Advancing Models and Theories for Digital Behavior Change Interventions

Eric B. Hekler, Susan Michie, Misha Pavel, Daniel E. Rivera, Linda M. Collins, Holly B. Jimison, Claire Garnett, Skye Parral, Donna Spruijt-Metz

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)825-832
Number of pages8
JournalAmerican journal of preventive medicine
Issue number5
StatePublished - Nov 1 2016

ASJC Scopus subject areas

  • Epidemiology
  • Public Health, Environmental and Occupational Health


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