Grant Number:	2R01CA240713-05A1 Interpret this number
Primary Investigator:	Hedeker, Donald
Organization:	University Of Chicago
Project Title:	Novel Statistical Models for Intensive Longitudinal Analyses of Cancer Control Behaviors
Fiscal Year:	2024

PROJECT SUMMARY This project will develop, test, apply, and disseminate multilevel statistical models and software for estimating effects of intraindividual means, variances, slopes generated from multi-burst and continuous ILD designs to predict cancer control behaviors and outcomes. Cancer remains a leading cause of mortality. Approximately 42% of new cancer cases in the U.S. are viewed as potentially avoidable including 19% caused by smoking and 18% caused by excess body weight, physical inactivity, excess alcohol consumption, and poor nutrition. Intensive Longitudinal Data (ILD) methods, which collect many assessments captured at high density on a micro- timescale (e.g., seconds, minutes, hours) using real-time data capture methodologies (e.g., Ecological Momentary Assessment [EMA] and accelerometry), offer enormous opportunities for insight into the dynamic nature of cancer control behaviors and outcomes. In ILD studies, it is common to have hundreds to thousands of observations per subject, and this allows us to model intraindividual parameters comprised of time-varying variables such as means (e.g., how unhappy is a subject, on average, across occasions?), variances (e.g., how erratic is a subject’s mood across occasions?), and slopes (e.g., is a subject’s mood related to feelings of energy across occasions?). In our prior work, we developed a software, called MixWILD, consisting of a series of two- stage multilevel statistical models testing the effects of intraindividual means, variances, and slopes on time- varying and subject-level outcomes. The next generation of ILD studies has begun to use multi-burst (e.g., multiple day EMA periods interspersed with days with no assessment) and continuous (e.g., 24-hour/days per week smartwatch accelerometry) measurement designs, allowing the entire study to extend across months or years. However, available data analysis techniques cannot address common substantive questions that arise with multi-burst and continuous ILD designs such as does momentary mood variability increase across a year? Also, do month-to-month increases in momentary mood variability predict declines in sleep duration over a year? To address these gaps, we will develop multilevel models capable of (Aim 1) jointly estimating how within-burst means, variability, and slopes differ between bursts and/or subjects, (Aim 2) testing predictors (either occasion, burst-, person-level) of how within-burst means, variability, and slopes differ between bursts and/or subjects, and (Aim 3) testing whether random effects from Aim 1 predict subject- and burst-level cancer control outcomes. We will test and apply these statistical features by conducting secondary analyses of data from a multi-burst ILD study of cancer control behaviors and outcome, which conducted mobile sensing, EMA, and accelerometry from 246 emerging adults (ages 18-29) across 12 months. We will also develop, test, and disseminate a stand-alone software with GUI capable of running these statistical models to be used by applied behavioral and social science researchers. The methods to be developed can easily generalize to a variety of other disease areas such asthma, disordered eating, suicide prevention, HIV risk, medication adherence, and environmental exposures.




Ask Less, Learn More: Adapting Ecological Momentary Assessment Survey Length by Modeling Question-Answer Information Gain.
Authors: Li J. , Ponnada A. , Wang W.L. , Dunton G.F. , Intille S.S. .
Source: Proceedings Of The Acm On Interactive, Mobile, Wearable And Ubiquitous Technologies, 2024 Nov; 8(4), .
EPub date: 2024-11-21 00:00:00.0.
PMID: 39664111
Related Citations

Pleasure and Satisfaction as Predictors of Future Cigarette and E-cigarette Use: A Novel Two-Stage Modeling Approach.
Authors: Hedeker D. , Brooks J. , Diviak K. , Jao N. , Mermelstein R.J. .
Source: Nicotine & Tobacco Research : Official Journal Of The Society For Research On Nicotine And Tobacco, 2024-10-22 00:00:00.0; 26(11), p. 1472-1479.
PMID: 38775349
Related Citations

Fast estimation of mixed-effects location-scale regression models.
Authors: Gill N. , Hedeker D. .
Source: Statistics In Medicine, 2023-02-16 00:00:00.0; , .
EPub date: 2023-02-16 00:00:00.0.
PMID: 36796352
Related Citations

Temporal stability of behavior, temporal cue-behavior associations, and physical activity habit strength among mothers with school-aged children.
Authors: Maher J.P. , Wang W.L. , Hedeker D. , Dunton G.F. .
Source: Psychology & Health, 2022-06-27 00:00:00.0; , p. 1-16.
EPub date: 2022-06-27 00:00:00.0.
PMID: 35757845
Related Citations

How acute affect dynamics impact longitudinal changes in physical activity among children.
Authors: Dunton G.F. , Wang W.L. , Intille S.S. , Dzubur E. , Ponnada A. , Hedeker D. .
Source: Journal Of Behavioral Medicine, 2022-03-28 00:00:00.0; , .
EPub date: 2022-03-28 00:00:00.0.
PMID: 35347520
Related Citations

A shared-parameter location-scale mixed model to link the responsivity in self-initiated event reports and the event-contingent Ecological Momentary Assessments.
Authors: Ma Q. , Mermelstein R.J. , Hedeker D. .
Source: Statistics In Medicine, 2022-02-09 00:00:00.0; , .
EPub date: 2022-02-09 00:00:00.0.
PMID: 35139579
Related Citations

Early effects of the COVID-19 pandemic on fertility preferences in the United States: an exploratory study.
Authors: Naya C.H. , Saxbe D.E. , Dunton G.F. .
Source: Fertility And Sterility, 2021-07-26 00:00:00.0; , .
EPub date: 2021-07-26 00:00:00.0.
PMID: 34325920
Related Citations

An empirical example of analysis using a two-stage modeling approach: within-subject association of outdoor context and physical activity predicts future daily physical activity levels.
Authors: Yang C.H. , Maher J.P. , Ponnada A. , Dzubur E. , Nordgren R. , Intille S. , Hedeker D. , Dunton G.F. .
Source: Translational Behavioral Medicine, 2021-04-26 00:00:00.0; 11(4), p. 912-920.
PMID: 33159452
Related Citations

A Three-Level Mixed Model to Account for the Correlation at both the Between-Day and the Within-Day Level for Ecological Momentary Assessments.
Authors: Ma Q. , Mermelstein R. , Hedeker D. .
Source: Health Services & Outcomes Research Methodology, 2020 Dec; 20(4), p. 247-264.
EPub date: 2020-09-23 00:00:00.0.
PMID: 33122963
Related Citations

Ambulatory Assessment for Physical Activity Research: State of the Science, Best Practices and Future Directions.
Authors: Reichert M. , Giurgiu M. , Koch E. , Wieland L.M. , Lautenbach S. , Neubauer A.B. , von Haaren-Mack B. , Schilling R. , Timm I. , Notthoff N. , et al. .
Source: Psychology Of Sport And Exercise, 2020 Sep; 50, .
EPub date: 2020-06-17 00:00:00.0.
PMID: 32831643
Related Citations

MixWILD: A program for examining the effects of variance and slope of time-varying variables in intensive longitudinal data.
Authors: Dzubur E. , Ponnada A. , Nordgren R. , Yang C.H. , Intille S. , Dunton G. , Hedeker D. .
Source: Behavior Research Methods, 2020 08; 52(4), p. 1403-1427.
PMID: 31898295
Related Citations

Conceptualizing Health Behaviors as Acute Mood-Altering Agents: Implications for Cancer Control.
Authors: Dunton G.F. , Kaplan J.T. , Monterosso J. , Pang R.D. , Mason T.B. , Kirkpatrick M.G. , Eckel S.P. , Leventhal A.M. .
Source: Cancer Prevention Research (philadelphia, Pa.), 2020-01-16 00:00:00.0; , .
EPub date: 2020-01-16 00:00:00.0.
PMID: 31948998
Related Citations