Engagement and Participant Experiences With Consumer Smartwatches for Health Research: Longitudinal, Observational Feasibility Study

Abstract

Background: Wearables provide opportunities for frequent health data collection and symptom monitoring. The feasibility of using consumer cellular smartwatches to provide information both on symptoms and contemporary sensor data has not yet been investigated.

Objective: This study aimed to investigate the feasibility and acceptability of using cellular smartwatches to capture multiple patient-reported outcomes per day alongside continuous physical activity data over a 3-month period in people living with knee osteoarthritis (OA).

Methods: For the KOALAP (Knee OsteoArthritis: Linking Activity and Pain) study, a novel cellular smartwatch app for health data collection was developed. Participants (age ≥50 years; self-diagnosed knee OA) received a smartwatch (Huawei Watch 2) with the KOALAP app. When worn, the watch collected sensor data and prompted participants to self-report outcomes multiple times per day. Participants were invited for a baseline and follow-up interview to discuss their motivations and experiences. Engagement with the watch was measured using daily watch wear time and the percentage completion of watch questions. Interview transcripts were analyzed using grounded thematic analysis.

Results: A total of 26 people participated in the study. Good use and engagement were observed over 3 months: most participants wore the watch on 75% (68/90) of days or more, for a median of 11 hours. The number of active participants declined over the study duration, especially in the final week. Among participants who remained active, neither watch time nor question completion percentage declined over time. Participants were mainly motivated to learn about their symptoms and enjoyed the self-tracking aspects of the watch. Barriers to full engagement were battery life limitations, technical problems, and unfulfilled expectations of the watch. Participants reported that they would have liked to report symptoms more than 4 or 5 times per day.

Conclusions: This study shows that capture of patient-reported outcomes multiple times per day with linked sensor data from a smartwatch is feasible over at least a 3-month period.

International registered report identifier (irrid): RR2-10.2196/10238.

Keywords: mHealth; medical informatics computing; mobile phone; musculoskeletal diseases; patient-reported outcomes; self-tracking; smartwatch/wearable.

Figure 1

User interface of KOALAP app. Left: notification of an active survey; middle: data entry screen for survey “level of knee pain”; right: data are entered by swiping the numeric rating scale icon.

Figure 2

Active participants (blue) per study day, participants temporary nonusage (yellow), permanent nonusage (red) or lost to follow-up (dark blue).

Figure 3

Average duration of continuous sensor data collection, per participant. Each bar corresponds to a participant. The bar starts at the average time of day that sensor data collection started and ends at the average time of day that sensor data collection ceased (duration in hours shown in middle of bar). On the right: the median wear time and number of days the participant was active. Median wear time can be higher than clock time duration of the longest wearing episode, as some participants recharged the watch and put it on multiple times.

Figure 4

Engagement per study day, showing mean hours of sensor data (lower) and mean watch question completeness (upper). Dark blue diamonds correspond to median over all 26 participants; light blue squares correspond to median over all active participants.

Figure 5

End-of-study study survey—Comfort, convenience of prompts, and self-tracking. Proportion of participants (100%=23) that chose a specific answer; bars to the right of zero reflect positive experiences.

Figure 6

Engagement of case study 1 over 90 study days.

Figure 7

Engagement of case study 2 over 90 study days.