ArticleClinical and translational science2026
AI-Powered Chatbot as a Health Literacy Tool for Enhancing Oral Cancer Awareness: Expert Feedback.
Article in Clinical and translational science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- A comparative analysis of large language models for providing oral cavity cancer information.Scientific reports · 2026Article
- Methodological Considerations for AI-Powered Chatbots in Oral Cancer Awareness: Stakeholder Diversity, Instrument Transparency, and Safety Auditing.Clinical and translational science · 2026Article
- AI-Powered Chatbot as a Health Literacy Tool for Enhancing Oral Cancer Awareness: Expert Feedback.Clinical and translational science · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Artificial intelligence (AI)-powered chatbots have emerged as potentially effective tools for delivering personalized, interactive, and culturally sensitive health education. Avoidable factors majorly cause oral and oropharyngeal cancers, and usually present with confusable symptoms, often leading to delayed diagnoses and poorer outcomes. Traditional oral health education methods have limitations in addressing the unique accessibility needs of groups that are most impacted by these outcomes. The primary aim of this study was to evaluate the usability and accuracy of an AI-powered chatbot prototype as an approachable, trustworthy, and engaging educational resource to enhance oral cancer awareness. A mixed-methods evaluation was conducted with six experts in behavioral science, oncology, dentistry, and AI. Experts interacted with the chatbot via a web interface and provided feedback via surveys rating usability and accuracy. Qualitative insights were gathered through open-ended survey questions and analyzed using thematic analysis, and quantitative data were collected through REDCap. The experts provided positive and constructive feedback, recognizing the chatbot's potential as an educational tool aiming to improve oral cancer-related information. They particularly praised its ease of access and the reliability of the information provided. However, experts identified areas for enhancement, including user interface changes, simplifying medical terminology, providing clearer initial guidance for users, and improving visual accessibility. Additionally, recommendations included integrating supplementary educational resources and clearer medical definitions to support deeper understanding and user engagement. This expert evaluation will guide the refinement for broader implementation in the project's next phase, evaluating acceptability and efficacy among non-expert users.
Indexed as
Identifiers
What OpenQuestion holds
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.