Upcoming Webinars

To focus on continuing to connect our community, ISMPB will be supporting various webinars throughout the year.  These webinars have been created to offer insight to our community.  If you have any suggestions for webinars that may be of interest, please contact us.

Past Webinars


Virtual Fall Symposium

A Year in Steps: Modeling Longitudinal Trajectories of Physical Activity in a Cohort of 80 Sedentary Adults
Dr. Predrag “Pedja” Klasnja, University of Michigan

Sensing Psychosis: Intensive Longitudinal Assessment of Severe Mental Illness
Dr. Justin T. Baker, Mclean Hospital

Originally Presented on October 24th, 2023 

Hybrid Experimental Designs for Optimizing Digital Interventions at Varying Timescales
Dr. Inbal Nahum-Shani, University of Michigan

Understanding Micro-Temporal Processes Underlying Physicial Activity Adoption and Maintenance: The Time Study
Dr. Genevieve Dunton, University of Southern California & 
Dr. Stephen Intille, Northeastern University

Originally Presented on October 25th, 2023 

Sponsored by SENS motion

Speaker BIOS

Dr. Predrag “Pedja” Klasnja is an Associate Professor in the School of Information at the University of Michigan. His research lies at the intersection of human-computer interaction, behavioral science, and health informatics and he studies how technology can better enable people to manage their health in their day-to-day lives. As an implementation researcher, the central focus of his work is on the development of causal pathway diagramming, which is an approach to represent causal processes hypothesized to underlie the functioning of implementation strategies. This approach allows researchers and practitioners to select strategies that are most likely to impact prioritized determinants of behavior, uncover factors that may influence the effectiveness of these strategies, and determine the appropriate measurement variable, which indicates that the implementation initiative is working as intended. As part of the Intensive Longitudinal Health Behavior Network, he was a Co-Principal Investigator on the “Dynamic Models of Behavior Study” (https://ilhbn.ssri.psu.edu/projects/dmb-dynamic-models-behavior), which was a micro-randomized  trial of a multi-component, multiscale, adaptive intervention to increase physical activity and sedentary behavior (https://www.si.umich.edu/people/pedja-klasnja).

Dr. Justin T. Baker, MD, PhD, is the scientific director of the McLean Institute for Technology in Psychiatry (ITP) and director of the Laboratory for Functional Neuroimaging and Bioinformatics at McLean Hospital. Dr. Baker’s research uses both large-scale studies and deep, multilevel phenotyping approaches to understand the nature and underlying biology of mental illnesses. His current deep phenotyping projects use single-case experimental designs in individuals with severe conditions including bipolar disorder, schizophrenia, borderline personality disorder, and obsessive-compulsive disorder. By applying computational approaches, such as latent construct modeling, machine learning, and dynamical systems analysis, the data collected from each study—and each individual—can reveal key relationships to advance human neuroscience and develop novel, personalized therapeutics. His research studies involve the collection and analysis of temporally dense behavioral assessments to study neuropsychiatric conditions using an array of acquisition technologies and analytic approaches. As part of the Intensive Longitudinal Behavior Network (https://ilhbn.ssri.psu.edu/projects/bls-bi-polar-longitudinal-study), he was the Co-Principal Investigator on the “Bi-Polar Longitudinal Study”, which aimed to predict adverse events (mania/psychosis) prior to their occurrence via the detection of changes in behavior of at-risk patients.  (https://www.mcleanhospital.org/profile/justin-baker).

Dr. Inbal Nahum-Shani is a Research Assistant Professor at the University of Michigan’s Institute for Social Research. Her research focuses on developing and employing behavioral theory and novel methodologies to construct adaptive interventions, namely interventions that modify the type, timing, dose, or delivery mode of support in order to address the unique and changing needs of individuals. She is an expert on deploying novel research methodologies including the Sequential Multiple Assignment Randomized Trial (SMART) design, related data analytic methods for constructing adaptive interventions, Factorial and Fractional Factorial Designs, and Multilevel Data Analysis and Experimental Designs for developing behavioral interventions. As part of the Intensive Longitudinal Health Behavior Network (https://ilhbn.ssri.psu.edu/projects), she was the Principal Investigator on the “Mobile Application for regulating Smoking study” (https://ilhbn.ssri.psu.edu/projects/mars-mobile-application-regulating-smoking), which aimed to identify states of vulnerability and receptivity to just-in-time interventions. The study employed methods for the joint modeling of EMA, location, motion sensors, and time to event as a function of underlying latent states (https://ihpi.umich.edu/our-experts/inbal).

Dr. Genevieve Dunton is a Professor of Preventive Medicine and Psychology at the University of Southern California. Dr. Dunton´s research examines the etiology of health behaviors related to chronic disease risk in children and adults, with a focus on physical activity and nutrition. Dr. Dunton is the Director of the USC REACH (Real-Time Eating Activity and Children’s Health) lab, the goals of which are to develop, test, and apply real-time data capture methodologies, including EMA and wearable sensors, to better understand the effects of time-varying psychological, social, and environmental factors on eating and physical activity episodes. As part of the Intensive Longitudinal Health Behavior Network (https://ilhbn.ssri.psu.edu/projects/time-temporal-influences-movement-and-exercise), she was the Co-Principal Investigator on the “Time Influences of Movement and Exercise study,” which aimed to assess differences in the micro-temporal processes underlying the adoption vs. maintenance of physical activity and sedentary behaviors (https://keck.usc.edu/faculty-search/genevieve-dunton/).

Dr. Stephen Intille is an Associate Professor in the Khoury College of Computer Sciences and the Bouve College of Health Sciences at Northeastern University. He leads a multi-disciplinary research team exploring the application of advanced sensing and mobile technologies to preventive health domains. An area of interest is the measurement of health-related behaviors, such as physical activity, sedentary behavior, and sleep, as well as measurement of eating behaviors and other contextual factors and affective states, often via context-sensitive self-report. He is experienced in deploying and evaluating systems in a variety of domains where automatic pattern recognition algorithms may support novel preventive health technologies that measure health behavior and motivate health behavior change with “just-in-time” information presentation. As part of the Intensive Longitudinal Behavior Network (https://ilhbn.ssri.psu.edu/projects/time-temporal-influences-movement-and-exercise), he was the Co-principal investigator on the “Time Influences of Movement and Exercise study,” which aimed to assess differences in the micro-temporal processes underlying the adoption vs. maintenance of physical activity and sedentary behaviors (https://www.khoury.northeastern.edu/people/stephen-intille/).

NHANES 2011-2014 Physical Activity Monitor data – now FREE!

Richard P. Troiano, Ph.D.
CAPT, U.S. Public Health Service
NIH Program Director, Risk Factor Assessment Branch of the Epidemiology and Genomics Research Program in NCI’s Division of Cancer Control and Population Sciences (DCCPS)

Dr. Troiano worked with the NHANES to implement the use of devices in the survey to obtain objective measures of participants’ physical activity-related movement and sleep, as well as body strength.  His presentation will be dedicated to the release of the activity monitor data for 2011-2014.

Originally Presented on January 28, 2021 

Mutual understanding of physical behaviors across scientific disciplines

Andreas Holtermann, National Research Center for the Working Environment Copenhagan
Ulf Ekelund, Norwegian School of Sport Science
Svend Erik Mathiassen, University of Gavle
Bente Klarlund Pedersen, University of Copenhagen
Örjan Ekblom, The Swedish School of Sport and Sciences
Jorunn Helbostad, Norwegian University of Science and Technology

Originally presented October 8th, 2020 

The objective of this session is to facilitate a mutual understanding of physical behaviors (physical activity, sedentary behavior, sleep) across scientific disciplines and promote collaboration on integrated research. Presentations will cover the basic view and the ‘key elements’ of physical behaviors from a panel of experts in public and occupational health, physical activity and  sports medicine, exercise science and clinical and rehabilitation science.

Assessing Physical Activity for Beginners – in the view of different perspectives

Facilitator: Associate professor Örjan Ekblom, The Swedish School of Sport and Health Sciences

Originally presented October 16th, 2020

The objective of this session is to introduce device-based assessment of physical activity pattern and provide details for a first data collection. The presentation will cover rationale and perspective of using accelerometry for your studies as well as a crash course on how the data looks like and traditional analysis.

Compositional data analysis (CoDA): The whys, the hows and future applications of CoDA in physical behavior research

Facilitator and speakers

Nidhi Gupta, National Research Center for the Working Environment Copenhagen
Charlotte Lund Rasmussen, National Research Center for the Working Environment Copenhagen
Svend Erik Mathiassen, Department of Occupational Health Sciences and Psychology, University of Gavle
Sebastien Chastin, Glasgow Caledonian University

Originally Presented October 26th, 2020 

The objective of this session is to introduce participants to the basic steps of CoDA, and how to use CoDA in their own research. A panel of experts will guide you through the rationale, basics and examples of CoDA. Challenges and potential for future applications will be discussed.