Since technology has been entering into human beings’ everyday life, individuals established a deep relationship with digital technology, thus an embodied link between people and digital instruments has been born. This is particularly evidenced by recent literature about screen time (duration of time spent by the individual in using electronic/digital media like television, smartphone, tablet or computer), it significantly influences different human beings’ dimensions: physical, psychological and neurological functions. Impact of digital technology on human beings can be considered as a result of syntonic functioning in order to improve different people’s life areas (e.g., work, social or intimate relationship, learning), while the dystonic relationship is evidenced as a result of human addiction to digital technology. The present study aims to provide a cognitive and social psychology perspective on how screen time is changing our existences, defining digital technology as a gift which people should be aware of in terms of positive but even negative consequences in everyday life.

Emotion recognition ability (ERA) is a core component of social cognition and behavioral regulation. While previous studies have focused on individuals with neuroanatomical impairments, little is known about multisensory emotion misperception in typically developing children with behavioral difficulties. This study explored the relationship between multisensory emotional confusion and behavioral problems in early childhood, using the Diagnostic Analysis of Nonverbal Accuracy – Second Edition, Revised Version (DANVA-2-RV) and the Strengths and Difficulties Questionnaire – Teacher Version (SDQ-TV). Data were collected from three first-grade classes in two public elementary schools in Southern Italy. Both institutions are inclusive, but only typically developing children were included in the normative sample. Forty children (mean age = 6.1 years; 21 males) completed the DANVA-2-RV to assess recognition of basic emotional expressions, while their main teachers completed the SDQ-TV to evaluate behavioral functioning. Results showed that multisensory emotional confusion was consistently associated with behavioral maladjustment. Moreover, the emotional confusion index emerged as a significant predictor of behavioral difficulties, highlighting its potential as an early indicator of socio-emotional vulnerability. These findings support the inclusion of confusion metrics in assessments and emphasize the importance of early interventions to strengthen children’s socio-emotional skills.

Background: Emotion recognition ability (ERA) plays a central role in children’s socio-emotional functioning, supporting early social interactions. This study examined whether ERA shows a pre–post change in a classroom-based training context and explored the association between ERA and socio-emotional adjustment. A secondary aim was to compare ERA between children with and without behavioral difficulties. Methods: A quasi-experimental study using a controlled non-randomized pre–post design was conducted. The sample included 159 children attending four public elementary schools. Study 1 compared an experimental and a control group assessed before and after the intervention using the DANVA-2-RV. Study 2 examined associations between ERA and behavioral functioning assessed via teacher reports (SDQ-TV) using correlational and group comparison analyses. Results: In Study 1, multivariate analyses revealed a significant main effect of Time, indicating overall variation across assessment points, whereas the Time × Group interaction was not statistically significant. Follow-up analyses were therefore interpreted descriptively. In Study 2, lower ERA was associated with higher socio-emotional difficulties, particularly peer problems. Conclusions: Across both studies, ERA varied over time regardless of group condition and was linked to socio-emotional adjustment in early childhood. However, the findings do not support a causal interpretation attributing these changes to the intervention. Future randomized studies are needed to determine whether targeted interventions can effectively modify ERA.

The digital transformation of mental health practice increasingly requires psychologists to integrate technological literacy with emotional and cognitive skills. This study presents a pilot project combining Visual Education and Artificial Intelligence (AI) through a Computer Vision model for emotional recognition. A convolutional neural network (CNN), based on MobileNetV2, was trained to identify facial emotions and tested for educational use within a serious game for psychologists’ professional development. Using transfer learning, the model achieved an accuracy of about 75% under controlled conditions but only 15.54% on a biased dataset. These results reveal both the potential and limitations of AI in emotional learning. The findings are discussed in relation to visual literacy, digital mental health, and AI ethics, illustrating how computational bias can become a pedagogical tool for psychology professionals.