| Title |
Probability discounting of treatment decisions in multiple sclerosis: associations with disease knowledge, neuropsychiatric status, and adherence
|
|---|---|
| Published in |
Psychopharmacology, September 2018
|
| DOI | 10.1007/s00213-018-5037-y |
| Pubmed ID | |
| Authors |
Jared M. Bruce, Amanda S. Bruce, Sharon Lynch, Joanie Thelen, Seung-Lark Lim, Julia Smith, Delwyn Catley, Derek D. Reed, David P. Jarmolowicz |
| Abstract |
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. |
X Demographics
The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 46% |
| United Kingdom | 1 | 8% |
| Italy | 1 | 8% |
| Spain | 1 | 8% |
| Qatar | 1 | 8% |
| Unknown | 3 | 23% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 11 | 85% |
| Practitioners (doctors, other healthcare professionals) | 2 | 15% |
Mendeley readers
The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 46 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 6 | 13% |
| Student > Ph. D. Student | 5 | 11% |
| Researcher | 4 | 9% |
| Professor > Associate Professor | 3 | 7% |
| Student > Master | 3 | 7% |
| Other | 9 | 20% |
| Unknown | 16 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 8 | 17% |
| Medicine and Dentistry | 5 | 11% |
| Nursing and Health Professions | 5 | 11% |
| Unspecified | 2 | 4% |
| Neuroscience | 2 | 4% |
| Other | 7 | 15% |
| Unknown | 17 | 37% |
Attention Score in Context
This research output has an Altmetric Attention Score of 17. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 October 2018.
All research outputs
#1,908,404
of 23,103,903 outputs
Outputs from Psychopharmacology
#456
of 5,377 outputs
Outputs of similar age
#42,547
of 340,695 outputs
Outputs of similar age from Psychopharmacology
#13
of 66 outputs
Altmetric has tracked 23,103,903 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,377 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has done particularly well, scoring higher than 91% of its peers.
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We're also able to compare this research output to 66 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.