ArticleEuropean urology open science2024
Effectiveness of the Medical Chatbot PROSCA to Inform Patients About Prostate Cancer: Results of a Randomized Controlled Trial.
Article in European urology open science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses 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
15 citing papers in PubMed, 2 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
- The Effectiveness and Feasibility of Conversational Agents in Supporting Care for Patients With Cancer: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Leveraging generative AI to enhance doctor-patient communication.Nature reviews. Urology · 2026Article
- Patients prefer ChatGPT to institutional websites for questions on radiation-based imaging exams: international mixed-methods study.Radiology advances · 2026Article
- AI chatbots for health information seeking among Chinese patients with precancerous ENT lesions: a descriptive qualitative study.BMJ open · 2026Article
- Transforming Urological Care With Artificial Intelligence Chatbots: From Digital Assistants to Clinical Partners.International neurourology journal · 2026Review
- Quality and Usability of Prostate Cancer Information Generated by Artificial Intelligence Chatbots: A Comparative Analysis.Cancers · 2026Article
- Implementation of AI in oncology: a systematic review of educational and clinical integration in global contexts.Frontiers in digital health · 2026Review
- Privacy-by-Design Framework for Large Language Model Chatbots in Urology.International neurourology journal · 2025Article
- Design and Validation of a Chatbot-Based Cervical Cancer Screening Decision Aid for Women Experiencing Socioeconomic Disadvantage: User-Centered Approach Study.JMIR cancer · 2025Article
- Artificial intelligence and patient education.Current opinion in urology · 2025Review
- Artificial intelligence in oncology: promise, peril, and the future of patient-physician interaction.Frontiers in digital health · 2025Review
- Concordance with CONSORT-AI guidelines in reporting of randomised controlled trials investigating artificial intelligence in oncology: a systematic review.BMJ oncology · 2025Article
- Usefulness and Ease of Use of an Artificial Intelligence Chatbot for Kidney Stone Formers.Cureus · 2025Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and objective: Artificial intelligence (AI)-powered conversational agents are increasingly finding application in health care, as these can provide patient education at any time. However, their effectiveness in medical settings remains largely unexplored. This study aimed to assess the impact of the chatbot "PROState cancer Conversational Agent" (PROSCA), which was trained to provide validated support from diagnostic tests to treatment options for men facing prostate cancer (PC) diagnosis. Methods: The chatbot PROSCA, developed by urologists at Heidelberg University Hospital and SAP SE, was evaluated through a randomized controlled trial (RCT). Patients were assigned to either the chatbot group, receiving additional access to PROSCA alongside standard information by urologists, or the control group (1:1), receiving standard information. A total of 112 men were included, of whom 103 gave feedback at study completion. Key findings and limitations: Over time, patients' information needs decreased significantly more in the chatbot group than in the control group ( Conclusions and clinical implications: With the introduction of the PROSCA chatbot, we created and evaluated an innovative, evidence-based AI health information tool as an additional source of information for PC. Our RCT results showed significant benefits of the chatbot in reducing patients' information needs and enhancing their understanding of PC. This easy-to-use AI tool provides accurate, timely, and accessible support, demonstrating its value in the PC diagnosis process. Future steps include further customization of the chatbot's responses and integration with the existing health care systems to maximize its impact on patient outcomes. Patient summary: This study evaluated an artificial intelligence-powered chatbot-PROSCA, a digital tool designed to support men facing prostate cancer diagnosis by providing validated information from diagnosis to treatment. Results showed that patients who used the chatbot as an additional tool felt better informed than those who received standard information from urologists. The majority of users appreciated the ease of use of the chatbot and expressed a desire to use it again; this suggests that PROSCA could be a valuable resource to improve patient understanding in prostate cancer diagnosis.
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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.