Symptoms of Attention-Deficit/Hyperactivity Disorder (ADHD), namely hyperactivity, impulsivity, and inattention, are one of the most common reasons for referral to Child and Adolescent Mental Health Services (CAMHS) in the UK and in other countries as well.

As with other (neuro)psychiatric disorders, the diagnosis of ADHD is based on a subjective assessment of symptoms. Discrepancies among sources of information (e.g., parents and teachers) as well as uncertainties related to issues of differential diagnosis may delay the diagnostic process. Indeed, ADHD diagnostic delay, which has been reported across many countries (e.g., Fridman M et al., 2017; Purper-Ouakil D et al., 2007) is an important concern as it increases the strain on individuals and families, and leads to substantially higher health care costs.

Even though no biomarker is available for the diagnosis of ADHD (and for any other psychiatric condition), a number of objective assessments have been proposed to support the diagnostic process.

In 2016, the U.S. Food and Drug Administration (FDA) approved the QbTest but as a device that can aid the diagnosis of ADHD rather than a stand-alone diagnostic tool per se.

The QbTest, originally developed by a company in Sweden, combines an objective, computerised test of attention (Continuous Performance Test, CPT) with a measurement of motor activity via infrared camera.

Although a sizeable portion of individuals with ADHD present with neuropsychological dysfunctions that can be measured with objective tests (such as tests of attention), these neuropsychological dysfunctions are not universal in ADHD. Furthermore, different subgroups of individuals with ADHD present with different neuropsychological dysfunctions (e.g., deficits in tests of attention, inhibition, or impulsivity) and some of them do not have any neuropsychological dysfunction. Therefore, none of the available neuropsychological tests can be used for the diagnosis of ADHD, which is based on the presence of an impairing, age inappropriate and persistent cluster of observable (behavioural) symptoms of inattention and or hyperactivity/impulsivity, as reported by parents, teachers and possibly other observers. However, including an objective assessment such as the QbTest may increase the efficiency of the diagnostic process and also be cost-effective. How well QbTest can achieve this is a question of paramount relevance for the daily clinical practice of professionals in child mental health services.

The elegant trial by Prof. Chris Hollis and co-workers (Assessing QbTest Utility in ADHD-Trial (AQUA-Trial) aimed to provide empirical evidence to answer this question using a clever and methodologically sound design (Hollis et al, 2018).

Methods

AQUA was a two-arm, parallel group, single-blind pragmatic randomised trial recruiting from 10 centres (CAMHS and community paediatric clinics) across the UK. Participants were children and adolescents, aged 6-17 years, referred for a first ADHD assessment. All participants received assessment as usual for ADHD along with a QbTest performed at the baseline. They were then randomly assigned to two groups:

• In the first, their clinician immediately received the QbTest report (n = 123);
• In the second, the report was withheld until the end of the study (n = 127).

The primary outcome was the number of appointments until a diagnosis of ADHD was confirmed (or not) within 6 months of study baseline. The secondary outcomes were: number of days until a diagnostic decision was reached, duration of consultations until a diagnosis was made, clinician’s confidence in diagnostic decision (assessed on a 7-point Likert scale), and stability in diagnosis ( = change in diagnosis throughout the study period). Importantly, the clinician’s diagnosis with and without QbTest report was contrasted against a diagnosis made following a consensus by two experienced clinicians blind to the group assignment.

The economic evaluation focused on reduction in the incremental cost when including QbTest. Full costs for each visit were obtained for each participant.

Multilevel linear and nonlinear modelling were used to analyse continuous and categorical outcomes, respectively.  ROC curve modeling was used to assess diagnostic accuracy.

Results

• The diagnosis of ADHD was earlier (15% reduction in total time) and 44% more likely when results of the QbTest were available
• As for the secondary outcomes, a diagnosis of ADHD was significantly more likely and ADHD was twice as likely to be excluded when QbTest reports were available
• Importantly, there were no significant differences in terms of diagnostic accuracy between the two study arms
• Both cost savings and cost effectiveness were supported by the results of the study, although cost savings were small, so that the intervention was classified as “cost neutral”.

Conclusions

This randomised controlled trial, conducted in a “real world” clinical setting provided evidence supporting the use of QbTest to improve diagnostic efficiency, with a reduction of the diagnostic delay, preserving the diagnostic accuracy.

Strengths and limitations

One of the main strengths of this study is that it was designed as a pragmatic, rather than a conventional, randomised controlled trial, meaning that it was conducted in the real world of clinical practice rather than restricting the inclusion of participant to a highly selected group or using sophisticated therapeutic approaches that it would be challenge to implement in the majority of mental health services.

Another strength is the inclusion of cost-effectiveness analyses, which make the results more informative and appealing to commissioners, besides clinicians and services user users. Finally, it is important to highlight that the assessors who independently validated the diagnosis of ADHD were blinded to the allocation of the participants to the two study groups.

The results should also be considered in the light of the study limitations. In particular, the follow-up was limited to 6 months after the baseline. Since one-third of participants had still not received a diagnostic decision after 6 months, the authors could not determine the impact of the QbTest on the possible diagnosis in the participants who were still waiting for a diagnostic decision.  Additionally, the study was not powered enough to assess possible age effects. Finally, it goes without saying that the effect of the QbTest on the speed and efficiency of the diagnosis was assessed in the absence of a true gold standard for the diagnosis of ADHD

Implications for practice

QbTest can be considered as a cost-effective tool that can be used in the daily clinical practice; to reduce diagnostic delay and preserve diagnostic accuracy.

Conflicts of interest

Dr Cortese reports receiving reimbursement for travel and accommodation expenses from the Association for Child and Adolescent Central Health (ACAMH), a non-profit organisation, in relation to lectures that he delivered for ACAMH and by Healthcare Convention for educational activity on ADHD.

Links

Primary paper

Hollis C, Hall CL, Guo B, James M, Boadu J, Groom MJ, Brown N, Kaylor-Hughes C, Moldavsky M, Valentine AZ, Walker GM, Daley D, Sayal K, Morriss R; the AQUA Trial Group. (2018) The impact of a computerised test of attention and activity (QbTest) on diagnostic decision-making in children and young people with suspected attention deficit hyperactivity disorder: single-blind randomised controlled trial. J Child Psychol Psychiatry. 2018 Apr 26. doi: 10.1111/jcpp.12921.

Other references

Fridman M, Banaschewski T, Sikirica V, Quintero J, Chen KS (2017). Access to diagnosis, treatment, and supportive services among pharmacotherapy-treated children/adolescents with ADHD in Europe: data from the Caregiver Perspective on  Pediatric ADHD survey. Neuropsychiatr Dis Treat. 2017;13:947-958.

Purper-Ouakil D, Cortese S, Wohl M, Asch M, Acquaviva E, Falissard B, Michel G, Gorwood P, Mouren MC (2007). Predictors of diagnostic delay in a clinical sample of French children with attention-deficit/hyperactivity disorder. Eur Child Adolesc Psychiatry. 2007 Dec;16(8):505-9. [PubMed abstract]

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