Anxiety disorders represent one of the most widespread mental health challenges globally, yet access to traditional therapeutic interventions remains constrained, particularly in resource-limited settings. This study evaluated the effectiveness of an AI-powered chatbot, developed using ChatGPT, in managing anxiety symptoms through evidence-based cognitive-behavioral therapy (CBT) techniques. Fifty participants with mild to moderate anxiety symptoms engaged with the chatbot over two observational phases, each lasting seven days. The chatbot delivered personalized interventions, including mindfulness exercises, cognitive restructuring, and breathing techniques, and was accessible 24/7 to provide real-time support during emotional distress. The findings revealed a significant reduction in anxiety symptoms in both phases, with an average improvement of 21.15% in Phase 1 and 20.42% in Phase 2. Enhanced engagement in Phase 2 suggested the potential for sustained usability and familiarity with the chatbot’s functions. While participants reported high satisfaction with the accessibility and personalization of the chatbot, its inability to replicate human empathy underscored the importance of integrating AI tools with human oversight for optimal outcomes. This study highlights the potential of AI-driven interventions as valuable complements to traditional therapy, providing scalable and accessible mental health support, particularly in regions with limited access to professional services.

Anxiety disorders are among the most prevalent mental health conditions globally, causing significant personal and societal burdens. Traditional therapies, while effective, often face barriers such as limited accessibility, high costs, and the stigma associated with seeking mental health care. The emergence of artificial intelligence (AI) chatbots offers a novel solution by providing accessible, cost-effective, and immediate support for individuals experiencing anxiety. This comprehensive review examines the evolution, efficacy, advantages, limitations, challenges, and future perspectives of AI chatbots in the treatment of anxiety disorders. A methodologically rigorous literature search was conducted across multiple databases, focusing on publications from 2010 to 2024 that evaluated AI chatbot interventions targeting anxiety symptoms. Empirical studies demonstrate that AI chatbots can effectively reduce anxiety symptoms by delivering therapeutic interventions like cognitive-behavioral therapy through interactive and personalized dialogues. The advantages include increased accessibility without geographical or temporal limitations, reduced costs, and an anonymity that encourages openness and reduces stigma. However, limitations persist, such as the lack of human empathy, ethical and privacy concerns related to data security, and technical challenges in understanding complex human emotions. The key challenges identified involve enhancing the emotional intelligence of chatbots, integrating them with traditional therapy, and establishing robust ethical frameworks to ensure user safety and data protection. Future research should focus on improving AI capabilities, personalization, cultural adaptation, and user engagement. In conclusion, AI chatbots represent a promising adjunct in treating anxiety disorders, offering scalable interventions that can complement traditional mental health services. Balancing technological innovation with ethical responsibility is crucial to maximize their potential benefits.

Background/Objectives: Otitis media (OM) is a common pediatric condition that significantly impacts hearing, language development, and quality of life. Emerging evidence suggests that vitamin D plays a crucial role in immune regulation and that deficiency may predispose children to recurrent OM. This study aimed to evaluate whether low serum vitamin D levels are associated with increased incidence and severity of OM in children aged 2–7 years. Methods: A cross-sectional study was conducted at a pediatric otolaryngology clinic in northwest Romania between November 2023 and April 2024. A total of 118 children were enrolled, including 87 children with documented episodes of OM within the preceding six months and 31 quasi-controls without recent OM episodes. Participants were stratified into three age groups (2–3, 4–5, and 6–7 years) and classified into clinical subtypes of OM (Acute Suppurative Otitis Media, Serous Otitis Media, and Acute Congestive Otitis Media). Serum 25-hydroxyvitamin D levels were measured using a chemiluminescence immunoassay and categorized as deficient (≤20 ng/mL), insufficient (21–29 ng/mL), or sufficient (≥30 ng/mL). Statistical analyses included one-way ANOVA with post-hoc tests, chi-square tests, linear regression, logistic regression, and Poisson regression. Results: Children with OM exhibited significantly lower vitamin D levels compared to controls, with the most pronounced deficiency observed in the Acute Suppurative OM group. One-way ANOVA revealed significant differences among the groups (F(3,114) = 82.30, p < 0.001), and linear regression demonstrated a strong inverse correlation between vitamin D levels and the frequency of OM episodes (r = −0.793, adjusted R² = 0.63, p < 0.001). Logistic regression indicated that vitamin D insufficiency significantly increased the odds of OM (OR ≈ 120.74, p < 0.001), while Poisson regression showed incidence rate ratios of 13.62 for deficient and 10.47 for insufficient vitamin D status (p < 0.001). Conclusions: The findings indicate that low serum vitamin D levels are significantly associated with an increased risk and frequency of otitis media in preschool-aged children. These results support the role of vitamin D deficiency as an independent, modifiable risk factor for recurrent OM, suggesting that vitamin D screening and supplementation could be beneficial in reducing the clinical and economic burden of this condition.