Advancing Models and Theories for Digital Behavior Change Interventions
Open accessAbstract
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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Digital models often require programming for a strict definition of the desired outcome and the type and amount of intervention proposed and are in constant flux to tailor interventions.
“However, digital models often require programming for a strict definition of the desired outcome and the type and amount of intervention proposed and are in constant flux to tailor interventions104.”
From Smart wearable devices in cardiovascular care: Where we are and how to move forward (2021) · cites this paper as [104]
Hekler et al. proposed a framework for the use of digital BCTs, such as just-in-time adaptive interventions, to encourage and maintain health.
“Hekler et al. proposed a framework for the use of digital BCTs, such as just-in-time adaptive interventions, to encourage and maintain health104.”
From Smart wearable devices in cardiovascular care: Where we are and how to move forward (2021) · cites this paper as [104]
The Hekler et al. framework highlights the importance of the state-space, the readiness to respond to an intervention according to intrinsic factors (state) and contextual factors (space).
“This framework highlights the importance of the ‘state-space’, essentially the readiness to respond to an intervention according to intrinsic factors (state) and contextual factors (space).”
From Smart wearable devices in cardiovascular care: Where we are and how to move forward (2021) · cites this paper as [104]
Supervised learning predicts adherence and effects from early use patterns, which enables early intervention for users at risk.
“Supervised learning predicts adherence and effects from early use patterns, which enables early intervention for users at risk [31,33,34].”
From Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data (2017) · cites this paper as [34]
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References 57 · Cited by 174
Research works printed but not linked: 1
- [28]Bandura A Social Foundations of Thought and Action: A Social Cognitive Theory Englewood Cliffs, NJ Prentice Hall 1986
- Authors
- Hekler, E. B., Michie, S., Pavel, M., Rivera, D. E., Collins, L. M., Jimison, H. B., Garnett, C., Parral, S., & Spruijt-Metz, D.
- Affiliations
- Arizona State University (US)
- University College London (GB)
- Pennsylvania State University (US)
- Northeastern University (US)
- University of Southern California (US)
- Corresponding author
- Hekler, Eric B.
- Venue
- American Journal of Preventive Medicine
- Publisher
- Elsevier BV
- Published
- 2016-11
- Volume
- 51
- Issue
- 5
- Pages
- 825-832
- ISSN
- 0749-3797 (ISSN-L)
- PMC
- PMC5506832
- OpenAlex
- W2531901946
- Cited by
- 174
- References
- 57
- Citations by year
- 2026: 12 · 2025: 12 · 2024: 18 · 2023: 14 · 2022: 23 · 2021: 22 · 2020: 11 · 2019: 19 · 2018: 23 · 2017: 16 · 2016: 3
- FWCI
- 31.33
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- American Journal of Preventive Medicine (acceptedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- NIH Office of Behavioral and Social Sciences Research (OBSSR)
- Medical Research Council (MRC)
- National Institute for Health Research (NIHR)
- OBSSR
- Robert Wood Johnson Foundation (71995)
- National Science Foundation (1539846, 1449751)
- U.S. National Science Foundation (1407928, 1521740)
- National Institutes of Nursing Research (P20-NR015320)
- U.S. National Institutes of Health (P50DA039838, P01CA180945, R01DK097364, R01AA022931)
- Topics
- Social Sciences › Psychology › Applied Psychology › Behavioral Health and Interventions
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- digital behaviour change interventions, behaviour change theory, state-space model, interindividual variability, mechanism of action, health behavior change
- MeSH terms
- Health Promotion, Humans, Models, Theoretical, Research Design, Telecommunications, Health Behavior
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