Using Organismic Integration Theory to Explore the Associations Between Users' Exercise Motivations and Fitness Technology Feature Set Use

Abstract

Fitness technology feature use items were not available in the literature, and thus, were developed for the current study. Items were developed for each feature set following the procedure described next. We used a four-step process to determine the fitness technology features that make up our first-order subconstructs. First, we compiled a list of currently available fitness devices and their associated apps using lists of wearables published in popular media outlets. The original list contained 72 devices and was compiled using lists of wearables from CNET, PC Magazine, The Wall Street Journal, Engadget, Gizmodo, and others. While not comprehensive, the redundancy across multiple lists suggests that our list, at the very least, contains the most popular devices in the wearables category at the time the data was collected. Second, the three researchers independently visited every website of each device/app on the list and collected the features the company advertised for the fitness technology. Third, all three of the researchers' feature lists were compared, discussed, and used to create an integrated list. Fourth, once survey items were created, an expert panel was convened to examine the feature list and scales as described below.Accepted procedural methods (Churchill 1979;MacKenzie et al. 2011) were followed in developing the fitness technology use items. Once the items were developed, an expert panel was convened. The expert panel consisted of two faculty members who are well versed in surveybased methodologies, two faculty members who were active users of fitness technologies, and two employees of a fitness technology company. The expert panel was instructed to examine the entire survey instrument for clarity and to provide feedback on wording and note if any fitness technology features were missing. The expert panel did not provide any new fitness technology features, which indicated our list was reasonably comprehensive. The expert panel did suggest wording changes to the fitness technology features set use items and the addition of a few more fitness device and apps to our list (primarily new versions of devices already present in our list). We compiled the expert panel wording suggestions and considered each suggestion. Most wording suggestions from the expert panel were implemented, improving the clarity of the survey items.

Wearables as Augmentation Means: Conceptual Definition, Pathways, and Research Framework

“…However, motivational effects (such as feedback and goal setting with teams) may outweigh minimalist design concerns among certain users. This observation aligns with the conclusion by James et al [20] that users' profiles of fitness technology feature set use correspond with the motivation to exercise.…”

“…As a recent phenomenon, academic studies examining wearables from an IS theoretic and organizational perspective are few. James et al [20] categorized wearable technology features into three sets (social interaction features, exercise control features, and data management features) and investigated how the use of each feature set is influenced by individuals' exercise motivations. Drawing from self-determination theory and affordances, they concluded that individuals "with different motivations toward exercise have unique fitness technology use profiles," and that "to achieve the most effective outcomes … it may be wise to consider personalizing use to the users' characteristics."…”

“…For example, in a randomized clinical trial to test the efficacy of wearable technology as a weight loss intervention, Jakicic et al [19] concluded that "devices that monitor and provide feedback on physical activity [wearables] may not offer an advantage over standard behavioral weight loss approaches". Similarly, James et al [20] found that "social interaction and data management features of current fitness technologies show promise in assisting well-being outcomes, but only for the more selfdetermined and amotivated subtypes of exercisers". Furthermore, a 2014 commercial study by Endeavour Partners showed that 30% of users of activity trackers stop using their wearable device within six months of acquiring them (cited in [8]).…”

“…Similarly, Prasopoulou [29] urges IS research to "focus on the body (flesh, feelings, and thoughts) for sourcing knowledge on human-non-human encounters in emerging cyber-physical spaces like the Internet of Things." And James et al [20] suggested the need to extend traditional motivational theories "to accommodate advances in personal informatics technologies that allow users to customize the environment in which they are performing activities. "…”

“…As the editors of a recent special issue of ISR note: "there is still a lack of coherent discussion and an integrated body of literature on the direct implications of how IA and AI research can contribute to organizational and societal applications and to their impact on the future of work" [18]. Second, extant studies on wearables have treated them as artifacts [20] that exist separate and apart from the humans who wear them. Thus, how wearables relate to humans, and vice versa, has not been explored.…”