Although wearable technology could potentially be a benefit to patients with
Chronic disease management is becoming increasingly reliant on technology, including in MS, where
An online survey was conducted between December 2024 and January 2025, with patients recruited through patient advocacy networks. Patients with MS were recruited, as well as patients with other chronic diseases. Participants were assessed through 6 constructs with a 5-point Likert scale used to measure each construct, with 1 meaning the patient strongly disagreed and 5 meaning that the patient strongly agreed. The constructs included perceived usefulness (PU), perceived ease of use (PEOU), behavior intention (BI), social influence (SI), trust in technology (TT), and technological anxiety (TA). Patients were asked questions about the use of technology within the context of MS.
The use of technology was measured through self-report, with patients reporting whether they used a wearable device regularly, occasionally, or not at all. Patients were also asked if they used a health app that was supported by AI regularly, occasionally, or not at all. Symptom severity, specifically fatigue, cognitive challenges, and motoric impairments, was assessed on a 5-point scale.
There were 64 patients with MS who were included in the study, who had a mean (SD) age of 46.8 (11.2) years and were mostly women (73.4%). The mean duration of disease was 8.4 (6.1) years. There were 14 participants who had a chronic condition that was not MS.
Scores for the 6 constructs were similar across the board in patients with MS, with a mean score of 3.87 (0.74) for PU, 3.54 (0.82) for PEOU, 3.72 (0.89) for BI, 3.21 (0.94) for SI, 3.38 (0.91) for TT, and 2.84 (1.02) for TA. There were negligible differences between the groups in all core acceptance constructs. Actual wearable use was significantly lower despite comparable intentions, with those with MS reporting 34.4% were wearing regularly, 31.3% occasionally, and 34.4% who were not users, compared with patients with other chronic conditions reporting that 57.1% of them wore their technology regularly, 35.7% occasionally, and 7.1% who did not use their wearable technology.
AI app use was also lower in patients with MS, of whom only 18.8% reported they used apps regularly compared with 35.7% of those with other chronic conditions; 53.1% of those with MS reported not using apps at all compared with 28.6% of those with any chronic condition. Trust in technology (β = .52), technological anxiety (β = .38), and social influence (β = .23) were significant predictors of behavioral intention, whereas behavioral intention (OR, 2.14), trust in technology (OR, 1.87), and symptom severity (OR, 0.61) were all predictors of actual use, with those who had higher severity of symptoms having lower usage of technology.
There were some limitations to this study. The comparison group had a small sample size and was significantly smaller than the MS group. Recall bias could have affected patients with different cognitive loads. Symptom ratings were subjective and could have missed fluctuations that affect the use of wearable technology. The link between acceptance and clinical effectiveness was not studied.
“Trust in technology and technological anxiety emerged as central drivers of behavioral intention, while perceived usefulness and ease of use appeared attenuated and partially overlapping, particularly under higher symptom burden,” the authors concluded.
References
- Höpfl F, Brundiers M. Trust and anxiety as primary drivers of digital health acceptance in multiple sclerosis: toward an extended disease-specific technology acceptance model. Front Digit Health. 2026;8:1763329. doi:10.3389/fdgth.2026.1763329
- King ME. Wearable sensors. National Multiple Sclerosis Society. June 2, 2021. Accessed March 31, 2026.
https://www.nationalmssociety.org/news-and-magazine/momentum-magazine/research-and-science/wearable-sensors
