Reinforcer pathology: the behavioral economics of abuse liability testing
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Understanding the abuse liability of novel drugs is critical to understanding the risk these new compounds pose to society. Behavioral economics, the integration of psychology and economics, can be used to predict abuse liability of novel substances. Here, we describe the behavioral economic concept of reinforcer pathology and how it may predict the use of novel drugs in existing drug‐users and initiation of use in the drug‐naive.
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The concept of reinforcer pathology is a recent development in the field of the behavioral economics of addiction specifically focused on how the window of time over which reinforcers are integrated can determine the relative valuation of alcohol and drugs versus other prosocial reinforcers, such as relationships and employment.
“The concept of reinforcer pathology is a recent development in the field of the behavioral economics of addiction specifically focused on how the window of time over which reinforcers are integrated can determine the relative valuation of alcohol and drugs versus other prosocial reinforcers, such as relationships and employment [22–24].”
From Addiction Biomarkers: Dimensional Approaches to Understanding Addiction (2018) · cites this paper as [24]
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Madden, G. J., Petry, N. M., Badger, G. J., & Bickel, W. K. (1997) · Experimental and Clinical Psychopharmacology · doi:10.1037/1064-1297.5.3.256 · Cited by 911 · see citing works
Self-citationThe behavioral economics of substance use disorders: reinforcement pathologies and their repair
Bickel, W. K., Johnson, M. W., Koffarnus, M. N., MacKillop, J., & Murphy, J. G. (2014) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-032813-153724 · Cited by 655 · see citing works
Self-citationRelative reinforcing efficacy of alcohol among college student drinkers.
Murphy, J. G., & MacKillop, J. M. (2006) · Experimental and Clinical Psychopharmacology · doi:10.1037/1064-1297.14.2.219 · Cited by 399 · see citing works
Bickel, W. K., Koffarnus, M. N., Moody, L., & Wilson, A. G. (2014) · Neuropharmacology · doi:10.1016/j.neuropharm.2013.06.013 · Cited by 386 · see citing works
Self-citationThe Behavioral Economics of Tobacco Products
Bickel, W. K., Moody, L. N., Snider, S. E., Mellis, A. M., Stein, J. S., & Quisenberry, A. J. (2017) · Routledge eBooks · doi:10.4324/9781315637938-3 · Cited by 12 · see citing works
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Bickel, W. K., Mellis, A. M., Snider, S. E., Athamneh, L. N., Stein, J. S., & Pope, D. A. (2018) · Pharmacology Biochemistry and Behavior · doi:10.1016/j.pbb.2017.09.009 · Cited by 134 · see citing works
Self-citationAddiction Biomarkers: Dimensional Approaches to Understanding Addiction
Kwako, L. E., Bickel, W. K., & Goldman, D. (2018) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2017.12.007 · Cited by 103 · see citing works
Self-citationStrickland, J. C., Lile, J. A., & Stoops, W. W. (2019) · Psychopharmacology · doi:10.1007/s00213-019-05234-y · Cited by 51 · see citing works
A systematic review and meta-analysis of delay discounting and cannabis use.
Strickland, J. C., Lee, D. C., Vandrey, R. G., & Johnson, M. W. (2020) · Experimental and Clinical Psychopharmacology · doi:10.1037/pha0000378 · Cited by 47 · see citing works
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Gilroy, S. P., Kaplan, B. A., Schwartz, L. P., Reed, D. D., & Hursh, S. R. (2021) · Journal of the Experimental Analysis of Behavior · doi:10.1002/jeab.679 · Cited by 46 · see citing works
The influence of sex and estrous cyclicity on cocaine and remifentanil demand in rats
Lacy, R. T., Austin, B. P., & Strickland, J. C. (2019) · Addiction Biology · doi:10.1111/adb.12716 · Cited by 42 · see citing works
Bickel, W. K., Crabbe, J. C., & Sher, K. J. (2018) · Alcoholism Clinical and Experimental Research · doi:10.1111/acer.13912 · Cited by 33 · see citing works
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Pritschmann, R. K., Yurasek, A. M., & Yi, R. (2021) · Behavioural Processes · doi:10.1016/j.beproc.2021.104339 · Cited by 28 · see citing works
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Hall, P. A., Bickel, W. K., Erickson, K. I., & Wagner, D. D. (2018) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.13868 · Cited by 23 · see citing works
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Self-citationOberlin, B. G., Shen, Y. I., & Kareken, D. A. (2019) · Neurotherapeutics · doi:10.1007/s13311-019-00817-1 · Cited by 12 · see citing works
HUESTIS, M., & Tyndale, R. F. (2017) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.575 · Cited by 12 · see citing works
Pericot‐Valverde, I., Yoon, J. H., & Gaalema, D. E. (2019) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2019.107740 · Cited by 11 · see citing works
Weidberg, S. E., Secades‐Villa, R., Pérez, Á. G., González‐Roz, A., & Hermida, J. R. F. (2018) · Experimental and Clinical Psychopharmacology · doi:10.1037/pha0000248 · Cited by 9 · see citing works
Naudé, G. P., Dolan, S. B., Strickland, J. C., Berry, M. S., Cox, D. J., & Johnson, M. W. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph182312637 · Cited by 8 · see citing works
Gilroy, S. P., Strickland, J. C., Naudé, G. P., Johnson, M. W., Amlung, M. T., & Reed, D. D. (2022) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2022.806944 · Cited by 8 · see citing works
Rasmussen, E. B., Camp, L., & Lawyer, S. R. (2024) · Perspectives on Behavior Science · doi:10.1007/s40614-024-00403-7 · Cited by 8 · see citing works
Campbell, K. W., Voss, A. T., Acuff, S. F., Pebley, K., Berlin, K. S., Martens, M. P., Borsari, B. E., Dennhardt, A. A., & Murphy, J. G. (2020) · Experimental and Clinical Psychopharmacology · doi:10.1037/pha0000420 · Cited by 7 · see citing works
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Grodin, E. N., Montoya, A. K., Bujarski, S., & Ray, L. A. (2020) · Addiction Biology · doi:10.1111/adb.12949 · Cited by 6 · see citing works
Delay Discounting, Dating Applications, and Risky Sexual Behavior: An Exploratory Study
Bable, R. A., & Brandt, J. A. A. (2022) · The Psychological Record · doi:10.1007/s40732-021-00506-6 · Cited by 5 · see citing works
Naudé, G. P., Strickland, J. C., Berry, M. S., Dolan, S. B., Cox, D. J., & Johnson, M. W. (2024) · Journal of the Experimental Analysis of Behavior · doi:10.1002/jeab.4223 · Cited by 2 · see citing works
Madden, G. J., McClure, S. M., & Bickel, W. K. (2019) · Springer eBooks · doi:10.1007/978-3-030-20992-6_7 · Cited by 2 · see citing works
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Bassett, D. T. (2018) · Cited by 1 · see citing works
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Strickland, J. C. (2019) · UKnowledge (University of Kentucky) · doi:10.13023/etd.2019.030 · Cited by 1 · see citing works
Epstein, L. H., Rizwan, A., Rashid, S., Bickel, W. K., & Ghanim, H. (2023) · Appetite · doi:10.1016/j.appet.2023.107160 · Cited by 1 · see citing works
Self-citationBellitti, J. S., & Fazzino, T. L. (2026) · Appetite · doi:10.1016/j.appet.2026.108450
Sheffer, C. E., Proctor, M., Foinquinos, V., Lemos, R. F., Bickel, W. K., & Fields, S. A. (2026) · doi:10.2196/preprints.92201
Self-citationNist, A. N., Tegge, A. N., Fontes, R. M., Lemos, R. F., Stein, J. S., Bickel, W. K., & Sheffer, C. E. (2026) · Addictive Behaviors · doi:10.1016/j.addbeh.2026.108683
Self-citationSheffer, C. E., Proctor, M., Foinquinos, V., Lemos, R. F., Bickel, W. K., & Fields, S. A. (2026) · JMIR Research Protocols · doi:10.2196/92201
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- Authors
- Bickel, W., Snider, S., Quisenberry, A., & Stein, J.
- Affiliations
- Addiction Recovery Research Center, Virginia Tech Carilion Research Institute Roanoke Virginia USA
- Carilion Clinic (US)
- Venue
- Clinical Pharmacology & Therapeutics
- Publisher
- Wiley
- Published
- 2016-09-19
- Volume
- 101
- Issue
- 2
- Pages
- 185-187
- ISSN
- 0009-9236 (ISSN-L)
- 1532-6535
- PMC
- PMC9812002
- OpenAlex
- W2476637292
- Cited by
- 37
- References
- 5
- Citations by year
- 2026: 4 · 2024: 3 · 2023: 2 · 2022: 2 · 2021: 4 · 2020: 4 · 2019: 9 · 2018: 6 · 2017: 3
- FWCI
- 5.62
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Clinical Pharmacology & Therapeutics (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Drug Abuse (R01DA042535, R01DA034755)
- National Cancer Institute (U19CA157345, P01CA200512)
- Topics
- Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Keywords
- abuse liability, behavioral economics, novel drugs, drug initiation, drug use prediction, substance abuse risk
- MeSH terms
- Alcohol Drinking, Alcoholic Intoxication, Humans, Substance-Related Disorders, Economics, Behavioral
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