New Directions for Neurodevelopmental Conditions

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Jane, Julie, and Jemma are 6-year-old classmates. The three girls show several similarities in behaviour and cognition. All three struggle with starting new tasks, task-switching, sustaining attention, and remaining engaged in social interactions. All three show mild delays in language development.

Despite these similarities in daily functioning, Jane has been diagnosed with Autism Spectrum Disorder (autism). Julie has been diagnosed with inattentive type Attention Deficit Hyperactivity Disorder (ADHD). Jemma does not meet the diagnostic criteria for any condition.

Based on the above diagnostic classifications, Jane receives more support than Julie, and Jemma does not qualify for support at all. Moreover, even though Jane and Julie’s challenges in daily life are very similar, they both receive very different ADHD- or autism-specific supports in the school and therapy environments.

Research has shown that diagnostic status is a crude characterisation of a child’s needs. Diagnostic labels are relatively ineffective in predicting what kind of cognitive or behavioral support an individual needs. A categorical diagnosis, therefore, only provides researchers, practitioners, and teachers with a very coarse picture of the needs of the individual.

Current definition of neurodevelopmental conditions

Neurodevelopmental conditions (NDCs) are a set of challenges that begin to emerge during childhood. According to current clinical handbooks, neurodevelopmental conditions generally appear in early childhood, usually before children start school, and can persist into adulthood. Key characteristics of these conditions include a negative impact on adaptive functioning in one or more domains of life (social, academic, personal, occupational).

All of these conditions and their levels of impairment exist on a spectrum, and affected individuals can experience varying degrees of symptoms and deficits despite having the same diagnosis. However, diagnosis is categorical, and one either has or doesn’t have a certain condition. Specific conditions included under the neurodevelopmental header include: intellectual disability, communication disorders, autism spectrum disorder, ADHD, neurodevelopmental motor disorders, and specific learning disorders.

The status quo for NDCs: categorical diagnostics

Currently, observations like the above, where some individuals meet diagnostic criteria and others do not meet these criteria despite very similar experienced challenges, are common. In large part, this is due to our current reliance on categorical classification systems for mental health and neurodevelopmental conditions. Both clinical practice and research are guided by the Diagnostic and Statistical Manual of Mental Disorders (DSM) and the International Classification of Diseases (ICD).

Both classification manuals, which are routinely used by mental health professionals as well as researchers, specify diagnostic inclusion and exclusion criteria for discrete mental health and neurodevelopmental conditions. In these manuals, each neurodevelopmental condition is considered as a discrete silo with clearly defined boundaries. For example, one either meets the criteria for an ADHD diagnosis or one does not, and one can be categorized as belonging in the ADHD and/or autism silos.

Categorical diagnoses have been viewed as a best practice by many researchers and clinicians. Study design, sampling, analytic approaches, theory, assessment, and treatment all build on the premise that neurodevelopmental condition categories capture the underlying reality. This categorical thinking has shaped and continues to shape every aspect of the scientific architecture of NDCs.

Three issues with a categorical approach to NDCs

There are three fundamental problems with the current categorical classification systems for NDCs. First, current diagnostic systems are not effective in capturing the needs of the broader population requiring support in the areas of learning, behaviour, or social functioning. The use of arbitrary thresholds causes individuals with milder difficulties that nonetheless significantly impact their functioning to be classified as not in need of support and, as a consequence, unable to access support. Examples are children like Jemma, who show difficulties and delays but do not meet diagnostic criteria for any categorical condition.

Second, current diagnostic systems struggle to account for and deal with high levels of symptom heterogeneity within categorical NDCs. For example, individuals with the same diagnosis often vary widely in the nature and impact of their symptoms. This makes diagnosis an unreliable guide for research recruitment or intervention support.

Third, current diagnostic systems cannot easily accommodate the overlap across these proposed discrete conditions. For example, many studies have resorted to the recruitment of highly selective samples based on the presence or absence of a particular diagnosis, screening out those with co-occurring conditions at recruitment.

A multi-dimensional, transdiagnostic alternative for research, assessment, and support

A multi-dimensional, transdiagnostic approach provides the basis for a broader-based assessment of the potential needs of the child, irrespective of whether those align with a particular neurodevelopmental diagnosis. This child-centred approach directly informs the two core questions asked by practitioners: what are this child’s strengths and difficulties, and how can we enable them to flourish?

A benefit of a transdiagnostic framework is that its methods are likely more sensitive to subtle difficulties that may not meet a threshold for a diagnosis, but which are nonetheless impactful in everyday life. This could facilitate earlier intervention before functional outcomes compound to show sufficiently marked problems to meet diagnostic thresholds. Moreover, putting fixed diagnostic criteria aside opens the way for more dynamic characterisations of NDCs that allow for developmental change. Evidence-based transdiagnostic, multi-dimensional approaches provide compelling alternatives with the flexibility to capture the true heterogeneity of NDCs in the population at large.