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Is medical treatment of Alcohol Withdrawal Syndrome a Stag Hunt? Challenges and opportunities in managing risk and uncertainty in addiction cessation

Overview of attention for article published in Risk Management and Healthcare Policy, December 2017
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2 X users

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31 Mendeley
Title
Is medical treatment of Alcohol Withdrawal Syndrome a Stag Hunt? Challenges and opportunities in managing risk and uncertainty in addiction cessation
Published in
Risk Management and Healthcare Policy, December 2017
DOI 10.2147/rmhp.s144831
Pubmed ID
Authors

Roger Lee Mendoza

Abstract

While the individual and social costs of alcoholism or alcohol use disorder are well established, few are aware that medical problems can arise during detoxification, some of which can be life-threatening. This study determines if sustained treatment for Alcohol Withdrawal Syndrome (AWS) might be based on the strategic choices and expectations of patients and health care providers alike, as well as the risk mitigation options available to them. AWS was modeled as a Stag Hunt to explain both risk and decision-making in medical treatments for detoxification, since it can deduce a set of equilibrium strategies available to both patient and provider. Modeling was based on a review of juried literature gathered from search engines with the use medical subject heading terms. While there is little evidence that decision-making is shared between patient and physician in AWS treatments, the outcomes of their interactions depend on utility-maximizing choices each makes in anticipation of the other. Payoff-dominant and risk-dominant treatment outcomes are equally likely and equally cost-efficient, as conditioned by the presence (or absence) of mutual trust and assurance in reciprocal transactions. Simulation games, such as the Stag Hunt, offer a viable framework to understand patient and provider incentives and health-affecting behaviors during treatments for addiction cessation. If both anticipate indefinitely interacting in the absence of any predetermined or foreseeable final visit, they can maximize future payoffs from mutual cooperation and accountability, which fosters health promotion. However, this study suggests that the effect of cooperation is distinct from the effect of time in AWS and other addiction-cessation programs.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 16%
Student > Bachelor 4 13%
Student > Ph. D. Student 4 13%
Researcher 3 10%
Librarian 2 6%
Other 3 10%
Unknown 10 32%
Readers by discipline Count As %
Nursing and Health Professions 4 13%
Medicine and Dentistry 4 13%
Psychology 3 10%
Computer Science 2 6%
Environmental Science 1 3%
Other 7 23%
Unknown 10 32%
Attention Score in Context

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 10 May 2018.
All research outputs
#14,370,803
of 23,012,811 outputs
Outputs from Risk Management and Healthcare Policy
#283
of 622 outputs
Outputs of similar age
#236,502
of 437,955 outputs
Outputs of similar age from Risk Management and Healthcare Policy
#3
of 4 outputs
Altmetric has tracked 23,012,811 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 622 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.0. This one has gotten more attention than average, scoring higher than 50% 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 437,955 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
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.