Decoding the Black Box: Wearables and Data Analytics

Theoretical Background and research questions/hypothesis: Data analytics, wearables, and primarily mobile and/or mHealth strategies are a central component to measuring engagement. Advancements in evaluation strategies are being made through the use of personalized digital technologies that allow for digitizing offline behavior (a.k.a., the Internet of Things [IOT]). These include Fitbit and location-based services on cellular devices, which can aggregate a myriad of useful data points. This trend toward mass personalization opens new doors in the way we track consumer engagement and could assist in closing the loop between online causes and offline effects.

Methods and Results (informing the conceptual analysis): Interviews were conducted about new advancements in technology and their impact on health and health communication research, exploring cutting edge thinking around data collection and usage generated by tools such as the recently launched Apple ResearchKit. We mapped how these technologies allow for a deeper, more centralized integration within the offline and online components outlined in the AIR Health Behavior Engagement Model.

Conclusions: As computing systems get smarter and more advanced, application strategies that improve  seamless communication have become the mantra of modern day digital media planners. As technologies transcend physical boundaries, including them will be a critical part of a strategic approach to health behavior change.

Implications for research and/or practice:  Technologies with screenless innovations (e.g., image projection wristbands, Google glasses, and various other augmented-reality technologies) can assist connections between consumers, whether in the nonprofit or for-profit sector, and ultimately health to measure and influence knowledge, attitudes, and behaviors. Future research and practice should explore how these technologies fit into health communication frameworks, new or existing, in order to strategically influence behavior. .