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.

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.

Objectives: This study aimed to identify coronavirus disease 2019 (COVID-19) vaccine perception, acceptance, confidence, hesitancy, and barriers among health care workers (HCWs).Methods: An online national cross-sectional pilot-validated questionnaire was self-administered by HCWs in Saudi Arabia, which is a nation with MERS-CoV experience. The main outcome variable was HCWs’ acceptance of COVID-19 vaccine candidates. The factors associated with vaccination acceptance were identified through a logistic regression analysis, and the level of anxiety was measured using a validated instrument to measure general anxiety levels.Results: Out of the 1512 HCWs who completed the study questionnaire—of which 62.4% were women—70% were willing to receive COVID-19 vaccines. A logistic regression analysis revealed that male HCWs (ORa = 1.551, 95% CI: 1.122–2.144), HCWs who believe in vaccine safety (ORa = 2.151; 95% CI: 1.708–2.708), HCWs who believe that COVID vaccines are the most likely way to stop the pandemic (ORa = 1.539; 95% CI: 1.259–1.881), and HCWs who rely on the Centers for Disease Control and Prevention website for COVID 19 updates (ORa = 1.505, 95% CI: 1.125–2.013) were significantly associated with reporting a willingness to be vaccinated. However, HCWs who believed that the vaccines were rushed without evidence-informed testing were found to be 60% less inclined to accept COVID-19 vaccines (ORa = 0.394, 95% CI: 0.298–0.522).Conclusion: Most HCWs are willing to receive COVID-19 vaccines once they are available; the satisfactoriness of COVID-19 vaccination among HCWs is crucial because health professionals’ knowledge and confidence toward vaccines are important determining factors for not only their own vaccine acceptance but also recommendation for such vaccines to their patients.

Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.