The BEHAVE application as a tool to monitor inclusive interventions for subjects with neurodevelopmental disorders.

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.

Psychotherapy as a Moderator of the Relationship Between Coping Strategies and Anxiety During the COVID-19 Pandemic.

The COVID-19 pandemic has led to the development of several risk factors for mental health, not only for people directly infected but also for those experiencing social isolation, loneliness, and concern for their health. The impact of these factors on individuals' health and well-being also depends on the type of coping strategies adopted. Moreover, one of the main effects of COVID-19 is the increase in the prevalence of people who manifest anxious or depressive syndromes. This study investigates the relationship between coping strategies and a multidimensional assessment of anxiety symptoms measured during the COVID-19 pandemic in people who were having psychotherapy sessions, while participating in the study had psychotherapy sessions (clinical group) and those who have never done them (non-clinical group). The results of a questionnaire administered online to Italian subjects from June to July, 2020 were analyzed through multiple linear regressions methods to evaluate the role of psychotherapy as moderator between anxiety symptoms and coping strategies. The results of this study highlight that there are substantial differences in functioning between the clinical and non-clinical groups, underlying the key role of psychotherapy as a moderator between anxiety and the coping strategies of avoidance, social support, and positive attitude.

The WHAAM Application: a Tool to Support the Evidence-Based Practice in the Functional Behaviour Assessment.

BACKGROUND: The most recent computing technologies can promote the application of evidence-based practice (EBP) in the field of Applied Behavior Analysis (ABA). OBJECTIVE: The study describes how the use of technology can simplify the application of evidence-based practices in applied behaviour analysis. METHODS: The WHAAM application demonstrates this in the following two case studies. We are monitoring dysfunctional behaviours, collecting behavioural data, performing systematic direct observations, creating a 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 identified behaviour "to get out of bed in time" (r = -.79, TAU-U = -.58, p < .05) and the frequency of the behaviour "interrupting others" (r= -.96, TAU-U = -.82, p < .01) decreased. CONCLUSION: 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 evidence-based practices and increasing the communication among clinical, educational and family environments.

Development and Validation of a Functional Behavioural Assessment Ontology to Support Behavioural Health Interventions.

BACKGROUND: In the cognitive-behavioral approach, Functional Behavioural Assessment is one of the most effective methods to identify the variables that determine a problem behavior. In this context, the use of modern technologies can encourage the collection and sharing of behavioral patterns, effective intervention strategies, and statistical evidence about antecedents and consequences of clusters of problem behaviors, encouraging the designing of function-based interventions. OBJECTIVE: The paper describes the development and validation process used to design a specific Functional Behavioural Assessment Ontology (FBA-Ontology). The FBA-Ontology is a semantic representation of the variables that intervene in a behavioral observation process, facilitating the systematic collection of behavioral data, the consequential planning of treatment strategies and, indirectly, the scientific advancement in this field of study. METHODS: The ontology has been developed deducing concepts and relationships of the ontology from a gold standard and then performing a machine-based validation and a human-based assessment to validate the Functional Behavioural Assessment Ontology. These validation and verification processes were aimed to verify how much the ontology is conceptually well founded and semantically and syntactically correct. RESULTS: The Pellet reasoner checked the logical consistency and the integrity of classes and properties defined in the ontology, not detecting any violation of constraints in the ontology definition. To assess whether the ontology definition is coherent with the knowledge domain, human evaluation of the ontology was performed asking 84 people to fill in a questionnaire composed by 13 questions assessing concepts, relations between concepts, and concepts' attributes. The response rate for the survey was 29/84 (34.52%). The domain experts confirmed that the concepts, the attributes, and the relationships between concepts defined in the FBA-Ontology are valid and well represent the Functional Behavioural Assessment process. CONCLUSIONS: The new ontology developed could be a useful tool to design new evidence-based systems in the Behavioral Interventions practices, encouraging the link with other Linked Open Data datasets and repositories to provide users with new models of eHealth focused on the management of problem behaviors. Therefore, new research is needed to develop and implement innovative strategies to improve the poor reproducibility and translatability of basic research findings in the field of behavioral assessment.