Lupus & antiphospholipid syndrome
Artificial Intelligence–Based Online Symptom Assessment Tools for Systemic Lupus Erythematosus Diagnosis: Patient Perspectives
Authors' conclusion
This article provides SLE patient perspectives on the benefits and limitations of AI-based online symptom assessment tools in addressing diagnostic delays of a complex diagnostic condition.
Study context
- Population
- Adults with systemic lupus erythematosus (SLE) from an SLE research cohort4 focus groups
- Participants
- 24 adults
- Outcome
- Perceptions of patients with SLE regarding AI-based online symptom assessment tools and their potential to address diagnostic barriers
Methodological detailsvirtual focus groups, inductive thematic analysis, English and French sessions, Sessions of 60 to 90 minutes facilitated by trained moderators with standardized questions, incl. a demonstration of an artificial intelligence (AI)-based symptom checker application
- Virtual focus groups
- Inductive thematic analysis
- English and French sessions
- Sessions of 60 to 90 minutes facilitated by trained moderators with standardized questions, incl. a demonstration of an AI-based symptom checker application
Main finding
As reported in the abstract
Themes
- Themes: diagnostic journeys incl. barriers to timely SLE diagnosis; familiarity with online health tools; perceived benefits; concerns regarding AI symptom assessment tools
- Most prominent benefits: symptom awareness and validation, encouragement to seek care, facilitation of health care discussions
- Concerns: narrow usefulness given SLE complexity, structural limitations (health care access, provider receptiveness), possible misinformation, minor data privacy issues
Further findings
Participant characteristics
- Mean age, years (SD 9.7)
- 50.4
- Mean duration since SLE diagnosis, years (SD 8.8)
- 19.1
- Female
- 92%
- White
- 50%
Original publication
Artificial Intelligence–Based Online Symptom Assessment Tools for Systemic Lupus Erythematosus Diagnosis: Patient Perspectives. Arthritis Care Res (Hoboken). Published 15 May 2026. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →