Background: Several app-based studies share similar characteristics of a light touch approach that recruit, enroll, and onboard via a smartphone app and attempt to minimize burden through low-friction active study tasks while emphasizing the collection of passive data with minimal human contact. However, engagement is a common challenge across these studies, reporting low retention and adherence.
Objective: This study aims to describe an alternative to a light touch digital health study that involved a participant-centric design including high friction app-based assessments, semicontinuous passive data from wearable sensors, and a digital engagement strategy centered on providing knowledge and support to participants.
Methods: The Stress and Recovery in Frontline COVID-19 Health Care Workers Study included US frontline health care workers followed between May and November 2020. The study comprised 3 main components: (1) active and passive assessments of stress and symptoms from a smartphone app, (2) objective measured assessments of acute stress from wearable sensors, and (3) a participant codriven engagement strategy that centered on providing knowledge and support to participants. The daily participant time commitment was an average of 10 to 15 minutes. Retention and adherence are described both quantitatively and qualitatively.
Results: A total of 365 participants enrolled and started the study, and 81.0% (n=297) of them completed the study for a total study duration of 4 months. Average wearable sensor use was 90.6% days of total study duration. App-based daily, weekly, and every other week surveys were completed on average 69.18%, 68.37%, and 72.86% of the time, respectively.
Conclusions: This study found evidence for the feasibility and acceptability of a participant-centric digital health study approach that involved building trust with participants and providing support through regular phone check-ins. In addition to high retention and adherence, the collection of large volumes of objective measured data alongside contextual self-reported subjective data was able to be collected, which is often missing from light touch digital health studies.
Trial registration: ClinicalTrials.gov NCT04713111; https://clinicaltrials.gov/ct2/show/NCT04713111.
Keywords: COVID-19; alternative; app; assessment; design; digital health; engagement; frontline; health care worker; knowledge; sensor; stress; support; wearable.
©Sarah M Goodday, Emma Karlin, Alexandria Alfarano, Alexa Brooks, Carol Chapman, Rachelle Desille, Daniel R Karlin, Hoora Emami, Nancy Fugate Woods, Adrien Boch, Luca Foschini, Mackenzie Wildman, Francesca Cormack, Nick Taptiklis, Abhishek Pratap, Marzyeh Ghassemi, Anna Goldenberg, Sujay Nagaraj, Elaine Walsh, Stress And Recovery Participants, Stephen Friend. Originally published in JMIR Formative Research (https://formative.jmir.org), 10.12.2021.