Dynamic systems modeling to identify a cohort of problem drinkers with similar mechanisms of behavior change

Authors

  • Kidist Bekele-Maxwell North Carolina State University
  • R. A. Everett North Carolina State University
  • Sijing Shao Northwell Health
  • Alexis Kuerbis City University of New York
  • Lyric Stephenson North Carolina State University
  • H. T. Banks North Carolina State University
  • Jon Morgenstern Northwell Health

DOI:

https://doi.org/10.17505/jpor.2017.09

Keywords:

Mathematical psychology, inverse problems, behavior change, personalized medicine, dynamical modeling, ecological momentary assessment data

Abstract

One challenge to understanding mechanisms of behavior change (MOBC) completely among individuals with alcohol use disorder is that processes of change are theorized to be complex, dynamic (time varying), and at times non-linear, and they interact with each other to influence alcohol consumption. We used dynamical systems modeling to better understand MOBC within a cohort of problem drinkers undergoing treatment. We fit a mathematical model to ecological momentary assessment data from individual patients who successfully reduced their drinking by the end of the treatment. The model solutions agreed with the trend of the data reasonably well, suggesting the cohort patients have similar MOBC. This work demonstrates using a personalized approach to psychological research, which complements standard statistical approaches that are often applied at the population level.

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Published

2018-03-11

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Section

Articles