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Past Workshops

Using Item Response Theory (IRT) Methods to Refine Measurement & Reduce Participant Burden in Aging Research

January 26, 2024

Matthew Diemer

Matthew Diemer
Abstract: Item Response Theory (IRT) methods are best known for their role in large-scale achievement tests, such as the SAT and GRE. However, IRT methods have unique—and often overlooked—advantages for improving measurement and reducing participant burden in aging, and related fields. The first advantage of IRT is illuminating how precise a measure is for people across different levels of the underlying latent construct, an affordance not provided by factor analysis. This more precise capacity to estimate participants’ level of ability better-informs identification of selective attrition in panel surveys, such as whether low-ability respondents were more likely to attrit. The second advantage of IRT is identifying redundant and/or imprecise items for removal, reducing longer scales in favor of more efficient, yet similarly precise, streamlined measures. IRT is therefore useful in reducing the time and money it costs to administer surveys.

These two advantages are also important in reducing participant burden. Shorter measures may increase consent rates by reducing participant time burden, which may lead respondents to consent to subsequent data collections. Shorter measures may similarly minimize attrition, in that participants are more likely to complete shorter surveys – which also have the effect of yielding better data quality. In sum, by producing shorter and more efficient measures, IRT has the potential to reduce attrition, increase consent rates, and improve data quality in aging research.

Workshop video recording (YouTube)

Workshop slides and other materials (PowerPoint)

Community Advisory Boards in Aging Research

August 31, 2023

Joseph E. Gaugler

Joseph E. Gaugler
University of Minnesota

Abstract: The robust incorporation of research participant and community perspectives in aging science is critical to propelling our research across the translational continuum. This workshop will share how one research team (the Families and Long-Term Care Projects) have incorporated persons with dementia, family/friend care partner, and care professional perspectives in various research projects and other elements of aging-related, scientific infrastructure via community advisory boards and similar efforts. The workshop will highlight other key efforts to incorporate participants’ perspectives throughout the research lifecycle in dementia, and the implications of these efforts for future research in this area.

Joe Gaugler is the Robert L. Kane Endowed Chair in Long-Term Care & Aging in the School of Public Health and a Distinguished McKnight University Professor at the University of Minnesota. He is the Director of the Center for Healthy Aging and Innovation, Director of the national BOLD Public Health Center of Excellence on Dementia Caregiving, and Editor-in-Chief of The Gerontologist. His research focuses on dementia care innovation.

Workshop video recording (YouTube)

Workshop Slides (PowerPoint)

Designing and Implementing American Life in Realtime, a benchmark digital health study

May 16, 2023

Ritika ChaturvediRitika Chaturvedi

University of Southern California

Abstract: This workshop presents an overview of American Life in Realtime (ALiR) a population health study involving wearables in partnership with the Understanding America Study. ALiR is a benchmark digital health cohort, research infrastructure, and dataset that seeks to explore how everyday life affects health in a comprehensive and equitable manner. ALiR’s cohort is a probability based representative sample of U.S. adults, with an oversample of racial/ethnic minorities and/or under-resourced groups. Participants continuously wear study-provided Fitbits and answer frequent electronic surveys about their health and well-being for at least one year, though most continue to participate indefinitely. ALiR’s dataset, using FAIR standards (findable, accessible, interoperable, reusable), overlays (1) continuous Fitbit biometrics; (2) in-depth, longitudinal self-reported measures of sociodemographics, social, structural, and environmental exposures, personality, behaviors, and health measured via high-quality, validated instruments; and, (3) geospatially and temporally matched public environmental data on individual time-series. Ultimately, ALiR is a model for achieving diversity, equity, inclusion, transparency and multi-disciplinary collaboration in precision digital health.

Workshop video recording (YouTube)

Community-Based Participatory Research in Practice

April 24, 2023

Carina Gronlund, Zachary Rowe, Tam Perry, Fatima Hazimeh, Evan Villeneuve, Brenda Butler

Carina GronlundZachary RoweTam PerryFatima HazimehEvan VilleneuveBrenda Butler

University of Michigan Institute for Social Research, Friends of Parkside, Wayne State University

Abstract: What in the world is communitybased participatory research? In this workshop, attendees will get a taste of this research paradigm in which community and academic partners work together as co-investigators. We will discuss partnership formation and the nature of community-academic collaborations throughout the research process: including developing the research questions, applying for funding, recruitment and retention of participants, and dissemination of the findings in the peer-reviewed literature, sharing results back to the participants, and dissemination in many other forums. Real-world successes and challenges from academic and community partners will be shared, and attendees will be invited to ponder how they might incorporate CBPR principles into their own work.

Workshop video recording (YouTube)

Workshop Slides (PDF) 

Using Smartphones for Passive and Active Data Collection in Older Populations

February 8, 2023

Florian KeuschFlorian Keusch

University of Mannheim, Germany

Smartphones have become integral parts of many people’s lives. For researchers, the main advantage of smartphones lies in the fact that many users carry them around with them throughout the day. Thus, the devices are often present in the same physical and social contexts as their users. In addition, smartphones include a large set of built-in sensors and support multiple modes of communication greatly facilitating widespread, longitudinal active (e.g., EMA, taking pictures, scanning receipts) and passive (e.g., location tracking, physical activity, call logs, browsing history) data collection in situ. On the flipside, there are multiple challenges to collecting data via smartphones especially among older populations, including selectivity of smartphone ownership and (non)willingness to provide sensor data or perform active data collection tasks.

This workshop will introduce the potentials and challenges when implementing passive and active data collection on smartphones in longitudinal studies of older populations. We will discuss technical aspects of the data collection process and for what types of research questions they can be used. The workshop will also review best practices when implementing smartphone data collection in studies of older populations to reduce errors of measurement and representation.

Workshop slides (PDF) 

Yajuan Si
Applying Weights to Longitudinal Survey Data

September 15, 2022

Yajuan Si

University of Michigan

Longitudinal surveys collect rich data about individual characteristics and enable trajectory modeling to understand the developmental course and lifespan. Examples include the Monitoring the Future (MTF) panel study, the Panel Study of Income Dynamics (PSID), and the Midlife in the United States (MIDUS) Series. However, the quality of estimates can be attenuated by panel attrition. Moreover, sample selection procedures for longitudinal studies are often complex in nature, including design features such as stratification, cluster sampling, and survey weights for probability samples. A failure to account for these selection features in estimation could affect the inferential validity and generalizability of descriptive summary measures and estimates of trajectory models. Weighting approaches have been popular in the survey statistics literature to simultaneously adjust for these complex sample design features and panel attrition. However, there is no clear consensus in the literature on whether or how to apply weighting adjustments for attrition in longitudinal trajectory modeling. In this workshop, we will provide an overview of the main methodological issues and focus on hands-on analysis with survey weights using statistical software (e.g., R). We will illustrate the workflow with applications to data from the MTF, PSID, and MIDUS studies.

Workshop video recording (YouTube)

Workshop materials (Zip file)