Learning disorders and difficulties: From a categorical to a dimensional perspective

Abstract

According to the emerging dimensional framework, most neurodevelopmental disorders may be conceptualised as extreme ends of developmental continua that span through the entire population (e.g., Astle et al., 2022; Peters & Ansari, 2019). This framework describes not only learning difficulties, but potentially most neurodiversity as the result of individuals being distributed along a manifold of variously correlated and continuous dimensions, that span from neurotypicality to neurodivergence in a largely seamless way. In this, a heterogeneous range of conditions may easily be reframed as part of the general variability in the population, rather than as segmented subpopulations with qualitatively different features. In the present editorial, we discuss this framework with reference to the field of learning disorders and difficulties. We will repeatedly refer to the suggestions made by Astle et al. (2022) in their review on the “transdiagnostic revolution” of neurodevelopmental disorders. The research program that they advocate has two methodological tenets: investigating underlying continuous dimensions (dimensional framework), and exploring clustering (with an eye to potentially developing new data-driven taxonomies). Here, we mainly endorse adopting a dimensional framework, at least in the field of learning disorders, while we raise some cautionary notes on the risks of clustering. We also discuss open issues related to recruiting participants, improving psychometrics tools, and discovering cognitive and non-cognitive correlates of conditions when it comes to studying learning difficulties and learning disorders.