mental health

The incorporation of Artificial Intelligence (AI) into language development has garnered considerable interest, especially within the realm of English as a Foreign Language (EFL) education. Psychological flow is regarded as a pivotal element that affects learning outcomes; however, its significance in the context of AI-assisted language learning has yet to be thoroughly investigated. This study examines the relationship between psychological flow induced by AI, tendencies of fortitude, mental health, and critical thinking among 214 university students enrolled in EFL programs who utilized AI-integrated language learning aids. Data were gathered via structured online surveys, and the relationships among the variables were examined utilizing Structural Equation Modeling (SEM). The findings suggest that the psychological flow induced by AI has a substantial impact on learners' levels of fortitude, mental well-being, and critical thinking. The findings indicate that when learners engage in AI-assisted language learning and experience a state of flow, they exhibit elevated levels of perseverance, improved mental well-being, and enhanced critical thinking. These outcomes underscore the dual function of flow in AI-assisted language learning, as it not only augments learners' cognitive engagement but also fosters positive emotional states that are conducive to improved mental health and enhanced problem-solving abilities. The findings of the study possess significant pedagogical implications, indicating that AI-based platforms ought to be developed to promote a state of fluidity by integrating personalized learning trajectories, real-time feedback mechanisms, and engaging features.

Objective: Insomnia, marked by difficulty falling or staying asleep, affects many students and contributes to increased worry, cognitive distortions, and depression, exacerbating their overall well-being and academic performance. This study evaluates the effectiveness of Mindfulness-Based Stress Reduction (MBSR) in reducing worry, cognitive distortions, and depression in students with insomnia symptoms. Method: The research utilized a quasi-experimental design with a pretest-posttest control group. The statistical population consisted of university students in Ardabil Province during the 2023-2024 academic year. A total of 34 students were purposefully selected based on predefined criteria (e.g., insomnia symptoms) and then randomly assigned to either the intervention group (n = 17) or the control group (n = 17). The research instruments included the Insomnia Severity Index (2001), the Penn State Worry Questionnaire (1990), the Cognitive Distortions Questionnaire (2004), and the Beck Depression Inventory (1996). The intervention group participated in eight weekly sessions of 90-minute MBSR, while the control group received no intervention. Data were analyzed using multivariate analysis of covariance with SPSS-27. Results: The results indicated that MBSR significantly reduced worry (F = 46.86), rejection in interpersonal relationships (F = 30.07), unrealistic expectations in relationships (F = 41.54), misperception in interpersonal relationships (F = 30.38), and depression (F = 41.20) among students with insomnia symptoms (P < 0.001). Conclusion: The results highlight the potential of MBSR as a valuable non-pharmacological intervention for managing insomnia and associated psychological challenges in academic settings. Given its effectiveness, further research could explore long-term benefits and applicability across diverse student populations and settings.