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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
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#37 of 125)
  • High Attention Score compared to outputs of the same age (83rd percentile)

Mentioned by

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1 blog
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6 X users
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1 Facebook page

Citations

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65 Dimensions

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mendeley
123 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 M McPherson, Ekaterina Burduli, Crystal Lederhos Smith, Jalene Herron, Oladunni Oluwoye, Katherine Hirchak, Michael F Orr, Michael G McDonell, John M 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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 123 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 123 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 12%
Student > Master 14 11%
Other 11 9%
Student > Ph. D. Student 9 7%
Student > Doctoral Student 8 7%
Other 23 19%
Unknown 43 35%
Readers by discipline Count As %
Psychology 28 23%
Medicine and Dentistry 19 15%
Nursing and Health Professions 9 7%
Social Sciences 8 7%
Biochemistry, Genetics and Molecular Biology 2 2%
Other 6 5%
Unknown 51 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 10 September 2022.
All research outputs
#2,834,924
of 25,385,509 outputs
Outputs from Substance abuse and rehabilitation
#37
of 125 outputs
Outputs of similar age
#55,371
of 341,886 outputs
Outputs of similar age from Substance abuse and rehabilitation
#2
of 4 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 125 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 33.1. This one has gotten more attention than average, scoring higher than 70% of its peers.
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 341,886 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.