BACKGROUND: There are many epidemiology based programs designed to improve primary prevention in populations at high risk for specific diseases. Epidemiologists also generate large datasets to discover approaches to control specific conditions and improve the health environment for those already suffering. The emergence of new technologies and advanced informatics offers an opportunity to enhance these public health and disease surveillance systems in order to build upon programs to reduce persistent disparities in disease distribution and outcomes. Evaluating new rapid and low burden data collection methods and engagement tools that are accessible to diverse populations is a critical first step to assess the extent of the opportunity to impact the health environment.
METHODS: We established a richly diverse multi-disciplinary team that included representation from: academic institutions; a non-profit with ties to public health at the national, state and local government levels; a small disadvantage business entity; and key private sector employers in order to develop gamified and non-gamified versions of a mobile app for use on Android and iOS based smartphones. The low burden mobile paradigm was crafted and designed to function for any disease, to allow data comparison across study arms, to reach respondents regardless of location, and to provide data in real time in a HIPAA compliant environment. Through one of the team members we approached a population of approximately 5000 undergraduate college students to assess a possible data collection solution delivered using a mobile application.
RESULTS: We were able to easily enroll participants and exceed enrollment goals in just a few days. In ongoing data collection assessments, we also observed significantly higher response rates compared to those usually observed for non-mobile approaches. The study provided data on the potential for technology to reach a specific group of respondents, an assessment of burden and response rapidity, and illustrated adaptations that could be utilized in future work in multiple populations.
CONCLUSIONS: We exceeded enrollment expectations and uncovered novel specific information to continue building our approach and align data collection methods to include a new mobile paradigm to improve population-based health. Our early data analysis suggests mobile tools that offer rapid adaptation and real time data capture for specific populations may improve data collection for primary prevention and could be used to improve participant engagement and subsequent health outcomes.