ArticleJournal of education and health promotion2025
Nurses' assessment of artificial ıntelligence chatbots for health literacy education.
Article in Journal of education and health promotion, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 3 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Artificial intelligence (AI) for social innovation in health education: promoting health literacy through personalized ai-driven learning tools - a systematic review.BMC medical education · 2025Pooled it
- Artificial intelligence in the identification and prediction of adverse transfusion reactions(ATRs) and implications for clinical management: a systematic review of models and applications.BMC medical informatics and decision making · 2025Pooled it
- AI literacy and competency in nursing education: preparing students and faculty members for an AI-enabled future-a systematic review and meta-analysis.Frontiers in medicine · 2025Pooled it
- Conversational Agents for Asthma and Chronic Obstructive Pulmonary Disease Management: Scoping Review.Journal of medical Internet research · 2026Article
- Artificial Intelligence-Supported Virtual Nursing at Home: A Systematic Review.Florence Nightingale journal of nursing · 2026Article
- Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundArtificial intelligence (AI)-powered chatbots are emerging as a new tool in healthcare, offering the potential to provide patients with information and support. Despite their growing presence, there are concerns regarding the medical reliability of the information they provide and the potential risks to patient safety. MATERIAL AND
methodsThe aim of this study is to assess the medical reliability of responses to health-related questions provided by an AI-powered chatbot and to evaluate the risks to patient safety. The study is designed using a mixed-methods phenomenology approach. The participants are 44 nurses working at a private hospital in Cyprus. Data collection was conducted via survey forms and focus group discussions. Quantitative data were analyzed using descriptive statistics, while qualitative data were examined using content analysis.
resultsThe results indicate that according to the nurses' evaluations, the medical reliability of the AI chatbot's responses is generally high. However, instances of incorrect or incomplete information were also noted. Specifically, the quantitative analysis showed that a majority of the nurses found the chatbot's responses to be accurate and useful. The qualitative analysis revealed concerns about the potential for the chatbot to misdirect patients or contribute to diagnostic errors. These risks highlight the importance of monitoring and improving the AI systems to minimize errors and enhance reliability.
conclusionAI chatbots can provide valuable information and support to patients, improving accessibility and engagement in healthcare. However, concerns about medical reliability and patient safety remain. Continuous evaluation and improvement of these systems are necessary, alongside efforts to enhance patients' health literacy to help them accurately assess information from AI chatbots.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.