Effectiveness of serious games in social skills training to autistic individuals: A systematic review.

Autism Spectrum Disorder (ASD) is a complex neurological condition that significantly impacts individuals' daily lives and social interactions due to challenges in verbal and non-verbal communication. Game-based tools for psychological support and patient education are rapidly gaining traction. Among these tools, teaching social skills via serious games has emerged as a particularly promising educational strategy for addressing specific characteristics associated with autism. Unlike traditional games, serious games are designed with a dual purpose: to entertain and to fulfill a specific educational or therapeutic goal. This systematic review aims to identify and categorize serious computer games that have been used to teach social skills to autistic individuals and to assess their effectiveness. We conducted a comprehensive search across seven databases, resulting in the identification and analysis of 25 games within 26 studies. Out of the 104 criteria assessed across these studies, 57 demonstrated significant improvement in participants. Furthermore, 22 of these studies reported significant enhancements in at least one measured criterion, with 13 studies observing significant improvements in all assessed outcomes. These findings overwhelmingly support the positive impact of computer-based serious game interventions in teaching social skills to autistic individuals.

Validity and reliability of the Persian version of the Patient readiness to engage in health information technology (PRE-HIT) instrument.

BACKGROUND: The Patient readiness to engage in health information technology (PRE-HIT) is a conceptually and psychometrically validated questionnaire survey tool to measure willingness of patients with chronic conditions to use health information technology (HIT) resources. OBJECTIVES: This study aimed to translate and validate a health information technology readiness instrument, the PRE-HIT instrument, into the Persian language. METHODS: A rigorous process was followed to translate the PRE-HIT instrument into the Persian language. The face and content validity was validated by impact score, content validity index (CVI) and content validity ratio (CVR). The instrument was used to measure readiness of 289 patients with chronic diseases to engage with digital health with a four point Likert scale. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) was used to check the validity of structure. The convergent and discriminant validity, and internal reliability was expressed by average variance extracted (AVE), construct reliability (CR), maximum shared squared variance (MSV), average shared square variance (ASV), and Cronbach's alpha coefficient. Independent samples, t-test and one-way ANOVA were used respectively to compare the impact of sex, education and computer literacy on the performance of all PRE-HIT factors. RESULTS: Eight factors were extracted: health information needs, computer anxiety, computer/internet experience and expertise, preferred mode of interaction, no news is good news, relationship with doctor, cell phone expertise, and internet privacy concerns. They explained 69% of the total variance and the KMO value was 0.79; Bartlett's test of sphericity was also statistically significant (sig < 0.001). The communality of items was higher than 0.5. An acceptable model fit of the instrument was achieved (CFI = 0.943, TLI = 0.931, IFI = 0.944, GFI = 0.893, RMSEA ≤ 0.06, χ2/df = 1.625, df = 292, P-value ≤ 0.001). The Cronbach's alpha coefficient achieved a satisfactory level of 0.729. The AVE for all factors was higher than 0.50 except for PMI (0.427) and CIEE (0.463) and also the CR for all factors was higher than 0.7, therefore, the convergent validity of the instrument is adequate. The MSV and ASV values for each factor were lower than AVE values; therefore, the divergent validity was acceptable. CONCLUSION: The Persian version of the PRE-HIT was empirically proved for its validity to assess the level of readiness of patients to engage with digital health.

Evaluation of M-Health Applications Use in Epilepsy: A Systematic Review.

BACKGROUND: Epilepsy is a neurological disorder characterized by seizures and recurrent attacks. Self-management leads to seizure control and maximizes the quality of life in epileptic patients. The purpose of this study was to evaluate the quality of applications available in the epileptic google play store based on the rating features of MARS (Mobile Applications Rating Scale). METHODS: The search was conducted systematically using the keywords "epilepsy", "seizure", "mobile health" at the Android google play store. Data were extracted and analyzed from Feb 2018 to Apr 2019. RESULTS: Accordingly, 45 apps were identified potentially relevant of which 20 met inclusion criteria. Twenty-five apps were excluded because they were unrelated to epilepsy self-management, or not Development for people with epilepsy, not in English language or were not free and available. The total mean MARS score was 3.21 out of 5, and more than half of apps (17, 85%) had a minimum acceptability score of 3.0. The mean of apps' items were 3.27 in Engagement, 3.96 in function, 3.30 in Aesthetics, 2.96 in Information and 2.73 in subjective quality items. CONCLUSION: Few apps meet prespecified criteria for quality, content, and functionality for epilepsy self-management. Despite the rapid evolution of self-management apps, lack of validation studies is a significant concern that limits the clinical value of these apps. Moreover, having a guideline and benchmarking in the field of mobile application development, in epilepsy management, can help analyze the content of established applications.