UCLA’s Office of Advanced Research Computing Mobile Research App group has successfully partnered with several researchers on grants from the NIH, VA and NSF to build mobile apps for the purpose of collecting data. The MWS team has worked to leverage gamification tactics to encourage participation in these studies as well as leveraging a series of app analytics we could monitor app performance with. Specific gamification strategies deployed include simulated pet caregiving, automated positive message delivery, audible congratulations, lottery mechanisms, peer support encouragement and personalized social support networks. UCLA's Mobilize Labs Team has also defined and implemented an app analytics framework so that researchers could better support their participants during these studies.
We will share what has worked, as well as lessons learned from across our experiences. These mobile apps also present the digital transformation of human based research. For a very long time, the human experience in research studies has only been captured on written surveys completed entirely on ‘recall’ long after the period of study has concluded. In our efforts to digitize participant “sensing”, we have worked to deploy the mechanism called Ecological Momentary Assessments or EMAs and research has shown that these data responses are much more accurate due to proximity to the research study experiences. These data have the following characteristics of ‘real-time’, ‘real-place’, proximity to the event and easy to collect.
Native mobile apps function fully offline, even when there is no external connection to wireless. It can be difficult to figure out what is going on with a study participant, when the device they are collecting data on, has not synced its data recently. We will share the app analytics model we deployed to track how these apps were behaving, as well as diagnose when things were off course. In addition we will share lessons learned for mobile app research studies and considerations for creating accessible mobile user interfaces for special populations.