Skip to main content
SpringerLink
Log in

Being Kind to Your Future Self: Probability Discounting of Health Decision-Making

  • Original Article
  • Published:
Annals of Behavioral Medicine

Abstract

Introduction

Nearly 50 % of patients with chronic medical illness exhibit poor treatment adherence. When making treatment decisions, these patients must balance the probability of current side effects against the probability of long-term benefits. This study examines if the behavioral economic construct of probability discounting can be used to explain treatment decisions in chronic disease.

Methods

Thirty-eight nonadherent and 39 adherent patients with multiple sclerosis (MS) completed a series of hypothetical treatment scenarios with varied risk and benefit probabilities.

Results

As described by a hyperbolic probability discounting model, all patients reported decreased medication initiation as the probability of treatment efficacy decreased and the probability of treatment side effects increased. When compared to adherent patients, nonadherent patients significantly devalued treatment efficacy and inflated treatment risk.

Discussion

The methods in this study can be used to identify optimal risk/benefit ratios for treatment development and inform the process by which patients make treatment decisions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Petri M, Perez-Gutthann S, Longenecker J, et al. Morbidity of systemic lupus erythematosus: role of race and socio-economic status. Am J Med. 1991; 91: 345-53.

    Article  CAS  PubMed  Google Scholar 

  2. Harrison T, Derose S, Cheetham C, et al. Primary nonadherence to statin therapy: patients’ perceptions. Am J Manag Care. 2013; 19(4): e133-e9.

    PubMed  Google Scholar 

  3. Ferrari C, de Sousa R, Castro L. Factors associated with treatment non-adherence in patients with epilepsy in Brazil. Seizure. 2013; 22(5): 384-9.

    Article  PubMed  Google Scholar 

  4. Sabate E. Adherence to Long-Term Therapies - Evidence for Action. Geneva: World Health Organziation; 2003.

    Google Scholar 

  5. Benedict RHB, Wahlig E, Bakshi R, et al. Predicting quality of life in multiple sclerosis: accounting for physical disability, fatigue, cognition, mood disorder, personality, and behavior change. J Neurol Sci. 2005; 231(1–2): 29-34.

    Article  PubMed  Google Scholar 

  6. Bruce JM, Hancock L, Arnett P, et al. Treatment adherence in multiple sclerosis: association with emotional status, personality and cognition. J Behav Med. 2010; 33(3): 219-27.

    Article  PubMed  Google Scholar 

  7. Rao SM, Leo GJ, Ellington L, et al. Cognitive dysfunction in multiple sclerosis. II. Impact on employment and social functioning. Neurology. 1991; 41(5): 692-6.

    Article  CAS  PubMed  Google Scholar 

  8. Kieseier BC, Wiendl H, Leussink VI, et al. Immunomodulatory treatment strategies in multiple sclerosis. J Neurol. 2008; 255(Suppl 6): 15-21.

    Article  CAS  PubMed  Google Scholar 

  9. Margolis JM, Fowler R, Johnson BH, et al. Disease-modifying drug initiation patterns in commercially insured multiple sclerosis patients: a retrospective cohort study. BMC Neurol. 2011; 11: 122.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Bruce JM, Lynch S. Multiple Sclerosis: MS treatment adherence- how to keep patients on medication? Nat Rev Neurol. 2011; 7(8): 421-2.

    Article  PubMed  Google Scholar 

  11. Wong J, Gomes T, Mamdani M, et al. Adherence to Multiple Sclerosis Disease-Modifying Therapies in Ontario is Low. Can J Neurol Sci. 2011; 38(3): 429-33.

    Article  PubMed  Google Scholar 

  12. Reynolds MW, Stephen R, Seaman C, et al. Persistence and adherence to disease modifying drugs among patients with multiple sclerosis. Curr Med Res Opin. 2010; 26(3): 663-74.

    Article  CAS  PubMed  Google Scholar 

  13. Pozzilli C, Schweikert B, Ecari U, et al. Supportive strategies to improve adherence to IFN Beta-1b in multiple sclerosis - results of the BPlus observational cohort study. J Neurol Sci. 2011; 307(1–2): 120-6.

    Article  PubMed  Google Scholar 

  14. Daugherty K, Butler J, Mattingly M, et al. Factors leading patients to discontinue multiple sclerosis therapies. J Am Pharm Assoc. 2005; 45(3): 371-5.

    Article  Google Scholar 

  15. Shead NW, Hodgins DC. Probability discounting of gains and losses: implications for risk attitudes and impulsivity. J Exp Anal Behav. 2009; 92(1): 1-16.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Yi R, Chase WD, Bickel WK. Probability discounting among cigarette smokers and nonsmokers: molecular analysis discerns group differences. Behav Pharmacol. 2007; 18(7): 633-9.

    Article  CAS  PubMed  Google Scholar 

  17. Rasmussen EB, Lawyer SR, Reilly W. Percent body fat is related to delay and probability discounting for food in humans. Behav Processes. 2010; 83(1): 23-30.

    Article  PubMed  Google Scholar 

  18. Lawyer SR, Schoepflin FJ. Predicting domain-specific outcomes using delay and probability discounting for sexual versus monetary outcomes. Behav Processes. 2013; 96: 71-8.

    Article  PubMed  Google Scholar 

  19. Polman CH, Reingold SC, Edan G, et al. Diagnostic criteria for multiple sclerosis: 2005 revisions to the "McDonald Criteria". Ann Neurol. 2005; 58(6): 840-6.

    Article  PubMed  Google Scholar 

  20. Bruce JM, Hancock L, Arnett P, et al. Objective adherence monitoring in MS: Initial validation and association with self-report. Mult Scler. 2010; 16(1): 112-20.

    Article  PubMed  Google Scholar 

  21. Fisk JD, Pontefract A, Ritvo PG, et al. The impact of fatigue on patients with multiple sclerosis. Can J Neurol Sci. 1994; 21: 9-14.

    Article  CAS  PubMed  Google Scholar 

  22. Veit CT, Ware JE Jr. The structure of psychological distress and well-being in general populations. J Consult Clin Psychol. 1983; 51(5): 730-42.

    Article  CAS  PubMed  Google Scholar 

  23. Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology. 1983; 33: 1444-52.

    Article  CAS  PubMed  Google Scholar 

  24. Mazur J. An adjusting procedure for studying delayed reinforcement. In: Mazur J, Commons M, Nevin J, Rachlin H, eds. Quantitative Analyses of Behavior, Vol 5: The effect of delay and of intervening events on reinforcement value. Hillsdale: Erlbaum; 1987.

    Google Scholar 

  25. Green L, Myerson J. A discounting framework for choice with delayed and probabilistic rewards. Psychol Bull. 2004; 130(5): 769-92.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Myerson J, Green L, Warusawitharana M. Area under the curve as a measure of discounting. J Exp Anal Behav. 2001; 76(2): 235-43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Rachlin H, Raineri A, Cross D. Subjective probability and delay. J Exp Anal Behav. 1991; 55(2): 233-44.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Green L, Myerson J, Holt DD, et al. Discounting of delayed food rewards in pigeons and rats: is there a magnitude effect? J Exp Anal Behav. 2004; 81(1): 39-50.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Bickel W, Vuchinich RE, editors. Reframing health behavior change with behavioral economics: Psychology Press; 2000.

  30. Jarmolowicz DP, Cherry JB, Reed DD, et al. Robust relation between temporal discounting rates and body mass. Appetite. 2014; 78: 63-7.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Odum AL, Madden GJ, Badger GJ, et al. Needle sharing in opioid-dependent outpatients: psychological processes underlying risk. Drug Alcohol Depend. 2000; 60(3): 259-66.

    Article  CAS  PubMed  Google Scholar 

  32. Bickel WK, Jarmolowicz DP, Mueller ET, et al. Altruism in time: social temporal discounting differentiates smokers from problem drinkers. Psychopharmacology (Berl). 2012; 224(1): 109-20.

    Article  CAS  Google Scholar 

  33. Johnson MW, Bruner NR. The Sexual Discounting Task: HIV risk behavior and the discounting of delayed sexual rewards in cocaine dependence. Drug Alcohol Depend. 2012; 123(1–3): 15-21.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Fagerlin A, Ubel PA, Smith DM, et al. Making numbers matter: present and future research in risk communication. Am J Health Behav. 2007; 31(Suppl 1): S47-56.

    Article  PubMed  Google Scholar 

  35. Nelson WL, Han PK, Fagerlin A, et al. Rethinking the objectives of decision aids: a call for conceptual clarity. Med Decis Making. 2007; 27(5): 609-18.

    Article  PubMed  Google Scholar 

  36. Fagerlin A, Zikmund-Fisher BJ, Ubel PA. “If I’m better than average, then I’m ok?”: Comparative information influences beliefs about risk and benefits. Patient Educ Couns. 2007; 69(1–3): 140-4.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Tversky A, Kahneman D. The framing of decisions and the psychology of choice. Science. 1981; 211(4481): 453-8.

    Article  CAS  PubMed  Google Scholar 

  38. Critchfield TS, Reed DD. What are we doing when we translate from quantitative models? Behav Anal. 2009; 32: 339-361.

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

This project was supported in part by grant to J. Bruce from the National Multiple Sclerosis (HC 0138) and a grant to M. Glusman from the University of Missouri-Kansas City School of Graduate Studies.

Author information

Authors and Affiliations

  1. University of Missouri-Kansas City, Kansas City, MO, USA

    Jared M. Bruce PhD, Delwyn Catley PhD, Seung-Lark Lim PhD, Morgan Glusman BA & Abigail R. Ness MA

  2. Department of Pediatrics, University of Kansas Medical Center, 3901 Rainbow Blvd Mail Stop 4004, Kansas City, KS, 66160, USA

    Amanda S. Bruce PhD

  3. Children’s Mercy Hospital, Kansas City, MO, USA

    Amanda S. Bruce PhD & Kathleen Goggin PhD

  4. Department of Neurology, University of Kansas Medical Center, Kansas City, KS, 66160, USA

    Sharon Lynch MD

  5. University of Kansas, Lawrence, KS, USA

    Derek Reed PhD & David P. Jarmolowicz PhD

  6. Kessler Foundation, West Orange, NJ, USA

    Lauren Strober PhD

Authors
  1. Jared M. Bruce PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Amanda S. Bruce PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Delwyn Catley PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sharon Lynch MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Kathleen Goggin PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Derek Reed PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Seung-Lark Lim PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Lauren Strober PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Morgan Glusman BA
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Abigail R. Ness MA
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. David P. Jarmolowicz PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Amanda S. Bruce PhD.

Ethics declarations

Authors’ Statement of Conflict of Interest and Adherence to Ethical Standards

Dr. J. Bruce is a member of the Novartis Unbranded Speakers Bureau and the Novartis MS Cognition Medical Advisory Board. He is also a consultant to the National Hockey League. Authors A. Bruce, Catley, Lynch, Goggin, Reed, Lim, Strober, Glusman, Ness, and Jarmolowicz declare that they have no conflict of interest. All procedures, including the informed consent process, were conducted in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000.

Appendix

Appendix

Medical Decision Making Questionnaire

When thinking about whether to take or not to take a Disease Modifying Medication, patients must weigh the potential costs and benefits associated with each decision. Please indicate how likely you would be to take a Disease Modifying Medication if each of the following statements were true.

figure afigure afigure afigure a

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bruce, J.M., Bruce, A.S., Catley, D. et al. Being Kind to Your Future Self: Probability Discounting of Health Decision-Making. ann. behav. med. 50, 297–309 (2016). https://doi.org/10.1007/s12160-015-9754-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12160-015-9754-8

Keywords

Search

Navigation