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Modeling Alcohol Use Disorder Severity: An Integrative Structural Equation Modeling Approach

Overview of attention for article published in Frontiers in Psychiatry, January 2013
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Title
Modeling Alcohol Use Disorder Severity: An Integrative Structural Equation Modeling Approach
Published in
Frontiers in Psychiatry, January 2013
DOI 10.3389/fpsyt.2013.00075
Pubmed ID
Authors

Nathasha R. Moallem, Kelly E. Courtney, Guadalupe A. Bacio, Lara A. Ray

Abstract

Background: Alcohol dependence is a complex psychological disorder whose phenomenology changes as the disorder progresses. Neuroscience has provided a variety of theories and evidence for the development, maintenance, and severity of addiction; however, clinically, it has been difficult to evaluate alcohol use disorder (AUD) severity. Objective: This study seeks to evaluate and validate a data-driven approach to capturing alcohol severity in a community sample. Method: Participants were non-treatment seeking problem drinkers (n = 283). A structural equation modeling approach was used to (a) verify the latent factor structure of the indices of AUD severity; and (b) test the relationship between the AUD severity factor and measures of alcohol use, affective symptoms, and motivation to change drinking. Results: The model was found to fit well, with all chosen indices of AUD severity loading significantly and positively onto the severity factor. In addition, the paths from the alcohol use, motivation, and affective factors accounted for 68% of the variance in AUD severity. Greater AUD severity was associated with greater alcohol use, increased affective symptoms, and higher motivation to change. Conclusion: Unlike the categorical diagnostic criteria, the AUD severity factor is comprised of multiple quantitative dimensions of impairment observed across the progression of the disorder. The AUD severity factor was validated by testing it in relation to other outcomes such as alcohol use, affective symptoms, and motivation for change. Clinically, this approach to AUD severity can be used to inform treatment planning and ultimately to improve outcomes.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 15%
Researcher 4 15%
Lecturer 2 8%
Student > Doctoral Student 2 8%
Student > Bachelor 2 8%
Other 3 12%
Unknown 9 35%
Readers by discipline Count As %
Psychology 6 23%
Mathematics 2 8%
Medicine and Dentistry 2 8%
Neuroscience 2 8%
Nursing and Health Professions 1 4%
Other 5 19%
Unknown 8 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 29 July 2013.
All research outputs
#20,196,821
of 22,715,151 outputs
Outputs from Frontiers in Psychiatry
#7,620
of 9,834 outputs
Outputs of similar age
#248,768
of 280,748 outputs
Outputs of similar age from Frontiers in Psychiatry
#163
of 185 outputs
Altmetric has tracked 22,715,151 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
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