Exploring Non-Experts Experiences with Understanding of Radiological Reports with Assistance of Artificial Intelligence. Insights from Polish study

Aims: This paper explores AI-powered tools in healthcare, focusing on their role in communicating MRI and CT scan results to patients from two groups: young adults and seniors. The study examines three research questions: 1. How do respondents perceive AI-simplified imaging reports in terms of usefulness and trust?; 2. What are the expectations of respondents regarding communication with professionals about the results of imaging scans?; 3. What are the intentions of respondents to use an AI-powered application for interpreting imaging results? Methods: Two fictitious MRI reports were created to resemble standard radiological reports. AI-generated, layperson-friendly explanations of these reports were produced using ChatGPT-01 and presented as “leaflets” to respondents. An online survey was conducted, where participants first evaluated the standard MRI reports and then assessed the AI-generated versions using a five-point Likert scale. Results: The final sample included 60 anonymous respondents (26 under 31, 34 aged 60+). The key findings: 1. Over half of both age groups struggled to understand at least one standard MRI report; 2. Over two-thirds of the respondents in the young adult group agreed with the statement that the information generated by AI for MRI Report 1 (leaflet 1) would be more informative than the presented "standard" report; 3. Young adult respondents trust artificial intelligence significantly less than respondents from the senior group; 4. In both analyzed groups, the majority of respondents declared that they would like to receive an explanation of the MRI reports from a doctor, similar to the format used in the leaflets; 5. In both groups, respondents declared high intention to use application for “explaining” the imaging reports. Due to convenience sampling and a limited sample size, results are not generalizable. Conclusions: Many respondents valued AI-assisted explanations but preferred them as a supplement to discussions with medical professionals, reinforcing the need for AI implementation within trusted healthcare frameworks.