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

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Abstract

Rationale

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.

Objectives

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.

Methods

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.

Results

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.

Conclusions

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.

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Funding

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

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Authors and Affiliations

  1. Department of Psychology, University of Missouri – Kansas City, 5030 Cherry Hall, Kansas City, MO, 64110, USA

    Jared M. Bruce, Joanie Thelen, Seung-Lark Lim & Julia Smith

  2. Department of Biomedical and Health Informatics, University of Missouri – Kansas City, Kansas City, MO, USA

    Jared M. Bruce

  3. Center for Healthy Lifestyles and Nutrition, Children’s Mercy Hospital, Kansas City, MO, USA

    Amanda S. Bruce & Delwyn Catley

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

    Amanda S. Bruce

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

    Sharon Lynch

  6. Department of Applied Behavior Science, University of Kansas, Lawrence, KS, USA

    Derek D. Reed & David P. Jarmolowicz

  7. Cofrin-Logan Center for Addiction Research and Treatment, Lawrence, KS, USA

    Derek D. Reed & David P. Jarmolowicz

Authors
  1. Jared M. Bruce
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  2. Amanda S. Bruce
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  3. Sharon Lynch
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  4. Joanie Thelen
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  5. Seung-Lark Lim
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  6. Julia Smith
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  7. Delwyn Catley
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  8. Derek D. Reed
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  9. David P. Jarmolowicz
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Corresponding author

Correspondence to Jared M. Bruce.

Ethics declarations

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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Bruce, J.M., Bruce, A.S., Lynch, S. et al. Probability discounting of treatment decisions in multiple sclerosis: associations with disease knowledge, neuropsychiatric status, and adherence. Psychopharmacology 235, 3303–3313 (2018). https://doi.org/10.1007/s00213-018-5037-y

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  • DOI: https://doi.org/10.1007/s00213-018-5037-y

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