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Motivating Mobility and Health on a Global Scale

Principal Investigator

Scott Delp, Professor of Bioengineering and Mechanical Engineering

Co-Principal Investigators

Euan Ashley, Professor of Medicine and Pathology

Zhenan Bao, Professor of Materials Science and Engineering and of Chemistry

Alia Crum, Assistant Professor of Psychology

Abby King, Professor Epidemiology and of Medicine

James Landay, Professor of Computer Science 

Jure Leskovec, Associate Professor of Computer Science 

Paula Moya, Professor of English

Pablo Paredes, Instructor of Radiology 

Michael Snyder, Professor in Genetics


We all know that physical activity is good for us. Yet nearly half of U.S. adults fail to get enough activity, and it is costing us in terms of dollars and lives: 5 million deaths worldwide per year due to diseases like heart disease, stroke, and diabetes could be prevented just by increasing physical activity. Understanding and developing solutions to motivate individuals to change their behavior, like becoming more physically active, is a major challenge.

Smartphones and wearable devices have the potential to address this challenge, collecting vast amounts of data about physical activity and health and enabling near-continuous interactions with users to motivate healthy behaviors. However, existing health apps—which are largely uninformed by advances in behavioral psychology and human-computer interaction theory—have had limited success. Independent efforts from diverse disciplines across Stanford have successfully motivated behavior change on a small scale. A framework for integrating these different approaches, guided by data-driven insights, has the potential to produce a highly effective, personalized solutions. Our 3-year, $3 million catalyst project will create and deploy a powerful motivational engine using smartphones and wearable sensors to increase physical activity and improve health at low cost on a global scale.

We have formed a highly collaborative team that engages students, staff, and faculty from 16 departments across Stanford to achieve this shared vision. Our team has expertise from faculty in (1) psychology and on how to motivate behavior change, (2) human-computer interaction on how to sustain engagement, (3) English on how to use stories to make sense of one’s experiences, (4) data science on how to harness the wealth of data being generated by sensors to understand behavior change, (5) bioengineering on state-of-the-art biosensor design, and (6) medicine on interventions and best practices for prescribing physical activity. Together, these diverse experts bring a unique perspective to this long-standing problem.

We will focus on increasing physical activity to combat cardiovascular disease and obesity, prevent diabetes, and reduce pain. We will develop a framework for integrating state-of-the-art theories about motivation and engagement from varied disciplines to create interventions that successfully motivate long-term increases in physical activity. We will run tests to refine the user experience, followed by large-scale testing of millions of users in partnership with industry to show we can improve health outcomes at scale. To guide our design process, we will mine massive datasets from our industry and academic partners to elucidate relationships between motivational factors, activity and health. Our proven track record of working with large companies (e.g., Facebook and Under Armour) ensures we will overcome the hurdles that have hampered past efforts.

Our project will create a powerful and flexible solution for motivating physical activity at low cost and on a massive scale. The new framework we will establish for synergistically integrating diverse motivational approaches will form the foundation of our smartphones and wearables-based technology to improve health in individuals with conditions like osteoarthritis, diabetes, and cardiovascular disease. Its generalizability will enable it to be applied to improve health in a wide range of other conditions, including mental illness and cognitive decline.