A network approach to modeling comorbid internalizing and alcohol use disorders.

نویسندگان

  • Justin J Anker
  • Miriam K Forbes
  • Zack W Almquist
  • Jeremiah S Menk
  • Paul Thuras
  • Amanda S Unruh
  • Matt G Kushner
چکیده

Internalizing disorders co-occur with alcohol use disorder (AUD) at a rate that exceeds chance and compromise conventional AUD treatment. The "vicious cycle" model of comorbidity specifies drinking to cope (DTC) as a link between these disorders that, when not directly addressed, undermines the effectiveness of conventional treatments. Interventions based on this model have proven successful but there is no direct evidence for how and to what extent DTC contributes to the maintenance of comorbidity. In the present study, we used network analysis to depict associations between syndrome-specific groupings of internalizing symptoms, alcohol craving, and drinking behavior, as well as DTC and other extradiagnostic variables specified in the vicious cycle model (e.g., perceived stress and coping self-efficacy). Network analyses of 362 individuals with comorbid anxiety and AUD assessed at the beginning of residential AUD treatment indicated that while internalizing conditions and drinking elements had only weak direct associations, they were strongly connected with DTC and perceived stress. Consistent with this, centrality indices showed that DTC ranked as the most central/important element in the network in terms of its "connectedness" to all other network elements. A series of model simulations-in which individual elements were statistically controlled for-demonstrated that DTC accounted for all the relationships between the drinking-related elements and internalizing elements in the network; no other variable had this effect. Taken together, our findings suggest that DTC may serve as a "keystone" process in maintaining comorbidity between internalizing disorders and AUD. (PsycINFO Database Record

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عنوان ژورنال:
  • Journal of abnormal psychology

دوره 126 3  شماره 

صفحات  -

تاریخ انتشار 2017