm and extend the results.
Implications
The results have significant implications for both clinical practice and educational interventions:
References
Primary reference
Kanevski, M., Booth, J. N., Stewart, T. M., & Rhodes, S. M. (2024). Cognitive heterogeneity in Attention Deficit Hyperactivity Disorder: Implications for maths.British Journal of Developmental Psychology.https://doi.org/10.1111/bjdp.12517
Other references
Capano, L., Minden, D., Chen, S. X., Schachar, R. J., & Ickowicz, A. (2008). Mathematical learning disorder in school-age children with attention-deficit hyperactivity disorder.The Canadian Journal of Psychiatry,53(6), 392-399.https://doi.org/10.1177/070674370805300609
Coghill, D. R., Seth, S., & Matthews, K. (2014). A comprehensive assessment of memory, delay aversion, timing, inhibition, decision making and variability in attention deficit hyperactivity disorder: advancing beyond the three-pathway models.Psychological medicine,44(9), 1989-2001.
Cragg, L., Keeble, S., Richardson, S., Roome, H. E., & Gilmore, C. (2017). Direct and indirect influences of executive functions on mathematics achievement.Cognition,162, 12-26.https://doi.org/10.1016/j.cognition.2017.01.014
Czamara, D., Tiesler, C. M., Kohlböck, G., Berdel, D., Hoffmann, B., Bauer, C. P., … & Heinrich, J. (2013). Children with ADHD symptoms have a higher risk for reading, spelling and math difficulties in the GINIplus and LISAplus cohort studies.PloS one,8(5), e63859.https://doi.org/10.1371/journal.pone.0063859
DuPaul, G. J., Gormley, M. J., & Laracy, S. D. (2013). Comorbidity of LD and ADHD: Implications of DSM-5 for assessment and treatment.Journal of learning disabilities,46(1), 43-51.https://doi.org/10.1177/0022219412464351
Geary, D. C., Hoard, M. K., Byrd‐Craven, J., Nugent, L., & Numtee, C. (2007). Cognitive mechanisms underlying achievement deficits in children with mathematical learning disability.Child development,78(4), 1343-1359.https://doi.org/10.1111/j.1467-8624.2007.01069.x
Goulardins, J. B., Marques, J. C., & De Oliveira, J. A. (2017). Attention deficit hyperactivity disorder and motor impairment: A critical review.Perceptual and motor skills,124(2), 425-440.https://doi.org/10.1177/0031512517690607
Hong, S. B., Dwyer, D., Kim, J. W., Park, E. J., Shin, M. S., Kim, B. N., … & Cho, S. C. (2014). Subthreshold attention-deficit/hyperactivity disorder is associated with functional impairments across domains: a comprehensive analysis in a large-scale community study.European child & adolescent psychiatry,23, 627-636.https://doi.org/10.1007/s00787-013-0501-z
Kofler, M. J., Irwin, L. N., Soto, E. F., Groves, N. B., Harmon, S. L., & Sarver, D. E. (2019). Executive functioning heterogeneity in pediatric ADHD.Journal of abnormal child psychology,47, 273-286.https://doi.org/10.1007/s10802-018-0438-2
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Saul McLeod, PhD
BSc (Hons) Psychology, MRes, PhD, University of Manchester
Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.
Olivia Guy-Evans, MSc
BSc (Hons) Psychology, MSc Psychology of Education
Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.
