Attention deficit hyperactivity disorder (ADHD) is typically diagnosed using clinical observation and subjective informant reports. Once children commence ADHD medication, robust monitoring is required to detect partial or non-responses. The extent to which neuropsychological continuous performance tests (CPTs) and objective measures of activity can clinically aid the assessment and titration process in ADHD is not fully understood. This review describes the current evidence base for the use of CPTs and objectively measured activity to support the diagnostic procedure and medication management for children with ADHD. Four databases (PsycINFO, Medline, Allied and Complementary Medicine (AMED) and PsycARTICLES) were systematically searched to understand the current evidence base for: (1) the use of CPTs to aid clinical assessment of ADHD; (2) the use of CPTs to aid medication management; (3) the clinical utility of objective measures of activity in ADHD. Sixty relevant articles were identified. The search revealed six commercially available CPTs that had been reported on for their clinical use. There were mixed findings with regard to the use of CPTs to assess and manage medication, with contrasting evidence on their ability to support clinical decision making. There was a strong evidence base for the use of objective measures of activity to aid ADHD/non-ADHD group differentiation, which appears sensitive to medication effects and would also benefit from further research on their clinical utility. The findings suggest that combining CPTs and an objective measure of activity may be particularly useful as a clinical tool and worthy of further pursuit.

The Swanson, Nolan, and Pelham Rating Scale (SNAP-IV) is a widely used scale that measures the core symptoms of attention deficit hyperactivity disorder (ADHD). However, there are contradictory findings regarding factor structure. Factor structure and measurement equivalence/invariance analysis on parent and teacher SNAP-IV for children referred for an ADHD assessment ( N = 250; 6-17 years), revealed a two-factor structure provided the best fit. SNAP-IV scores were also compared with clinician diagnosis of ADHD and research diagnoses of ADHD and hyperkinetic disorder. Parent ratings of inattention and hyperactivity/impulsivity were good predictors of research but not clinician diagnosis. For teacher ratings, only hyperactivity/impulsivity scores were associated with research and clinician diagnosis. SNAP-IV scores showed high sensitivity but low specificity to clinician diagnosis. The SNAP-IV is a valid outcome measure for use in randomized controlled trials and clinical settings, and is best used as a screening rather than a diagnostic tool for ADHD.

Background: Diagnosis of attention deficit hyperactivity disorder (ADHD) relies on subjective methods which can lead to diagnostic uncertainty and delay. This trial evaluated the impact of providing a computerised test of attention and activity (QbTest) report on the speed and accuracy of diagnostic decision-making in children with suspected ADHD. Methods: Randomised, parallel, single-blind controlled trial in mental health and community paediatric clinics in England. Participants were 6-17 years-old and referred for ADHD diagnostic assessment; all underwent assessment-as-usual, plus QbTest. Participants and their clinician were randomised to either receive the QbTest report immediately (QbOpen group) or the report was withheld (QbBlind group). The primary outcome was number of consultations until a diagnostic decision confirming/excluding ADHD within 6-months from baseline. Health economic cost-effectiveness and cost utility analysis was conducted. Assessing QbTest Utility in ADHD: A Randomised Controlled Trial was registered at ClinicalTrials.gov (https://clinicaltrials.gov/ct2/show/ NCT02209116). Results: One hundred and thirty-two participants were randomised to QbOpen group (123 analysed) and 135 to QbBlind group (127 analysed). Clinicians with access to the QbTest report (QbOpen) were more likely to reach a diagnostic decision about ADHD (hazard ratio 1.44, 95% CI 1.04-2.01). At 6-months, 76% of those with a QbTest report had received a diagnostic decision, compared with 50% without. QbTest reduced appointment length by 15% (time ratio 0.85, 95% CI 0.77-0.93), increased clinicians' confidence in their diagnostic decisions (odds ratio 1.77, 95% CI 1.09-2.89) and doubled the likelihood of excluding ADHD. There was no difference in diagnostic accuracy. Health economic analysis showed a position of strict dominance; however, cost savings were small suggesting that the impact of providing the QbTest report within this trial can best be viewed as 'cost neutral'. Conclusions: QbTest may increase the efficiency of ADHD assessment pathway allowing greater patient throughput with clinicians reaching diagnostic decisions faster without compromising diagnostic accuracy.

Background The Strengths and Difficulties Questionnaire (SDQ) is widely used to assess child and adolescent mental health problems. However, the factor structure of the SDQ is subject to debate and there is limited evidence investigating measurement equivalence invariance (ME/I) between treatment groups, informants, and across time. Method A randomised controlled trial (RCT) recruited 250 participants (6–17 years) who had been referred for an attention deficit hyperactivity disorder (ADHD) assessment. Participants and their clinician either received or did not receive a QbTest report (computer task measuring attention, impulsivity and activity). Parents and teachers completed the SDQ at baseline and 6-months later. This study aimed to understand the factor structure of the SDQ in a clinic referred ADHD sample, and validate the scale as a screening/diagnostic aide and as a measure of treatment outcome both in clinical and research settings. Exploratory Structural Equation Modelling (ESEM) was performed to examine the factor structure, and ME/I was assessed between treatment groups, informants, and time points. The criterion validity of the SDQ predictive algorithm for ADHD was compared with clinician and research diagnoses using logistic regression and tests of diagnostic accuracy. Results A 5-factor structure provided the best fit with strong factorial invariance between treatment groups and across time points, but not across informants (parent and teacher ratings). SDQ ratings of ‘probable’ hyperactivity disorder were good predictors of clinical (OR = 10.20, 95%CI 2.18–48.71,p = 0.003) and research diagnoses of ADHD (OR = 6.82, 95%CI 1.95–23.84,p = 0.003), and research diagnoses of Hyperkinetic disorder (OR = 4.02, 95%CI 1.13–14.25,p = 0.031). Further examination of the SDQ hyperactivity ‘probable’ rating showed good specificity (84.5%-74.5%) but poor sensitivity (45.0–42.5%) for ADHD. Conclusion The findings indicate the SDQ is a valid outcome measure for use in RCTs and clinical settings. However, care should be taken when using the SDQ predictive algorithm to screen for ADHD in clinically referred samples.