ArticleJMIR research protocols2019
Digital Tracking of Rheumatoid Arthritis Longitudinally (DIGITAL) Using Biosensor and Patient-Reported Outcome Data: Protocol for a Real-World Study.
Article in JMIR research protocols, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05603806 (Exploring Rheumatoid Arthritis Patients' Disease Activity Using Patient Reported Outcome Measures and Biometric Sensor Data), which is not on this map. Cited by 14 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Exploring Rheumatoid Arthritis Patients' Disease Activity Using Patient Reported Outcome Measures and Biometric Sensor Data (WEarables Activity in Patients With Rheumatoid Arthritis)
Who cites it
14 citing papers in PubMed, 19 citations in OpenAlex.
- Article
- A systematic review of digital and imaging technologies for measuring fatigue in immune mediated inflammatory diseases.NPJ digital medicine · 2025Article
- Wearable activity tracker study exploring rheumatoid arthritis patients' disease activity using patient-reported outcome measures, clinical measures, and biometric sensor data (the wear study).Contemporary clinical trials communications · 2024Article
- Participant Engagement and Adherence to Providing Smartwatch and Patient-Reported Outcome Data: Digital Tracking of Rheumatoid Arthritis Longitudinally (DIGITAL) Real-World Study.JMIR human factors · 2023Article
- Machine Learning Approaches to Classify Self-Reported Rheumatoid Arthritis Health Scores Using Activity Tracker Data: Longitudinal Observational Study.JMIR formative research · 2023Article
- Assessment of Real-World Patient-Reported Outcomes in Patients Initiating Biologic Agents for the Treatment of Autoimmune Diseases: An Observational Study in Four Patient-Powered Research Networks.Patient related outcome measures · 2023Article
- Advances toward transformative therapies for tendon diseases.Science translational medicine · 2022Review
- Smartphones for musculoskeletal research - hype or hope? Lessons from a decennium of mHealth studies.BMC musculoskeletal disorders · 2022Review
- The Impact of Wearable Technologies in Health Research: Scoping Review.JMIR mHealth and uHealth · 2022Article
- Patient-Powered Research Networks of the Autoimmune Research Collaborative: Rationale, Capacity, and Future Directions.The patient · 2021Article
- Disruptions in Rheumatology Care and the Rise of Telehealth in Response to the COVID-19 Pandemic in a Community Practice-Based Network.Arthritis care & research · 2021Article
- Physical activity measured using wearable activity tracking devices associated with gout flares.Arthritis research & therapy · 2020Article
- Acceptance, Usage, and Barriers of Electronic Patient-Reported Outcomes Among German Rheumatologists: Survey Study.JMIR mHealth and uHealth · 2020Article
- A Smartphone App for Self-Monitoring of Rheumatoid Arthritis Disease Activity to Assist Patient-Initiated Care: Protocol for a Randomized Controlled Trial.JMIR research protocols · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRheumatoid 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 the regular passive collection of patients' biometric and activity data. If it is shown to be strongly related to data captured by patient-reported outcome (PRO) measures, information collected passively from wearable digital technology could serve as an objective proxy or be complementary to patients' subjective experience of RA symptoms.
objectiveThe goal 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 app.
methodsThis 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 electronic PRO (ePRO) measures for the first 3 months.
resultsThe 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.
conclusionsThe completion of this study will provide important data regarding the following: (1) the relationship 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 RA 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. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/14665.
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