Identifying and subtyping dyscalculia in a sample of children with and without dyscalculia - a data-driven approach
| dc.contributor.author | Kißler, Christian | |
| dc.contributor.author | Kuhn, Jörg-Tobias | |
| dc.date.accessioned | 2025-10-06T09:15:38Z | |
| dc.date.available | 2025-10-06T09:15:38Z | |
| dc.date.issued | 2025-09-23 | |
| dc.description.abstract | Introduction: Dyscalculia is a very heterogeneous disorder. This is illustrated by the fact that numerous possible subtypes have been described in previous studies. Therefore, the present study addresses the question of whether children with dyscalculia form a homogeneous group that can be distinguished from children without dyscalculia or whether distinct dyscalculia subtypes should be assumed. Methods: A sample of 1,015 children was analyzed in a data-driven subtyping approach (mixture model analysis). 93 of these children were identified as dyscalculic (criterion: percentage rank <10) with a standardized test (HRT 1–4) to examine how these children were distributed across the identified subtypes. Various cognitive performance domains that were measured with standardized tests were included in the analyses: mathematical skills (basic numerical processing, complex number processing, calculation), working memory, reading fluency, and intelligence. To check the subgrouping results for robustness, four different approaches were used, which differed with respect to which variables were included in the mixture model analysis (only mathematical skills: n1 = 1,015/ all variables: n2 = 478; n2 with a reduced sample size according to missing data) and to what extent the measured results were aggregated into constructs (construct level) or considered as individual test results (subtest level). Results: In three of these four different subtyping approaches, at least one of the identified subgroups showed significant deficits in mathematical skills and included disproportionately many children with dyscalculia. Furthermore, one of these three approaches (the subtyping analysis at the subtest level based on mathematical skills only) suggests that there may be two subtypes of children with dyscalculia: a subtype with mild deficits and a severely impaired subtype. In one approach (subtyping analysis at the construct level with all variables included), children with dyscalculia were not identified as a separable group. Discussion: In summary, dyscalculia subtypes (as well as children with dyscalculia in general) do not seem to be clearly distinguishable from children without dyscalculia: the boundaries are fluid. For educational practice, this fluent transition between dyscalculic and non-dyscalculic children means that all children who have difficulties in mathematics should be supported and not only those who are classified as dyscalculic. | en |
| dc.identifier.uri | http://hdl.handle.net/2003/44010 | |
| dc.language.iso | en | |
| dc.relation.ispartofseries | Frontiers in psychology; 16 | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Dyscalculia | en |
| dc.subject | Subtypes | en |
| dc.subject | Learning disorder | en |
| dc.subject | Working memory | en |
| dc.subject | Reading fluency | en |
| dc.subject | Mathematical competence | en |
| dc.subject.ddc | 370 | |
| dc.subject.rswk | Rechenschwäche | |
| dc.subject.rswk | Lernstörung | |
| dc.title | Identifying and subtyping dyscalculia in a sample of children with and without dyscalculia - a data-driven approach | en |
| dc.type | Text | |
| dc.type.publicationtype | ResearchArticle | |
| dcterms.accessRights | open access | |
| eldorado.doi.register | false | |
| eldorado.secondarypublication | true | |
| eldorado.secondarypublication.primarycitation | Kißler C and Kuhn J-T (2025) Identifying and subtyping dyscalculia in a sample of children with and without dyscalculia — a data-driven approach. Front. Psychol. 16:1590581. doi: 10.3389/fpsyg.2025.1590581 | |
| eldorado.secondarypublication.primaryidentifier | https://doi.org/10.3389/fpsyg.2025.1590581 |