This article discusses the challenges and implications of artificial intelligence powered chatbot (AI-Chatbots) in nursing education. Chat Generative Pre-trained Transformer (ChatGPT) is an AI-Chatbot that can engage in detailed dialog and pass qualification tests in various fields. It can be applied for drafting course materials and administrative paperwork. Students can use it for personalized self-paced learning. AI-Chatbot technology can be applied in problem-based learning for hands-on practice experiences. There are concerns about over-reliance on the technology, including issues with plagiarism and limiting critical thinking skills. Educators must provide clear guidelines on appropriate use and emphasize the importance of critical thinking and proper citation. Educators must proactively adjust their curricula and pedagogy. AI-Chatbot technology could transform the nursing profession by aiding and streamlining administrative tasks, allowing nurses to focus on patient care. The use of AI-Chatbots to socially assist patients and for therapeutic purposes in mental health shows promise in improving well-being of patients, and potentially easing shortage and burnout for healthcare workers. AI-Chatbots can help nursing students and researchers to overcome technical barriers in nursing informatics, increasing accessibility for individuals without technical background. AI-Chatbot technology has potential in easing tasks for nurses, improving patient care, and enhancing nursing education.

Objective: Community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) is an emerging global public health threat. In response to a highlighted strategic priority of the World Health Organization Global Action Plan on Antimicrobial Resistance, to “strengthen the knowledge and evidence base through surveillance and research”, we synthesized published articles to estimate CA-MRSA carriage prevalence in the Asia-Pacific region. Methods: A systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PROSPERO CRD:42017067399). We searched MEDLINE, EMBASE, and PubMed for articles published from 1 January 2000 to 19 May 2017, which reported CA-MRSA carriage (defined as either colonization or infection) in Asia-Pacific region from 2000 to 2016. Studies were stratified according to settings (community or hospital where CA-MRSA was isolated) and study populations (general public or subpopulations with specified characteristics). Ranges of CA-MRSA carriage prevalence were reported for study groups. Results: In total, 152 studies were identified. Large diversity was observed among studies in most study groups. In community-level studies, the CA-MRSA carriage prevalence among the general public ranged from 0% to 23.5%, whereas that ranged from 0.7% to 10.4% in hospital settings. From community-level studies, countries with the highest prevalence were India (16.5%–23.5%), followed by Vietnam (7.9%) and Taiwan (3.5%–3.8%). Children aged ≤6 (range: 0.5%–40.3%) and household members of CA-MRSA carriers (range: 13.0%–26.4%) are subgroups without specific health conditions but with much higher CA-MRSA carriage when compared to the general population. Conclusion: Our CA-MRSA prevalence estimates serve as the baseline for future national and international surveillance. The ranges of prevalence and characteristics associated with CA-MRSA carriage can inform health authorities to formulate infection control policies for high-risk subgroups. Future studies should explore the heterogeneities in CA-MRSA carriage prevalence among subgroups and countries to clarify the predominant transmission mechanisms in Asia-Pacific and other regions.

Objective: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement has been developed as a guideline for reporting systematic reviews and meta-analyses. Despite the prevalent use of the PRISMA statement in medicine and nursing, no studies have examined authors’ perception of it. The purpose of this study is to explore the perception of the PRISMA statement of authors who published reviews, meta-analyses, or both in nursing journals. Design: Cross-sectional descriptive study. Methods: An online survey was conducted among authors who published reviews, meta-analyses, or both in nursing journals between 2011 and 2017. The selected authors’ email addresses were extracted from the PUBMED database. A questionnaire—with a 10-point Likert scale (1— not important at all to 10— very important )—was developed to elicit their responses regarding their perception of not only the PRISMA statement as a whole, but also the individual items therein. Results: Invitations were sent to 1960 valid email addresses identified, with 230 responses (response rate: 11.7%) and 181 completed responses (completion rate: 9.2%). The average perceived importance of the PRISMA statement was 8.66 (SD=1.35), while the perceived importance for the individual items ranged from 7.74 to 9.32. Six items were rated significantly higher than the average rating, whereas one item was rated significantly lower. Conclusion: Most respondents perceived the PRISMA statement as important. Items related to information sources, selection, search-flow presentation, summary of findings, limitations and interpretation were deemed more important while the registration was deemed less so.

The reported study illustrates a methodology for compiling training datasets to fine-tune Large Language Models (LLMs) for healthcare information in Vietnamese, a low-resource language. The objective is to bridge the gap in medical information accessibility and enhance healthcare communication in developing countries by adapting LLMs to specific linguistic nuances and domain needs. The methodology involves selecting a base model, compiling a domain-specific dataset, and fine-tuning the model with this dataset. Three open-source models were selected. The dataset, comprising approximately 337,000 prompt-response pairs in Vietnamese, was compiled using existing datasets, data crawled from Vietnamese medical online forums, and distilled from Vietnamese medical textbooks. The three models were fine-tuned using the Low-Rank adaptation (LoRA) and Quantized Low-Rank adaptation (QLoRA) techniques. Models' performances were evaluated using BertScore score, Rouge-L score, and the "LLM-as-a-Judge" method. The fine-tuned models showed enhancements in performance over their base versions across evaluation metrics in BertScore score, Rouge-L score and "LLM-as-a-Judge" method, confirming the effectiveness of the fine-tuning process. This study details the process of fine-tuning open-source LLMs for health information inquiries in Vietnamese, demonstrating its potential to improve healthcare communication in low-resource languages. Deploying the fine-tuned LLM on-premise enhances data privacy and security. However, the significant computing power and costs required pose challenges, especially for organizations in developing countries. This case study highlights the unique challenges faced by developing countries using low-resource languages. Initiatives are needed to emphasize efforts to bridge healthcare gaps in underserved areas and contribute to global health equity.