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BackgroundCongestive heart failure (CHF) is a disease that requires complex management involving multiple medications, exercise, and lifestyle changes. It mainly affects older patients with depression and anxiety, who commonly find management difficult. Existing mobile apps supporting the self-management of CHF have limited features and are inadequately validated. ObjectiveThe HeartMan project aims to develop a personal health system that would comprehensively address CHF self-management by using sensing devices and artificial intelligence methods. This paper presents the design of the system and reports on the accuracy of its patient-monitoring methods, overall effectiveness, and patient perceptions. MethodsA mobile app was developed as the core of the HeartMan system, and the app was connected to a custom wristband and cloud services. The system features machine learning methods for patient monitoring: continuous blood pressure (BP) estimation, physical activity monitoring, and psychological profile recognition. These methods feed a decision support system that provides recommendations on physical health and psychological support. The system was designed using a human-centered methodology involving the patients throughout development. It was evaluated in a proof-of-concept trial with 56 patients. ResultsFairly high accuracy of the patient-monitoring methods was observed. The mean absolute error of BP estimation was 9.0 mm Hg for systolic BP and 7.0 mm Hg for diastolic BP. The accuracy of psychological profile detection was 88.6%. The F-measure for physical activity recognition was 71%. The proof-of-concept clinical trial in 56 patients showed that the HeartMan system significantly improved self-care behavior (P=.02), whereas depression and anxiety rates were significantly reduced (P

A plethora of neuroimaging studies have focused on the discovery of potential neuroendophenotypes useful to understand the etiopathogenesis of autism and predict treatment response. Social robotics has recently been proposed as an effective tool to strengthen the current treatments in children with autism. However, the high clinical heterogeneity characterizing this disorder might interfere with behavioral effects. Neuroimaging is set to overcome these limitations by capturing the level of heterogeneity. Here, we provide a preliminary evaluation of the neural basis of social robotics and how extracting neural hallmarks useful to design more effective behavioral applications. Despite the endophenotype-oriented neuroimaging research approach is in its relative infancy, this preliminary evidence encourages innovation to address its current limitations.

This study is a randomized control trial aimed at testing the role of a human-assisted social robot as an intervention mediator in a socio-emotional understanding protocol for children with autism spectrum disorders (ASD). Fourteen children (4-8 years old) were randomly assigned to 10 sessions of a cognitive behavioural therapy (CBT) intervention implemented in a group setting either with or without the assistance of a social robot. The CBT protocol was based on Rational Emotive Behaviour Therapy (REBT) principles. Pre- and post-intervention assessments were conducted using the Test of Emotional Comprehension (TEC) and the Emotional Lexicon Test (ELT). Substantial improvements in contextualized emotion recognition, comprehension and emotional perspective-taking through the use of human-assisted social robots were attained.

Background: Receptive language, the ability to comprehend and respond to spoken language, poses significant challenges for individuals with Autism Spectrum Disorder (ASD). To support communication in autistic children, interventions like Lovaas' simple-conditional method and Green's conditional-only method are commonly employed. Personalized approaches are essential due to the spectrum nature of autism. Advancements in technology have opened new avenues for personalizing therapeutic interventions. This single case study compares traditional and technology-based learning sets in a receptive labeling teaching program using Green's method. Methods: An alternating treatments design assessed the number of sessions required to achieve mastery in receptive identification of stimuli presented on flashcards or tablets. The study involved a six-year-old Italian child with ASD named Pietro. Initial assessment using the Verbal Behavior Milestone Assessment and Placement Program (VB-MAPP) determined Pietro's strengths and weaknesses. Six stimuli were selected and divided into two sets: traditional and technology-based. Sessions were semi-randomly alternated, and the teaching procedures remained constant across conditions. In the traditional condition, sessions were conducted twice a week, using flashcards. Correct responses received immediate social reinforcement. In the technological condition, the same stimuli were presented on a tablet via PowerPoint slides. Results: Pietro achieved mastery more quickly with flashcard instruction than with tablet instruction. Learning was exponential in the traditional condition and linear in the digital condition. Follow-up assessments three weeks post-treatment showed no differences in the generalization and maintenance of skills between the two modalities. Discussion: The findings indicate that the format of stimulus delivery affects the learning process, with traditional flashcards leading to faster mastery in this case. Individual motivation appears crucial, suggesting that Pietro's learning history influenced his performance. Personalized approaches remain vital in autism interventions. Further research is needed to determine if these differences extend to other skills or contexts. Conclusion: While technology-based interventions offer new opportunities, they are not universally more effective than traditional methods. Careful consideration of individual differences, especially motivational factors, is essential in designing effective autism intervention programs. [ABSTRACT FROM AUTHOR]

Introduction: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder characterized by a range of intellectual and language abilities. Its heterogeneity is acknowledged in modern diagnostics, complicating research and necessitating precision medicine and a multidimensional approach for individualized treatment and accurate assessment. Intellectual and language functioning influence adaptive skills and symptomatology. Thus, assessing adaptive functioning in a multidimensional and multi-informant manner is crucial, highlighting the importance of comprehensive evaluations. This study explores the interplay between autistic traits, demographic variables, IQ, adaptive functioning, and the applicability of ICD-11 classifications. Methods: We analyzed data from the initial global evaluation of 60 diverse autistic children (aged 35 to 120 months; IQ range 16 to 118). Parent-reports using the Vineland Adaptive Behavior Scale (VABS-II) were compared with standardized assessments from the PsychoEducational Profile (PEP-3). Children's intellectual levels were assessed using Griffiths Scales of Child Development (Griffiths III) and the Autism Diagnostic Observation Schedule (ADOS-2) was used for autistic traits. They were further classified according to the ICD-11 diagnostic system, functional language, and intellectual functioning levels. Correlations among variables, group comparisons, and multivariate analyses were performed. Results: The analysis indicates a linear effect of IQ on all adaptive scales and the impact of autistic traits on directly measured adaptive functioning. A factorial effect was observed due to changes concerning specific age, intellectual, and linguistic levels, which do not completely align with ICD-11 categorization. Additionally, a negative correlation between intelligence and measured autistic traits was found. Parental age, education level, and age at childbirth were also found to affect various adaptive scales. Discussion: The study questions the ICD-11's proposed distinctions in IQ and language functioning for ASD, advocating for more refined categorization and developmental considerations. It underscores the intricate relationship between autistic traits, IQ, and communication skills, casting doubt on the precision of diagnostic tools across the spectrum. Parental reports and direct assessments are essential for comprehensive evaluation, with parental education and age influencing children's behaviors and skills. The study calls for a nuanced approach to ASD assessment, integrating various metrics and sources of information for a detailed phenotyping necessary for personalized interventions and biological research. [ABSTRACT FROM AUTHOR]

Background and aims: Giulia, an 11-year-old girl diagnosed with ligyrophobia, has been experiencing intense anxiety related to loud noises since the age of two. This case report aims to explore the efficacy of Third-Wave Cognitive Behavioral Therapy, specifically Acceptance and Commitment Therapy (ACT), in addressing Giulia's anxiety and avoidance behaviors. The primary goal is to examine the impact of ACT on reducing ligyrophobic symptoms and enhancing psychological flexibility. Methods: The therapeutic intervention spanned 24 sessions and was divided into two phases. The initial phase focused on emotional competence using characters from the movie "Inside Out," aiding Giulia in recognizing and understanding her emotions. The subsequent phase targeted the six processes of psychological inflexibility identified in ACT, fostering increased flexibility. Results: Throughout the intervention, Giulia demonstrated significant improvements in anxiety symptoms, as evidenced by a decrease in Subjective Units of Distress (SUD) scores. Avoidance behaviors also diminished, and Giulia exhibited enhanced mindfulness skills. She became more cognizant of her emotional experiences and more certain of her personal ideals as a result of the therapy. Giulia's active participation and commitment to exposure exercises led to a substantial reduction in ligyrophobic reactions. Discussion: The successful application of ACT in Giulia's case suggests that targeting psychological inflexibility through mindfulness and values clarification can be effective in treating ligyrophobia in children. The integration of metaphors and creative exercises proved valuable in engaging Giulia and fostering therapeutic progress. The findings underscore the importance of a tailored, third-wave therapeutic approach in addressing specific phobias in pediatric populations. [ABSTRACT FROM AUTHOR]

The rising prevalence of mental illness is straining global mental health systems, particularly affecting older adults who often face deteriorating physical health and decreased autonomy and quality of life. Early detection and targeted rehabilitation are crucial in mitigating these challenges. Mindfulness acceptance and commitment therapy (ACT) holds promise for enhancing motivation and well-being among the elderly, although delivering such psychological interventions is hindered by limited access to services, prompting exploration of remote delivery options like mobile applications. In this paper, we introduce the BrainHeart App (v.1.1.8), a mobile application tailored to improve physical and mental well-being in seniors. The app features a 10-day ACT program and other sections promoting healthy lifestyle. In a pilot study involving twenty participants, individuals engaged in daily mental exercises for 10 days using the app. Clinical evaluations, including assessments of psychological flexibility, overall cognitive profile, mindfulness disposition, cognitive fusion, and heart rate collected with Polar H10, were conducted at baseline (T0) and one month post-intervention (T1). Analysis revealed significant improvements in almost all neuropsychological scores, with high usability reported (system usability scale average score: 82.3 ± 9.31). Additionally, a negative correlation was found between usability and experiential avoidance (r = −0.51; p = 0.026), and a notable difference in heart rate was observed between baseline and post-intervention (F-value = 3.06; p-value = 0.09). These findings suggest that mindfulness-ACT exercises delivered via the BrainHeart App can enhance the well-being of elderly individuals, highlighting the potential of remote interventions in addressing mental health needs in this population. [ABSTRACT FROM AUTHOR]