Journal Article

Evaluating the Efficacy of ChatGPT as a Patient Education Tool in Prostate Cancer: Multimetric Assessment

Seth, Ishith, Jackson, Stuart, Siu, Adrian, Mehan, Nicholas, Gibson, Damien, Shanmugasundaram, Ramesh, Leslie, Scott, Ahmadi, Nariman, Kam, Jonathan, Patel, Manish I, Thanigasalam, Ruban, Jeffery, Nicola

2024

Overview

Artificial intelligence (AI) chatbots, such as ChatGPT, have made significant progress. These chatbots, particularly popular among health care professionals and patients, are transforming patient education and disease experience with personalized information. Accurate, timely patient education is crucial for informed decision-making, especially regarding prostate-specific antigen screening and treatment options. However, the accuracy and reliability of AI chatbots' medical information must be rigorously evaluated. Studies testing ChatGPT's knowledge of prostate cancer are emerging, but there is a need for ongoing evaluation to ensure the quality and safety of information provided to patients. This study aims to evaluate the quality, accuracy, and readability of ChatGPT-4's responses to common prostate cancer questions posed by patients. Overall, 8 questions were formulated with an inductive approach based on information topics in peer-reviewed literature and Google Trends data. Adapted versions of the Patient Education Materials Assessment Tool for AI (PEMAT-AI), Global Quality Score, and DISCERN-AI tools were used by 4 independent reviewers to assess the quality of the AI responses. The 8 AI outputs were judged by 7 expert urologists, using an assessment framework developed to assess accuracy, safety, appropriateness, actionability, and effectiveness. The AI responses' readability was assessed using established algorithms (Flesch Reading Ease score, Gunning Fog Index, Flesch-Kincaid Grade Level, The Coleman-Liau Index, and Simple Measure of Gobbledygook [SMOG] Index). A brief tool (Reference Assessment AI [REF-AI]) was developed to analyze the references provided by AI outputs, assessing for reference hallucination, relevance, and quality of references. The PEMAT-AI understandability score was very good (mean 79.44%, SD 10.44%), the DISCERN-AI rating was scored as \"good\" quality (mean 13.88, SD 0.93), and the Global Quality Score was high (mean 4.46/5, SD 0.50). Natural Language Assessment Tool for AI had pooled mean accuracy of 3.96 (SD 0.91), safety of 4.32 (SD 0.86), appropriateness of 4.45 (SD 0.81), actionability of 4.05 (SD 1.15), and effectiveness of 4.09 (SD 0.98). The readability algorithm consensus was \"difficult to read\" (Flesch Reading Ease score mean 45.97, SD 8.69; Gunning Fog Index mean 14.55, SD 4.79), averaging an 11th-grade reading level, equivalent to 15- to 17-year-olds (Flesch-Kincaid Grade Level mean 12.12, SD 4.34; The Coleman-Liau Index mean 12.75, SD 1.98; SMOG Index mean 11.06, SD 3.20). REF-AI identified 2 reference hallucinations, while the majority (28/30, 93%) of references appropriately supplemented the text. Most references (26/30, 86%) were from reputable government organizations, while a handful were direct citations from scientific literature. Our analysis found that ChatGPT-4 provides generally good responses to common prostate cancer queries, making it a potentially valuable tool for patient education in prostate cancer care. Objective quality assessment tools indicated that the natural language processing outputs were generally reliable and appropriate, but there is room for improvement.

• Publisher: Journal of Medical Internet Research,Gunther Eysenbach MD MPH, Associate Professor,JMIR Publications
• Subject: Accuracy / Air pollution / Algorithms / Appropriateness / Artificial Intelligence / Cancer / Cancer patients / Chatbots / Citations / Clinical assessment / Clinical decision making / Clinical information / Computational linguistics / Consumer health information / Decision making / Education / Efficacy / Evaluation / Hallucinations / Health care / Health education / Health services / Human-computer interaction / Humans / Indexes / Information / Keywords / Language assessment / Language processing / Male / Medical decision making / Medical personnel / Medical prognosis / Medical research / Medical screening / Medical treatment / Medicine, Experimental / Multimedia / Natural language / Natural language interfaces / Natural language processing / Organizational effectiveness / Original Paper / Patient education / Patient Education as Topic - methods / Patients / Peer review / Prostate / Prostate cancer / Prostatic Neoplasms / Quality assessment / Quality of care / Readability / Reliability / Responses / Safety / Secondary education / Smog / Social networks / Treatment methods