Title |
Hunger increases delay discounting of food and non-food rewards
|
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Published in |
Psychonomic Bulletin & Review, September 2019
|
DOI | 10.3758/s13423-019-01655-0 |
Pubmed ID | |
Authors |
Jordan Skrynka, Benjamin T. Vincent |
Abstract |
How do our valuation systems change to homeostatically correct undesirable psychological or physiological states, such as those caused by hunger? There is evidence that hunger increases discounting for food rewards, biasing choices towards smaller but sooner food reward over larger but later reward. However, it is not understood how hunger modulates delay discounting for non-food items. We outline and quantitatively evaluate six possible models of how our valuation systems modulate discounting of various commodities in the face of the undesirable state of being hungry. With a repeated-measures design, an experimental hunger manipulation, and quantitative modeling, we find strong evidence that hunger causes large increases in delay discounting for food, with an approximately 25% spillover effect to non-food commodities. The results provide evidence that in the face of hunger, our valuation systems increase discounting for commodities, which cannot achieve a desired state change as well as for those commodities that can. Given that strong delay discounting can cause negative outcomes in many non-food (consumer, investment, medical, or inter-personal) domains, the present findings suggest caution may be necessary when making decisions involving non-food outcomes while hungry. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 14 | 16% |
Germany | 4 | 4% |
United States | 4 | 4% |
Poland | 4 | 4% |
Denmark | 2 | 2% |
Norway | 2 | 2% |
Mexico | 2 | 2% |
Canada | 2 | 2% |
Japan | 2 | 2% |
Other | 13 | 14% |
Unknown | 41 | 46% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 59 | 66% |
Scientists | 19 | 21% |
Practitioners (doctors, other healthcare professionals) | 11 | 12% |
Science communicators (journalists, bloggers, editors) | 1 | 1% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 78 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 15 | 19% |
Student > Ph. D. Student | 12 | 15% |
Student > Bachelor | 12 | 15% |
Researcher | 4 | 5% |
Student > Doctoral Student | 3 | 4% |
Other | 10 | 13% |
Unknown | 22 | 28% |
Readers by discipline | Count | As % |
---|---|---|
Psychology | 27 | 35% |
Neuroscience | 11 | 14% |
Business, Management and Accounting | 3 | 4% |
Agricultural and Biological Sciences | 3 | 4% |
Biochemistry, Genetics and Molecular Biology | 3 | 4% |
Other | 7 | 9% |
Unknown | 24 | 31% |