Search Results (403)

Background/Objectives: While artificial intelligence (AI) is rapidly transforming education, its specific effectiveness for students with learning disabilities (LD) requires rigorous evaluation. This systematic review aims to assess the efficacy of AI-based educational interventions for students with LD, with a specific focus on the methodological quality and risk of bias of the available evidence. Methods: A systematic search was conducted across seven major databases (Google Scholar, ScienceDirect, APA PsycInfo, ERIC, Scopus, PubMed) for experimental studies published between 2022 and 2025. This review followed PRISMA guidelines, using the PICOS framework for inclusion criteria. A formal risk of bias assessment was performed using the ROBINS-I and JBI critical appraisal tools. Results: Eleven studies (representing 10 independent experiments), encompassing 3033 participants, met the inclusion criteria. The most studied disabilities were dyslexia (six studies) and other specific learning disorders (three studies). Personalized/adaptive learning systems and game-based learning were the most common AI interventions. All 11 studies reported positive outcomes. However, the risk of bias assessment revealed significant methodological limitations: no studies were rated as having a low risk of bias, with most presenting a moderate (70%) to high/serious (30%) risk. Despite these limitations, quantitative results from the stronger studies showed large effect sizes, such as in arithmetic fluency (d = 1.63) and reading comprehension (d = −1.66). Conclusions: AI-based interventions demonstrate significant potential for supporting students with learning disabilities, with unanimously positive reported outcomes. However, this conclusion must be tempered by the considerable risk of bias and methodological weaknesses prevalent in the current literature. The limited and potentially biased evidence base warrants cautious interpretation. Future research must prioritize high-quality randomized controlled trials (RCTs) and longitudinal assessments to establish a definitive evidence base and investigate long-term effects, including the risk of cognitive offloading. Full article

Background/Objectives: In an increasingly pervasive digital environment, trait boredom has been identified as a key psychological factor in the onset and maintenance of problematic digital technology use. This systematic review aims to investigate the role of trait boredom in digital behavioral addictions, including problematic smartphone use, Internet and social media overuse, and gaming addiction, through theoretical models such as the I-PACE model and the Compensatory Internet Use Theory (CIUT). Methods: A systematic literature search was conducted across multiple scientific databases (PsycINFO, Web of Science, PubMed, and Scopus), yielding a total of 4603 records. Following the PRISMA guidelines after duplicate removal and screening based on title and abstract, 152 articles were assessed for full-text eligibility, and 28 studies met the predefined inclusion and exclusion criteria and were included in the final review. Results: Findings reveal that trait boredom functions as both a direct and indirect factor in problematic technology use. It serves as a mediator and moderator in the relationship between psychological vulnerabilities (e.g., depression, alexithymia, vulnerable narcissism) and dysfunctional digital behaviors. Furthermore, as an independent variable, it has an influence on technological variables through Fear of Missing Out (FoMO), loneliness, low self-regulation, and dysfunctional metacognitions, while protective factors such as mindfulness and attentional control mitigate its impact. Conclusions: Boredom represents a central psychological lever for understanding behavioral addictions in the digital age and should be considered a key target in preventive and therapeutic interventions focused on enhancing self-regulation and meaningful engagement with free time. Full article

This study introduces a novel tripartite evolutionary game model to analyze the strategic interactions among electric vehicle (EV) aggregators, local governments, and EV users in vehicle–grid interaction (VGI) markets. The core novelty lies in capturing bounded rationality and dynamic decision-making across the three stakeholders, revealing how policy incentives and market mechanisms drive the transition from disordered charging to bidirectional VGI. Key findings include the following: (1) The system exhibits five stable equilibrium points, corresponding to three distinct developmental phases of the VGI market: disordered charging (V0G), unidirectional VGI (V1G), and bidirectional VGI (V2G). (2) Peak–valley price differences are the primary driver for transitioning from V0G to V1G. (3) EV aggregators’ willingness to adopt V2G is influenced by upgrade costs, while local governments’ subsidy strategies depend on peak-shaving benefits and regulatory costs. (4) Increasing the subsidy differential between V1G and V2G accelerates market evolution toward V2G. The framework offers actionable policy insights for sustainable VGI development, while advancing evolutionary game theory applications in energy systems. Full article

This research highlights the importance of Emotion Aware Technologies (EAT) and their implementation in serious games to assist children with Autism Spectrum Disorder (ASD) in developing social-emotional skills. As AI is gaining popularity, such tools can be used in mobile applications as invaluable teaching tools. In this paper, a new AI framework application is discussed that will help children with ASD develop efficient social-emotional skills. It uses the Jetpack Compose framework and Google Cloud Vision API as emotion-aware technology. The framework is developed with two main features designed to help children reflect on their emotions, internalise them, and train them how to express these emotions. Each activity is based on similar features from literature with enhanced functionalities. A diary feature allows children to take pictures of themselves, and the application categorises their facial expressions, saving the picture in the appropriate space. The three-level minigame consists of a series of prompts depicting a specific emotion that children have to match. The results of the framework offer a good starting point for similar applications to be developed further, especially by training custom models to be used with ML Kit. Full article

Current technological development has made the Internet and new technologies increasingly present in people’s lives, expanding their opportunities but also potentially posing risks for dysfunctional use. This study aims to identify psychopathological factors associated with dysfunctional ICT use, extending the evidence beyond the well-established relationships with mood disorders to include personality disorders (i.e., cluster C in particular). A total of 711 participants (75.70% female; Mage = 28.33 years, SD = 12.30) took part in the data collection. Firstly, the results showed positive correlations between higher levels of addictive patterns for the Internet, social networks, smartphones and applications, and video games and higher levels of borderline symptoms as assessed by the Borderline Symptom List 23—Short Version. Moreover, scores reflecting high addictive patterns also positively correlated with general narcissistic traits as indicated by the total score of the Narcissistic Personality Inventory 13—Short Version and those specifically described by its Entitlement/Exploitativeness dimension, as well as with higher levels of almost all the personality traits assessed by the Personality Inventory for DSM 5—Brief Form (i.e., negative affectivity, detachment, disinhibition, and psychoticism). These findings broaden the still scarce body of evidence on the relationship between personality disorders and dysfunctional ICT use, which, however, needs to be further explored. Full article

Neuro-Affective Intelligence (NAI) integrates neuroscience, psychology, and artificial intelligence to support neurodivergent children through personalized Child–Machine Interaction (CMI). This paper presents an adaptive neuro-affective system designed to enhance engagement in children with neurodevelopmental disorders through serious games. The proposed framework incorporates real-time biophysical signals—including EEG-based concentration, facial expressions, and in-game performance—to compute a personalized engagement score. We introduce a novel mechanism, Bayesian Immediate Feedback Learning (BIFL), which dynamically selects visual, auditory, or textual stimuli based on real-time neuro-affective feedback. A multimodal CNN-based classifier detects mental states, while a probabilistic ensemble merges affective state classifications derived from facial expressions. A multimodal weighted engagement function continuously updates stimulus–response expectations. The system adapts in real time by selecting the most appropriate cue to support the child’s cognitive and emotional state. Experimental validation with 40 children (ages 6–10) diagnosed with Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD) demonstrates the system’s effectiveness in sustaining attention, improving emotional regulation, and increasing overall game engagement. The proposed framework—combining neuro-affective state recognition, multimodal engagement scoring, and BIFL—significantly improved cognitive and emotional outcomes: concentration increased by 22.4%, emotional engagement by 24.8%, and game performance by 32.1%. Statistical analysis confirmed the significance of these improvements ($p<0.001$, Cohen’s $d>1.4$). These findings demonstrate the feasibility and impact of probabilistic, multimodal, and neuro-adaptive AI systems in therapeutic and educational applications. Full article

Internet gaming disorder (IGD) has been a prominent social problem throughout the world, causing various physical health issues, and interoceptive sensibility—the ability to perceive internal bodily signals—may be a key factor in this process. However, the relationship between interoceptive sensibility and IGD remains unclear. This study examined how interoceptive sensibility contributes to IGD, the potential mediating roles of positive outcome expectancy and flow experience, as well as the moderating role of refusal self-efficacy. The serial mediation and moderated mediation analyses of data collected from 1733 students (1031 males and 702 females, M_age = 19.56) revealed that interoceptive sensibility was positively associated with IGD, and this connection was serially mediated by positive outcome expectancy and flow experience. Moreover, refusal self-efficacy buffered the positive association between positive outcome expectancy and IGD and between flow experience and IGD. These findings suggest that interoceptive sensibility plays a crucial role in the occurrence of IGD, highlighting the importance of addressing bodily awareness in prevention and intervention strategies. Additionally, enhancing refusal self-efficacy may help mitigate the negative effects of positive outcome expectancy and flow experience, offering potential avenues for reducing IGD risk. Full article

Pupil detection is a key technology in fields such as human–computer interaction, fatigue driving detection, and medical diagnosis. Existing pupil detection algorithms still face challenges in maintaining robustness under variable lighting conditions and occlusion scenarios. In this paper, we propose a novel pupil detection algorithm, ViMSA, based on the ViM model. This algorithm introduces weighted feature fusion, aiming to enable the model to adaptively learn the contribution of different feature patches to the pupil detection results; combines ViM with the MSA (multi-head self-attention) mechanism), aiming to integrate global features and improve the accuracy and robustness of pupil detection; and uses FFT (Fast Fourier Transform) to convert the time-domain vector outer product in MSA into a frequency–domain dot product, in order to reduce the computational complexity of the model and improve the detection efficiency of the model. ViMSA was trained and tested on nearly 135,000 pupil images from 30 different datasets, demonstrating exceptional generalization capability. The experimental results demonstrate that the proposed ViMSA achieves 99.6% detection accuracy at five pixels with an RMSE of 1.67 pixels and a processing speed exceeding 100 FPS, meeting real-time monitoring requirements for various applications including operation under variable and uneven lighting conditions, assistive technology (enabling communication with neuro-motor disorder patients through pupil recognition), computer gaming, and automotive industry applications (enhancing traffic safety by monitoring drivers’ cognitive states). Full article

Background: Binge eating is a disordered eating behavior implicated in eating disorders such as binge eating disorder (BED) and bulimia nervosa; it significantly affects an individual’s physical and mental health. Recent studies suggest shared neurobiological mechanisms between binge eating and addictive behaviors. Comorbid addiction (e.g., substance use disorders and behavioral addictions) is also frequently reported in binge-eating patients. However, it is still unclear whether binge-eating individuals with comorbid addictions differ in their cognitive and mental health characteristics from those without comorbid addictions. Objectives: The present study aimed to examine the cognitive and mental health profiles of binge-eating individuals with and without co-occurring addictions. We hypothesized that binge-eating individuals with comorbid addictions would show greater impairments in impulsivity and self-control, as well as elevated depression and emotion dysregulation. Methods: In the present study, we assessed psychometric scales on various cognitive and mental health domains (e.g., impulsivity, behavioral inhibition, self-control, emotion regulation, mood, and anxiety) across 30 binge-eating individuals with co-occurring addictive behaviors (i.e., alcohol, nicotine, gambling, and video games), 32 binge-eating individuals without addiction, and 180 healthy control subjects with neither binge-eating tendencies nor addiction. Results: Both binge-eating groups showed a significant increase in punishment sensitivity, perceived stress, and state/trait anxiety compared to healthy controls, but there was no difference between the two binge-eating groups. Higher impulsivity and lower self-control were observed in both binge-eating groups to a significantly greater degree in the group with comorbid addiction. Notably, significantly increased depression and impaired emotion regulation (reduced use of cognitive reappraisal) were observed only in the binge-eating group with comorbid addiction when compared to the healthy controls. Conclusions: Our findings demonstrated the commonalities and differences in binge-eating populations with and without comorbid addiction. It will help to elucidate cognitive and mental health aspects of comorbid addiction in the binge-eating population and to develop more tailored diagnoses and treatments. Full article

Gaming is a popular leisure activity with an increasing number of participants worldwide. It has positive aspects as well as a problematic side—Internet Gaming Disorder (IGD). This behavior attracts concern among mental health and education professionals because of possible negative psycho-emotional factors. This study aimed to assess IGD among Japanese and Israeli university students and other young adults. We explored the association of culture and IGD based on gender, burnout, and loneliness. It was hypothesized that IGD would differentiate based on the respondent country (i.e., Japan or Israel) and gender, with males reporting higher levels. Furthermore, IGD would be associated with higher levels of loneliness and burnout, regardless of country. Qualtrics and Excel platforms were used to collect responses to the Internet Gaming Disorder Scale–Short Form, De Jong Gierveld Loneliness Scale, and Short Burnout Measure (SBM). Data was gathered from a cross-cultural sample of 1318 male and female university students and other young adults in Japan and Israel, between 2022 and 2023. Japanese gamers showed less IGD (p < 0.05); and males evidenced higher levels regardless of their country (p < 0.001). IGD was significantly associated with loneliness (p < 0.001) and burnout (p < 0.001). However, multiple regression analysis showed that IGD is predicted only by burnout and gender (p < 0.001), Adjusted R² = 0.234. This study provides information for policy, prevention, and intervention purposes targeting burnout particularly among males who are a high-risk group. Additionally, this study contributes to possible joint online program development to reduce IGD among Japanese and Israeli gamers. Further research should examine the association between IGD and loneliness, controlling gender and other factors such as substance use, religiosity, eating behavior, depression, game genre, and motivation to play. Full article

Children with neurodevelopmental disorders, such as ADHD, ASD and SLDs, often face challenges in executive functioning that can impact their inclusion and participation in educational and social experiences. Digital technologies, in particular video games, are becoming increasingly more integrated into children’s lives and are receiving attention as tools to support cognitive development in these populations. This systematic review analyses the effects of video games on Working Memory (WM) and Executive Functions (EFs) in neurodivergent individuals, to evaluate their effectiveness as training tools and their impact in terms of inclusion. Following the PRISMA guidelines, 25 peer-reviewed studies published between 2013 and 2025 were analysed. The interventions included action-video games, exergames, serious games and ad hoc video game training with a pre- and post-assessment in neurodiverse participants. The results indicate that action-video games and exergames show promise in enhancing EFs, while serious games and ad hoc video game training seem to support WM. Despite a few contrasting results, overall, video games are emerging as promising tools of inclusive education thanks to their interactive, customisable and socially empowering nature, especially significant for neurodiverse children. The discussion will depict multiple ways in which video games can make education more inclusive for these populations. Full article

In the face of the limitations in pharmacological and surgical interventions for neurological conditions such as Parkinson’s and Alzheimer’s disease, patients are increasingly turning to non-pharmacological and alternative therapies to manage their symptoms and improve their quality of life. This shift underscores the urgent need for accessible, effective, and affordable treatments. This literature review examines a range of alternative and personalized therapies, including game therapy, animal-assisted therapy, dance therapy, art therapy, music therapy, aroma therapy, and shinrin-yoku therapy. These modalities have demonstrated promising results in mitigating symptoms and enhancing well-being among individuals grappling with neurological disorders. Moreover, these therapies offer a holistic approach that complements traditional medical interventions, underscoring the importance of integrating diverse treatment modalities. Despite their historical roots in non-clinical settings, their potential in modern clinical practice remains untapped. The findings suggest the necessity for further research, particularly large cohort studies, to validate the efficacy of these personalized therapies and advocate for their widespread adoption. In an era marked by escalating healthcare costs, the exploration of alternative therapies presents a compelling avenue for enhancing patient care while simultaneously addressing economic challenges within the healthcare system. Full article

Dyscalculia is a specific learning disorder that affects numerical comprehension, arithmetic reasoning, and problem-solving skills, significantly impacting academic performance and daily life activities. Traditional teaching methods often fail to address the unique cognitive challenges faced by students with dyscalculia, highlighting the need for innovative educational approaches. Recent studies suggest that educational robotics and game-based learning can provide engaging and adaptive learning environments, enhancing numerical cognition and motivation in students with mathematical difficulties. The intervention was designed to improve calculation skills, problem-solving strategies, and overall engagement in mathematics. The study involved 73 secondary students, divided into three classes, among whom only a specific group had been diagnosed with dyscalculia. Data were collected through pre- and post-intervention assessment evaluating improvements in numerical accuracy, processing speed, and support motivation. Preliminary findings indicate that robotics and gamification create an interactive, less anxiety-inducing learning experience, facilitating conceptual understanding and retention of mathematical concepts. The results suggest that these tools hold promise as supplementary interventions for children with dyscalculia. Future research should explore long-term effects, optimal implementation strategies, and their integration within formal educational settings. Full article

Background/Objectives: The problematic use of video games (PG), social media (PSMU), and alcohol (PAU) is widespread from adolescence onwards. According to theoretical models, personality traits are relevant for these problematic behavioral patterns; however, only very few longitudinal studies are available. The aim of this longitudinal study was to investigate for the first time whether Big Five personality dimensions (BFPD) are predictors for the development of PG, PSMU, or PAU, or conversely, whether these behavioral patterns are predictive of the BFPD. Methods: Surveys were conducted over three measurement time points (t1 to t3) using standardized instruments on PG, PSMU, PAU, and BFPD. A total of 492 young people (average age: 16.83 years, 44.1% female and 55.9% male) were investigated at t1, 475 persons (mean age: 17.93 years, 44.8% female, 55.2% male) at t2, and 443 cases (average age: 20.11 years, 45.1% female, 54.9% male) at t3. We calculated cross-lagged panel analyses over three measurement points (structural equation modeling). Results: Of the BFPD, lower Conscientiousness and lower Extraversion were predictors of PG, higher Negative Emotionality (Neuroticism) predicted PSMU, and lower Agreeableness was a predictor of PAU. Only PAU was a predictor of a Big Five dimension (lower Agreeableness). Conclusions: The findings were not consistent across the measurement points (t1 to t2 vs. t2 to t3) with one exception in an explorative analysis: problematic gaming was a predictor for both problematic social media use and problematic alcohol use in youth (t1 to t2 and t2 to t3). The influence of lower Conscientiousness was confirmed for PG and initial longitudinal results for PSMU and PAU were observed. These novel findings could be considered when developing or revising preventive measures. Full article

The content in digital intervention therapies for children with attention deficit hyperactivity disorder (ADHD) requires various technical elements to interest and motivate the children. Their structure is often quiz-based, which allows easy access to quantitative assessments. However, in this study, I verify the effectiveness of digital intervention therapy by implementing story-based game content with active participation. In this study, 48 children aged 6 to 13 years diagnosed with ADHD were recruited and assigned to experimental (story-based content) and control (quiz-based content) groups; their attention improvements were compared. The improvement in attention was assessed by comparing the change rate of the Comprehension Attention Test (CAT) and Korean ADHD Rating Scale (K-ARS) scores before and after the intervention. At 4 weeks, the CAT score change rate was significantly different between the groups (p = 0.039, p = 0.040); the CAT score change rate before and after the intervention was significantly greater in the experimental than in the control group (p = 0.038). After adjusting for the baseline, the experimental group showed a significantly greater reduction in the K-ARS impulsivity and total K-ARS scores compared with the control group (p = 0.018, p = 0.012). Therefore, story-based content is more effective than quiz-based content in digital intervention therapy for children with ADHD. Full article