Wearable Technology
Literature Review
Noah M. El-Radi
Point Loma Nazarene University
Introduction
The purpose of this literature review is to to understand the motivations users have when it comes to maintaining use of their fitness tracking device, and the behavioral change techniques (BCTs) that accompany the ongoing use of the device. Validating for consistency and accuracy will also be touched on within this review, as well as the comparison of popular trackers for accuracy. The user adoption and literacy of digital health tracking tools will also be discussed, and whether or not these play a role in prolonged use of wearable technology. Finally, the use of social media will be discussed to see if this plays a role in maintaining the prolonged use of trackers and accomplishing set goals.
Body
Motivations
The use of fitness trackers have gained new popularity due to their ease of use and stylish appearance for some, this has lead into users increasing their motivation to exercise and signaled towards a trend of self-efficacy. However, these motivations are related to many factors of the device and do not come from directly within the user. “The empirical analysis and findings demonstrate that users’ motivation and self-efficacy are highly dependent on successful data, gamification, and content design of the apps as well as sensing context and providing appropriate motivational feedback to the user” (Asimakopoulos, Asimakopoulos, & Spillers, 2017). Asimakopoulos et al. proved within their article that wearables are an effective way to help people gain self-efficacy in order to become more physically active through the use of this technology, but depends heavily on the said factors above.
Long term motivation is also brought about during the research of Thomas Fritz et al., which details that the use of wearable fitness trackers and the long term healthy behaviors they may present for long term use. Fritz et al. support their claim by interviewing subjects about what influences them to use their activity trackers, and why they choose to use them long term. “The numerical feedback provided by the devices was generally motivating for participants, manifested in their desire to meet step goals, or their pride in achieving high numbers” (Fritz, Huang, Murphy, & Zimmermann, 2014). The desire to meet goals based on numbers, and the ease of use for the user interface are the two motivations that are most popular when maintaining long term use of wearable trackers.
Baker et al. employs the transtheoretical model of behavior change (TTM) that considers the effects of digital tracking tools on users behaviour. Baker et al. support their claim by employing surveys to 214 participants which measure their motivation(s) according the the goals they set for themselves, and whether or not fitness trackers helped reach those goals. An interesting point to note within this study is that participants health seemed to improve when sharing their goals on social media was involved, as this changed perceptions of the individuals by comparing themselves to others (Baker, Pember, Xueying Zhang, & Bissell, 2016)
Emily E. Dunn and Jennifer Robertson-Wilson's article "Behavior Change Techniques and Physical Activity Using the Fitbit Flex® (2018)", examines the increased availability of fitness trackers such as Fitbit® that could make users perceive the behavioral change techniques differently. Dunn and Robertson-Wilson support their claim by gaining feedback and activity information from users and organizing this into a statistical analysis based on their answers to selected open-end questions. Dunn and Robertson-Wilson's purpose of the article is to examine the use of participants activity data in order to understand how this changes their perception of the behavioral change techniques. What they found is that just by wearing the Fitbit®, users became more motivated to become physically active and this resulted in an overall greater level awareness and physical activity habits (Dunn & Robertson-Wilson, 2018).
Health Literacy
Health literacy is “how people obtain, understand, use, and communicate about health information to make informed decisions” (Mackert, Mabry-Flynn, Champlin, Donovan, & Pounders, 2016). The literacy of health information technology (HIT) is a way to display numerical data, relating to health. This is the same way activity trackers display their data, but this can be a problem for individuals who see their HIT as being private and not wanting it to be tracked. Mackert et al. surveyed a diverse group of 4974 participants across all race, gender and ages, and those, 15.96% (794) showed to have low health literacy. In addition to this, low health literacy was positively associated with trust in HIT and user privacy. In short, users who show low health literacy also display a lack of trust towards companies due to the fact that they think their data is being shared. This leads to such users not purchasing activity trackers and a loss of sales towards these individuals for companies.
Accuracy, Limitations, and Consistency
Advances in technology for wearable technology has the opportunity to help advance training in athletes and the general public. However, these devices are hindered almost useless if they are not accurate or valid when generating data from movement when worn. An article written by Cardinale and Varley explains the current applications and challenges to come when using wearables to train in order for this type of technology to become an everyday tool for training. Their findings suggest that “…many internal- and external-load parameters can be measured using wearable technology with relative accuracy and in a reliable manner. However, it is important to stress that many manufacturers do not provide information about the accuracy, validity, and reliability of their equipment nor give access to the raw data for further analysis” (Cardinale & Varley, 2017). Providing access to see how each company uses their users data is something that should be essential, especially if the user is concerned with the accuracy of their device. Not providing a user their own data should be a limitation for any user who is looking for a reliable and valid tracking device. Showing the data also shows the consumer the company has a valid product, and failure to do so most likely means the company does not have a reliable or valid product.
Wen et al. journal article " Evaluating the Consistency of Current Mainstream Wearable Devices in Health Monitoring: A Comparison Under Free-Living Conditions (2017)", compares the consistency of 10 popular activity trackers in order to determine the accuracy of multiple types of wearables. What they found is that the consistencies of total distance and steps were all relatively similar, this means these two indicators can be used to track health. “The consistencies of the measurements on activity duration, energy expenditure, sleep duration, and deep sleep duration were only fair or poor” (Wen, Zhang, Liu, & Lei, 2017). These factors ultimately will affect consumers’ directly with acceptance of wearable devices and making a final purchasing decision.
Factors For Prolonged Use
Wang et al. journal article "Mobile and Wearable Device Feature that Matter in Promoting Physical Activity (2016)", examines the features in fitness trackers that are useful (or not) in encouraging prolonged use of the device. Wang et al. support their claim by analyzing participants use of their tracker and any extras such as the app or text messaging they may be using in addition. The main purpose of this journal article is to measure the level of engagement with fitness tracking, in order to see whether or not extra features (like text messaging) helped to prolong the use of wearing a fitness tracker and overall activity done.
Hermsen et al. journal article "Determinants for Sustained Use of an Activity Tracker: Observational Study (2017)", analyzes the major determinants that are used for sustained use of an activity tracker for the first year. Hermsen et al. supports their claim by analyzing several participants questionnaires and their reasons for quitting the use of the tracker. Their findings were surprising found that “The primary reason for not using the device, given by half of those indicating low or nonuse, was technical failure or other technical problems, including empty batteries. Other reasons included losing the device or being on a holiday” (Hermsen, Moons, Kerkhof, Wiekens, & De Groot, 2017). These findings are interesting due to the fact that no matter how strong or weak the users goals were, they all had this same primary reason for stopping the use of their device.
Maher et al. research article "Users’ experiences of wearable activity trackers: a cross-sectional study (2017)", aims to explore the user experience of wearable activity trackers that may relate to habits and specific behavior changes. Maher et al. supports their claim by focusing on habits and data patterns of those who use wearable activity trackers, as well as barriers to use. Their purpose of this article is to analyze survey answers and find a pattern in the data in order to see where users motivation lies and where the technicalities stand with these devices for prolonged use. It is interesting that the users in this study “…were slightly more likely to value the trackers’ real-time feedback more than long term monitoring capabilities. The majority of users perceived they had increased their physical activity as a result of using the activity tracker” (Maher, Ryan, Ambrosi, & Edney, 2017). This means that for the majority of wearable users, they mostly just care about the current feedback (like when exercising), rather than the long term benefits they can receive for prolonging the use of such a devie.
Conclusion
In conclusion, it seems that users motivations for using wearable technology lies in the ease of use. The studies showed that the easier the user interface was to use and interact with, the more likely users were to maintain use of their device. This also plays into the health literacy of the consumers and being able to read their data easily, so that they can use and understand the device. Those who have a low health literacy seem to be more concerned about their data privacy, and this is their main reason for not purchasing and using any wearable technology. The prolonged use of these devices seems to also have an effect of the user interface and features that the user is offered. Things like social media and text messaging kept users motivated and were more likely to use their device for a longer duration of time. Taking all of this into account, companies looking to improve their wearable devices for consumers should take all of these factors into account when producing such a product. These factors will benefit both the consumer and technology company when producing a device that users will use consistently, and for a prolonged amount of time.
References
Asimakopoulos, S., Asimakopoulos, G., & Spillers, F. (2017). Motivation and User Engagement in Fitness Tracking: Heuristics for Mobile Healthcare Wearables. Informatics, 4(1), 5. https://doi.org/10.3390/informatics4010005
Baker, K., Pember, S., Xueying Zhang, & Bissell, K. (2016). Counting Steps? How’s That Working for You? Assessing the Effects of Tracking Monitors and Social Contexts on Fitness Goals. Journal of Fitness Research, 5(3), 46–56.
Cardinale, M., & Varley, M. C. (2017). Wearable Training-Monitoring Technology: Applications, Challenges, and Opportunities. International Journal of Sports Physiology & Performance, 12, S2-55.
Dunn, E. E., & Robertson-Wilson, J. (2018). Behavior Change Techniques and Physical Activity Using the Fitbit Flex®. International Journal of Exercise Science, 11(7), 561–574.
Fritz, T., Huang, E. M., Murphy, G. C., & Zimmermann, T. (2014). Persuasive technology in the real world: a study of long-term use of activity sensing devices for fitness. In Proceedings of the 32nd annual ACM conference on Human factors in computing systems – CHI ’14(pp. 487–496). Toronto, Ontario, Canada: ACM Press. https://doi.org/10.1145/2556288.2557383
Hermsen, S., Moons, J., Kerkhof, P., Wiekens, C., & De Groot, M. (2017). Determinants for Sustained Use of an Activity Tracker: Observational Study. JMIR MHealth and UHealth, 5(10). https://doi.org/10.2196/mhealth.7311
Mackert, M., Mabry-Flynn, A., Champlin, S., Donovan, E. E., & Pounders, K. (2016). Health Literacy and Health Information Technology Adoption: The Potential for a New Digital Divide. Journal of Medical Internet Research, 18(10), e264. https://doi.org/10.2196/jmir.6349
Maher, C., Ryan, J., Ambrosi, C., & Edney, S. (2017). Users’ experiences of wearable activity trackers: a cross-sectional study. BMC Public Health, 17(1), 880–880. https://doi.org/10.1186/s12889-017-4888-1
Wang, J. B., Cataldo, J. K., Ayala, G. X., Natarajan, L., Cadmus-Bertram, L. A., White, M. M., … Pierce, J. P. (2016). Mobile and Wearable Device Features that Matter in Promoting Physical Activity. Journal of Mobile Technology in Medicine, 5(2), 2–11. https://doi.org/10.7309/jmtm.5.2.2
Wen, D., Zhang, X., Liu, X., & Lei, J. (2017). Evaluating the Consistency of Current Mainstream Wearable Devices in Health Monitoring: A Comparison Under Free-Living Conditions. Journal of Medical Internet Research, 19(3), e68. https://doi.org/10.2196/jmir.6874