ReviewJournal of cancer education : the official journal of the American Association for Cancer Education2025
Evidence-Based Analysis of AI Chatbots in Oncology Patient Education: Implications for Trust, Perceived Realness, and Misinformation Management.
Review in Journal of cancer education : the official journal of the American Association for Cancer Education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The waiting room of uncertainty: digital patient support for potentially bad news-a scoping review.Frontiers in digital health · 2025Pooled it
- The Missing Dimension in Cancer Education: Developmental Meaning-Making and the Expert's Illusion of Symmetry.Journal of cancer education : the official journal of the American Association for Cancer Education · 2026Review
- Comparison of artificial intelligence-based chatbots and expert periodontists in responding to patient questions: a multi-dimensional analysis.BMC oral health · 2026Article
- Evaluating the ability of AI chatbots to provide informed consent information for common oncological surgeries.Annals of the Royal College of Surgeons of England · 2026Article
- Development and feasibility testing of a conversational chatbot supporting genetic education and testing for hereditary cancer.Journal of community genetics · 2026Article
- Lessons Learned From Implementing a Culturally Tailored Virtual Support Program for Asian American Breast Cancer Survivors With Pain and Depression.Journal of medical Internet research · 2026Article
- Comment on "Overnight stiffness index from finger photoplethysmography in relation to markers of cardiovascular risk and vascular aging".Heart and vessels · 2026Article
- A comparative analysis of large language models for providing oral cavity cancer information.Scientific reports · 2026Article
- Applications of Artificial Intelligence (AI) in Breast Cancer Care Delivery and Education: A Scoping Review.International journal of environmental research and public health · 2026Article
- A complex intervention to improve life experience during and after acute treatment for breast cancer: Preliminary results from intervention development for the Continuum PAROLE-Onco 360 program.Canadian journal of public health = Revue canadienne de sante publique · 2026Article
- Artificial intelligence analysis of minimally invasive surgery data.Journal of robotic surgery · 2026Review
- Artificial Intelligence Chatbots in Peritoneal Dialysis Education: A Cross-Sectional Comparative Study of Quality, Readability, and Reliability.Journal of clinical medicine · 2026Article
- Preparedness for generative AI adoption among Chinese cancer survivors: a multi-center cross-sectional survey study.Frontiers in public health · 2026Article
- Empowering parents of children with ADHD through artificial intelligence.Child and adolescent psychiatry and mental health · 2025Article
- Empowering breast cancer clients through AI chatbots: transforming knowledge and attitudes for enhanced nursing care.BMC nursing · 2025Article
- Patient perceptions of empathy in physician and artificial intelligence chatbot responses to patient questions about cancer.NPJ digital medicine · 2025Article
- Performance of five free large language models in dental trauma: a 30-day longitudinal benchmark study.Frontiers in oral health · 2025Article
- Article
- Evaluating Chatbots as Nursing Assistants in Palliative Care: A Narrative Review.Indian journal of palliative careReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rapid integration of AI-driven chatbots into oncology education represents both a transformative opportunity and a critical challenge. These systems, powered by advanced language models, can deliver personalized, real-time cancer information to patients, caregivers, and clinicians, bridging gaps in access and availability. However, their ability to convincingly mimic human-like conversation raises pressing concerns regarding misinformation, trust, and their overall effectiveness in digital health communication. This review examines the dual-edged role of AI chatbots, exploring their capacity to support patient education and alleviate clinical burdens, while highlighting the risks of lack of or inadequate algorithmic opacity (i.e., the inability to see the data and reasoning used to make a decision, which hinders appropriate future action), false information, and the ethical dilemmas posed by human-seeming AI entities. Strategies to mitigate these risks include robust oversight, transparent algorithmic development, and alignment with evidence-based oncology protocols. Ultimately, the responsible deployment of AI chatbots requires a commitment to safeguarding the core values of evidence-based practice, patient trust, and human-centered care.
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.