درخت حوزه‌های تخصصی

The present study aimed to predict marital disaffection based on early maladaptive schemas with the mediation of cognitive emotion regulation in working women. This research was applied in terms of objective and correlational descriptive in terms of method, which was implemented using structural equation modeling. The statistical population of this research consisted of all working women studying in the Islamic Azad University of Karaj branch in the second semester of 2023-2024, and 308 of them were selected by available sampling method. The study tool included the Marital Disaffection Scale by Kayser (1996); the Young's Schema Questionnaire short version (1998) and the Cognitive Emotion Regulation Questionnaire by Garnefski et al.'s (2001). The structural equation modeling method was used to analyze the data. The results showed that marital disaffection is predicted based on early maladaptive schemas in working women (P=0.001, β=0.400). Marital disaffection is predicted based on maladaptive (p=0.001, β=0.449) and adaptive (p=0.001, β=-0.378) strategies of cognitive emotion regulation in working women. Marital disaffection is predicted based on based on early maladaptive schemas with the mediation of maladaptive (P=0.001, Z=4.11) and adaptive strategies (P=0.001, Z=3.73) cognitive regulation of emotion in working women.

Objective: Patients with Ménière's often experience multiple psychological problems and are not satisfied with the results of medication therapy. This study aimed to evaluate the effectiveness of cognitive-behavioral therapy (CBT) on anxiety, lifestyle, and experiential avoidance in patients with Ménière's disease.  Method: The study employed a quasi-experimental design with a pre-test, post-test, and one-month follow-up approach. The statistical population comprised all patients diagnosed with Ménière's disease who sought treatment at the specialized ear clinic affiliated with Mashhad Medical Sciences Hospital between January and March 2023. From this population, 30 patients meeting the inclusion criteria were selected using an oriented sampling method. Participants were randomly assigned to a CBT intervention group (n = 15) and a control group (n = 15). Data collected at three time points—pre-intervention, post-intervention, and 30 days after the intervention—using the Smith Lifestyle Questionnaire, Bond Experiential Avoidance Questionnaire, and the Anxiety subscale of the DASS-21. The data were analyzed using repeated measures analysis of variance. Results: The results indicated a significant reduction in anxiety levels in the CBT group compared to the control group in both the post-test and follow-up assessments (P < 0.05). Additionally, a significant improvement was observed in lifestyle scores in the CBT group relative to the control group (P < 0.05). The difference in experiential avoidance between the two groups was also statistically significant (P < 0.05).  Conclusion: The findings suggest that cognitive-behavioral therapy is effective in reducing anxiety and experiential avoidance while improving lifestyle in patients with Ménière's disease. These results underscore the potential of CBT as an adjunctive treatment in managing the psychological and lifestyle-related challenges associated with Ménière's disease.

Most studies on placebo mechanisms rely on Expectancy Theory, which suggests that conceptual expectations can bring about physiological change. However, the exact processes underlying this effect remain unclear. Perceptual Symbol Systems (PSS) Theory, grounded in Embodied Cognition Theory, offers a more specific explanation: mental representations grounded in sensory-motor systems may directly evoke bodily responses. This study tested whether embodied primes, based on PSS Theory, elicit stronger placebo responses than traditional expectancy-based suggestions. Using a within-subjects design, 71 university students underwent a cold pressure task under three conditions: (1) verbal suggestion of an analgesic cream, (2) visual priming with a photo of a person looking upward, and (3) combined visual-motor priming, where participants also looked upward themselves. The placebo response was measured by changes in pain intensity and heart rate. Results showed that both embodied conditions (visual and visual-motor priming) produced stronger placebo responses than the verbal suggestion condition, as indicated by lower pain intensity and reduced heart rate (F(2,140)=5.83; p<.01). However, the difference between the two embodied conditions was not statistically significant in terms of pain ratings. Notably, visual-motor priming led to a greater reduction in heart rate than visual priming alone (F(6,330)=1.99; p=.06), suggesting a subtle additive effect of motor engagement. These findings support the role of unconscious embodied processes—specifically, perceptual and motor representations—in modulating placebo responses. They offer a promising direction for understanding how non-verbal bodily cues may influence the complex perception of pain.

Objective: This review examined recent studies (2024–2025) to identify new conceptualizations of learning in the AI era, characterized by hybrid human-system collaboration, real-time personalization using multimodal data, interpretability, and a shift from teacher-centered to learner- and technology-driven approaches. Method: Nine peer-reviewed studies from 2024–2025 were analyzed thematically, sourced from databases including Scopus, Web of Science, PubMed, Google Scholar, and ResearchGate using keywords like "learning definition", "conceptualization of learning", "AI in education" and "hybrid intelligence." Result: The findings reveal that learning in the AI era is conceptualized as a dynamic, adaptive, and multidimensional process integrating cognitive, emotional, social, and interactive elements. Emerging theoretical frameworks include hybrid intelligence emphasizing human-system co-evolution, the integration of cognitive load theory with AI and educational neuroscience, and generalized online learning models prioritizing interpretability and continuous autonomous learning. Key novel features encompass multimodal learning leveraging neurophysiological tools, real-time adaptive pathways, human-machine collaborative processes, incorporation of behavioral and interactional data alongside neurophysiological indicators, and a strong emphasis on transparency and interpretability Conclusions: The core transformation is a paradigm shift toward learner- and technology-centered models, with social interaction gaining prominence in AI-mediated settings. While AI enables personalized feedback and dynamic adaptation, its limitations in context and causal reasoning underscore the necessity of human-AI synergy. Practical implications highlight the need for educator training in new technologies and careful attention to ethics and equitable access. These insights derive from a constrained sample of nine studies and may not encompass the entire scope of research on learning from 2024–2025.