The Psychological Record

, Volume 66, Issue 2, pp 253–261 | Cite as

Validation of a Novel Delay Discounting of Text Messaging Questionnaire

  • Derek D. Reed
  • Amel Becirevic
  • Paul Atchley
  • Brent A. Kaplan
  • Bruce S. Liese
Original Article


Using cellular phones for text messaging has become a ubiquitous mode of communication in today’s American culture. Text messaging has become a primary source of relationship development and maintenance for many Americans, especially youth. Researchers have begun classifying excessive reliance on text messaging as an addictive behavior, which may lead to risky activities such as texting while driving. This study interprets texting dependence within a behavioral economics framework of addictive behavior and proposes a novel Delay Discounting of Texting Questionnaire (DDTQ). The DDTQ involves a hypothetical scenario wherein the respondent chooses between paying for an immediate text now and waiting to receive a free text message in the future. We validated the DDTQ using a relatively diverse crowdsourced sample from Amazon Mechanical Turk. The DDTQ demonstrated expected degrees of systematic discounting and yielded higher rates of delay discounting with reward values in a within-subjects evaluation of the magnitude effect. Finally, the DDTQ successfully discriminated different profiles of possible text-messaging dependence. Collectively, these findings suggest the DDTQ is a viable task for use in studying the behavioral economics of possible text-messaging dependence.


Text message Technology Cellular phone Delay discounting Behavioral economics Amazon Mechanical Turk 


Compliance with Ethical Standards

Conflict of Interest


Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.


  1. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: Author.Google Scholar
  2. 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, 229–234. doi: 10.1016/j.jarmac.2012.09.001.CrossRefGoogle Scholar
  3. Atchley, P., Hadlock, C., & Lane, S. (2012). Stuck in the 70s: The role of social norms in distracted driving. Accident Analysis & Prevention, 40, 279–284. doi: 10.1016/j.aap.2012.01.026.CrossRefGoogle Scholar
  4. Bickel, W. K., Pitcock, J. A., Yi, R., & Angtuaco, E. J. (2009). Congruence of BOLD response across intertemporal choice conditions: Fictive and real money gains and losses. The Journal of Neuroscience, 29, 8839–8846. doi: 10.1523/JNEUROSCI.5319-08.2009.CrossRefPubMedPubMedCentralGoogle Scholar
  5. Bickel, W. K., Jarmolowicz, D. P., Mueller, E. T., & Gatchalian, K. M. (2011a). The behavioral economics and neuroeconomics of reinforcer pathologies: Implications for etiology and treatment of addiction. Current Psychiatry Report, 13, 406–415. doi: 10.1007/s11920-011-0215-1.CrossRefGoogle Scholar
  6. Bickel, W. K., Yi, R., Landes, R. D., Hill, P. F., & Baxter, C. (2011b). Remember the future: Working memory training decreases delay discounting among stimulant addicts. Biological Psychiatry, 69, 260–265. doi: 10.1016/j.biopsych.2010.08.017.CrossRefPubMedPubMedCentralGoogle Scholar
  7. Bickel, W. K., Jarmolowicz, D. P., MacKillop, J., Epstein, L. H., Carr, K., Mueller, E. T., Waltz, T. J., & Shaffer, H. J. (2012). The behavioral economics of reinforcement pathologies: Novel approaches to addictive disorders. In APA addiction syndrome handbook, Vol. 2: Recovery, prevention, and other issues (pp. 333–363). Washington, DC: American Psychological Association.CrossRefGoogle Scholar
  8. 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. doi: 10.1146/annurev-clinpsy-032813-153724.CrossRefPubMedPubMedCentralGoogle Scholar
  9. Billieux, J., van der Linden, M., D’Acremont, M., Ceschi, G., & Zermatten, A. (2007). Does impulsivity relate to perceived dependence on and actual use of the mobile phone? Applied Cognitive Psychology, 21, 527–537. doi: 10.1002/acp.1289.CrossRefGoogle Scholar
  10. Dai, Z., Grace, R. C., & Kemp, S. (2009). Reward contrast in delay and probability discounting. Learning & Behavior, 37, 281–288. doi: 10.3758/LB.37.3.281.CrossRefGoogle Scholar
  11. Estle, S. J., Green, L., Myerson, J., & Holt, D. D. (2006). Differential effects of amount on temporal and probability discounting of gains and losses. Memory and Cognition, 34, 914–928.CrossRefPubMedGoogle Scholar
  12. Green, R. M., & Lawyer, S. R. (2014). Steep delay and probability discoutning of potentially real versus hypothetical cigarettes (but not money) among smokers. Behavioural Processes, 108, 50–56. doi: 10.1016/j.beproc.2014.09.008.CrossRefPubMedGoogle Scholar
  13. Green, L., & Myerson, J. (2004). A discounting framework for choice with delayed and probabilistic rewards. Psychological Bulletin, 130, 769–792. doi: 10.1037/0033-2909.130.5.769.CrossRefPubMedPubMedCentralGoogle Scholar
  14. Green, L., Myerson, J., & Ostaszewski, P. (1999). Amount of reward has opposite effects on the discounting of delayed and probabilistic outcomes. Journal of Experimental Psychology Learning Memory and Cognition, 25, 418–427.CrossRefGoogle Scholar
  15. Green, L., Myerson, J., Holt, D. D., Slevin, J. R., & Estle, S. J. (2004). Discounting of delayed food rewards in pigeons and rats: Is there a magnitude effect? Journal of the Experimental Analysis of Behavior, 81, 39–50. doi: 10.1901/jeab.2004.81-39.CrossRefPubMedPubMedCentralGoogle Scholar
  16. 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.2014.07.026.CrossRefPubMedGoogle Scholar
  17. Igarashi, T., Motoyoshi, T., Takai, J., & Yoshida, T. (2005, April). The text messaging addiction scale: Factor structure, reliability, and validity. Paper presented at the sixth biennial conference of the Asian Association of Social Psychology, Wellington, New Zealand.Google Scholar
  18. Igarashi, T., Motoyoshi, T., Takai, J., & Yoshida, T. (2008). No mobile, no life: Self-perception and text message dependency among Japanese high school students. Computers in Human Behavior, 24, 2311–2324. doi: 10.1016/j.chb.2007.12.001.CrossRefGoogle Scholar
  19. Jarmolowicz, D. P., Reed, D. D., & Bickel, W. K. (2015). Neuroeconomics: Implications for understanding and treating addictive behavior. In S. W. Feldstein Ewing, K. Witkiewitz, & F. M. Filbey (Eds.), Neuroimaging and psychosocial addiction treatment: An integrative guide for researchers and clinicians (pp. 141–157). Houndmills, England: Palgrave Macmillan.Google Scholar
  20. Johnson, M. W., & Bickel, W. K. (2002). Within-subject comparison of real and hypothetical money rewards in delay discounting. Journal of the Experimental Analyses of Behavior, 77, 129–146. doi: 10.1901/jeab.2002.77-129.CrossRefGoogle Scholar
  21. Johnson, M. W., & Bickel, W. K. (2008). An algorithm for identifying nonsystematic delay-discounting data. Experimental and Clinical Psychopharmacology, 16, 264–274. doi: 10.1037/1064-1297.16.3.264.CrossRefPubMedPubMedCentralGoogle Scholar
  22. 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, 15–21. doi: 10.1016/j.drugalcdep.2011.09.032.CrossRefPubMedPubMedCentralGoogle Scholar
  23. Johnson, M. W., & Bruner, N. R. (2013). Test–retest reliability and gender differences in the sexual discounting task among cocaine-dependent individuals. Experimental and Clinical Psychopharmacology, 21, 277–286. doi: 10.1037/a0033071.CrossRefPubMedGoogle Scholar
  24. Johnson, M. W., Johnson, P. S., Herrmann, E. S., & Sweeney, M. M. (2015). Delay and probability discounting of sexual and monetary outcomes in individuals with cocaine use disorders and matched controls. PLoS ONE, 10, e0128641. doi: 10.1371/journal.pone.0128641.CrossRefPubMedPubMedCentralGoogle Scholar
  25. Kaplan, B. A., Reed, D. D., & McKerchar, T. L. (2014). Using a visual analogue scale to assess delay, social, and probability discounting of an environmental loss. The Psychological Record, 64, 261–269. doi: 10.1007/s40732-014-0041-z.CrossRefGoogle Scholar
  26. Koffarnus, M. N., Jarmolowicz, D. P., Mueller, E. T., & Bickel, W. K. (2013). Changing delay discounting in the light of the competing neurobehavioral decision systems theory: A review. Journal of the Experimental Analysis of Behavior, 99, 32–57. doi: 10.1002/jeab.2.CrossRefPubMedPubMedCentralGoogle Scholar
  27. Lagorio, C. H., & Madden, G. J. (2005). Delay discounting of real and hypothetical rewards: III. Steady-state assessments, forced-choice trials, and all real rewards. Behavioural Processes, 69, 173–187. doi: 10.1016/j.beproc.2005.02.003.CrossRefPubMedGoogle Scholar
  28. Lenhart, A., Smith, A., Anderson, M., Duggan, M., & Perrin, A. (2015). Teens, technology and friendships. Pew Research Center, Retrieved from Scholar
  29. MacKillop, J., Amlung, M. T., Few, L. R., Ray, L. A., Sweet, L. H., & Munafò, M. R. (2011). Delayed reward discounting and addictive behavior: A meta-analysis. Psychopharmacology, 216, 305–321. doi: 10.1007/s00213-011-2229-0.CrossRefPubMedPubMedCentralGoogle Scholar
  30. Madden, G. J., & Bickel, W. K. (2010). Impulsivity: The behavioral and neurological science of discounting. Washington, DC: American Psychological Association.CrossRefGoogle Scholar
  31. Madden, G. J., Begotka, A. M., Raiff, B. R., & Kastern, L. L. (2003). Delay discounting of real and hypothetical rewards. Experimental and Clinical Psychopharmacology, 11, 139–145. doi: 10.1037/1064-1297.11.2.139.CrossRefPubMedGoogle Scholar
  32. Madden, G. J., Raiff, B. R., Lagorio, C. H., Begotka, A. M., Mueller, A. M., Hehli, D. J., & Wegener, A. A. (2004). Delay discounting of potentially real and hypothetical rewards: II. Between-and within-subject comparisons. Experimental and Clinical Psychopharmacology, 12, 251–261. doi: 10.1037/1064-1297.12.4.251.CrossRefPubMedGoogle Scholar
  33. Matusiewicz, A. K., Carter, A. E., Landes, R. D., & Yi, R. (2013). Statistical equivalence and test–retest reliability of delay and probability discounting using real and hypothetical rewards. Behavioural Processes, 100, 116–122. doi: 10.1016/j.beproc.2013.07.019.CrossRefPubMedPubMedCentralGoogle Scholar
  34. Mazur, J. E. (1987). An adjusting procedure for studying delayed reinforcement. In M. L. Commons, J. E. Mazur, J. A. Nevin, & H. Rachlin (Eds.), Quantitative analyses of behavior: Vol. V. The effect of delay and intervening events on reinforcement value (pp. 55–73). Hillsdale, NJ: Erlbaum.Google Scholar
  35. McKerchar, T. L., Green, L., Myerson, J., Pickford, T. S., Hill, J. C., & Stout, S. C. (2009). A comparison of four models of delay discounting in humans. Behavioural Processes, 81, 256–259. doi: 10.1016/j.beproc.2008.12.017.CrossRefPubMedPubMedCentralGoogle Scholar
  36. McKerchar, T. L., Pickford, S., & Robertson, S. E. (2013). Hyperboloid discounting of delayed outcomes: Magnitude effects and the gain-loss asymmetry. The Psychological Record, 63, 441–451. doi: 10.11133/j.tpr.2013.63.3.003.CrossRefGoogle Scholar
  37. Mitchell, S. H., & Wilson, V. B. (2010). The subjective value of delayed and probabilistic outcomes: Outcome size matters for gains but not for losses. Behavioural Processes, 83, 36–40. doi: 10.1016/j.beproc.2009.09.003.CrossRefPubMedPubMedCentralGoogle Scholar
  38. Myerson, J., & Green, L. (1995). Discounting of delayed rewards: Models of individual choice. Journal of the Experimental Analysis of Behavior, 64, 263–276. doi: 10.1901/jeab.1995.64-263.CrossRefPubMedPubMedCentralGoogle Scholar
  39. Myerson, J., Green, L., & Warusawitharana, M. (2001). Area under the curve as a measure of discounting. Journal of the Experimental Analysis of Behavior, 76, 235–243. doi: 10.1901/jeab.2001.76-235.CrossRefPubMedPubMedCentralGoogle Scholar
  40. National Highway Traffic Safety Administration. (2011). Policy statement and compiled facts on distracted driving. Available from
  41. National Highway Traffic Safety Administration. (2013, April). Distracted driving 2011 (Publication No. DOT HS 811 737). Retrieved from
  42. Paolacci, G., & Chandler, J. (2014). Inside the Turk: Understanding Mechanical Turk as a participant pool. Current Directions in Psychological Science, 23, 184–188. doi: 10.1177/0963721414531598.CrossRefGoogle Scholar
  43. Pew Internet Project. (2014). Mobile technology fact sheet. Available from
  44. Pew Research Center. (April, 2015). The smartphone difference. Available at
  45. Reed, D. D., Kaplan, B. A., & Brewer, A. T. (2012). A tutorial on the use of Excel 2010 and Excel for Mac 2011 for conducting delay-discounting analyses. Journal of Applied Behavior Analysis, 45, 375–386. doi: 10.1901/jaba.2012.45-375.CrossRefPubMedPubMedCentralGoogle Scholar
  46. Yi, R., Landes, R. D., & Bickel, W. K. (2009). Novel models of intertemporal valuation: Past and future outcomes. Journal of Neuroscience, Psychology, and Economics, 2, 102–111. doi: 10.1037/a0017571.CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Association for Behavior Analysis International 2016

Authors and Affiliations

  • Derek D. Reed
    • 1
  • Amel Becirevic
    • 1
  • Paul Atchley
    • 1
  • Brent A. Kaplan
    • 1
  • Bruce S. Liese
    • 1
  1. 1.4048 Dole Human Development CenterUniversity of KansasLawrenceUSA

Personalised recommendations