Assessing Time-Varying Causal Effect Moderation in Mobile Health

In mobile health interventions aimed at behavior change and maintenance, treatments are provided in real time to manage current or impending high-risk situations or promote healthy behaviors in near real time. Currently there is great scientific interest in developing data analysis approaches to gui...

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Bibliographic Details
Published inJournal of the American Statistical Association Vol. 113; no. 523; pp. 1112 - 1121
Main Authors Boruvka, Audrey, Almirall, Daniel, Witkiewitz, Katie, Murphy, Susan A.
Format Journal Article
LanguageEnglish
Published United States Taylor & Francis 03.07.2018
Taylor & Francis Group,LLC
Taylor & Francis Ltd
Subjects
Behavior change
Data analysis
Drinking behavior
Effect modification
Health behavior
Healthy habits
High risk
Impending
Intervention
mHealth
Moderation
Moderators
Real time
Regression analysis
Smartphones
Smoking
Statistical methods
Statistics
Structural nested mean model
Telemedicine
Theory and Methods
effect modification
mHealth
structural nested mean model
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Summary:In mobile health interventions aimed at behavior change and maintenance, treatments are provided in real time to manage current or impending high-risk situations or promote healthy behaviors in near real time. Currently there is great scientific interest in developing data analysis approaches to guide the development of mobile interventions. In particular data from mobile health studies might be used to examine effect moderators-individual characteristics, time-varying context, or past treatment response that moderate the effect of current treatment on a subsequent response. This article introduces a formal definition for moderated effects in terms of potential outcomes, a definition that is particularly suited to mobile interventions, where treatment occasions are numerous, individuals are not always available for treatment, and potential moderators might be influenced by past treatment. Methods for estimating moderated effects are developed and compared. The proposed approach is illustrated using BASICS-Mobile, a smartphone-based intervention designed to curb heavy drinking and smoking among college students. Supplementary materials for this article are available online.
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ISSN:0162-1459
1537-274X
DOI:10.1080/01621459.2017.1305274