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Development of a dynamic computational model of social cognitive theory

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Translational Behavioral Medicine

Abstract

Social cognitive theory (SCT) is among the most influential theories of behavior change and has been used as the conceptual basis of health behavior interventions for smoking cessation, weight management, and other health behaviors. SCT and other behavior theories were developed primarily to explain differences between individuals, but explanatory theories of within-person behavioral variability are increasingly needed as new technologies allow for intensive longitudinal measures and interventions adapted from these inputs. These within-person explanatory theoretical applications can be modeled as dynamical systems. SCT constructs, such as reciprocal determinism, are inherently dynamical in nature, but SCT has not been modeled as a dynamical system. This paper describes the development of a dynamical system model of SCT using fluid analogies and control systems principles drawn from engineering. Simulations of this model were performed to assess if the model performed as predicted based on theory and empirical studies of SCT. This initial model generates precise and testable quantitative predictions for future intensive longitudinal research. Dynamic modeling approaches provide a rigorous method for advancing health behavior theory development and refinement and for guiding the development of more potent and efficient interventions.

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Acknowledgments

DR and EH were supported by a grant from National Science Foundation (IIS-1449751). DR also was supported by a grant from the National Institute on Drug Abuse (K25DA021173). MP was supported by a grant from the National Institute of Nursing Research (P20NR015320). AK was supported by grants from National Heart, Lung, and Blood Institute (R01HL116448), National Institute of Diabetes and Digestive and Kidney Diseases (R01DK102016), and National Institute of Biomedical Imaging and Bioengineering (U54EB020405). This paper represents the views and perspectives of the authors, not the funders or the National Institutes of Health. All authors participated in this article and take responsibility for the integrity of the conceptualizations and models described.

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Correspondence to William T. Riley PhD.

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This article presents conceptual and computational models; no human subject data were collected.

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The authors declare that they have no competing interests.

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Implications

Researchers: Using this initial computational dynamic model social cognitive theory (SCT) as a guide, researchers can test interrelations of SCT constructs that go beyond covariation and specify how much and in which ways SCT constructs influence one another.

Practitioners: Based on these theory-derived SCT equations, interventionists can generate hypothetical estimates of how much of a change in various SCT constructs is necessary to produce a clinically meaningful change in behavior.

Policymakers: These theory-derived SCT equations can generate hypothetical estimates of how policies targeting specific SCT parameters might impact behavior.

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Riley, W.T., Martin, C.A., Rivera, D.E. et al. Development of a dynamic computational model of social cognitive theory. Behav. Med. Pract. Policy Res. 6, 483–495 (2016). https://doi.org/10.1007/s13142-015-0356-6

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  • DOI: https://doi.org/10.1007/s13142-015-0356-6

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