Exploring attitudes and acceptance of artificial intelligence in multiple sclerosis from the patient perspective
Artificial intelligence (AI) is increasingly being integrated into healthcare, particularly in data-intensive chronic diseases that rely on longitudinal monitoring and shared decision-making. Multiple sclerosis is a prototypical example of such care, but real-world benefit will depend on whether people accept AI support in different clinical roles. We conducted a cross-sectional, web-based survey among 241 people with MS (pwMS) to assess comfort with AI across eight clinical domains and to identify predictors of…
In a survey of 241 people with MS, respondents reported higher comfort with AI when used for low-risk supportive roles like chronic management and symptom screening, with most preferring a joint model where clinicians retain final responsibility.
Findings reflect self-reported comfort in a cross-sectional survey, not measured clinical outcomes from deployed AI systems.
Evidence
- Peer-reviewedPLOS Digital Health2026-07-01
Truvace Impact Record TRV-2026-0107, v1: “Exploring attitudes and acceptance of artificial intelligence in multiple sclerosis from the patient perspective.” Truvace, 2026-07-13. /record/TRV-2026-0107 (accessed at citation time). sha256 88c973d316e866b2…
Calibration history
Every change to this record since certification, in the open. None yet — the reading has held since it entered the record.
Certified into the record
How to verify without trusting this page
Fetch the canonical text of any version from /api/record/TRV-2026-0107 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.