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Measuring Delay Discounting in Humans Using an Adjusting Amount Task
Published on: January 9, 2016
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Mixture models of delay discounting and smoking behavior
Andre Hofmeyr1, John Monterosso2,3,4, Andy C Dean5,6,7
1a School of Economics , University of Cape Town , Cape Town , South Africa.
The American Journal of Drug and Alcohol Abuse
|July 22, 2016
Summary
Current smokers exhibit steeper delay discounting than never-smokers. A mixture model revealed both exponential and hyperbolic discounting patterns, suggesting tailored addiction treatments may be beneficial.
Area of Science:
- Behavioral Economics
- Addiction Science
- Psychology
Background:
- Smokers display a pronounced tendency to devalue future rewards for immediate gratification.
- This delay discounting behavior is a key indicator of impulsivity and has implications for addiction theories and treatments.
Purpose of the Study:
- To investigate differences in the functional form of delay discounting among current smokers, ex-smokers, and never-smokers.
- To determine if current smokers exhibit a specific discounting pattern, such as hyperbolic discounting, more frequently than non-smokers.
Main Methods:
- A large sample (n=1205) completed a delay discounting questionnaire.
- Finite mixture modeling was employed to analyze data using simultaneous hyperbolic and exponential data-generating processes.
- Results were compared against a quasi-hyperbolic approximation.
Main Results:
- Current smokers showed steeper discounting compared to never-smokers across all tested models.
- A mixture model indicated significant contributions from both exponential and hyperbolic discounting, each explaining approximately 50% of choices.
- The mixture model provided a superior fit to the data compared to individual models.
Conclusions:
- While smokers discount rewards more steeply, they do not disproportionately favor hyperbolic discounting over exponential discounting compared to non-smokers.
- Findings support tailoring addiction treatment strategies based on individual discounting behavior patterns.
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