A Dynamical Systems Model for Understanding Behavioral Interventions for Weight Loss

Navarro-Barrientos, Jesús Emeterio; Rivera, Daniel E.

doi:10.1007/978-3-642-12079-4_23

Cited by 12 publications

(13 citation statements)

References 12 publications

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“…Advances have been made in this regard in terms of the development and utilization of techniques such as adaptive intervention designs [33], fractional factorial designs [34] and other methods based on engineering models [35]. Additionally, agent-based and other modeling methods can be used to identify intervention targets and time-points for successful intervention.…”

Section: Tdtb Methods and Trainingmentioning

confidence: 99%

Transdisciplinary translational behavioral (TDTB) research: opportunities, barriers, and innovations

Czajkowski

Lynch

Hall

et al. 2016

Behav. Med. Pract. Policy Res.

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The translation of basic behavioral science discoveries into practical strategies represents a promising approach to developing more effective preventive interventions to improve health. Since translational research inevitably involves making use of diverse perspectives from multiple disciplines, it is best conducted as a transdisciplinary enterprise. In this paper, we discuss current strategies used by NIH to support transdisciplinary translational behavioral (TDTB) research, summarize successful efforts, and highlight challenges encountered in conducting such work (ranging from conceptual to organizational to methodological). Using examples from NIH-funded projects we illustrate the potential benefits of, and barriers to, pursuing this type of research and discuss next steps and potential future directions for NIH-supported TDTB research.

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Section: Tdtb Methods and Trainingmentioning

confidence: 99%

Transdisciplinary translational behavioral (TDTB) research: opportunities, barriers, and innovations

Czajkowski

Lynch

Hall

et al. 2016

Behav. Med. Pract. Policy Res.

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“…These control system principles and procedures fit well with the rich longitudinal data and real-time intervention adaptations potentially available via mobile technologies. Interventions based on theories enriched by control system models also provide engineers and health behavior researchers with a common language for collaborating on new interventions delivered via mobile technologies [94]. …”

Section: Theoretical Basis For Mobile Health Behavior Interventions Amentioning

confidence: 99%

Health behavior models in the age of mobile interventions: are our theories up to the task?

Riley

Rivera

Atienza

et al. 2011

Behav. Med. Pract. Policy Res.

923

788

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Mobile technologies are being used to deliver health behavior interventions. The study aims to determine how health behavior theories are applied to mobile interventions. This is a review of the theoretical basis and interactivity of mobile health behavior interventions. Many of the mobile health behavior interventions reviewed were predominately one way (i.e., mostly data input or informational output), but some have leveraged mobile technologies to provide just-in-time, interactive, and adaptive interventions. Most smoking and weight loss studies reported a theoretical basis for the mobile intervention, but most of the adherence and disease management studies did not. Mobile health behavior intervention development could benefit from greater application of health behavior theories. Current theories, however, appear inadequate to inform mobile intervention development as these interventions become more interactive and adaptive. Dynamic feedback system theories of health behavior can be developed utilizing longitudinal data from mobile devices and control systems engineering models.

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“…To address some of the above needs and, in order to make the Psychological theories more actionable, Fluid Analogy models have been proposed in the literature recently [1,2,3,7,8,9] to represent and reason about human behavior. In these models, the state variables are viewed as tanks that store fluid and the interconnections and influences between the tanks are represented by using a network of pipes in which fluid can flow.…”

Section: 9mentioning

confidence: 99%

Bond graph models for human behavior

Mahamadi

Sastry

2016

2016 Conference of Basic Sciences and Engineering Studies (SGCAC)

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viii 3.10 When the resistance to PBC intervention is low, the participant responds promptly (top), behavior improves and the weight loss is achieved as desired. When the resistance is high (bottom), the behavior is undesirable and weight loss is not achieved.. .. .. .. .. 3.11 The weight dynamics for the participant in three scenarios. Scenario 1 is the baseline. The participant is resistant to change in Scenario 2 and the participant diligently complies with the recommendations in Scenario 3 as computed using the SCT bond graph model.. .. .. . 3.12 When the resistance to external cues intervention is low, the participant responds promptly (top), behavior improves and the weight loss is achieved as desired. When the resistance is high (bottom), the behavior is undesirable and weight loss is not achieved.. .. .. .. 3.13 Hybrid bond graph model for the Theory of Planned Behavior.. .. .. 4.1 Fluid analogy representation for the interaction between a Therapist and a Client.

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A Dynamical Systems Model for Understanding Behavioral Interventions for Weight Loss

Cited by 12 publications

References 12 publications

Transdisciplinary translational behavioral (TDTB) research: opportunities, barriers, and innovations

Transdisciplinary translational behavioral (TDTB) research: opportunities, barriers, and innovations

Health behavior models in the age of mobile interventions: are our theories up to the task?

Bond graph models for human behavior

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