“People who have a diagnosis of autism differ hugely, not only in terms of what we call core autism features – social and communication difficulties, and restricted and repetitive behaviours – but also in terms of other clinical associated features. For example, anxiety, depression, ADHD, and other clinical phenotypes. It’s an incredibly heterogeneous condition,” Prof Uljarevic explains.
“They also have varied outcomes and crucially different support needs, just given that kind of huge individual differences among them. And what’s also really important is they respond differently to the same or identical intervention. You might have two kids with the same diagnosis, receiving specific behavioural intervention; one might respond really well and one might not respond at all. So, it’s not only that they have different support needs, but they also respond differently to the same treatments.
“So, to understand what contributes to these individual differences and, most importantly and relatedly, to understand what supports are most suitable to a given person, a given child or a given family, we need large, enriched clinical data sets – information that will be essential for improving both clinical research and practice.”
Because of the limitations of a ‘one-size-fits-all’ diagnostic approach, alternatives have been put forward, including the US National Institute of Mental Health’s Research Domain Criteria and Hierarchical Taxonomy of Psychopathology.
“These dimensional frameworks were developed specifically to address the limitations of the current diagnostic systems,” Prof Uljarevic explains.
“The assessment protocol that we are currently in the process of validating with 3,500 kids and families was specifically developed to assess and quantify those clinical, cognitive and developmental domains that are essential for understanding the profile of each child.
“The way it works is our tool can help inform the diagnosis – like this child has these particular social difficulties; these particular repetitive behaviours – but it goes beyond that. It captures, for instance, how well this child can recognise someone’s emotions; how well they can empathise with someone; how well they can put themselves in someone else’s shoes; how good they are at regulating their emotions.
“Those are all the building blocks of healthy functioning and our ability to navigate the complexities of the world, but the current assessments don’t really capture those.”
Prof Uljarevic says the assessment tool will provide a detailed report for clinicians, with a full profile of a child’s clinical cognitive developmental characteristics, and that will support the development of a personalised care program for the child and the family.
“The other feature of the assessment is that it actually enables clinicians to track improvements over time,” he says.
“We’re developing what we call regression-based change norms, so we can quantify whether the change we are seeing at the level of each child is significant and clinically meaningful or not. It will have a graphic type of output for the clinician so they can see a chart – like now, then in three months and six months, showing how scores of the child change over time. That’s quite a unique feature. Most of the instruments don’t really provide that.
