JMIR Publications

ABSTRACT

Background:

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:

To describe an alternative to a ‘light touch’ digital health study that involved a participant centric design including high friction app-based assessments, semi-continuous 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 Healthcare Workers Study included US frontline healthcare workers followed between May-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 co-driven engagement strategy that centered on providing knowledge and support to participants. The daily participant time commitment was an average of 10-15 minutes. Retention and adherence are described both quantitatively and qualitatively.

Results:

Results:

365 participants enrolled and started the study and 81.0% (297/365) of them completed the study for a total study duration of 4 months. Average wearable sensor usage 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%, 72.86% of the time, respectively.

Conclusions:

Conclusions:

This study found evidence for feasibility and acceptability of a participant centric digital health study approach that involved building trust and respect 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 that is often missing from ‘light touch’ digital health studies. Clinical Trial: Clinicaltrials.Gov (NCT04713111)