Development of an Open-Source State-of-Receptivity MobileCoach Module for mHealth Field Studies

The ubiquitous presence of smartphone and wearable devices has led to a rise in studies that try to understand human behavioral or mental-health state using Ecological Momentary Assessments (EMA), or experiment with interventions that encourage targeted behavioral or mental-health outcomes, using just-in-time adaptive interventions (JITAI). These two methods, though different, have a common factor: both require the participant’s attention, and hence, require the participant to be engaged with the smartphone for successful response to the EMA prompt or meaningful reaction to the intervention. While the researchers are eager to have the participant complete an EMA prompt or internalize an intervention suggestion, these prompts can be disruptive to the participants; and unless there is immediate motivation to act on the prompt, the participants stop complying with the study protocols — an outcome experienced by many researchers. In line with recent findings, we anticipate that participants will be more willing to respond to a notification (including those triggered by EMA or JITAI) if the notification is triggered during a context when the participant is more likely to respond.

To this end, we propose to add a new module to the already existing MobileCoach application (maintained by researchers at CDHI). This module can (1) passively collect continuous sensing data from the smartphones during field studies, thus enabling researchers to analyze contextual information for behavioral and mental-health outcomes; and (2) enable a ‘state-of-receptivity’ predictor that can predict whether the participant is currently receptive to a particular EMA or intervention. This will help researchers to trigger notifications that are less disruptive, and hence achieve higher compliance (or engagement) in their studies.

Implementing the proposed module in the MobileCoach platform will enhance its capabilities to serve as a data-collection mechanism and/or serve intelligent notifications to the participants based on the type of notification and the participant’s receptivity towards that type of notification in that moment. We believe this enhanced MobileCoach would be useful for any researcher who wants to conduct smartphone-supported field studies, but be of special benefit to behavioral and mental-health researchers by helping them gather a greater quality and quantity of contextual data, and by enabling them to develop interventions that are more effective because they are triggered at moments of higher receptivity.