ArticleResearch and reports in urology2024
ChatGPT: Is This Patient Education Tool for Urological Malignancies Readable for the General Population?
Article in Research and reports in urology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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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
13 citing papers in PubMed, 12 citations in OpenAlex.
- Filling the information gap: a validated comparison of ChatGPT, Gemini, and Claude for penile cancer patient education.Translational andrology and urology · 2026Article
- The Alberta Quality Assessment Tool: Risk of Bias (AQAT:RoB) for the Evaluation of Medical Large Language Model Question-Answer Studies: Development and Pilot Validation.Journal of medical Internet research · 2026Article
- Generative AI for patient education in cancer care: A scoping review of evaluation practices and emerging trends.Technical innovations & patient support in radiation oncology · 2026Review
- Feasibility analysis of generative artificial intelligence tools as a means of medical science popularization on urological diseases.Translational andrology and urology · 2025Article
- Readability of Chatbot Responses in Prostate Cancer and Urological Care: Objective Metrics Versus Patient Perceptions.Current oncology (Toronto, Ont.) · 2025Article
- Clinical applications and limitations of large language models in nephrology: a systematic review.Clinical kidney journal · 2025Article
- Large language model integrations in cancer decision-making: a systematic review and meta-analysis.NPJ digital medicine · 2025Article
- Accuracy, readability, and understandability of large language models for prostate cancer information to the public.Prostate cancer and prostatic diseases · 2025Article
- Assessing the Quality and Reliability of ChatGPT's Responses to Radiotherapy-Related Patient Queries: Comparative Study With GPT-3.5 and GPT-4.JMIR cancer · 2025Article
- Evaluating the quality of large language model-generated preoperative patient education material: a comparative study across models and surgery types.Frontiers in medicine · 2025Article
- Comparing patient education tools for chronic pain medications: Artificial intelligence chatbot versus traditional patient information leaflets.Indian journal of anaesthesia · 2024Article
- Large language models in patient education: a scoping review of applications in medicine.Frontiers in medicine · 2024Article
- Article
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 at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: With widespread adoption of technological advancements in everyday life, patients are now increasingly able and willing to obtain information about their health conditions, treatment options, and indeed expected outcomes via the convenience of any device than can access the worldwide web. This introduces another aspect of patient care in the provision of healthcare for the modern doctor. ChatGPT is the first of an increasing number of self learning programs that have been released recently which may revolutionize and impact healthcare delivery. Methods: The aim of this study is to obtain an objective measure of the readability of information provided on ChatGPT when compared with current validated patient information sheets provided by government health institutions in Western Australia. The same structured questions were input into the program for three major urological malignancies (urothelial, renal, and prostate), with the response generated evaluated with a validated readability scoring system - Flesch-Kincaid reading ease score. The same scoring system was then applied to current patient information sheets in circulation from Cancer Council Australia and UpToDate. Results: Findings in this study looking at ease of readability of information provided on ChatGPT as compared to other government bodies and healthcare institutions confirm that they are non-inferior and may be a useful tool or adjunct to the traditional clinic based consultations. Ease of use of the information generated from ChatGPT was increased further when the question was modified to target an audience of 16 years of age, the average level of education attained by an Australian. Discussion: Future research can be done to look into incorporating the use of similar technologies to increase efficiency in the healthcare system and reduce healthcare costs.
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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.