Introduction: The COVID-19 pandemic is likely to increase anxiety levels within the community and in particular medical students who are already considered psychologically vulnerable groups. Since the COVID-19 outbreak, no study has yet estimated the effect of this pandemic on university students in the UAE or its impact on the psychological well-being of medical students. Methods and Materials: We surveyed 1485 medical (comprising medical and dental) and non-medical university students across 4 emirates within the UAE. We used an online platform to assess knowledge, sources of information, changes in hygienic behavior, perceptions of fear and worry and anxiety levels using the generalized anxiety disorder 7 (GAD-7) scale. The GAD-7 score was measured at three time points: during hospital visits for medical/dental students, before the introduction of online learning and after online learning for all students. Results: The majority of students demonstrated high levels of knowledge and utilized reliable sources of information. Non-medical students exercised higher compliance with social restrictions, while medical students practiced better hand hygiene. Almost half of students reported anxiety levels ranging from mild to severe with females reporting higher anxiety scores during hospital visits (OR=2.02, 95% CI, 1.41 to 2.91) and medical students reporting lower anxiety levels in comparison to dental students (OR=0.61, 95% CI, 0.45 to 0.84). Medical students reported higher levels of anxiety during their clinical rotations which decreased with the introduction of online learning, yet, non-medical students’ anxiety levels increased with online learning. Conclusion: This study provides important information on the initial response and anxiety levels in university students across the UAE during the COVID-19 pandemic. The findings from our study can be used to support the development of effective screening strategies and interventions to build psychological resilience among university students during the COVID-19 pandemic or any other public health emergencies in the future.

This study aimed to assess the knowledge, attitudes, and intended practices of healthcare workers (HCWs) in Saudi Arabia towards ChatGPT, an artificial intelligence (AI) Chatbot, within the first three months after its launch. We also aimed to identify potential barriers to AI Chatbot adoption among healthcare professionals. A cross-sectional survey was conducted among 1057 HCWs in Saudi Arabia, distributed electronically via social media channels from 21 February to 6 March 2023. The survey evaluated HCWs’ familiarity with ChatGPT-3.5, their satisfaction, intended future use, and perceived usefulness in healthcare practice. Of the respondents, 18.4% had used ChatGPT for healthcare purposes, while 84.1% of non-users expressed interest in utilizing AI Chatbots in the future. Most participants (75.1%) were comfortable with incorporating ChatGPT into their healthcare practice. HCWs perceived the Chatbot to be useful in various aspects of healthcare, such as medical decision-making (39.5%), patient and family support (44.7%), medical literature appraisal (48.5%), and medical research assistance (65.9%). A majority (76.7%) believed ChatGPT could positively impact the future of healthcare systems. Nevertheless, concerns about credibility and the source of information provided by AI Chatbots (46.9%) were identified as the main barriers. Although HCWs recognize ChatGPT as a valuable addition to digital health in the early stages of adoption, addressing concerns regarding accuracy, reliability, and medicolegal implications is crucial. Therefore, due to their unreliability, the current forms of ChatGPT and other Chatbots should not be used for diagnostic or treatment purposes without human expert oversight. Ensuring the trustworthiness and dependability of AI Chatbots is essential for successful implementation in healthcare settings. Future research should focus on evaluating the clinical outcomes of ChatGPT and benchmarking its performance against other AI Chatbots.

Background: Artificial intelligence (AI) chatbots have recently gained use in medical practice by health care practitioners. Interestingly, the output of these AI chatbots was found to have varying degrees of hallucination in content and references. Such hallucinations generate doubts about their output and their implementation. Objective: The aim of our study was to propose a reference hallucination score (RHS) to evaluate the authenticity of AI chatbots’ citations. Methods: Six AI chatbots were challenged with the same 10 medical prompts, requesting 10 references per prompt. The RHS is composed of 6 bibliographic items and the reference’s relevance to prompts’ keywords. RHS was calculated for each reference, prompt, and type of prompt (basic vs complex). The average RHS was calculated for each AI chatbot and compared across the different types of prompts and AI chatbots. Results: Bard failed to generate any references. ChatGPT 3.5 and Bing generated the highest RHS (score=11), while Elicit and SciSpace generated the lowest RHS (score=1), and Perplexity generated a middle RHS (score=7). The highest degree of hallucination was observed for reference relevancy to the prompt keywords (308/500, 61.6%), while the lowest was for reference titles (169/500, 33.8%). ChatGPT and Bing had comparable RHS (β coefficient=–0.069; P=.32), while Perplexity had significantly lower RHS than ChatGPT (β coefficient=–0.345; P<.001). AI chatbots generally had significantly higher RHS when prompted with scenarios or complex format prompts (β coefficient=0.486; P<.001). Conclusions: The variation in RHS underscores the necessity for a robust reference evaluation tool to improve the authenticity of AI chatbots. Further, the variations highlight the importance of verifying their output and citations. Elicit and SciSpace had negligible hallucination, while ChatGPT and Bing had critical hallucination levels. The proposed AI chatbots’ RHS could contribute to ongoing efforts to enhance AI’s general reliability in medical research.

Objectives: To quantify parental acceptance of the COVID-19 vaccine and assess the vaccine hesitancy (VH) for COVID-19 vs. childhood vaccines.Methods: Eight vaccine hesitancy scale (VHS) items, adopted from WHO's Strategic Advisory Group of Immunization (SAGE), were used to assess VH for COVID-19 vaccine vs. routine childhood vaccines. We distributed the online survey to parents with the commence of the national childhood COVID-19 vaccination program in Saudi Arabia.Results: Among 3,167 parents, 47.6% are decided to vaccinate their children against COVID-19. The most common reasons for refusal were inadequate safety information (69%) and worry about side effects (60.6%). Parents have a significantly greater positive attitudes toward children's routine vaccines vs. the COVID-19 vaccine, with higher mean VHS (±SD) = 2.98 ± 0.58 vs. 2.63 ± 0.73, respectively (p-value < 0.001). Parents agreed more that routine childhood vaccines are more essential and effective as compared to the COVID-19 vaccine (Cohen's D: 0.946, and 0.826, consecutively; T-test p-value < 0.00). There is more parental anxiety about serious side effects of the COVID-19 vaccine vs. routine childhood vaccines (Cohen's D = 0.706, p-value < 0.001). Parents who relied on the Ministry of Health information were more predicted (OR = 1.28, p-value = 0.035) to intend to vaccinate as opposed to those who used the WHO website (OR = 0.47, −53%, p-value < 0.001). In a multivariate logistic regression analysis, the factors associated with intention to vaccinate children were parents who received COVID-19 vaccine, older parents, having children aged 12–18, and parents with lower education levels.Conclusions: Significant proportion of parents are hesitant about the COVID-19 vaccine because they are less confident in its effectiveness, safety, and whether it is essential for their children. Relying on the national official healthcare authority's website for the source of information was associated with increased acceptance of childhood COVID-19 vaccination. As parental intention to vaccinate children against COVID-19 is suboptimal, healthcare authorities could boost vaccine uptake by campaigns targeting hesitant parents.

Generative Artificial Intelligence (GAI) has driven several advancements in healthcare, with large language models (LLMs) such as OpenAI’s ChatGPT, Google’s Gemini, and Microsoft’s Copilot demonstrating potential in clinical decision support, medical education, and research acceleration. However, their closed-source architecture, high computational costs, and limited adaptability to specialized medical contexts remained key barriers to universal adoption. Now, with the rise of DeepSeek’s DeepThink (R1), an open-source LLM, gaining prominence since mid-January 2025, new opportunities and challenges emerge for healthcare integration and AI-driven research. Unlike proprietary models, DeepSeek fosters continuous learning by leveraging publicly available open-source datasets, possibly enhancing adaptability to the ever-evolving medical knowledge and scientific reasoning. Its transparent, community-driven approach may enable greater customization, regional specialization, and collaboration among data researchers and clinicians.

Introduction: Middle East respiratory syndrome coronavirus (MERS-CoV) continues to cause frequent outbreaks in hospitals in Saudi Arabia. Since healthcare workers (HCWs) have a higher risk of acquiring and spreading MERS-CoV, we aimed to evaluate the perceived risk and anxiety level of HCWs in Saudi Arabia regarding MERS. Methodology: An anonymous, self-administered questionnaire was sent online to HCWs at King Khalid University Hospital in Saudi Arabia. The total knowledge and anxiety scores were calculated. Logistic regression analyses were used to identify predictors of high anxiety scores. Results: Of 591 (70%) HCWs that responded, 284 (55%), 164 (32%), and 68 (13.2%) were physicians, nurses, and technicians, respectively. Physicians obtained a lower median knowledge score (6/9) compared to other professions (7/9). The mean anxiety score was similar for physicians and other HCWs (3/5); however, non-physicians expressed higher levels of anxiety toward the risk of transmitting MERS-CoV to their families, with an anxiety score of 4/5. The ability of the virus to cause severe disease or death was the most frequently reported reason for worry by physicians (89.7%) and non-physicians (87.2%). Overall, 80% of physicians and 90% of non-physicians reported improvement in adherence to hand hygiene and standard precautions while in hospital (p = 0.002). Concern over transmitting MERS-CoV to family members was the most predictive factor for anxiety among non-physician HCWs. Conclusion: A significant proportion of HCWs expressed anxiety about the risk of acquiring MERS-CoV infection. Healthcare institutions need to develop an integrated psychological response for HCWs to the occupational and psychological challenge of MERS-CoV outbreaks.