The Quantity of Evidence Supporting the Validity and Reliability of Commercially Available Fitness Trackers
Mentor 1
Ann Swartz
Location
Union Wisconsin Room
Start Date
5-4-2019 1:30 PM
End Date
5-4-2019 3:30 PM
Description
Physical activity assessment devices or fitness trackers (wearables) have become very popular. For example, according to FitBit as of February 2018 there were over 25 million users, with Fitbits accounting for ~ 19%. Because these devices are so widely used, and individuals spend between ~$100-$500 on a device, it is important that the consumer is aware of the accuracy and reliability of these devices. The purpose of this research was to review and summarize features and quantify the number of published validity and reliability studies for commercially available wearables. To determine features, an Internet search was performed. To determine the number of peer-reviewed articles published on each device, a PubMed search was performed using the “Wearable name” and either the term “validity” or “reliability”. Initially, features of 34 commercially available wearables were collected. Features reviewed included price, Bluetooth syncing availability, aspects of physical activity, posture, breathing, sleep, and battery life. Results showed that FitBit was the most extensively evaluated wearable in terms of both validity and reliability, having 25 published studies on validity and 11 published studies on reliability, with 18 of these studies focusing on the FitBit Zip model. Apple Watch Series 1 (N=1) and Xiaomi Mi Band (N=1) had the fewest number of articles on validity, and Jawbone (N=2) and Garmin (N=2) had the fewest studies published that evaluated the reliability of the device. There were no published studies that evaluated the validity or reliability of the Motiv, Samsung, Polar, Lumo Bodytech, and Moov brands. While features are very important to consumers when choosing a wearable device, they should also consider the validity and reliability of the device. This would be especially true if tracking data is used to guide health management, as decisions based on accurate data are more likely to help them achieve their goals.
The Quantity of Evidence Supporting the Validity and Reliability of Commercially Available Fitness Trackers
Union Wisconsin Room
Physical activity assessment devices or fitness trackers (wearables) have become very popular. For example, according to FitBit as of February 2018 there were over 25 million users, with Fitbits accounting for ~ 19%. Because these devices are so widely used, and individuals spend between ~$100-$500 on a device, it is important that the consumer is aware of the accuracy and reliability of these devices. The purpose of this research was to review and summarize features and quantify the number of published validity and reliability studies for commercially available wearables. To determine features, an Internet search was performed. To determine the number of peer-reviewed articles published on each device, a PubMed search was performed using the “Wearable name” and either the term “validity” or “reliability”. Initially, features of 34 commercially available wearables were collected. Features reviewed included price, Bluetooth syncing availability, aspects of physical activity, posture, breathing, sleep, and battery life. Results showed that FitBit was the most extensively evaluated wearable in terms of both validity and reliability, having 25 published studies on validity and 11 published studies on reliability, with 18 of these studies focusing on the FitBit Zip model. Apple Watch Series 1 (N=1) and Xiaomi Mi Band (N=1) had the fewest number of articles on validity, and Jawbone (N=2) and Garmin (N=2) had the fewest studies published that evaluated the reliability of the device. There were no published studies that evaluated the validity or reliability of the Motiv, Samsung, Polar, Lumo Bodytech, and Moov brands. While features are very important to consumers when choosing a wearable device, they should also consider the validity and reliability of the device. This would be especially true if tracking data is used to guide health management, as decisions based on accurate data are more likely to help them achieve their goals.
