Recently, a group of University of Pittsburgh researchers partnered on a text-message based intervention for young adults at risk for binge drinking. To their delight, a series of text message reminders and encouragements to reduce alcohol consumption significantly decreased alcohol consumption in the test subjects. The university/researchers commercialized the application, CaringTXT, and distributed it for use at universities throughout the US.
However, a fundamental question remained: what is the underlying reason why such an intervention worked? What is it about the participants’ attitudes toward alcohol that would cause a series of text messages to reduce their consumption?
In the fall of 2016 researchers asked NuRelm to develop a mobile app that would test their study participants’ attitudes/beliefs toward alcohol, using commonly employed clinical psychology tools (stroop test, questionnaires to identify biases/beliefs surrounding alcohol, alcohol approach and avoidance tasks).
The study was designed for participants to use their own smartphones to download an app and complete a series of tasks. In research and clinical trials this is referred to as BYOD, or “bring your own device”, and is uncommon because there are many variables associated with different hardware, software, and operating system parameters.
NuRelm conducted extensive testing to demonstrate latency across various devices and configurations to ensure results coming from a mobile app would be accurate. After conducting statistical analysis of the results, NuRelm developers and researchers concluded that the data was minimally variable if certain devices and configurations were supported, so the project moved forward.
Using the Ionic mobile framework, NuRelm developers built a mobile application, Mechanisms for Alcohol Treatment Change (MATCH) Trial, for study participants to perform the tasks, get information on the study, communicate with researchers, and receive financial rewards for successful completion of their tasks. To support the researchers’ efforts to onboard participants, review their data, and download results for off-line analysis, NuRelm developers built a web portal on the Ruby on Rails framework.
To date, a sizable group of young adults has been recruited from emergency rooms to participate in the study. Hopefully, with the help of MATCH, we will understand the mechanisms by which at-risk individuals respond to systems of text reminders and encouragements, and how the language, timing, and nature of those communications can be refined to further improve outcomes and the safety and well-being of young adults.