Modeling effects of side-effect probability, side-effect severity, and medication efficacy on patients with multiple sclerosis medication choice.

Multiple sclerosis (MS) is an autoimmune disease that causes a range of problematic symptoms. These symptoms tend to get worse over time, causing substantial impairment in patient quality of life. Although many effective disease-modifying therapies (DMTs) exist that slow the course of MS, patients often do not choose to take them, which may be because these medications carry substantial risks of side effects, varying from mild to severe, while only decreasing the probability of future symptoms. In the current study, we examined MS patients' self-reported likelihood of taking medications with a range of efficacies (11 values, ranging from 0.1% to 99.9%), side-effect probabilities (11 values, ranging from 0.1% to 99.9%), and side-effect severities (mild, moderate, or severe). These data were well-described by a three-dimensional probability-discounting model that isolated patients' undiscounted likelihood of taking DMTs, as well as their discounting and psychophysical scaling/weighting of side-effect probabilities and efficacy. (PsycINFO Database Record