Addiction and Rational Choice: Evidence from an Eye Tracking Experiment with Cigarette Packages
Gerstenbluth, M.; Harris, J. E.; Triunfo, P.
Show abstract
We asked 97 current cigarette smokers to make 12 binary choices between experimental packages with varying warnings and background colors. Each participant had to decide which of the two packages contained cigarettes less risky for his health. Confronted with repugnant, threatening images, these smokers nonetheless made choices that were context independent, adhered to transitivity, and consistent with an additive utility model. Eye tracking measurements confirmed that the choices of 65 percent of participants were further compatible with a noise-reducing lexicographic utility model. This subset of participants smoked significantly more cigarettes per day. Our findings support a model in which addiction permits the smoker to suppress aversive stimuli and negative emotions that would otherwise interfere with short-term rational decision making.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- I judge you by your profit: Judgments of effort exerted by selfand others are influenced by task contingent rewards 92%
- Spontaneous eye blink rate predicts individual differences in exploration and exploitation during reinforcement learning 91%
- Emergence of hierarchical organization in memory for random material 91%
Similar papers in this journal
Similar papers in this journal
- Impact of a regional educational advertising campaign on harm perceptions of e-cigarettes, prevalence of e-cigarette use, and quit attempts among smokers 91%
- Associations between e-cigarette use and e-cigarette flavors with cigarette smoking quit attempts and quit success: Evidence from a US large, nationally representative 2018-2019 survey 90%
- Review of evidence regarding attributes and behaviours of smokers as smoking prevalence falls, including evidence relevant to the 'hardening hypothesis' 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.