TY  - JOUR
AU  - Nowell, William B
AU  - Curtis, Jeffrey R
AU  - Zhao, Hong
AU  - Xie, Fenglong
AU  - Stradford, Laura
AU  - Curtis, David
AU  - Gavigan, Kelly
AU  - Boles, Jessica
AU  - Clinton, Cassie
AU  - Lipkovich, Ilya
AU  - Venkatachalam, Shilpa
AU  - Calvin, Amy
AU  - Hayes, Virginia S
PY  - 2023
DA  - 2023/11/7
TI  - Participant Engagement and Adherence to Providing Smartwatch and Patient-Reported Outcome Data: Digital Tracking of Rheumatoid Arthritis Longitudinally (DIGITAL) Real-World Study
JO  - JMIR Hum Factors
SP  - e44034
VL  - 10
KW  - real-world evidence
KW  - real-world data
KW  - patients
KW  - rheumatoid arthritis
KW  - patient-reported outcomes
KW  - patient-generated health data
KW  - mobile technology
KW  - wearable digital technology
KW  - mobile phone
AB  - Background: Digital health studies using electronic patient-reported outcomes (ePROs) and wearables bring new challenges, including the need for participants to consistently provide trial data. Objective: This study aims to characterize the engagement, protocol adherence, and data completeness among participants with rheumatoid arthritis enrolled in the Digital Tracking of Arthritis Longitudinally (DIGITAL) study. Methods: Participants were invited to participate in this app-based study, which included a 14-day run-in and an 84-day main study. In the run-in period, data were collected via the ArthritisPower mobile app to increase app familiarity and identify the individuals who were motivated to participate. Successful completers of the run-in period were mailed a wearable smartwatch, and automated and manual prompts were sent to participants, reminding them to complete app input or regularly wear and synchronize devices, respectively, during the main study. Study coordinators monitored participant data and contacted participants via email, SMS text messaging, and phone to resolve adherence issues per a priori rules, in which consecutive spans of missing data triggered participant contact. Adherence to data collection during the main study period was defined as providing requested data for >70% of 84 days (daily ePRO, ≥80% daily smartwatch data) or at least 9 of 12 weeks (weekly ePRO). Results: Of the 470 participants expressing initial interest, 278 (59.1%) completed the run-in period and qualified for the main study. Over the 12-week main study period, 87.4% (243/278) of participants met the definition of adherence to protocol-specified data collection for weekly ePRO, and 57.2% (159/278) did so for daily ePRO. For smartwatch data, 81.7% (227/278) of the participants adhered to the protocol-specified data collection. In total, 52.9% (147/278) of the participants met composite adherence. Conclusions: Compared with other digital health rheumatoid arthritis studies, a short run-in period appears useful for identifying participants likely to engage in a study that collects data via a mobile app and wearables and gives participants time to acclimate to study requirements. Automated or manual prompts (ie, “It’s time to sync your smartwatch”) may be necessary to optimize adherence. Adherence varies by data collection type (eg, ePRO vs smartwatch data). International Registered Report Identifier (IRRID): RR2-10.2196/14665 
SN  - 2292-9495
UR  - https://humanfactors.jmir.org/2023/1/e44034
UR  - https://doi.org/10.2196/44034
UR  - http://www.ncbi.nlm.nih.gov/pubmed/37934559
DO  - 10.2196/44034
ID  - info:doi/10.2196/44034
ER  -