Digital nudging leverages behavioral science and information technology to provide a new set of tools for designers to change behavior and create habits. Examples of digital nudges include smart feedback and reminders and technology defaults. I study the role of design and data in digital nudging and applications in the domains of consumer choices, health behavior, and daily work. To help expand research and practice, I propose three principles for the design of digital nudging solutions: choice of technology, use of data, and digital experimentation.
Technology in Behavioral Health
Digital technology has the potential to transform healthcare in general, and mental healthcare in particular. By redefining illness identification and management, digital and mobile health provide novel opportunities to measure disease and therapeutic response in ways that matter most to patients and clinicians. Although much clinical research is being done in these areas, there have been almost no successful attempts to integrate multiple technological tools in a personalized fashion within specific real-world clinical settings.
Digital biomarkers are the physiological and behavioral measures collected via connected digital devices or wearable and mobile computing systems. A set of accurately and reproducibly measurable digital biomarkers can be used to predict and influence various health conditions, outcomes, and to generate actionable insights. In recent years, we observed a rapid growth in adoption of digital biomarkers in the medical literature, computer science research, and digital health industry. Advancing the translational science of digital biomarkers requires the continuous integration of key technological innovations from the areas of mobile computing, machine learning, health sciences and medicine.
Selected Research Projects
The stressors of parenting are normative and unavoidable. Mindfulness meditation is a promising modality for stress-regulation. Mindfulness-based stress reduction demonstrated positive changes in psychological or physiological outcomes related to anxiety/stress. Mobile devices make mindfulness, and other stress-regulation exercises accessible and convenient to use anytime and anywhere. However, engagement in mobile-based stress regulation exercises is suboptimal. The goal of this pilot study is to investigate whether contextual data regarding parent state (temporary behaviors, feelings, or experiences) can be used to inform the delivery of real-time recommendations to engage in stress-regulation activities. During this 30 day pilot study, parent with children (up to 18 years) at home will be micro-randomized every day to either a prompt recommending a mobile-based stress-regulation exercise or no prompt. The study will explore if and under what conditions a recommendation prompt is more useful compared to no prompt in terms of (a) promoting engagement with a mobile-based stress-regulation exercise; and b) reducing daily level of stress.
Mobile devices and the rise of mobile health (mHealth) changed our ability to assess and intervene with individuals remotely, providing an avenue for ambulatory diagnostic testing and interventions. Our objective was to develop and validate an impulsivity mHealth diagnostics and monitoring application called the Digital Marshmallow Test (DMT) using both the Apple and Android platforms for widespread dissemination to researchers, clinicians, and the general public. The Digital Marshmallow Test (DMT) was developed using Apple's ResearchKit (iOS) and Android’s ResearchStack open source frameworks for developing health research study apps. The DMT app consists of three main modules: self-report, ecological momentary assessment (EMA), and active behavioral and cognitive tasks. We conducted a study with a 21-day assessment period (N=116) to validate the novel measures of the DMT app. The study demonstrated the potential for assessing different facets of trait and state impulsivity during everyday life and clinical settings using the Digital Marshmallow Test (DMT) mobile app. The DMT app can be further used to enhance our understanding of the individual facets that underlie impulsive behaviors, as well as to provide a promising avenue for digital interventions.
Many people want to reduce their smartphone usage to increase productivity and well-being, but fail to accomplish this goal. We conducted a randomized control trial with a student population (N=112) over three weeks to test the effectiveness of two widely available digital nudges for screen time reduction. Along with a tracking-only control condition, a passive digital nudge (i.e., grayscale mode) was compared to an active digital nudge (i.e., time limits). The passive nudge led to an immediate, significant reduction of objectively measured screen time compared to the control condition. Conversely, the active nudge led to a smaller and gradual screen time reduction. Those in the control condition, who simply tracked their usage, did not lower their screen time. As opposed to the popular belief that reducing screen time is beneficial, we found no immediate causal effects of reducing screen time on subjective well-being and academic performance.
The widespread adoption of intelligent voice assistants (IVAs), like Amazon’s Alexa or Google's Assistant, presents new opportunities for designers of persuasive technologies to explore how to support people's behavior change goals and habits with voice technology. In this work, we explore how to use planning prompts, a technique from behavior science to make specific and effective plans, with IVAs. We design and conduct usability testing (N=13) on a voice app called Planning Habit that encourages users to formulate daily plans out loud. We identify strategies that make it possible to successfully adapt planning prompts to voice format. We then conduct a week-long online deployment (N=40) of the voice app in the context of daily productivity. Overall, we find that traditional forms of planning prompts can be adapted to and enhanced by IVA technology.