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7 - Behavioral Economic Considerations of Novel Addictions and Nonaddictive Behavior: Research and Analytic Methods

from Part II - Clinical and Research Methods in the Addictions

Published online by Cambridge University Press:  13 July 2020

By
Derek D. Reed ,
Gideon P. Naudé ,
Brett W. Gelino  and
Michael Amlung
Edited by
Steve Sussman
Steve Sussman
Affiliation:
University of Southern California
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Summary

Behavioral economics is a subfield of behavioral psychology that integrates microeconomic principles with the experimental analysis of behavior. Decades of behavioral economic work have identified two concepts robustly related to issues of risky health decisions and behavioral addictions: discounting and operant demand. Discounting is the phenomenon wherein uncertain or delayed outcomes lose value, often resulting in myopic decisions (e.g., choosing short-term benefits of heroin use over long-term healthy behaviors). Operant demand describes organisms’ persistent efforts to maintain access to reward. Collectively, discounting and demand comprise the reinforcement pathology model of unhealthy behavior, wherein counterproductive discounting and excessive demand coalesce to render risky and unhealthy reward preferences. This reinforcement pathology model may help explain behavioral addictions, issues of dependence, and other behavioral issues. This chapter describes the history of discounting and demand, common behavioral economic tasks to derive indices of discounting and demand, the hypothetical purchasing task, and the range of applications to addictions, novel addictions, and nonaddictive behaviors in the literature, to date.

Keywords

behavioral economicsdiscountingoperant demandhypothetical purchasingaddiction
Type
Chapter
Information
The Cambridge Handbook of Substance and Behavioral Addictions , pp. 73 - 86
Publisher: Cambridge University Press
Print publication year: 2020

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References

Ainslie, G. (1975). Specious reward: A behavioral theory of impulsiveness and impulse control. Psychological Bulletin, 82(4), 463–496. doi: 10.1037/h0076860CrossRefGoogle ScholarPubMed
Amlung, M. T., Acker, J., Stojek, M. K., Murphy, J. G. & MacKillop, J. (2012). Is talk “cheap”? An initial investigation of the equivalence of alcohol purchase task performance for hypothetical and actual rewards. Alcoholism: Clinical and Experimental Research, 36(4), 716–724. https://doi.org/10.1111/j.1530-0277.2011.01656.xCrossRefGoogle ScholarPubMed
Aston, E. R., Farris, S. G., MacKillop, J. & Metrik, J. (2017). Latent factor structure of a behavioral economic marijuana demand curve. Psychopharmacology, 234(16), 2421–2429. https://doi.org/10.1007/s00213-017-4633-6CrossRefGoogle ScholarPubMed
Aston, E. R., MacKillop, J., Cassidy, R. & Metrik, J. (2015). Initial validation of a marijuana purchase task. Drug and Alcohol Dependence, 146, e212. https://doi.org/10.1016/j.drugalcdep.2014.09.044CrossRefGoogle Scholar
Aston, E. R., Metrik, J. & MacKillop, J. (2015). Further validation of a marijuana purchase task. Drug and Alcohol Dependence, 152, 32–38. https://doi.org/10.1016/j.drugalcdep.2015.04.025Google Scholar
Atchley, P. & Warden, A. C. (2012). The need of young adults to text now: Using delay discounting to assess informational choice. Journal of Applied Research in Memory and Cognition, 1(4), 229–234. doi: 10.1016/j.jarmac.2012.09.001CrossRefGoogle Scholar
Becirevic, A., Reed, D. D. & Amlung, M. (2017). An initial investigation of the effects of tanning-related cues on demand and craving for indoor tanning. Psychological Record, 67(2), 149–160. https://doi.org/10.1007/s40732-017-0246-zCrossRefGoogle Scholar
Becirevic, A., Reed, D. D., Amlung, M., et al. (2017). An initial study of behavioral addiction symptom severity and demand for indoor tanning. Experimental and Clinical Psychopharmacology, 25(5), 346–352. https://doi.org/10.1037/pha0000146CrossRefGoogle ScholarPubMed
Bickel, W. K. & Madden, G. J. (1999). A comparison of measures of relative reinforcing efficacy and behavioral economics: Cigarettes and money in smokers. Behavioural Pharmacology, 10(6–7), 627–637. https://doi.org/10.1097/00008877-199908001-00023Google Scholar
Bickel, W. K., Degrandpre, R. J. & Higgins, S. T. (1993). Behavioral economics: A novel experimental approach to the study of drug dependence. Drug and Alcohol Dependence, 33(2), 173–192. https://doi.org/10.1016/0376-8716(93)90059-YGoogle Scholar
Bickel, W. K., DeGrandpre, R. J., Higgins, S. T. & Hughes, J. R. (1990). Behavioral economics of drug self-administration. I. Functional equivalence of response requirement and drug dose. Life Sciences, 47(17), 1501–1510.CrossRefGoogle ScholarPubMed
Bickel, W. K., DeGrandpre, R. J., Hughes, J. R. & Higgins, S. T. (1991). Behavioral economics of drug self‐administration. II. A unit‐price analysis of cigarette smoking. Journal of the Experimental Analysis of Behavior, 55(2), 145–154.CrossRefGoogle Scholar
Bickel, W. K., Jarmolowicz, D. P., Mueller, E. T. & Gatchalian, K. M. (2011). The behavioral economics and neuroeconomics of reinforcer pathologies: Implications for etiology and treatment of addiction. Current Psychiatry Reports, 13(5), 406–415. https://doi.org/10.1007/s11920-011-0215-1CrossRefGoogle ScholarPubMed
Bickel, W. K., Johnson, M. W., Koffarnus, M. N., MacKillop, J. & Murphy, J. G. (2014). The behavioral economics of substance use disorders: reinforcement pathologies and their repair. Annual Review of Clinical Psychology, 10, 641–677. https://doi.org/10.1146/annurev-clinpsy-032813-153724CrossRefGoogle ScholarPubMed
Bickel, W. K., Odum, A. L. & Madden, G. J. (1999). Impulsivity and cigarette smoking: Delay discounting in current, never, and ex-smokers. Psychopharmacology, 146(4), 447–454. doi: 10.1007/PL00005490CrossRefGoogle ScholarPubMed
Borges, A. M., Kuang, J., Milhorn, H. & Yi, R. (2016). An alternative approach to calculating area-under-the-curve (AUC) in delay discounting research. Journal of the Experimental Analysis of Behavior, 106(2), 145–155. doi: 10.1002/jeab.219CrossRefGoogle ScholarPubMed
Bradshaw, C. M. & Killeen, P. R. (2012). A theory of behaviour on progressive ratio schedules, with applications in behavioural pharmacology. Psychopharmacology (Berl), 222(4), 549–564. https://doi.org/10.1007/s00213-012-2771-4CrossRefGoogle ScholarPubMed
Branch, M. N. (2006). How research in behavioral pharmacology informs behavioral science. Journal of the Experimental Analysis of Behavior, 85(3), 407–423. https://doi.org/10.1901/jeab.2006.130-04CrossRefGoogle ScholarPubMed
Broadbent, J. & Dakki, M. A. (2015). How much is too much to pay for internet access? A behavioral economic analysis of internet use. Cyberpsychology, Behavior, and Social Networking, 18(8), 457–461. https://doi.org/10.1089/cyber.2014.0367Google Scholar
Bruner, N. R. & Johnson, M. W. (2014). Demand curves for hypothetical cocaine in cocaine-dependent individuals. Psychopharmacology, 231(5), 889–897. https://doi.org/10.1007/s00213-013-3312-5CrossRefGoogle ScholarPubMed
Catania, A. C. & Reynolds, G. S. (1968). A quantitative analysis of the responding maintained by interval schedules of reinforcement. Journal of the Experimental Analysis of Behavior, 11(3S2), 327–383.CrossRefGoogle ScholarPubMed
Cheever, N. A., Rosen, L. D., Carrier, L. M. & Chavez, A. (2014). Out of sight is not out of mind: The impact of restricting wireless mobile device use on anxiety levels among low, moderate and high users. Computers in Human Behavior, 37, 290–297. doi: 10.1016/j.chb.2014.05.002Google Scholar
Chung, S. & Herrnstein, R. J. (1967). Choice and delay of reinforcement. Journal of the Experimental Analysis of Behavior, 10(1), 67–74. doi: 10.1901/jeab.1967.10-67Google Scholar
Collins, R. L., Parks, G. A. & Marlatt, G. A. (1985). Social determinants of alcohol consumption: The effects of social interaction and model status on the self-administration of alcohol. Journal of Consulting and Clinical Psychology, 53(2), 189–200. https://doi.org/10.1037/0022-006X.53.2.189Google Scholar
Collins, R. L., Vincent, P. C., Yu, J., Liu, L. & Epstein, L. H. (2014). A behavioral economic approach to assessing demand for marijuana. Experimental and Clinical Psychopharmacology, 22(3), 211–221. https://doi.org/10.1037/a0035318Google Scholar
Comer, S. D., Bickel, W. K., Yi, R., et al. (2010). Human behavioral pharmacology, past, present, and future: Symposium presented at the 50th annual meeting of the Behavioral Pharmacology Society. Behavioural Pharmacology, 21(4), 251–277. https://doi.org/10.1097/Fbp.0b013e32833bb9f8Google Scholar
Dariotis, J. K. & Johnson, M. W. (2015). Sexual discounting among high-risk youth ages 18–24: Implications for sexual and substance use risk behaviors. Experimental and Clinical Psychopharmacology, 23(1), 49–58. doi: 10.1037/a0038399Google Scholar
DeGrandpre, R. J., Bickel, W. K., Hughes, J. R. & Higgins, S. T. (1992). Behavioral economics of drug self-administration. Psychopharmacology, 108(1–2), 1–10.CrossRefGoogle ScholarPubMed
DeGrandpre, R. J., Bickel, W. K., Hughes, J. R., Layng, M. P. & Badger, G. (1993). Unit price as a useful metric in analyzing effects of reinforcer magnitude. Journal of the Experimental Analysis of Behavior, 60(3), 641–666.CrossRefGoogle Scholar
Du, W., Green, L. & Myerson, J. (2002). Cross-cultural comparisons of discounting delayed and probabilistic rewards. The Psychological Record, 52(4), 479–492.CrossRefGoogle Scholar
Epstein, L. H., Dearing, K. K. & Roba, L. G. (2010). A questionnaire approach to measuring the relative reinforcing efficacy of snack foods. Eating Behaviors, 11(2), 67–73. https://doi.org/10.1016/j.eatbeh.2009.09.006Google Scholar
Epstein, L. H., Salvy, S. J., Carr, K. A., Dearing, K. K. & Bickel, W. K. (2010). Food reinforcement, delay discounting and obesity. Physiology & Behavior, 100(5), 438–445. doi: 10.1016/j.physbeh.2010.04.029Google Scholar
Evenden, J. L. & Ryan, C. N. (1996). The pharmacology of impulsive behaviour in rats: The effects of drugs on response choice with varying delays of reinforcement. Psychopharmacology, 128(2), 161–170. doi: 10.1007/s002130050121CrossRefGoogle ScholarPubMed
Fagerström, K. O. (1978). Measuring degree of physical dependence to tobacco smoking with reference to individualization of treatment. Addictive Behaviors, 3(3–4), 235–241. https://doi.org/10.1016/0306-4603(78)90024-2Google Scholar
Felton, M. & Lyon, D. O. (1966). The post‐reinforcement pause. Journal of the Experimental Analysis of Behavior, 9(2), 131–134.CrossRefGoogle ScholarPubMed
Few, L. R., Acker, J., Murphy, C. & MacKillop, J. (2012). Temporal stability of a cigarette purchase task. Nicotine & Tobacco Research, 14(6), 761–765. https://doi.org/10.1093/ntr/ntr222Google Scholar
Field, M., Santarcangelo, M., Sumnall, H., Goudie, A. & Cole, J. (2006). Delay discounting and the behavioural economics of cigarette purchases in smokers: The effects of nicotine deprivation. Psychopharmacology, 186(2), 255–263. https://doi.org/10.1007/s00213-006-0385-4CrossRefGoogle ScholarPubMed
Gray, J. C., Amlung, M. T., Palmer, A. A. & MacKillop, J. (2016). Syntax for calculation of discounting indices from the monetary choice questionnaire and probability discounting questionnaire. Journal of the Experimental Analysis of Behavior, 106(2), 156–163. doi: 10.1002/jeab.221Google Scholar
Green, L., Myerson, J., Shah, A. K., Estle, S. J. & Holt, D. D. (2007). Do adjusting-amount and adjusting-delay procedures produce equivalent estimates of subjective value in pigeons? Journal of the Experimental Analysis of Behavior, 87(3), 337–347. doi: 10.1901/jeab.2007.37-06Google Scholar
Greenwald, M. K. & Hursh, S. R. (2006). Behavioral economic analysis of opioid consumption in heroin-dependent individuals: Effects of unit price and pre-session drug supply. Drug and Alcohol Dependence, 85(1), 35–48. https://doi.org/http://dx..org/10.1016/j.drugalcdep.2006.03.007CrossRefGoogle ScholarPubMed
Griffiths, R. R., Bigelow, G. E. & Henningfield, J. E. (1980). Similarities in animal and human drug-taking behavior. In Mello, N. K. (Ed.), Advances in Substance Abuse (Volume 1). Greenwich, CT: JAI Press, pp. 1–90.Google Scholar
Griffiths, R. R., Brady, J. V. & Bradford, L. D. (1979). Predicting the abuse liability of drugs with animal drug self-administration procedures: Psychomotor stimulants and hallucinogens. In Thompson, T. & Dews, P. B. (Eds.), Advances in Behavioral Pharmacology (Volume 2). New York: Academic Press, pp. 163–208.Google Scholar
Heatherton, T. F., Kozlowski, L. T., Frecker, R. C. & Fagerström, K. O. (1991). The Fagerström test for nicotine dependence: A revision of the Fagerström Tolerance Questionnaire. British Journal of Addiction, 86(9), 1119–1127. https://doi.org/10.1111/j.1360-0443.1991.tb01879.xCrossRefGoogle ScholarPubMed
Henley, A. J., DiGennaro Reed, F. D., Kaplan, B. A. & Reed, D. D. (2016). Quantifying efficacy of workplace reinforcers: An application of behavioral economic demand to evaluate hypothetical work performance. Translational Issues in Psychological Science, 2(2), 174–183. https://doi.org/10.1037/tps0000068CrossRefGoogle Scholar
Herrmann, E. S., Hand, D. J., Johnson, M. W., Badger, G. J. & Heil, S. H. (2014). Examining delay discounting of condom-protected sex among opioid-dependent women and non-drug-using control women. Drug and Alcohol Dependence, 144, 53–60. doi: 10.1016/j.drugalcdep.2014.07.026Google Scholar
Herrnstein, R. J. (1971). Quantitative hedonism. Journal of Psychiatric Research, 8(3–4), 399–412. https://doi.org/Doi 10.1016/0022-3956(71)90033-1Google Scholar
Hodos, W. (1961). Progressive ratio as a measure of reward strength. Science, 134(3483), 943–944. Retrieved from www.ncbi.nlm.nih.gov/pubmed/13714876Google Scholar
Hurlbut, S. C. & Sher, K. J. (1992). Assessing alcohol problems in college students. Journal of the American College Health Association, 41(2), 49–58. https://doi.org/10.1080/07448481.1992.10392818Google Scholar
Hursh, S. R. (1980). Economic concepts for the analysis of behavior. Journal of the Experimental Analysis of Behavior, 34(2), 219–238. https://doi.org/http://dx..org/10.1901/jeab.1980.34-219Google Scholar
Hursh, S. R. (1984). Behavioral economics. Journal of the Experimental Analysis of Behavior, 42(3), 435–452. https://doi.org/http://dx..org/10.1901/jeab.1984.42-435Google Scholar
Hursh, S. R. (1993). Behavioral economics of drug self-administration – An introduction. Drug and Alcohol Dependence, 33(2), 165–172. https://doi.org/10.1016/0376-8716(93)90058-XCrossRefGoogle ScholarPubMed
Hursh, S. R. (2014). Behavioral economics and analysis of consumption and choice. In McSweeney, F. K. & Murphy, E. S. (Eds.), The Wiley Blackwell Handbook of Classical and Operant Conditioning. West Sussex, UK: John Wiley & Sons, pp. 275–305.Google Scholar
Hursh, S. R. & Roma, P. G. (2013). Behavioral economics and empirical public policy. Journal of the Experimental Analysis of Behavior, 99(1), 98–124. https://doi.org/10.1007/s00213-008-1120-0Google Scholar
Hursh, S. R. & Silberberg, A. (2008). Economic demand and essential value. Psychological Review, 115(1), 186–198. https://doi.org/10.1037/0033-295x115.1.186CrossRefGoogle ScholarPubMed
Hursh, S. R., Madden, G. J., Spiga, R., DeLeon, I. G. & Francisco, M. T. (2013). The Translational Utility of Behavioral Economics: The Experimental Analysis of Consumption and Choice. Washington, DC: American Psychological Association. https://doi.org/http://dx..org/10.1037/13938-008Google Scholar
Jacobs, E. A. & Bickel, W. K. (1999). Modeling drug consumption in the clinic using simulation procedures: Demand for heroin and cigarettes in opioid-dependent outpatients. Experimental and Clinical Psychopharmacology, 7(4), 412–426. https://doi.org/10.1037//1064-1297.7.4.412CrossRefGoogle ScholarPubMed
Jarmolowicz, D. P. & Lattal, K. A. (2010). On distinguishing progressively increasing response requirements for reinforcement. The Behavior Analyst, 33(1), 119–125.Google Scholar
Jarmolowicz, D. P. & Schneider, T. D. (2020). Behavioral economics and addictive disorders. In Sussman, S. (Ed.) The Cambridge Handbook of Substance and Behavioral Addictions, Cambridge, UK: Cambridge University Press, pp. 12–22.Google Scholar
Jarmolowicz, D. P., Bickel, W. K. & Gatchalian, K. M. (2013). Alcohol-dependent individuals discount sex at higher rates than controls. Drug and Alcohol Dependence, 131(3), 320–323. doi: 10.1016/j.drugalcdep.2012.12.014Google Scholar
Jarmolowicz, D. P., Landes, R. D., Christensen, D. R., et al. (2014). Discounting of money and sex: Effects of commodity and temporal position in stimulant-dependent men and women. Addictive Behaviors, 39(11), 1652–1657. doi: 10.1016/j.addbeh.2014.04.026CrossRefGoogle ScholarPubMed
Jarmolowicz, D. P., Lemley, S. M., Mateos, A. & Sofis, M. J. (2016). A multiple-stimulus-without-replacement assessment for sexual partners: Purchase task validation. Journal of Applied Behavior Analysis, 49(3), 723–729. https://doi.org/10.1002/jaba.313Google Scholar
Jarmolowicz, D. P., Reed, D. D. & Bickel, W. K. (2015). Neuroeconomics: Implications for understanding and treating addictive behavior. In Feldstein Ewing, S. W. & Filbey, F. M. (Eds.), Neuroimaging and Psychosocial Addiction Treatment: An Integrative Guide for Researchers and Clinicians. New York, NY: Palgrave Macmillan, pp. 141–157.Google Scholar
Jarmolowicz, D. P., Reed, D. D., Bruce, A. S., et al. (2016). Using EP50 to forecast treatment adherence in individuals with multiple sclerosis. Behavioural Processes, 132, 94–99. doi: 10.1016/j.beproc.2016.09.003Google Scholar
Johnson, M. W. & Bickel, W. K. (2008). An algorithm for identifying nonsystematic delay-discounting data. Experimental and Clinical Psychopharmacology, 16(3), 264–274. doi:10.1037/1064-1297.16.3.264Google Scholar
Johnson, M. W. & Bruner, N. R. (2012). The Sexual Discounting Task: HIV risk behavior and the discounting of delayed sexual rewards in cocaine dependence. Drug and Alcohol Dependence, 123(1–3), 15–21. https://doi.org/10.1016/j.drugalcdep.2011.09.032Google Scholar
Johnson, M. W., Herrmann, E. S., Sweeney, M. M., LeComte, R. S. & Johnson, P. S. (2017). Cocaine administration dose-dependently increases sexual desire and decreases condom use likelihood: The role of delay and probability discounting in connecting cocaine with HIV. Psychopharmacology, 234(4), 599–612. doi: 10.1007/s00213-016-4493-5Google Scholar
Junco, R. & Cotten, S. R. (2012). No A 4 U: The relationship between multitasking and academic performance. Computers & Education, 59(2), 505–514. doi: 10.1016/j.compedu.2011.12.023CrossRefGoogle Scholar
Kaplan, B. A., Amlung, M., Reed, D. D., et al. (2016). Automating scoring of delay discounting for the 21- and 27-item monetary choice questionnaires. The Behavior Analyst, 39(2), 293–304. doi: 10.1007/s40614-016-0070-9Google Scholar
Kaplan, B. A., Foster, R. N. S., Reed, D. D., et al. (2018). Understanding alcohol motivation using the alcohol purchase task: A methodological systematic review. Drug and Alcohol Dependence, 191, 117–140. https://doi.org/10.1016/J.DRUGALCDEP.2018.06.029Google Scholar
Kaplan, B. A., Gelino, B. W. & Reed, D. D. (2018). A behavioral economic approach to green consumerism: Demand for reusable shopping bags. Behavior and Social Issues, 27, 20–30. https://doi.org/10.5210/bsi.v.27i0.8003Google Scholar
Kirby, K. N. & Maraković, N. N. (1996). Delay-discounting probabilistic rewards: Rates decrease as amounts increase. Psychonomic Bulletin & Review, 3(1), 100–104. doi: 10.3758/BF03210748Google Scholar
Kirby, K. N., Petry, N. M. & Bickel, W. K. (1999). Heroin addicts have higher discount rates for delayed rewards than non-drug-using controls. Journal of Experimental Psychology: General, 128(1), 78–87. doi: 10.1037/0096-3445.128.1.78Google Scholar
Koffarnus, M. N. & Bickel, W. K. (2014). A 5-trial adjusting delay discounting task: Accurate discount rates in less than one minute. Experimental and Clinical Psychopharmacology, 22(3), 222–228. doi: 10.1037/a0035973Google Scholar
Kwon, M., Lee, J., Won, W., et al. (2013). Development and validation of a smartphone addiction scale (SAS). PLoS ONE, 8(2), 7.Google Scholar
Lawyer, S. R. (2008). Probability and delay discounting of erotic stimuli. Behavioural Processes, 79(1), 36–42. doi: 10.1016/j.beproc.2008.04.009CrossRefGoogle ScholarPubMed
Lea, S. E. (1976). Titration of schedule parameters by pigeons. Journal of the Experimental Analysis of Behavior, 25(1), 43–54. doi: 10.1901/jeab.1976.25-43Google Scholar
Lemley, S. M., Kaplan, B. A., Reed, D. D., Darden, A. C. & Jarmolowicz, D. P. (2016). Reinforcer pathologies: Predicting alcohol related problems in college drinking men and women. Drug and Alcohol Dependence, 167, 57–66. https://doi.org/10.1016/j.drugalcdep.2016.07.025CrossRefGoogle ScholarPubMed
Leslie, J. C. (2003). A history of reinforcement: The role of reinforcement schedules in behavior pharmacology. The Behavior Analyst Today, 4(1), 98–108. http://dx.doi.org/10.1037/h0100017Google Scholar
MacKillop, J. & Tidey, J. W. (2011). Cigarette demand and delayed reward discounting in nicotine-dependent individuals with schizophrenia and controls: An initial study. Psychopharmacology, 216(1), 91–99. https://doi.org/10.1007/s00213-011-2185-8Google Scholar
MacKillop, J., Murphy, J. G., Ray, L. A., et al. (2008). Further validation of a cigarette purchase task for assessing the relative reinforcing efficacy of nicotine in college smokers. Experimental and Clinical Psychopharmacology, 16(1), 57–65. https://doi.org/10.1037/1064-1297.16.1.57Google Scholar
Madden, G. J. & Bickel, W. K. (1999). Abstinence and price effects on demand for cigarettes: A behavioral-economic analysis. Addiction, 94(4), 577–588. https://doi.org/10.1046/j.1360-0443.1999.94457712.xGoogle Scholar
Madden, G. J. & Bickel, W. K. (2010). Impulsivity: The Behavioral and Neurological Science of Discounting (1st edition). Washington, DC: American Psychological Association.Google Scholar
Madden, G. J., Petry, N. M. & Johnson, P. S. (2009). Pathological gamblers discount probabilistic rewards less steeply than matched controls. Experimental and Clinical Psychopharmacology, 17(5), 283–290. https://doi.org/10.1037/A0016806Google Scholar
Mazur, J. E. (1987). An adjusting procedure for studying delayed reinforcement. In Commons, M. L., Mazur, J. E., Nevin, J. A. & Rachlin, H. (Eds.), Quantitative Analysis of Behavior: Volume 5. The Effect of Delay and Intervening Events on Reinforcement Value. Hillsdale, NJ: Erlbaum, pp. 55–73. Retrieved from https://search.proquest.com/docview/617226485?accountid=14556Google Scholar
Metrik, J., Aston, E. R., Kahler, C. W., et al. (2016). Cue-elicited increases in incentive salience for marijuana: Craving, demand, and attentional bias. Drug and Alcohol Dependence, 167, 82–88. https://doi.org/10.1016/j.drugalcdep.2016.07.027Google Scholar
Mischel, W. & Ebbesen, E. B. (1970). Attention in delay of gratification. Journal of Personality and Social Psychology, 16(2), 329–337. doi: 10.1037/h0029815CrossRefGoogle Scholar
Mischel, W., Ebbesen, E. B. & Raskoff Zeiss, A. (1972). Cognitive and attentional mechanisms in delay of gratification. Journal of Personality and Social Psychology, 21(2), 204–218. doi: 10.1037/h0032198Google Scholar
Mischel, W., Shoda, Y. & Peake, P. K. (1988). The nature of adolescent competencies predicted by preschool delay of gratification. Journal of Personality and Social Psychology, 54(4), 687–696. doi: 10.1037/0022-3514.54.4.687Google Scholar
Mischel, W., Shoda, Y. & Rodriguez, M. L. (1989). Delay of gratification in children. Science, 244(4907), 933–938. doi: 10.1126/science.2658056Google Scholar
Mulhauser, K., Short, E. M. & Weinstock, J. (2018). Development and psychometric evaluation of the pornography purchase task. Addictive Behaviors, 84(December 2017), 207–214. https://doi.org/10.1016/j.addbeh.2018.04.016Google Scholar
Murphy, J. G. & MacKillop, J. (2006). Relative reinforcing efficacy of alcohol among college student drinkers. Experimental and Clinical Psychopharmacology, 14(2), 219–227. https://doi.org/10.1037/1064-1297.14.2.219CrossRefGoogle ScholarPubMed
Murphy, J. G., MacKillop, J., Skidmore, J. R. & Pederson, A. A. (2009). Reliability and validity of a demand curve measure of alcohol reinforcement. Experimental and Clinical Psychopharmacology, 17(6), 396–404. https://doi.org/10.1037/a0017684Google Scholar
Murphy, J. G., MacKillop, J., Tidey, J. W., Brazil, L. A. & Colby, S. M. (2011). Validity of a demand curve measure of nicotine reinforcement with adolescent smokers. Drug and Alcohol Dependence, 113(2–3), 207–214. https://doi.org/10.1016/J.DRUGALCDEP.2010.08.004Google Scholar
Myerson, J. & Green, L. (1995). Discounting of delayed rewards: Models of individual choice. Journal of the Experimental Analysis of Behavior, 64(3), 263–276. doi: 10.1901/jeab.1995.64-263CrossRefGoogle ScholarPubMed
Myerson, J., Baumann, A. A. & Green, L. (2014). Discounting of delayed rewards: (A)theoretical interpretation of the Kirby questionnaire. Behavioural Processes, 107, 99–105. doi: 10.1016/j.beproc.2014.07.021CrossRefGoogle ScholarPubMed
Myerson, J., Green, L. & Warusawitharana, M. (2001). Area under the curve as a measure of discounting. Journal of the Experimental Analysis of Behavior, 76(2), 235–243. doi: 10.1901/jeab.2001.76-235Google Scholar
Navarick, D. J. & Fantino, E. (1972). Interresponse time as a factor in choice. Psychonomic Science, 27(1), 4–6. doi: 10.3758/BF03328868CrossRefGoogle Scholar
O'Donnell, S. & Epstein, L. H. (2019). Smartphones are more reinforcing than food for students. Addictive Behaviors, 90, 124–133.Google Scholar
Odum, A. L., Baumann, A. A. L. & Rimington, D. D. (2006). Discounting of delayed Hypothetical money and food: Effects of amount. Behavioural Processes, 73(3), 278–284. doi: 10.1016/j.beproc.2006.06.008Google Scholar
Petry, N. M. (2000). Effects of increasing income on polydrug use: A comparison of heroin, cocaine and alcohol abusers. Addiction, 95(5), 705–717. https://doi.org/10.1046/j.1360-0443.2000.9557056.xCrossRefGoogle ScholarPubMed
Petry, N. M. (2001a). A behavioral economic analysis of polydrug abuse in alcoholics: Asymmetrical substitution of alcohol and cocaine. Drug and Alcohol Dependence, 62(1), 31–39. https://doi.org/10.1016/S0376-8716(00)00157-5CrossRefGoogle ScholarPubMed
Petry, N. M. (2001b). The effects of housing costs on polydrug abuse patterns: A comparison of heroin, cocaine, and alcohol abusers. Experimental and Clinical Psychopharmacology, 9(1), 47–58. https://doi.org/10.1037/1064-1297.9.1.47Google Scholar
Petry, N. M. & Bickel, W. K. (1998). Polydrug abuse in heroin addicts: A behavioral economic analysis. Addiction, 93(3), 321–335. https://doi.org/10.1046/j.1360-0443.1998.9333212.xGoogle Scholar
Petry, N. M. & Bickel, W. K. (1999). A behavioral economic analysis of polydrug abuse in heroin addicts. In Chaloupka, F. J., Grossman, M., Bickel, W. K. & Saffer, H. (Eds.), The Economic Analysis of Substance Use and Abuse: An Integration of Econometrics and Behavioral Economic Research. Chicago, IL: University of Chicago Press, pp. 213–250. https://doi.org/10.1046/j.1360-0443.1998.9333212.xGoogle Scholar
Pickover, A. M., Messina, B. G., Correia, C. J., Garza, K. B. & Murphy, J. G. (2016). A behavioral economic analysis of the nonmedical use of prescription drugs among young adults. Experimental and Clinical Psychopharmacology, 24(1), 38–47. https://doi.org/10.1037/pha0000052CrossRefGoogle ScholarPubMed
Pope, H. G., Kean, J., Nash, A., et al. (2010). A diagnostic interview module for anabolic-androgenic steroid dependence: Preliminary evidence of reliability and validity. Experimental and Clinical Psychopharmacology, 18(3), 203–213. https://doi.org/10.1037/a0019370Google Scholar
Rachlin, H. (2006). Notes on discounting. Journal of the Experimental Analysis of Behavior, 85(3), 425–435. doi: 10.1901/jeab.2006.85-05Google Scholar
Rachlin, H. & Green, L. (1972). Commitment, choice and self-control. Journal of the Experimental Analysis of Behavior, 17(1), 15–22. doi: 10.1901/jeab.1972.17-15Google Scholar
Rachlin, H., Raineri, A. & Cross, D. (1991). Subjective probability and delay. Journal of the Experimental Analysis of Behavior, 55(2), 233–244. doi: 10.1901/jeab.1991.55-233Google Scholar
Reed, D. D. (2015). Ultra-violet indoor tanning addiction: A reinforcer pathology interpretation. Addictive Behaviors, 41, 247–251. https://doi.org/10.1016/j.addbeh.2014.10.026Google Scholar
Reed, D. D., Becirevic, A., Atchley, P., Kaplan, B. A. & Liese, B. S. (2016a). Validation of a novel delay discounting of text messaging questionnaire. The Psychological Record, 66(2), 253–261. doi: 10.1007/s40732-016-0167-2Google Scholar
Reed, D. D., Kaplan, B. A. & Becirevic, A. (2015). Basic research on the behavioral economics of reinforcer value. In Autism Service Delivery: Bridging the Gap Between Science and Practice. Springer Science + Business Media, pp. 279–306. https://doi.org/10.1007/978-1-4939-2656-5_10CrossRefGoogle Scholar
Reed, D. D., Kaplan, B. A., Becirevic, A., Roma, P. G. & Hursh, S. R. (2016b). Toward quantifying the abuse liability of ultraviolet tanning: A behavioral economic approach to tanning addiction. Journal of the Experimental Analysis of Behavior, 106(1), 93–106. https://doi.org/10.1002/jeab.216Google Scholar
Reed, D. D., Kaplan, B. A., Roma, P. G. & Hursh, S. R. (2014). Inter-method reliability of progression sizes in a hypothetical purchase task: Implications for empirical public policy. Psychological Record, 64(4), 671–679. https://doi.org/10.1007/s40732-014-0076-1Google Scholar
Reed, D. D., Naudé, G. P., Salzer, A. R., et al. (2020). Behavioral economic measurement of cigarette demand: A descriptive review of published approaches to the Cigarette Purchase Task. Experimental and Clinical Psychopharmacology. Advance online publication. doi: 10.1037/pha0000347CrossRefGoogle Scholar
Richards, J. B., Mitchell, S. H., de Wit, H. & Seiden, L. S. (1997). Determination of discount functions in rats with an adjusting-amount procedure. Journal of the Experimental Analysis of Behavior, 67(3), 353-366. doi: 10.1901/jeab.1997.67-353Google Scholar
Richards, J. B., Zhang, L., Mitchell, S. H. & de Wit, H. (1999). Delay or probability discounting in a model of impulsive behavior: Effect of alcohol. Journal of the Experimental Analysis of Behavior, 71(2), 121–143. doi: 10.1901/jeab.1999.71-121Google Scholar
Roberts, J. A., Petnji Yaya, L. H. & Manolis, C. (2014). The invisible addiction: Cell-phone activities and addiction among male and female college students. Journal of Behavioral Addictions, 3(4), 254–265. doi: 10.1556/JBA.3.2014.015Google Scholar
Ross, E. & Kenakin, T. (2001). Pharmacodynamics – Mechanisms of drug action and the relationship between drug concentration and effect. In Hardman, J. G. & Gilman, A. J. (Eds.), The Pharmacological Basis of Therapeutics (10th edition). London: McGraw.Google Scholar
Samuelson, P. A. (1937). A note on measurement of utility. Review of Economic Studies, 4, 155–161.Google Scholar
Saville, B. K., Gisbert, A., Kopp, J. & Telesco, C. (2010). Internet addiction and delay discounting in college students. Psychological Record, 60(2), 273–286.Google Scholar
Shoda, Y., Mischel, W. & Peake, P. K. (1990). Predicting adolescent cognitive and self-regulatory competencies from preschool delay of gratification: Identifying diagnostic conditions. Developmental Psychology, 26(6), 978–986. doi: 10.1037/0012-1649.26.6.978CrossRefGoogle Scholar
Skinner, B. F. (1953). Science and Human Behavior. Macmillan: Oxford.Google Scholar
Skinner, B. F. (1961). What is the experimental analysis of behavior? Journal of the Experimental Analysis of Behavior, 9(3), 213–218. https://doi.org/http://dx.doi.org/10.1037/11324-008Google Scholar
Sobell, L. C. & Sobell, M. B. (1992). Timeline follow-back. In Litten, R. Z. & Allen, J. P. (Eds.), Measuring Alcohol Consumption. Totowa, NJ: Humana Press, pp. 41–72. https://doi.org/10.1007/978-1-4612-0357-5_3CrossRefGoogle Scholar
Sobell, M. B. & Sobell, L. C. (1973). Individualized behavior therapy for alcoholics – Republished. Behavior Therapy, 4(1), 49–72. https://doi.org/https://doi.org/10.1016/S0005-7894(73)80074-7Google Scholar
Stafford, D., LeSage, M. G. & Glowa, J. R. (1998). Progressive-ratio schedules of drug delivery in the analysis of drug self-administration: A review. Psychopharmacology, 139(3), 169–184. https://doi.org/10.1007/s002130050702Google Scholar
Strickland, J. C., Lile, J. A. & Stoops, W. W. (2017). Unique prediction of cannabis use severity and behaviors by delay discounting and behavioral economic demand. Behavioural Processes, 140, 33–40. doi: 10.1016/j.beproc.2017.03.017Google Scholar
Strickland, J. C., Lile, J. A., Rush, C. R. & Stoops, W. W. (2016). Comparing exponential and exponentiated models of drug demand in cocaine users. Experimental and Clinical Psychopharmacology, 24(6), 447–455. https://doi.org/10.1037/pha0000096Google Scholar
Strickland, J. C., Reynolds, A. R. & Stoops, W. W. (2016). Regulation of cocaine craving by cognitive strategies in an online sample of cocaine users. Psychology of Addictive Behaviors, 30(5), 607–612. https://doi.org/10.1037/adb0000180CrossRefGoogle Scholar
Vincent, P. C., Collins, R. L., Liu, L., et al. (2017). The effects of perceived quality on behavioral economic demand for marijuana: A web-based experiment. Drug and Alcohol Dependence, 170, 174–180. https://doi.org/10.1016/j.drugalcdep.2016.11.013CrossRefGoogle ScholarPubMed
Weinstock, J., Mulhauser, K., Oremus, E. G. & D’Agostino, A. R. (2016). Demand for gambling: Development and assessment of a gambling purchase task. International Gambling Studies, 16(2), 316–327. https://doi.org/10.1080/14459795.2016.1182570CrossRefGoogle Scholar
Winger, G., Hursh, S. R., Casey, K. L. & Woods, J. H. (2002). Relative reinforcing strength of three methyl-d-aspartate antagonists with different onsets of action. Journal of Pharmacology and Experimental Therapeutics, 301(2), 690–697.CrossRefGoogle ScholarPubMed
Yoon, J. H. & Higgins, S. T. (2008). Turning k on its head: Comments on use of an ED50 in delay discounting research. Drug and Alcohol Dependence, 95(1–2), 169–172. doi: 10.1016/j.drugalcdep.2007.12.011Google Scholar
Yurasek, A. M., Murphy, J. G., Clawson, A. H., Dennhardt, A. A. & MacKillop, J. (2013). Smokers report greater demand for alcohol on a behavioral economic purchase task. Journal of Studies on Alcohol and Drugs, 74(4), 626–34. https://doi.org/http://dx.doi.org/10.15288/jsad.2013.74.626Google Scholar

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