Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common psychiatric conditions in childhood. Observation of the behavior of the young person plays a key role in Cognitive-Behavioural (CB) approaches to the treatment of ADHD, but traditional pen and pen-and-paper based methods have a number of disadvantages which inhibit their use in realworld situations. The WHAAM mobile application (WMA) provides teachers, parents and health experts with features to easily monitor behaviors in a Specific, Measurable, Attainable, Realistic and Timely (SMART) way.

Background: The most recent computing technologies can promote the application of evidence-based practice (EBP) in the field of applied behaviour analysis (ABA). Objective: The study describes how the use of technology can simplify the application of EBPs in ABA. Methods: The Web Health Application for ADHD Monitoring (WHAAM) application demonstrates this in the following two case studies. We are monitoring dysfunctional behaviours, collecting behavioural data, performing systematic direct observations, creating both visual baseline and intervention charts and evaluating the planned interventions using the TAU-U statistical index. Results: Significant positive changes of children’s problem behaviours are observed and recorded. Both the duration of the previously identified behaviour ‘to get out of bed in time’ (r = −0.79, TAU-U = −0.58, p < 0.05) and the frequency of the behaviour ‘interrupting others’ (r = −0.96, TAU-U = −0.82, p < 0.01) decreased. Conclusions: The WHAAM application is an effective tool to support functional behaviour assessments and it is an example of how technology can support practitioners by facilitating the application of EBPs and increasing the communication among clinical, educational and family environments.

Clinical informatics, decision support for health professionals, electronic health records, and ehealth infrastructures.

In the last few years, many educational and therapeutic interventions for young people with neurodevelopmental disorders are based on systematic monitoring of the outcomes. These interventions are typically conducted using single-case experimental designs, (SCEDs) a set of methods aimed at testing the effect of an intervention on a single subject or a small number of subjects. In SCEDs, an effective process of decision-making needs accurate, precise, and reliable data but also that caregivers and health professionals can gather information with minimal effort. The use of Information Communication Technologies in SCEDs can support the process of data collection and analysis, facilitating the collection of accurate and reliable data, providing reports accessible also by non-experts, and promoting interactions and sharing among clinicians, educators, and caregivers. The present paper introduces the BEHAVE application, a web-based highly customizable application, designed to implement SCEDs, supporting both data collection and automatic analysis of the datasets. Moreover, the paper will describe two case studies of kindergarten children with neurodevelopmental disorders, highlighting how the BEHAVE application supported the entire process, from data collection in multiple contexts to decision-making based on the analysis provided by the system. In particular, the paper describes the case studies of Carlo and Dario, two children with severe language and communication impairments, and the inclusive education interventions carried out to maximize their participation in a typical home and school setting increasing their mand repertoire. Results revealed an increase in the mand repertoire in both children who become able to generalize the outcomes to multiple life contexts. The active participation of the caregivers played a crucial role in the ability of children to use the learned skills in settings different from the ones they were learned in.