To be suitable for informing digital behavior change interventions, theories and models
of behavior change need to capture individual variation and changes over time. The
aim of this paper is to provide recommendations for development of models and theories
that are informed by, and can inform, digital behavior change interventions based
on discussions by international experts, including behavioral, computer, and health
scientists and engineers. The proposed framework stipulates the use of a state-space
representation to define when, where, for whom, and in what state for that person,
an intervention will produce a targeted effect. The “state” is that of the individual
based on multiple variables that define the “space” when a mechanism of action may
produce the effect. A state-space representation can be used to help guide theorizing
and identify crossdisciplinary methodologic strategies for improving measurement,
experimental design, and analysis that can feasibly match the complexity of real-world
behavior change via digital behavior change interventions.
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Article Info
Footnotes
This article is part of a theme section titled Digital Health: Leveraging New Technologies to Develop, Deploy, and Evaluate Behavior Change Interventions.
Identification
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© 2016 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
