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Background: A growing number of studies are questioning the validity of current DSM diagnoses, either as "discrete" or distinct mental disorders and/or as phenotypically homogeneous syndromes. In this study, we investigated how symptom domains in patients with a main diagnosis of obsessive-compulsive disorder (OCD), panic disorder (PD) and social anxiety disorder (SAD) coaggregate. We predicted that symptom domains would be unrelated to DSM diagnostic categories and less likely to cluster with each other as severity increases.
Methods: One-hundred eight treatment seeking patients with a main diagnosis of OCD, SAD or PD were assessed with the Dimensional Obsessive-Compulsive Scale (DOCS), the Social Phobia Inventory (SPIN), the Panic and Agoraphobia Scale (PAS), the Anxiety Sensitivity Index-Revised (ASI-R), and the Beck Depression and Anxiety Inventories (BDI and BAI, respectively). Subscores generated by each scale (herein termed "symptom domains") were used to categorize individuals into mild, moderate and severe subgroups through K-means clusterization and subsequently analysed by means of multiple correspondence analysis.
Results: Broadly, we observed that symptom domains of OCD, SAD or PD tend to cluster on the basis of their severities rather than their DSM diagnostic labels. In particular, symptom domains and disorders were grouped into (1) a single mild "neurotic" syndrome characterized by multiple, closely related and co-occurring mild symptom domains; (2) two moderate (complicated and uncomplicated) "neurotic" syndromes (the former associated with panic disorder); and (3) severe but dispersed "neurotic" symptom domains.
Conlusion: Our findings suggest that symptoms domains of treatment seeking patients with OCD and anxiety disorders tend to be better conceptualized in terms of severity rather than rigid diagnostic boundaries.
Background:
There is growing evidence that Internet-based cognitive behavioral therapy (ICBT) is as effective as a stand-alone treatment and helps facilitating access to treatment. Given the complexity of the treatment, we argue that the effect of ICBT could be even greater if guided by a therapist, as this could increase treatment adherence. We modified an established and well-evaluated treatment approach and developed a mobile application for treating social anxiety disorder (SAD). In the present study, we compare the efficacy of app use alone (APP) with video-based, therapist-guided app use (TG-APP) and with a wait-list control group (WLC) in terms of symptom reduction, and various secondary outcomes such as increase in quality of life or decrease of general psychological distress.
Methods/design:
A within-between interaction design with randomization to one of three conditions will be used. In the APP condition, patients receive only the app without any additional contact with therapists, while in the TG-APP condition, therapists provide 8 sessions of video-based treatment in addition to using the app. The study will be conducted in two university outpatient treatment centers with reliably diagnosed SAD patients. The primary outcome will be defined as change in SAD symptoms, as measured by the Liebowitz Social Anxiety Scale (expert rating). Furthermore, a wide range of self-reports and clinician ratings for other symptoms (depression, general psychopathology) or quality of life will be used. A simulation-based power analysis for a 3 × 2 interaction effect (group × time) on the primary outcome in a linear mixed model resulted in a total sample size of N = 165.
Discussion:
The present study will be one of the first to examine the additional benefit of therapist-guided video sessions regarding the use of an app treating SAD. Study results are pivotal to future treatment application in SAD.
Background: While the efficacy of cognitive therapy (CT) has been well established for social anxiety disorder (SAD) in several randomized controlled trials, there are still large differences between trials with respect to effect sizes. The present study investigates the question of whether enhanced training and the use of behavioral experiments (BEs) increases the efficacy of traditional CT, based on verbal methods of cognitive restructuring. Methods/design: A mixed within/between conditions design will be applied, with therapists and patients being randomly allocated to one of two conditions: (1) training of CT plus BEs, (2) training of CT “as usual”. Sixty patients with the primary diagnosis of SAD will be recruited and treated in the outpatient clinic of the Department of Psychology, University of Frankfurt. To ensure adherence to therapist protocols, all therapists will be trained and supervised by the project coordinators. In addition, videotaped treatment sessions will be independently evaluated to guarantee both adherence to protocols and the quality of the intervention. Treatment effects will be assessed by independent SAD symptom ratings using the Liebowitz Social Anxiety Scale as the primary outcome measure and self-report measures as secondary outcome measures. Discussion: The present cognitive behavioral therapy (CBT) trial will be the first to clarify the contribution of BEs to the efficacy of CT in a randomized controlled design. Study results are relevant to clinical training and implementation of evidence-based treatments. Trial registration: German Clinical Trials Register International Clinical Trials Registry Platform (ICTRP) identifier: DRKS00014349. Trial status: recruiting.
Body dysmorphic disorder (BDD), together with its subtype muscle dysmorphia (MD), has been relocated from the Somatoform Disorders category in the DSM-IV to the newly created Obsessive-Compulsive and Related Disorders category in the DSM-5. Both categorizations have been criticized, and an empirically derived classification of BDD is lacking. A community sample of N = 736 participants completed an online survey assessing different psychopathologies. Using a structural equation modeling approach, six theoretically derived models, which differed in their allocation of BDD symptoms to various factors (i.e. general psychopathology, somatoform, obsessive-compulsive and related disorders, affective, body image, and BDD model) were tested in the full sample and in a restricted sample (n = 465) which indicated primary concerns other than shape and weight. Furthermore, measurement invariance across gender was examined. Of the six models, only the body image model showed a good fit (CFI = 0.972, RMSEA = 0.049, SRMR = 0.027, TLI = 0.959), and yielded better AIC and BIC indices than the competing models. Analyses in the restricted sample replicated these findings. Analyses of measurement invariance of the body image model showed partial metric invariance across gender. The findings suggest that a body image model provides the best fit for the classification of BDD and MD. This is in line with previous studies showing strong similarities between eating disorders and BDD, including MD. Measurement invariance across gender indicates a comparable presentation and comorbid structure of BDD in males and females, which also corresponds to the equal prevalence rates of BDD across gender.