I'm an Assistant Professor in the Human-Centered Computing department in the School of Informatics and Computing at Indiana University-Purdue University Indianapolis (IUPUI).
I study how social computing technology can empower people to help each other with their health and wellness. I design pervasive technologies to encourage and enable new forms of social support online and offline, and I work with youth and their families as participants to shape both the technical systems and in-the-wild deployments.
National Library of Medicine Postdoctoral Fellow, 2016
University of Washington
PhD in Human-Centered Computing, 2014
Georgia Institute of Technology
MS in Human-Computer Interaction, 2006
Georgia Institute of Technology
BA in Cognitive Science, 2004
The effects of brain injury, structural damage, or the physiological disruption of brain function last far beyond initial clinical treatment. Self-tracking and management technologies have the potential to help individuals experiencing brain injury in their personal recovery—helping them to function at their best despite ongoing symptoms of illness. However, current self-tracking technologies may be unsuited for measuring the interconnected, nonlinear ways in which brain injury manifests. We conducted a qualitative study and used essentialist or realist thematic analysis to analyze the data collected through semistructured interviews and questionnaires, 2 weeks of structured data collection using brain injury–specific health-related quality of life instrument, quality of life after brain injury (QoLIBRI), and final interviews. Individuals with postacute brain injury found the lack of conceptual understanding of recovery and tools for making sense of their health data as major impediments for tracking and being aware of their personal recovery. There is an urgent need for a better framework for recovery and a process model for choosing patient-generated health data tools that focus on the holistic nature of recovery and improve the understanding of brain injury for all stakeholders involved throughout recovery.
Informal caregivers, such as close friends and family, play an important role in a hospital patient's care. Although CSCW researchers have shown the potential for social computing technologies to help patients and their caregivers manage chronic conditions and support health behavior change, few studies focus on caregivers’ role during a multi-day hospital stay. To explore this space, we conducted an interview and observation study of patients and caregivers in the inpatient setting. In this paper, we describe how caregivers and patients coordinate and collaborate to manage patients’ care and wellbeing during a hospital stay. We define and describe five roles caregivers adopt: companion, assistant, representative, navigator, and planner, and show how patients and caregivers negotiate these roles and responsibilities throughout a hospital stay. Finally, we identify key design considerations for technology to support patients and caregivers during a hospital stay.
Computer-supported fitness interventions for adolescents have the potential to improve adolescents’ attitudes and perceptions about physical activity through peer influence and interpersonal accountability. Past research has explored the potential of interventions based on competition and social-comparison mechanisms. We present a new approach: school-based, pervasive social fitness systems. We describe one such system: StepStream, a pedometer-based microblog we designed and deployed for four weeks with 42 US middle school students. StepStream users improved their attitudes about fitness and increased their sense of social support for fitness. The least-active students also increased their daily activity. We show that our school-based social fitness approach performed comparably in attitude and behavior change to more competitive or direct-comparison systems. These results expand the strategies available computer-supported fitness interventions. Our school-based social fitness approach to everyday adolescent health shows the potential for social computing systems to positively influence offline health behaviors in real-world settings.