Accepted for/Published in: JMIR Research Protocols
Date Submitted: May 9, 2019
Open Peer Review Period: May 9, 2019 - May 17, 2019
Date Accepted: Aug 17, 2019
(closed for review but you can still tweet)
Protocol for the DIGITAL (DIGItal Tracking of rheumatoid Arthritis Longitudinally) Real-World Study of Biosensor and Patient-Reported Outcome Data: Rationale and Study Design
ABSTRACT
Background:
Rheumatoid arthritis (RA) is a condition with symptoms that vary over time. The typical 3- to 6-month interval between physician visits may lead to patients’ failing to recall or underreporting symptoms experienced during the interim. Wearable digital technology enables regular passive collection of patients’ biometric and activity data. Information collected passively from wearable digital technology could serve as a proxy or be complementary to patients’ experience of RA symptoms as captured by patient-reported outcome (PRO) measures if it is shown to be strongly related.
Objective:
The objective of this study is to characterize the extent to which digital measures collected from a consumer-grade smartwatch agree with measures of RA disease activity and other PROs collected via a smartphone application (app).
Methods:
This observational study will last 6 months for each participant. We aim to recruit 250 members of the ArthritisPower registry with an RA diagnosis who will receive a smartwatch to wear for the period of the study. From the ArthritisPower mobile app on their own smartphone device, participants will be prompted to answer daily and weekly PRO measures electronically (ePROs) for the first 3 months.
Results:
The study was launched in December 2018 and will require up to 18 months to complete. Study results are expected to be published by the end of 2021.
Conclusions:
The completion of this study will provide important data regarding the following: (1) agreement between passively collected digital measures related to activity, heart rate, and sleep collected from a smartwatch with ePROs related to pain, fatigue, physical function, and measures of RA disease activity and flare entered via smartphone app, (2) determine predictors of adherence with smartwatch and smartphone app technology, and (3) assess the effect of study-specific reminders on adherence with the smartwatch.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.