B.L. Wagner, Z.W. Almquist, A. Unruh, M.K. Forbes, J. Simundson,

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B.L. Wagner, Z.W. Almquist, A. Unruh, M.K. Forbes, J. Simundson, A Network Approach to Modeling Comorbid Internalizing and Alcohol Use Disorders J.J. Anker, P. Thuras, J. Menk, B.L. Wagner, Z.W. Almquist, A. Unruh, M.K. Forbes, J. Simundson, M.G. Kushner University of Minnesota, Departments of Psychiatry, Minneapolis MN, 55454, United States

Conflicts of Interest Statement I, or an immediate family member, including a spouse or partner, have no financial relationships or any other relationship which could reasonably be considered a conflict of interest relevant to the content of this CE activity.

Objective 1: Visualize the network structure of the Vicious Cycle Model of comorbid internalizing (INT) and alcohol use disorder (AUD). Objective 2: Probe the contribution of specific elements to network connectivity to identify high value treatment targets.

Problem and Background

Comorbidity is highly prevalent among AUD patients Among AUD patients, rates of anxiety and depression disorders range between 25% to 50% AUD INT (Kushner, Krueger, Frye, & Peterson, 2008; Kushner et al., 2012)

Comorbidity interferes with AUD treatment Among AUD patients, rates of anxiety and depression disorders range between 25% to 50% AUD INT Dependence severity Withdrawal severity Persistence of AUD x2 Relapse Risk (Cornelius et al., 1997; Greenfield et al., 1998; Haver, 2003; Helzer & Pryzbeck, 1988; Kushner et al., 2005; Regier et al., 1990; Tómasson & Vaglum, 1995)

Treatment of INT does not improve AUD outcomes among comorbid individuals (meta-analysis by Hobbs et al., 2011) INT AUD COMORBIDITY x2 Relapse Risk

This suggests conditions beyond INT maintain comorbidity and increase risk for AUD relapse x2 Relapse Risk

DTC increases risk for AUD by a factor of 5 among those with an anxiety disorder Drinking to Cope NO Drinking to Cope 6 5 4 3 2 1 Menary, Kushner, Maurer, Thuras (2011). The prevalence and clinical implications of self-medication among individuals with anxiety disorders, JAD, 25, 335-339

Models of Comorbidity

Comorbidity develops through negatively reinforced drinking i. e Comorbidity develops through negatively reinforced drinking i.e., self-medication of INT symptoms → AUD INT AUD DTC Self-Medication (AUD ← INT)

Consequences of Drinking Drinking leads to stress-related neurobio adaptations and negative psychosocial consequences → INT INT AUD DTC Self-Medication (AUD ← INT) Consequences of Drinking (AUD → INT) AUD INT Stress

Combined, these processes form the Vicious Cycle Model of comorbidity INT AUD DTC Stress Stress

The Vicious Cycle provides an explanation of why treatment of INT does not improve AUD outcomes DTC AUD INT Stress

INT treatment alone fails to address DTC, which remains available to maintain or re-initiate the Vicious Cycle DTC AUD INT Stress

Study Objectives Objective 1: Use network analysis to visualize the structure of unique relationships between elements of the vicious cycle model. AUD INT DTC Comorbidity Stress Objective 2: Characterize changes in network structure when controlling for specific elements. Identify central elements, that, if removed, would maximally disrupt relationships among other elements in the network.

General Methods

Sample 363 AUD Residential inpatients with a comorbid anxiety disorder Assessed at the beginning of residential AUD treatment AUD INT

AUD INT Sample Level of Analysis 363 AUD Residential inpatients with a comorbid anxiety disorder Assessed at the beginning of residential AUD treatment Level of Analysis Most NA studies in psychopathology define network elements at the symptom level A smaller number define elements at the symptom/behavioral aggregate level We adopt the former to align with the theoretical conceptualization of the vicious cycle AUD INT

AUD INT Sample Level of Analysis Measures 363 AUD Residential inpatients with a comorbid anxiety disorder Assessed at the beginning of residential AUD treatment Level of Analysis Most NA studies in psychopathology define network elements at the symptom level A smaller number define elements at the symptom/behavioral aggregate level We adopt the former to align with the theoretical conceptualization of the vicious cycle Measures Network elements operationalized as summary scores representing levels of the following constructs: Depr Gen Anx DTC Self E Stress Crave Drink AUD INT Social Panic Agor

Objective 1: Visualizing the Network Structure of the Vicious Cycle

Using GLASSO to visualize the structure of unique relationships within the Vicious Cycle GLASSO Network *Lines/edges represents the relationship between two elements while controlling for all other elements

DTC and stress served as bridging elements between internalizing and alcohol elements GLASSO Network Element Legend Alcohol CRA Craving DRI Total Drinks Internalizing - Distress GA Gen Anxiety DEP Depression SOC Social Anxiety PAN Panic AGR Agoraphobia Vicious Cycle DTC Drinking to Cope SEL Self-efficacy STR Perceived Stress DRI CRA GA DTC STR SEL SOC PAN DEP AGR *Lines/edges represents the relationship between two elements while controlling for all other elements

DTC was the most central element in the GLASSO network Centrality Plot results for DTC Betweenness Closeness Strength DRI CRA SEL DTC GA SOC PAN STR AGR DEP DTC Betweenness: lies on the shortest path between other elements Strength: has the highest sum of connected edge weights Closeness: has the highest # of actual (vs. possible) connections *Lines/edges represents the relationship between two elements while controlling for all other elements

Objective 2: Models Probing the Contribution of Specific Elements to Network Connectivity

A zero-order correlation matrix was plotted using the Fruchterman and Reingold algorithm Baseline/Association Network Element Legend Alcohol CRA Craving DRI Total Drinks Internalizing - Distress GA Gen Anxiety DEP Depression SOC Social Anxiety PAN Panic AGR Agoraphobia Vicious Cycle DTC Drinking to Cope SEL Self-efficacy STR Perceived Stress We computed a series of semi-partial correlations that systematically controlled the variance associated with selected individual elements in the model. SEL STR DRI CRA PAN AGR GA SOC DEP DTC

After controlling for DTC the alcohol elements became isolated. Baseline/Association Network SEL STR DRI CRA PAN AGR GA SOC DEP DTC DTC Probe SEL STR DRI CRA PAN AGR GA SOC DEP

Baseline/Association Network DTC Probe STR DRI CRA PAN AGR GA SOC DEP DTC DTC Probe SEL STR DRI CRA PAN AGR GA SOC DEP

This level of change was unique to the influence of DTC Stress Probe DRI CRA SEL DTC PAN SOC AGR DEP GA Distress Probe DRI CRA STR DTC SEL PAN SOC AGR DTC Probe SEL STR DRI CRA PAN AGR GA SOC DEP Fear Probe DEP GA CRA DRI DTC SEL STR Internalizing Probe CRA SEL DTC DRI STR

This study characterized relationships between elements of the Vicious Cycle Model using network analysis. Summary of findings: DTC served as a bridge between internalizing and alcohol elements. Centrality indices indicated that DTC ranked as the most central element in maintaining network coherence. After controlling for DTC, alcohol elements became isolated from the other network elements. This level of change was unique to the influence of DTC and did not occur after other elements were controlled. Conclusion: These findings inform clinical hypotheses for interventions targeting DTC to eliminate the connection between comorbid internalizing and alcohol use disorders.

Acknowledgements Federal Grant Support Mentor Support Data collection NIAAA: R01 AA015069 Awarded to Matt. G. Kushner NIDA: T320A037183 To support the work of the Justin J. Anker and Miri K. Forbes Mentor Support Matt G. Kushner John Grabowski Marilyn E. Carroll Data collection Joani Van Demark Eric W. Maurer Chris Donahue Brenda Frye Kyle R. Menary Jennifer Hobbs Angela M. Haeny

Extra Slides

Study Sample the average age was 39.3 (standard deviation [SD] = 10.24) 38% were female (N = 138). Patients with more than one of the three anxiety disorders required for inclusion in the study were asked to identify their “primary” disorder in terms of its interference in their daily functioning: 41.7% endorsed primary social anxiety disorder (N = 151) 40.3% endorsed primary generalized anxiety disorder (N = 146) 14.9% endorsed primary panic disorder without agoraphobia (N = 54) 3.0% endorsing primary panic disorder with agoraphobia (N = 11) two or more co-occurring anxiety disorders (56.0%, N = 201) met diagnostic criteria for major depression (51.4%, N = 186).

Study Assessments Internalizing Distress Measures (Blue) Generalized Anxiety (GA) Penn State Worry Questionnaire 64.13 (11.59) Depression (DEP) Beck Depression Inventory 20.40 (9.09) Internalizing Fear Measures (Red) Social Phobia (SOC) Social Phobia Scale 32.43 (17.30) Panic Disorder (PAN) Panic Disorder Severity Scale 10.99 (6.34) Agoraphobia (AGR) Mobility Inventory for Agoraphobia 31.59 (19.78) Alcohol-Related Measures (Pink) Alcohol Craving (CRA) Obsessive Compulsive Drinking Scale 2.67 (1.05) Total Drinks 4 Months Before Treatment (DRI) Time Line Follow-Back Interview 1608.76 (1271.51) Stress and Coping Measures (Yellow) Perceived Stress (STR) Perceived Stress Scale 28.15 (5.50) Drinking to Cope with Negative Affect (DTC) Inventory of Drinking Situations – Unpleasant Emotions Subscale 62.93 (12.15) Coping Self-Efficacy (SEL) Situational Confidence Questionnaire – Negative Emotions Subscale 32.91 (10.91)