↓ Skip to main content

Dove Medical Press

Article Metrics

A review of contingency management for the treatment of substance-use disorders: adaptation for underserved populations, use of experimental technologies, and personalized optimization strategies

Overview of attention for article published in Substance abuse and rehabilitation, August 2018
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
2 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
50 Mendeley
Title
A review of contingency management for the treatment of substance-use disorders: adaptation for underserved populations, use of experimental technologies, and personalized optimization strategies
Published in
Substance abuse and rehabilitation, August 2018
DOI 10.2147/sar.s138439
Pubmed ID
Authors

Sterling McPherson, Ekaterina Burduli, Crystal Smith, Jalene Herron, Oladunni Oluwoye, Katherine Hirchak, Michael Orr, Michael McDonell, John Roll

Abstract

This review of contingency management (CM; the behavior-modification method of providing reinforcement in exchange for objective evidence of a desired behavior) for the treatment of substance-use disorders (SUDs) begins by describing the origins of CM and how it has come to be most commonly used during the treatment of SUDs. Our core objective is to review, describe, and discuss three ongoing critical advancements in CM. We review key emerging areas wherein CM will likely have an impact. In total, we qualitatively reviewed 31 studies in a systematic fashion after searching PubMed and Google Scholar. We then describe and highlight CM investigations across three broad themes: adapting CM for underserved populations, CM with experimental technologies, and optimizing CM for personalized interventions. Technological innovations that allow for mobile delivery of reinforcers in exchange for objective evidence of a desired behavior will likely expand the possible applications of CM throughout the SUD-treatment domain and into therapeutically related areas (eg, serious mental illness). When this mobile technology is coupled with new, easy-to-utilize biomarkers, the adaptation for individual goal setting and delivery of CM-based SUD treatment in hard-to-reach places (eg, rural locations) can have a sustained impact on communities most affected by these disorders. In conclusion, there is still much to be done, not only technologically but also in convincing policy makers to adopt this well-established, cost-effective, and evidence-based method of behavior modification.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 16%
Student > Master 7 14%
Other 6 12%
Student > Ph. D. Student 5 10%
Student > Bachelor 4 8%
Other 11 22%
Unknown 9 18%
Readers by discipline Count As %
Psychology 14 28%
Medicine and Dentistry 10 20%
Social Sciences 5 10%
Nursing and Health Professions 3 6%
Mathematics 1 2%
Other 3 6%
Unknown 14 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 17 July 2019.
All research outputs
#8,856,011
of 15,456,178 outputs
Outputs from Substance abuse and rehabilitation
#77
of 102 outputs
Outputs of similar age
#138,262
of 276,796 outputs
Outputs of similar age from Substance abuse and rehabilitation
#1
of 1 outputs
Altmetric has tracked 15,456,178 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 102 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.9. This one is in the 23rd percentile – i.e., 23% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 276,796 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them