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Cited by 381

The DOI matches its Crossref record; 252 of the 252 references it cites were found in a registry or an index.

Food reinforcement and eating: A multilevel analysis.

Open access
Epstein, Leonard H., Leddy, John J., Temple, Jennifer L., Faith, Myles S.·2007·Psychological Bulletin

Abstract

Eating represents a choice among many alternative behaviors. The purpose of this review is to provide an overview of how food reinforcement and behavioral choice theory are related to eating and to show how this theoretical approach may help organize research on eating from molecular genetics through treatment and prevention of obesity. Special emphasis is placed on how food reinforcement and behavioral choice theory are relevant to understanding excess energy intake and obesity and how they provide a framework for examining factors that may influence eating and are outside of those that may regulate energy homeostasis. Methods to measure food reinforcement are reviewed, along with factors that influence the reinforcing value of eating. Contributions of neuroscience and genetics to the study of food reinforcement are illustrated by using the example of dopamine. Implications of food reinforcement for obesity and positive energy balance are explored, with suggestions for novel approaches to obesity treatment based on the synthesis of behavioral and pharmacological approaches to food reinforcement.

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Crossref · 10.1037/0033-2909.133.5.884

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Metadata

Authors
Epstein, L. H., Leddy, J. J., Temple, J. L., & Faith, M. S.
Venue
Psychological Bulletin
Published
2007
Volume
133
Issue
5
Pages
884-906
ISSN
  • 0033-2909 (ISSN-L)
  • 1939-1455
OpenAlex
W2019414704
Cited by
381
References
252
FWCI
5.56
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Food reinforcement and eating: A multilevel analysis. https://app.cochat.ai/papers/10.1037/0033-2909.133.5.884
The paper
Epstein, L. H., Leddy, J. J., Temple, J. L., & Faith, M. S. (2007). Food reinforcement and eating: A multilevel analysis. Psychological Bulletin. https://doi.org/10.1037/0033-2909.133.5.884

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.