Smartphone-Based Cognitive Telerehabilitation: A Usability and Feasibility Study Focusing on Mild Cognitive Impairment.

The implementation of cognitive health apps in patients with mild cognitive impairment (MCI) is challenging because of their cognitive, age, and other clinical characteristics. In this project, we aimed to evaluate the usability and feasibility of the Rehastart app tested in MCI patients. Eighteen subjects affected by MCI due to neurodegenerative disorders (including Parkinson's disease, multiple sclerosis, and amnestic/multidomain MCI) and eighteen healthcare professionals were recruited to this study. Patients were registered on the app by clinicians and they were assigned a protocol of specific cognitive exercises. The recruitment was conducted in the period between March and June 2023. The trial testing of the app consisted of three sessions per week for three weeks, with each session lasting about 30 min. After three weeks, the participants as well as medical personnel were invited to rate the usability and feasibility of the Rehastart mobile application. The instruments employed to evaluate the usability and feasibility of the app were the System Usability Scale (SUS), The Intrinsic Motivation Inventory (IMI) and the Client Satisfaction Questionnaire (CSQ). We did not find statistically significant differences on the SUS (p = 0.07) between healthcare professionals and patients. In addition, we found promising results on subscales of the Intrinsic Motivation Inventory, suggesting high levels of interest and enjoyment when using the Rehastart app. Our study demonstrated that smartphone-based telerehabilitation could be a suitable tool for people with MCI due to neurodegenerative disorders, since the Rehastart app was easy to use and motivating for both patients and healthy people.

Paving the Way for Predicting the Progression of Cognitive Decline: The Potential Role of Machine Learning Algorithms in the Clinical Management of Neurodegenerative Disorders.

Alzheimer's disease (AD) is the most common form of neurodegenerative disorder. The prodromal phase of AD is mild cognitive impairment (MCI). The capacity to predict the transitional phase from MCI to AD represents a challenge for the scientific community. The adoption of artificial intelligence (AI) is useful for diagnostic, predictive analysis starting from the clinical epidemiology of neurodegenerative disorders. We propose a Machine Learning Model (MLM) where the algorithms were trained on a set of neuropsychological, neurophysiological, and clinical data to predict the diagnosis of cognitive decline in both MCI and AD patients. METHODS: We built a dataset with clinical and neuropsychological data of 4848 patients, of which 2156 had a diagnosis of AD, and 2684 of MCI, for the Machine Learning Model, and 60 patients were enrolled for the test dataset. We trained an ML algorithm using RoboMate software based on the training dataset, and then calculated its accuracy using the test dataset. RESULTS: The Receiver Operating Characteristic (ROC) analysis revealed that diagnostic accuracy was 86%, with an appropriate cutoff value of 1.5; sensitivity was 72%; and specificity reached a value of 91% for clinical data prediction with MMSE. CONCLUSION: This method may support clinicians to provide a second opinion concerning high prognostic power in the progression of cognitive impairment. The MLM used in this study is based on big data that were confirmed in enrolled patients and given a credibility about the presence of determinant risk factors also supported by a cognitive test score.

Virtual Reality Technology to Enhance Conventional Rehabilitation Program: Results of a Single-Blind, Randomized, Controlled Pilot Study in Patients with Global Developmental Delay.

Global developmental delay (GDD) is a complex disorder that requires multimodal treatment involving different developmental skills. The objective of this single-blind, randomized, controlled pilot study is to evaluate the feasibility and effectiveness of conventional rehabilitation programs integrated with the BTs-Nirvana virtual reality system. Patients with GDD aged 12 to 66 months were enrolled and treated for a 48-session cycle. Patients were randomized into two groups, (1) conventional treatment and (2) conventional treatment supplemented with the use of BTs-Nirvana, in a 1:1 ratio. Before and after treatments, areas of global development were tested with the Griffiths-III Mental Developmental Scale and the clinical indicator of global improvement were measured with the Clinical Global Impressions-Improvement (CGI-I). Feasibility was confirmed by the high retention rate. The experimental group presented a significantly improvement in General Quotient (GQ) after treatment (GQ, p = 0.02), and the effect of the two treatments was significantly different in both the GQ (t =2.44; p = 0.02) and the Foundations of Learning subscale (t =3.66; p < 0.01). The overall improvement was also confirmed by the CGI-I (p = 0.03). According to these preliminary data, virtual reality can be considered a useful complementary tool to boost the effectiveness of conventional therapy in children with GDD.

Feasibility, Usability, and Customer Satisfaction of the Tele-COVID19 Project, Sicilian Model.

Background and Objectives: In March 2020, COVID-19 pandemic affected the world. All countries, to limit viral transmission, imposed quarantine. This emergency exerted personal, social, economic, and psychological impact on people. For health systems, was needed to create alternative care pathways. Telemedicine can be helpful to reduce isolation, provide health care services, and monitor virus infections. Italian regions, including Sicily, have activated telemedicine services for management of patients with COVID-19. Objective: The purpose of study is to describe a Sicilian telemedicine model for management of COVID-19 patients, showing results on feasibility, usability and quality of service and patient satisfaction. Materials and Methods: This is a descriptive exploratory study on a telemedicine service for residents in Messina infected by COVID-19. It included monitoring of vital signs and specialist consultations (i.e., doctor, psychologists, social workers, and nutritionist biologists). Results: More than twenty percent (23.8%) of participants used tele-monitoring and tele-counselling services; 14.3% were only telemonitored. Participants judged positively telemedicine service (30% were quiet and 50% were very satisfied), as well as tool (70% were quiet and 10% were very satisfied). Telemonitoring had a low agreement (10% were slightly satisfied and 50% were neutral); tele-counselling had a high rate of satisfaction (40% quiet and 60% were very satisfied). Conclusions: This study showed that telemedicine model for Sicilian population affected by COVID-19 was feasible, easy to use and appreciated by patients. Our promising results allow us to assume that if in Sicily there was a return of the emergency, we would be ready to manage it This system can be the solution to remote management of these patients, to reduce isolation, provide health services, and monitor virus infections. The use of this technology should encourage future research to change the health care system and provides opportunities to ensure health and care for oneself and others.

Humanoid Robot Use in Cognitive Rehabilitation of Patients with Severe Brain Injury: A Pilot Study.

Severe acquired brain injury (SABI) is a major global public health problem and a source of disability. A major contributor to disability after SABI is limited access to multidisciplinary rehabilitation, despite evidence of sustained functional gains, improved quality of life, increased return to work, and reduced need for long-term care. Twelve patients with a diagnosis of SABI were enrolled and equally divided into two groups: experimental and control. Patients in both groups underwent intensive neurorehabilitation according to the severity of their disabilities (motor, psycho-cognitive, and sensory deficits). However, in the experimental group, the treatment was performed by using a humanoid robot. At baseline, the two groups differed significantly only in Severe Impairment Battery (SIB) scores. Results showed that the experimental treatment had a higher effect than the traditional one on quality of life and mood. In conclusion, this pilot study provides evidence of the possible effects of relational and cognitive stimulation in more severely brain-injured patients.

Care models for mental health in a population of patients affected by COVID-19.

OBJECTIVE: Emergency psychological interventions are needed in patients with COVID-19. During the pandemic, psychological counseling services have been provided using online platforms to address adverse psychological impacts and symptoms in patients and the general population. We investigated the effects of telepsychotherapy on emotional well-being and psychological distress in patients affected by COVID-19. METHODS: Forty-five Sicilian patients who had contracted COVID-19 joined "Telecovid Sicilia" from March to June 2020. Participants completed self-assessment questionnaires and psychological testing to measure levels of anxiety, presence of depressive symptoms, and altered circadian rhythm with consequent sleep disorders and psychological distress. Individual telepsychotherapy services were provided for 1 hour, twice a week, for 16 sessions in total. RESULTS: We enrolled 45 patients (42.2% women). We found significant changes between baseline and the end of follow-up in all outcome measures, especially depression (χ2 (1) = 30.1; effect size [ES] = 0.82), anxiety (χ2 (1) = 37.4; ES = 0.91), and paranoid ideation (χ2 (1) = 5.6; ES = 0.35). The proportion of participants with sleep disorders decreased to 84.1% after intervention (χ2 (1) = 58.6; ES = 1.14). CONCLUSION: A telepsychotherapeutic approach showed promising effects on psychological symptoms, with significantly reduced patient anxiety and depression.