Initial development and validation of a dimensional classification system for the emotional disorders

Problems with the current categorical approach to classification used by the Diagnostic and Statistical Manual of Mental Disorders (DSM) have led to proposals that classify the emotional disorders (EDs; anxiety and mood disorders) using a dimensional-categorical system based on shared ED vulnerabilities and phenotypes. Such profile-based approaches have yet to be empirically evaluated, in part because a single multidimensional assessment of shared ED vulnerabilities and phenotypes amenable to profile-based classification has not been developed. The present studies aimed to provide an initial examination of a categorical-dimensional approach to ED classification (Study 1) as well as develop and evaluate a multidimensional self-report assessment of shared ED vulnerabilities and phenotypes (the Multidimensional Emotional Disorder Inventory [MEDI], Study 2). The samples consisted of 1,218 (Study 1) and 227 (Study 2) participants who presented for assessment and treatment at an outpatient ED treatment center. All participants were assessed using a semi-structured ED interview and a set of ED self-report questionnaires. The MEDI was completed only by the participants in Study 2. Study 1 used mixture modeling to identify six unobserved groups (classes) of individuals sharing similar profiles across seven dimensional ED vulnerability and phenotype indicators. The external validity of the profiles was supported when related ED covariates were added to the solution. The incremental validity of the profiles was supported using hierarchical regression models; the profiles accounted for unique variance in ED outcomes beyond DSM diagnoses. In Study 2, exploratory structural equation modeling (ESEM) and confirmatory factor analysis were used to evaluate the factor structure of the MEDI. ESEM supported an eight-factor solution of a 47-item version of the MEDI. Differential magnitude of correlation analyses supported the convergent/discriminant validity of seven of the eight MEDI scales. A five-class (profile) solution, consistent with Study 1, was found when mixture modeling was applied to the MEDI scales. Collectively, the present studies provide compelling evidence in support of the development and utility of a hybrid dimensional-categorical profile approach to emotional disorder classification using multidimensional self-report assessment methods such as the MEDI

Experiential avoidance as a mechanism of change across cognitive-behavioral therapy in a sample of participants with heterogeneous anxiety disorders

Despite the substantial evidence that supports the efficacy of cognitive-behavioral therapy for the treatment of anxiety and related disorders, our understanding of mechanisms of change throughout treatment remains limited. The goal of the current study was to examine changes in experiential avoidance across treatment in a sample of participants (N = 179) with heterogeneous anxiety disorders receiving various cognitive-behavioral therapy protocols. Univariate latent growth curve models were conducted to examine change in experiential avoidance across treatment, followed by parallel process latent growth curve models to examine the relationship between change in experiential avoidance and change in anxiety symptoms. Finally, bivariate latent difference score models were conducted to examine the temporal precedence of change in experiential avoidance and change in anxiety. Results indicated that there were significant reductions in experiential avoidance across cognitive-behavioral treatment, and that change in experiential avoidance was significantly associated with change in anxiety. Results from the latent difference score models indicated that change in experiential avoidance preceded and predicted subsequent changes in anxiety, whereas change in anxiety did not precede and predict subsequent changes in experiential avoidance. Taken together, these results provide additional support for reductions in experiential avoidance as a transdiagnostic mechanism in cognitive-behavioral therapy.First author draf

A preliminary examination of the acceptability, feasibility, and effectiveness of a telehealth cognitive-behavioral therapy group for social anxiety disorder

In light of the growing interest in, and need for, the telehealth delivery of health care, additional research is needed on the acceptability and effectiveness of these types of interventions. This study examined the acceptability, feasibility, and preliminary effectiveness of an adapted telehealth-delivered group cognitive-behavioral therapy (CBT) intervention for adults with social anxiety disorder (SAD). This report describes the adaptation and subsequent implementation of an 8-week telehealth-delivered group treatment designed to reduce symptoms of SAD. Specific adaptations for delivering treatment during the COVID-19 pandemic and the subsequent enactment of social distancing measures are discussed. Posttreatment data indicated that the intervention was feasible to implement in an outpatient mental health clinic, acceptable to participants, and associated with reduction in symptoms of social anxiety, general anxiety, depression, and stress.Accepted manuscrip

The effects of extraverted temperament on agoraphobia in panic disorder

Although situational avoidance is viewed as the most disabling aspect of panic disorder, few studies have evaluated how dimensions of neurotic (i.e., neuroticism, behavioral inhibition) and extraverted (i.e., extraversion, behavioral activation) temperament may influence the presence and severity of agoraphobia. Using logistic regression and structural equation modeling, we examined the unique effects of extraverted temperament on situational avoidance in a sample of 274 outpatients with a diagnosis of panic disorder with and without agoraphobia. Results showed low extraverted temperament (i.e., introversion) to be associated with both the presence and the severity of situational avoidance. Findings are discussed in regard to conceptualizations of conditioned avoidance, activity levels, sociability, and positive emotions within the context of panic disorder with agoraphobia

Approximating A Dsm‐5 Diagnosis Of Ptsd Using Dsm‐Iv Criteria

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111929/1/da22364.pd

Lifetime Prevalence Of Dsm‐Iv Mental Disorders Among New Soldiers In The U.S. Army: Results From The Army Study To Assess Risk And Resilience In Servicemembers (Army Starrs)

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/110630/1/da22316.pd

Mental Disorders, Comorbidity, and Pre‐enlistment Suicidal Behavior Among New Soldiers in the U.S. Army: Results from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS)

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/115994/1/sltb12153.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/115994/2/sltb12153_am.pd

Developing a Risk Model to Target High-Risk Preventive Interventions for Sexual Assault Victimization Among Female U.S. Army Soldiers

Sexual violence victimization is a significant problem among female U.S. military personnel. Preventive interventions for high-risk individuals might reduce prevalence but would require accurate targeting. We attempted to develop a targeting model for female Regular U.S. Army soldiers based on theoretically guided predictors abstracted from administrative data records. As administrative reports of sexual assault victimization are known to be incomplete, parallel machine learning models were developed to predict administratively recorded (in the population) and self-reported (in a representative survey) victimization. Capture–recapture methods were used to combine predictions across models. Key predictors included low status, crime involvement, and treated mental disorders. Area under the receiver operating characteristic curve was .83–.88. Between 33.7% and 63.2% of victimizations occurred among soldiers in the highest risk ventile (5%). This high concentration of risk suggests that the models could be useful in targeting preventive interventions, although final determination would require careful weighing of intervention costs, effectiveness, and competing risks

How well can post‐traumatic stress disorder be predicted from pre‐trauma risk factors? An exploratory study in the WHO World Mental Health Surveys

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108700/1/wps20150.pd

Mental Disorders, Comorbidity, and Pre-enlistment Suicidal Behavior Among New Soldiers in the U.S. Army: Results from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS)

We examined the associations between mental disorders and suicidal behavior (ideation, plans, and attempts) among new soldiers using data from the New Soldier Study (NSS) component of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS; n=38,507). Most new soldiers with a pre-enlistment history of suicide attempt reported a prior mental disorder (59.0%). Each disorder examined was associated with increased odds of suicidal behavior (ORs=2.6–8.6). Only PTSD and disorders characterized by irritability and impulsive/aggressive behavior (i.e., bipolar disorder, conduct disorder, oppositional defiant disorder, and attention-deficit/hyperactivity disorder) predicted unplanned attempts among ideators. Mental disorders are important predictors of pre-enlistment suicidal behavior among new soldiers and should figure prominently in suicide screening and prevention efforts.Psycholog