#26 - Behavioral Economics for Real-Life Interventions w/ Dr. Brent Kaplan

Show Notes

• About the episode

  In this episode, Zach and Caleb discuss using behavioral economics for real-world interventions with Dr. Brent Kaplan.
  

  Learning Objectives

  1. Analyze behavioral data using quantitative math formulas to shift from descriptive representations of environment-behavior relations to forecasting quantitative numbers across untested parameters.

  2. Analyze how shifts in fixed response costs affect the consumption of a given commodity (reinforcer), and explain why immediate preference assessments at an FR1 baseline fail to predict reinforcement persistence under lean schedules.

  3. Design clinical environments by mapping how the shifting price or response requirement of one reinforcer functionally controls the cross-consumption of concurrent alternatives.

• Things to check out from the episode:
  
  Check out Dr. Kaplan’s Website to access copies of his publications, try out his behavioral-oriented software, and view other projects he’s working on: https://codedbx.com/
  
  

  References:
  Kaplan, B. A. & Reed, D. D. (2012). The matching law: A tutorial for practitioners. Behavior Analysis in Practice, 4(2), 15-24. doi: 10.1007/BF03391780
  
  Reed, D. D., Niileksela, C., & Kaplan, B. A. (2013). Behavioral economics: A tutorial for behavior analysts in practice. Behavior Analysis in Practice, 6, 34-54. doi: 10.1007/BF03391790

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