JMIR Publications

ABSTRACT

Background:

Generative artificial intelligence (GenAI) tools are widely accessible to the public who are engaging with them for a wide range of healthcare applications. Existing research has focused predominantly on clinician-facing adoption. Far less is known about how patients and family members use GenAI tools, particularly in rare disease contexts where diagnostic delay, limited specialist access, and unmet informational needs are common.

Objective:

We sought to examine experiences and opinions of patients with rare diseases and parents or guardians of children with rare diseases regarding the use of GenAI tools.

Methods:

Between November 2025 and January 2026, we conducted an exploratory mixed methods, web-based survey using convenience sampling through rare disease community organizations in the United States. The survey included closed-ended items assessing prior GenAI use, purposes of use, perceived influence on medical decisions and diagnosis, trust, concerns, communication with clinicians, and experiences of harm, alongside open-text questions capturing qualitative reflections. Descriptive statistics were used to summarize quantitative data. Inductive qualitative analysis was applied to open-text responses addressing experiences of harm, factors influencing cautious or non-use, and final reflections.

Results:

A total of 115 respondents completed the survey; a majority were parents or guardians of a child with a rare disease (74, 64.3%), and (41, 35.7%) were patients with a rare disease. Slightly more than half (63/115, 54.8%) reported some prior use of GenAI tools in the context of rare disease. Common purposes included exploring new treatments or clinical trials (53/115, 46.1%), interpreting medical tests or clinical notes (37/115, 32.2%), locating specialists or care centers (29/115, 25.2%), and suggesting possible diagnoses (28/115, 24.3%). Nearly a third, (32 %) reported some degree of influence of GenAI on their medical decisions. Nearly 10% reported contributions of GenAI to formal diagnosis. Trust in AI-generated health information was mixed, and concern about accuracy was widespread; 71/115 (61.8%) reported moderate to extreme concern. Most respondents (90/115, 78.3%) had not discussed AI-generated information with a clinician. Few respondents (7/115, 6.1%) reported experiencing harm. Qualitative analysis identified three overarching themes: (1) GenAI as a practical tool for augmenting patient and caregiver expertise and advocacy, (2) conditional trust and bounded use of GenAI with emphasis on verification and human oversight, and (3) perceived risks, harms, and structural concerns, including inaccuracies, genetic misinterpretation, and privacy and commercialization issues.

Conclusions:

Patients and families affected by rare diseases are actively experimenting with GenAI tools to support information seeking, preparation, and advocacy, while simultaneously expressing substantial caution and concern about reliability, safety, and appropriate boundaries of use. These findings highlight a growing but largely invisible layer of patient-facing GenAI use that occurs outside clinical oversight. These findings contrast sharply with clinician concerns that patients may lack the capacity to use GenAI tools with judiciously. Greater attention to patient-centered design, education, and governance is needed to ensure that emerging GenAI tools support, rather than exacerbate, existing inequities in rare disease care.