Research findings with exercise wearable population
Given the great deal of media noise about the high abandonment rate of exercise wearables; some sources pointing to 60% plus being shelved within 6 months of purchase, we thought it important to identify any system design and user characteristic factors including exercise behaviour that may affect the persistence of users with the technology in exercising.
Persistence here is defined as having at least one uploaded exercise within 60 days of the end of the source data file cut-off date.
A comprehensive classification and regression tree or CART analysis was conducted to find groups of attributes that classify users as either persistent or not persistent by this definition.
Attributes assessed included the following: Gender, indicator variables for a YouTube channel, Flickr account, Twitter account, Facebook account, a user who makes Comments at others, a user who receives Comments a user who Belongs to a Group, a user who has Followers, a user who has a an average Training Effect (TE) greater than 4 (roughly the top 10 percent of exercise intensity for this sample), a user who Receives Likes, a user who Gives Likes, and quartiles of Age, average of Fitness Index and Maximum of Weight. In effect a cross section of attributes that represent a number of possible variable bundles that can provide an indication of system-specific online sociability and fitness. The tree analysis was performed in R version 2.15.1 using therpart package.
The analysis revealed that regardless of other attributes, males in the highest quartile of Average Fitness Index and females in the highest quartile, except for the youngest females (i.e., under 30 years old), persistently exercise. Additionally, the majority of people who are in the top 50 percent of the Average Fitness Index persistently exercise regardless of their online sociability inside and outside of the exercise app. In the tree it was found that for users in the first and second quartile of Average Fitness Index who do not have the most intense exercise sessions (lower TE scores), but Who Have Followers persistently work out. For users who are in the lowest 50 percent of Average Fitness Index, that do not have the most intense workouts and have no Followers, but who have a Twitter account persistently work out with the system.
This finding may have an association with the subsequent analysis done in a subsequent survey-based study of a subset of the initial population that used a psychosocial scale incorporating a measure of relatedness to others in physical activity (ROPAS) to discern the relationship between a user’s score on this measure with their use of the social support features of the exercise app. It may be implied, subject to further investigation that
high ROPAS scores could be associated not only with the tweeting of exercise data but for the less fit, (based on the exercise app's scoring methods for this measure) it may positively influence their persistence with using the device for managing their exercise over a longer period of time. (Foy,2016)
This inference is illustrated in the following diagram.
In examining the intention to continue in sport amongst young adults, (Gucciardi & Jackson, 2013) found that positive attitudes stemming from satisfaction of basic psychological needs and perceived behavioural control predicted sport continuation. In a symptomatic population of individuals adhering to an exercise intervention for health reasons, the most persistent members possessed high levels of autonomous self-regulation, intrinsic motivation and perceived competence, (Teixeira, Silva, et al., 2012); not just satisfaction of the need to related to others. In hindsight, use of a more extensive set of scales for determining the levels of each of the 3 basic psychological needs (BPN component of Self Determination Theory) for individuals in the population sample may have helped to determine the potential role of the satisfaction of each need in persistent use of the system for exercise.
It's vital that the reader be aware of the limitations of the study before getting carried away with randomly adding a Tweet button to an app to tackle abandonment issues. The individuals and their data used in this project were overwhelmingly male (89 %), lean and fit and 75% of them had been regular exercisers before buying the wearable and using the app. It is an athletic population. More work needs to be done to see if any of the findings from this project are applicable to symptomatic users of wearables.
Gucciardi, D. and Jackson, B. (2015). Understanding sport continuation: An integration of the theories of planned behaviour and basic psychological needs. Journal of Science and Medicine in Sport, 18(1), pp.31-36.
Silva, M., Vieira, P., Coutinho, S., Minderico, C., Matos, M., Sardinha, L. and Teixeira, P. (2009). Using self-determination theory to promote physical activity and weight control: a randomized controlled trial in women. Journal of Behavioral Medicine, 33(2), pp.110-122.
Teixeira, P., Silva, M., Mata, J., Palmeira, A. and Markland, D. (2012). Motivation, self-determination, and long-term weight control. Int J Behav Nutr Phys Act, 9(1), p.22.