Lizbeth ‘Libby’ Benson, PhD, is a Research Assistant Professor in the Data Science for Dynamic Intervention Decision Making Center (d3c) at the University of Michigan’s Survey Research Center and Institute for Social Research. Before moving to Michigan, Dr. Benson completed a Postdoctoral Fellowship at the TSET Health Promotion Research Center within the NCI-designated Stephenson Cancer Center and University of Oklahoma Health Sciences Center. She received her PhD from the Pennsylvania State University in the department of Human Development and Family Studies and her BA in Psychology from the University of Wisconsin-Madison.

Dr. Benson’s research program is focused on intensive longitudinal methods for examining temporal dynamics of affective, social and health behavior experiences using ecological momentary assessment and sensor-based data collected from individuals in their daily lives. Her goals are to understand how behavioral processes unfold across multiple time-scales and contexts, and how this knowledge can be used to build personalized interventions to facilitate health behavior change. Dr. Benson’s research program is also focused on methods for adapting and personalizing mobile health (mHealth) interventions, including reinforcement learning algorithms and reflective data visualizations.

About the Lecture

Tobacco use is a leading cause of preventable disease and death worldwide. Digital health technologies have strong potential for delivering innovative, personalized smoking cessation interventions. In the first part of this talk, I will present on foundational empirical research examining the temporal dynamics of smoking cessation, and the usefulness of digital technologies for building self-regulatory capacity in adults attempting to quit smoking. The initial results are promising, and yet also point to several barriers limiting the benefits of self-regulatory strategies for smoking cessation. These include lack of knowledge about which strategies are useful in different contexts or forgetting to use a strategy in a high-risk moment. In the second part of this talk, I will present new, on-going research exploring whether self-reflection may be a mechanism through which individuals can learn which strategies are more or less effective in different situations, and increase their likelihood of smoking cessation. Specifically, this work leverages techniques from human-centered design, micro-randomized trial designs, and artificial intelligence to create digital prompts and personalized reflective data visualizations strategically designed to promote self-reflection on self-regulatory strategy use during smoking cessation. Guided by the multiphase optimization strategy for intervention development, the long-term goal of this work is to develop an optimized just-in-time adaptive intervention that delivers the right type of reflective visualization at the right time, while minimizing burden and habituation. Altogether, this research has exciting potential for increasing the impact of digitally delivered smoking cessation treatments.

Prof. Dr. Tobias Kowatsch, Associate Professor for Digital Health Interventions, Institute for Implementation Science in Health Care, University of Zurich; Director, School of Medicine, University of St.Gallen (HSG); Scientific Director, Centre for Digital Health Interventions (CDHI), ETH Zurich & HSG; Principal Investigator, Future Health Technologies programme, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore-ETH Centre, Singapore

Prof. Dr. Elgar Fleisch, Professor of Information Management, ETH Zürich; Professor of Technology Management, University of St.Gallen; Advisory Board Member, CDHI, ETH Zürich & University of St.Gallen; Principal Investigator, Future Health Technologies programme, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore-ETH Centre, Singapore

Prof. Dr. Florian von Wangenheim, Professor of Technology Marketing, ETH Zurich & Advisory Board Member, CDHI; Principal Investigator, Future Health Technologies programme, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore-ETH Centre, Singapore