, Volume 235, Issue 11, pp 3303–3313 | Cite as

Probability discounting of treatment decisions in multiple sclerosis: associations with disease knowledge, neuropsychiatric status, and adherence

  • Jared M. BruceEmail author
  • Amanda S. Bruce
  • Sharon Lynch
  • Joanie Thelen
  • Seung-Lark Lim
  • Julia Smith
  • Delwyn Catley
  • Derek D. Reed
  • David P. Jarmolowicz
Original Investigation



Patients weigh risks and benefits when making treatment decisions. Despite this, relatively few studies examine the behavioral patterns underpinning these decisions. Moreover, individual differences in these patterns remain largely unexplored.


The purpose of this study was to test a probability discounting model to explain the independent influences of risks and benefits when patients make hypothetical treatment decisions. Furthermore, we examine how individual differences in this probability discounting function are associated with patient demographics, clinical characteristics, disease knowledge, neuropsychiatric status, and adherence.


Two hundred eight participants with relapsing-remitting multiple sclerosis (MS) indicated their likelihood (0–100%) of taking a hypothetical medication as the probability of mild side effects (11 values from .1 to 99.9%) and reported medication efficacies (11 values from .1 to 99.9%) varied systematically. They also completed a series of questionnaires and cognitive tests.


Individual components of medication treatment decision making were successfully described with a probability discounting model. High rates of discounting based on risks were associated with poor treatment adherence and less disease-specific knowledge. In contrast, high rates of discounting of benefits was associated with poorer cognitive functioning. Regression models indicated that risk discounting predicted unique variance in treatment adherence.


Insights gained from the present study represent an important early step in understanding individual differences associated with medical decision making in MS. Future research may wish to use this knowledge to inform the development of empirically supported adherence interventions.


Multiple sclerosis Adherence Probability discounting Disease-modifying therapy Medical decision making 



This research was funded by a grant from the National Multiple Sclerosis Society to the first author (HC-1411-01993).

Compliance with ethical standards

This study was approved by the University of Missouri-Kansas City Institutional Review Board and the University of Kansas Medical Center Human Subjects Committee.

Competing interests

Dr. J. Bruce provides non-branded talks for Novartis, is a part-time employee of the National Hockey League, does consulting for Princeton University’s Department of Athletic Medicine, and is a consultant to Major League Soccer’s Sporting KC.

Dr. Sharon Lynch has participated in multi-center drug trials through Novartis, Teva, Biogen, Sanofi, Genzyme, Genentech, Roche, NMSS and NIH, Alexion, Opexa, Sun Pharma, Vaccinex, Actelion, and Mallinkrodt.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Jared M. Bruce
    • 1
    • 2
    Email author
  • Amanda S. Bruce
    • 3
    • 4
  • Sharon Lynch
    • 5
  • Joanie Thelen
    • 1
  • Seung-Lark Lim
    • 1
  • Julia Smith
    • 1
  • Delwyn Catley
    • 3
  • Derek D. Reed
    • 6
    • 7
  • David P. Jarmolowicz
    • 6
    • 7
  1. 1.Department of PsychologyUniversity of Missouri – Kansas CityKansas CityUSA
  2. 2.Department of Biomedical and Health InformaticsUniversity of Missouri – Kansas CityKansas CityUSA
  3. 3.Center for Healthy Lifestyles and NutritionChildren’s Mercy HospitalKansas CityUSA
  4. 4.Department of PediatricsUniversity of Kansas Medical CenterKansas CityUSA
  5. 5.Department of NeurologyUniversity of Kansas Medical CenterKansas CityUSA
  6. 6.Department of Applied Behavior ScienceUniversity of KansasLawrenceUSA
  7. 7.Cofrin-Logan Center for Addiction Research and TreatmentLawrenceUSA

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