Associate Professor
School of Information University of Michigan Contact 4413 North Quad 105 S State Street Ann Arbor, MI 48109-1285 phone: (734) 763-3581 email: klasnja [at] umich.edu twitter: @pklasnja |
I am an Associate Professor in the School of Information at the University of Michigan. I work in two main areas: mobile health (mHealth), and implementation science. My projects are highly interdisciplinary, and I am fortunate to be able to collaborate with a group of remarkable colleagues from psychology, computer science, statistics, engineering, and public health.
Mobile Health My mHealth research lies at the intersection of human-computer interaction, behavioral science, and health informatics. I study how technology can support people's efforts to manage their health in their day-to-day lives. Because a great deal of what people need to do to improve their health—being physically active, eating a healthy diet, taking medications regularly, etc.—happens in the midst of daily life and away from the clinic, one area I study is how technology can help people to adopt and sustain such health-promoting activities while dealing with their other life demands. I see mobile and pervasive technology, such as smartphones, smart watches, and voice assistants as particularly powerful tools for providing this support. I explore ways in which such technologies can help people stay engaged with their health goals over the long-term, discover opportunities for healthy behaviors that are accessible, feasible, and enjoyable, and reflect on their behavior patterns to identify ways to improve their health without disrupting relationships and routines that are important to them. In recent years, I have been exploring these issues through the development and evaluation of just-in-time-adaptive interventions (JITAIs), a new class of health technologies that aims to provide support when it is most needed and when individuals are most receptive to it. My main methodological focus is on methods for intervention optimization, and particularly on micro-randomized trials (MRTs), a new method for optimizing mHealth interventions developed by my collaborator Susan Murphy. MRTs enable researchers to evaluate whether intervention components within a JITAI are having their intended effects, how those effects change over time, and how the intervention effectiveness is influenced by the context in which the intervention is provided, recent history of intervention provision, the user's state (e.g., level of stress), and other such time-varying factors. Data from MRTs is also useful for "warm starting" learning algorithms that can be used to personalize intervention provision to each individual. In addition to MRTs, I have been working with Eric Hekler on the development of Agile Science, an approach to efficient development of tools for addressing complex sociotechnical problems and accumulation of usable evidence that can readily inform future research and practice. My projects cover a range of health domains, including bariatric care, hypertension, and diabetes. My current projects focus on supporting physical-activity in several patient populations. Implementation Science In addition to my research in mobile health, in recent years I have been collaborating with colleagues at Kaiser Permanente Washington and University of Washington on the development of optimization methods for implementation science. One central focus of this work is on the development of causal pathway diagramming, an approach to represent causal processes hypothesized to underlie the functioning of implementation strategies in order to help implementation researchers and practitioners to select strategies most likely to impact their prioritized determinants, uncover factors (preconditions and moderators) that may influence the effectiveness of these strategies, and decide what to measure in order to gather early evidence about whether their implementation initiative is working as intended. In addition, we are developing methods that help implementation researchers conduct efficient studies that match the rigor of resulting evidence to the nature of questions and decisions they are trying to address. My implementation science work is supported through two NIH-funded centers: OPTICC and IMPACT. Publications For an up-to-date list of my publications, check my Google Scholar profile. |
