ABSTRACT
Introduction: Virtual reality (VR) is a digital technology currently considered to implement rehabilitation programs for children with ADHD, a disorder characterised by inattention, overactivity and impulsiveness. This study presents the results of the acceptance and usability of a VR application developed for children with ADHD aiming to provide an environment capable of supporting the development of the different attentional components. Due to COVID-19 restrictions, this study had the secondary aim of assessing whether a remote evaluation was feasible and meaningful. Methods: A sample of 20 clinical experts (neuro and psychomotor therapists of the developmental age) was involved in assessing the proposed environment. Two different tools have been applied: the Technology Acceptance Model (TAM-3) questionnaire and a semi-structured interview were self-administered. Six sessions were planned in total, and each one lasted 30 min. Results: With respect to the acceptance of the system, the mean of the answers given is for most of the constructs greater than 4, showing agreement among experts. Cronbach alpha and correlations of subscales seem to confirm the reliability of measures. According to results from the interviews, the developed application has shown versatility in being able to be applied to the heterogeneity of the disorder and it was also possible to obtain valuable insights on possible additional features and functionalities. Regarding the secondary aim, the collected outcomes were positive: all the participants were satisfied with what they could perceive about the application. Conclusions: The results of this work pave the way for a future validation study with children due to the active participation of clinicians and their unanimous positive judgement confirming that the application was considered user-friendly and well accepted.
ABSTRACT
In recent years, telehealthcare systems (TSs) have become more and more widespread, as they can contribute to promoting the continuity of care and managing chronic conditions efficiently. Most TSs and nutrition recommendation systems require much information to return appropriate suggestions. This work proposes an ontology-based TS, namely HeNuALs, aimed at fostering a healthy diet and an active lifestyle in older adults with chronic pathologies. The system is built on the formalization of users’ health conditions, which can be obtained by leveraging existing standards. This allows for modeling different pathologies via reusable knowledge, thus limiting the amount of information needed to retrieve nutritional indications from the system. HeNuALs is composed of (1) an ontological layer that stores patients and their data, food and its characteristics, and physical activity-related data, enabling the inference a series of suggestions based on the effects of foods and exercises on specific health conditions;(2) two applications that allow both the patient and the clinicians to access the data (with different permissions) stored in the ontological layer;and (3) a series of wearable sensors that can be used to monitor physical exercise (provided by the patient application) and to ensure patients’ safety. HeNuALs inferences have been validated considering two different use cases. The system revealed the ability to determine suggestions for healthy, adequate, or unhealthy dishes for a patient with respiratory disease and for a patient with diabetes mellitus. Future work foresees the extension of the HeNuALs knowledge base by exploiting automatic knowledge retrieval approaches and validation of the whole system with target users.