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Grant Details

Grant Number: 7R01CA229542-05 Interpret this number
Primary Investigator: Coffman, Donna
Organization: University Of South Carolina At Columbia
Project Title: Developing Methodology to Examine Causal Mediation of Time-Varying Effects in Smoking Cessation Treatments
Fiscal Year: 2021


This project will examine new methods for understanding time-varying causal mediation effects in smoking cessation interventions. Mediation occurs when an independent variable (e.g., smoking cessation intervention) has an effect on an outcome (e.g., smoking abstinence) through a third variable (e.g., reduction in craving). In other words, we will develop new ways to understand the mechanisms by which smoking cessation interventions cause changes in people's smoking behavior, and how these effects vary over time. Understanding how interventions have their effect is key to designing more powerful, efficient interventions. To improve smoking cessation interventions, this proposal focuses on improving methods for the understanding of how people stop smoking and continue to abstain from smoking following a smoking cessation intervention. More broadly, the methods that we propose to develop will help us understand what causes behavioral interventions to affect people's engagement in and maintenance of healthy behaviors. We will develop and extend methods for analyzing intensive longitudinal data and conducting mediation analysis to better study time-varying effects, which refer to effects of one variable on another that change (i.e., strengthen or diminish) over time. We will extend methods, based on the potential outcomes framework for causal inference, to draw more valid causal inferences about time-varying effects in mediation and then apply these methods to two smoking cessation intervention studies. First, we will use ecological momentary assessment (EMA) data that asked people about their craving, mood, and smoking abstinence while they were enrolled in a randomized controlled trial of combination nicotine replacement therapy, the nicotine patch alone, and varenicline to develop mediation models in which the effect of the various study drugs on smoking abstinence is mediated by cravings or mood. These effects may vary over time. For example, a study drug may be very effective at reducing cravings shortly after the quit day, but the effect may weaken over time. Second, using data from pedometers, we will assess the effect of a physical activity/ smoking cessation intervention on daily step count and whether increases in daily step counts in turn have an effect on smoking cessation. We will disseminate the methods we develop in user-friendly software (e.g., R packages), journal articles, and conference presentations and workshops that are accessible to behavioral intervention researchers. Methods and findings will ultimately allow researchers to understand how their interventions work. With this knowledge, they will be able to design more efficacious and cost-effective interventions for smoking cessation by targeting the most relevant mediator(s) at the most relevant time.


Tutorial on causal mediation analysis with binary variables: An application to health psychology research.
Authors: Xu S. , Coffman D.L. , Luta G. , Niaura R.S. .
Source: Health psychology : official journal of the Division of Health Psychology, American Psychological Association, 2023 Nov; 42(11), p. 778-787.
EPub date: 2023-07-06.
PMID: 37410423
Related Citations

A Causal Approach to Functional Mediation Analysis with Application to a Smoking Cessation Intervention.
Authors: Coffman D.L. , Dziak J.J. , Litson K. , Chakraborti Y. , Piper M.E. , Li R. .
Source: Multivariate behavioral research, 2023 Sep-Oct; 58(5), p. 859-876.
EPub date: 2023-01-09.
PMID: 36622859
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Time-Varying Mediation of Pharmacological Smoking Cessation Treatments on Smoking Lapse via Craving, Cessation Fatigue, and Negative Mood.
Authors: Chakraborti Y. , Coffman D.L. , Piper M.E. .
Source: Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco, 2022-10-17; 24(10), p. 1548-1555.
PMID: 35287166
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Estimation and inference for the mediation effect in a time-varying mediation model.
Authors: Cai X. , Coffman D.L. , Piper M.E. , Li R. .
Source: BMC medical research methodology, 2022-04-18; 22(1), p. 113.
EPub date: 2022-04-18.
PMID: 35436861
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Varying Coefficient Mediation Model and Application to Analysis of Behavioral Economics Data.
Authors: Liao Y. , Liu J. , Coffman D.L. , Li R. .
Source: Journal of business & economic statistics : a publication of the American Statistical Association, 2022; 40(4), p. 1759-1771.
EPub date: 2021-09-27.
PMID: 36330150
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Covariate Information Number for Feature Screening in Ultrahigh-Dimensional Supervised Problems.
Authors: Nandy D. , Chiaromonte F. , Li R. .
Source: Journal of the American Statistical Association, 2022; 117(539), p. 1516-1529.
EPub date: 2021-02-10.
PMID: 36172297
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Linear Hypothesis Testing in Linear Models With High-Dimensional Responses.
Authors: Li C. , Li R. .
Source: Journal of the American Statistical Association, 2022; 117(540), p. 1738-1750.
EPub date: 2021-04-27.
PMID: 36908313
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Variable selection for causal mediation analysis using LASSO-based methods.
Authors: Ye Z. , Zhu Y. , Coffman D.L. .
Source: Statistical methods in medical research, 2021 Jun; 30(6), p. 1413-1427.
EPub date: 2021-03-23.
PMID: 33755518
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Variable selection for partially linear models via Bayesian subset modeling with diffusing prior.
Authors: Wang J. , Cai X. , Li R. .
Source: Journal of multivariate analysis, 2021 May; 183, .
EPub date: 2021-02-13.
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Time-varying Effects of GABRG1 and Maladaptive Peer Behavior on Externalizing Behavior from Childhood to Adulthood: Testing Gene × Environment × Development Effects.
Authors: Trucco E.M. , Yang S. , Yang J.J. , Zucker R.A. , Li R. , Buu A. .
Source: Journal of youth and adolescence, 2020 Jul; 49(7), p. 1351-1364.
EPub date: 2019-11-30.
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Prioritizing genetic variants in GWAS with lasso using permutation-assisted tuning.
Authors: Yang S. , Wen J. , Eckert S.T. , Wang Y. , Liu D.J. , Wu R. , Li R. , Zhan X. .
Source: Bioinformatics (Oxford, England), 2020-06-01; 36(12), p. 3811-3817.
PMID: 32246825
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Authors: Chu W. , Li R. , Liu J. , Reimherr M. .
Source: The annals of applied statistics, 2020 Mar; 14(1), p. 276-298.
EPub date: 2020-04-16.
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Scalar-on-function regression for predicting distal outcomes from intensively gathered longitudinal data: Interpretability for applied scientists.
Authors: Dziak J.J. , Coffman D.L. , Reimherr M. , Petrovich J. , Li R. , Shiffman S. , Shiyko M.P. .
Source: Statistics surveys, 2019; 13, p. 150-180.
EPub date: 2019-11-06.
PMID: 31745402
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Geographic Imputation of Missing Activity Space Data from Ecological Momentary Assessment (EMA) GPS Positions.
Authors: Mennis J. , Mason M. , Coffman D.L. , Henry K. .
Source: International journal of environmental research and public health, 2018-12-04; 15(12), .
EPub date: 2018-12-04.
PMID: 30518164
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