Date of Defense
Date of Graduation
Mark J. Rzeszutek
There is a rising prevalence for obesity in the United States. Obesity is associated with health issues such as heart disease, diabetes, and other health complications including worsened mental health. Because of this, it is important to look for effective solutions to address risk factors, such as overeating and a sedentary lifestyle, that are associated with obesity. Applied behavior analysis, the application of learning principles to socially significant issues, has potential in addressing factors that lead to obesity. Functional analysis and the antecedent-behavior-consequence (ABC) model can help explain “cause and effect” relationships between environment and behavior and why and how some behaviors occur from frequently over others. Some environmental factors can influence how an individual consumes, such as variety of food within certain food groups, distractions present when eating, portion size. Delay discounting, the devaluing of a reinforcer due to a delay, can also be useful in understanding how individuals become obese. Individuals who are obese display steeper discounting relative to controls, that is, prefer a smaller immediate reinforcer relative to a larger delayed one. Potential interventions based on the ABC model, such as changing discounting or manipulating antecedent and/or consequent stimuli, could be enhanced by individualized functional analyses. Goal setting and self-monitoring are also interventions to be considered. Although, there is support for a behavioral analytic approach to address risk factors associated with obesity, more research into specific areas, such as functional analyses of overeating, needs to be conducted to potentially improve clinical outcomes.
Khan, Fawzia, ""Incorporating behavior analysis to address risk factors for obesity"" (2021). Honors Theses. 3490.
Honors Thesis-Open Access