# Continuous Time Causal Mediation Models for Social Behavior in Health

> **NIH NIH R01** · CASE WESTERN RESERVE UNIVERSITY · 2020 · $395,421

## Abstract

Health research has been increasingly focused on discovering the mechanisms through which an
exposure or intervention affects health outcomes. Social science has become a part of this picture as
the importance of social behavior and other social factors in health has been increasingly recognized.
Causal mediation analysis methods have been developed to explore such mechanisms. However,
these approaches are rooted in discrete time models, and fail to account for the continuous time nature
of many, if not most, social and behavioral, as well as biological, processes. The proposed research will
develop a new continuous time causal mediation analysis model (CMM). In addition to allowing a
description of the dynamic interplay among variables in time, the new model will allow the incorporation
of continuous time features such as time lags and extinction effects. The model will accommodate
arbitrary data patterns, multiple causal links, continuous and categorical variables, and
interaction/modification effects. We start with a differential equation model based on a potential
outcome (causal) framework, and show the connection to a nonlinear model form that may be fit to
data. An integration approach may be used to estimate mediation/path effects and predict the effect of
new interventions. Secondly, we will extend CMMs to handle multi-level data, for example, family,
neighborhood or other social variables, which may themselves unfold over time. In addition, we will
model the impact of individuals on one another, providing a explanation for emergent social behavior.
We will apply our new methods to a randomized study of family interventions to improve dental care
use in children and a longitudinal observational study of family, neighborhood, behavioral and biologic
factors in the progression of dental caries in disadvantaged and high risk (including very low birth
weight) children. The new methods will be evaluated and refined through simulation studies. The new
continuous time mediation models will be further used to study design issues, including the number and
timing of measurements, and to investigator new designs, for example that randomize different subjects
to different measurement times. Finally, we will develop user-friendly computer programs to allow
behavioral and other health researchers to apply the new methods. The new methods will allow a more
valid and thorough exploration of causal mechanisms involving social behavior, with broad applicability
across heath areas. They will also facilitate the development of effective behavioral and other
interventions to improve health outcomes and decrease health disparities.

## Key facts

- **NIH application ID:** 9832141
- **Project number:** 5R01DE025835-04
- **Recipient organization:** CASE WESTERN RESERVE UNIVERSITY
- **Principal Investigator:** JEFFREY M ALBERT
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $395,421
- **Award type:** 5
- **Project period:** 2016-12-01 → 2021-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9832141

## Citation

> US National Institutes of Health, RePORTER application 9832141, Continuous Time Causal Mediation Models for Social Behavior in Health (5R01DE025835-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9832141. Licensed CC0.

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