Behavioral Assessment of Core ADHD Symptoms Using the QbTest

Objective: Hyperactivity, one of the core symptoms of ADHD, has been mostly neglected in neuropsychological assessment of childhood ADHD. The neuropsychological Quantified behavior Test (QbTest) separately assesses all three core symptoms of ADHD on a behavioral level. Factor structure of the QbTest and its concurrent and discriminant validity are presented. Method: An exploratory factor analysis (n = 828 children) was performed. In a second sample (n = 102 children) a Multi-Trait-Multi-Method (MTMM) approach was used for validity analyses. Results: A three factorial model explained 76 % of the total variance, with the resulting QbTest factors significantly influenced by age and gender. The MTMM approach yielded promising results for discriminant, yet inconsistent findings for concurrent validity between the QbTest and another attention test as well as for Conners' Parent and Teacher Rating Scales. Conclusion: Results indicate that the QbTest may be helpful for the behavioral assessment of childhood ADHD, yet further studies on its psychometric quality and clinical utility are needed. (J. of Att. Dis. 2012; XX(X) 1-XX).

The Bern psychopathology scale for the assessment of system-specific psychotic symptoms

The translation from psychiatric core symptoms to brain functions and vice versa is a largely unresolved issue. In particular, the search for disorders of single brain regions explaining classical symptoms has not yielded the expected results. Based on the assumption that the psychopathology of psychosis is related to a functional imbalance of higher-order brain systems, the authors focused on three specific candidate brain circuitries, namely the language, and limbic and motor systems. These domains are of particular interest for understanding the disastrous communication breakdown during psychotic disorders. Core symptoms of psychosis were mapped on these domains by shaping their definitions in order to match the related brain functions. The resulting psychopathological assessment scale was tested for interrater reliability and internal consistency in a group of 168 psychotic patients. The items of the scale were reliable and a principal component analysis (PCA) was best explained by a solution resembling the three candidate systems. Based on the results, the scale was optimized as an instrument to identify patient subgroups characterized by a prevailing dysfunction of one or more of these systems. In conclusion, the scale is apt to distinguish symptom domains related to the activity of defined brain systems. PCA showed a certain degree of independence of the system-specific symptom clusters within the patient group, indicating relative subgroups of psychosis. The scale is understood as a research instrument to investigate psychoses based on a system-oriented approach. Possible immediate advantages in the clinical application of the understanding of psychoses related to system-specific symptom domains are also discussed.

Pathways that make voices - White matter changes in auditory hallucinations

BACKGROUND: The origin of auditory hallucinations, which are one of the core symptoms of schizophrenia, is still a matter of debate. It has been hypothesized that alterations in connectivity between frontal and parietotemporal speech-related areas might contribute to the pathogenesis of auditory hallucinations. These networks are assumed to become dysfunctional during the generation and monitoring of inner speech. Magnetic resonance diffusion tensor imaging is a relatively new in vivo method to investigate the directionality of cortical white matter tracts. OBJECTIVE: To investigate, using diffusion tensor imaging, whether previously described abnormal activation patterns observed during auditory hallucinations relate to changes in structural interconnections between the frontal and parietotemporal speech-related areas. METHODS: A 1.5 T magnetic resonance scanner was used to acquire twelve 5-mm slices covering the Sylvian fissure. Fractional anisotropy was assessed in 13 patients prone to auditory hallucinations, in 13 patients without auditory hallucinations, and in 13 healthy control subjects. Structural magnetic resonance imaging was conducted in the same session. Based on an analysis of variance, areas with significantly different fractional anisotropy values between groups were selected for a confirmatory region of interest analysis. Additionally, descriptive voxel-based t tests between the groups were computed. RESULTS: In patients with hallucinations, we found significantly higher white matter directionality in the lateral parts of the temporoparietal section of the arcuate fasciculus and in parts of the anterior corpus callosum compared with control subjects and patients without hallucinations. Comparing patients with hallucinations with patients without hallucinations, we found significant differences most pronounced in the left hemispheric fiber tracts, including the cingulate bundle. CONCLUSION: Our findings suggest that during inner speech, the alterations of white matter fiber tracts in patients with frequent hallucinations lead to abnormal coactivation in regions related to the acoustical processing of external stimuli. This abnormal activation may account for the patients' inability to distinguish self-generated thoughts from external stimulation.

15 Years of Microstate Research in Schizophrenia - Where Are We? A Meta-Analysis

Schizophrenia patients show abnormalities in a broad range of task demands. Therefore, an explanation common to all these abnormalities has to be sought independently of any particular task, ideally in the brain dynamics before a task takes place or during resting state. For the neurobiological investigation of such baseline states, EEG microstate analysis is particularly well suited, because it identifies subsecond global states of stable connectivity patterns directly related to the recruitment of different types of information processing modes (e.g., integration of top-down and bottom-up information). Meanwhile, there is an accumulation of evidence that particular microstate networks are selectively affected in schizophrenia. To obtain an overall estimate of the effect size of these microstate abnormalities, we present a systematic meta-analysis over all studies available to date relating EEG microstates to schizophrenia. Results showed medium size effects for two classes of microstates, namely, a class labeled C that was found to be more frequent in schizophrenia and a class labeled D that was found to be shortened. These abnormalities may correspond to core symptoms of schizophrenia, e.g., insufficient reality testing and self-monitoring as during auditory verbal hallucinations. As interventional studies have shown that these microstate features may be systematically affected using antipsychotic drugs or neurofeedback interventions, these findings may help introducing novel diagnostic and treatment options.

Adjustment Disorders Are Uniquely Suited for eHealth Interventions: Concept and Case Study

Background: Adjustment disorders (also known as mental distress in response to a stressor) are among the most frequently diagnosed mental disorders in psychiatry and clinical psychology worldwide. They are also commonly diagnosed in clients engaging in deliberate self-harm and in those consulting general practitioners. However, their reputation in research-oriented mental health remains weak since they are largely underresearched. This may change when the International Statistical Classification of Diseases-11 (ICD-11) by the World Health Organization is introduced, including a new conceptualization of adjustment disorders as a stress-response disorder with positively defined core symptoms. Objective: This paper provides an overview of evidence-based interventions for adjustment disorders. Methods: We reviewed the new ICD-11 concept of adjustment disorder and discuss the the rationale and case study of an unguided self-help protocol for burglary victims with adjustment disorder, and its possible implementation as an eHealth intervention. Results: Overall, the treatment with the self-help manual reduced symptoms of adjustment disorder, namely preoccupation and failure to adapt, as well as symptoms of depression, anxiety, and stress. Conclusions: E-mental health options are considered uniquely suited for offering early intervention after the experiences of stressful life events that potentially trigger adjustment disorders.

Improving the clinical prediction of psychosis by combining ultra-high risk criteria and cognitive basic symptoms

OBJECTIVE Cognitive impairments are regarded as a core component of schizophrenia. However, the cognitive dimension of psychosis is hardly considered by ultra-high risk (UHR) criteria. Therefore, we studied whether the combination of symptomatic UHR criteria and the basic symptom criterion "cognitive disturbances" (COGDIS) is superior in predicting first-episode psychosis. METHOD In a naturalistic 48-month follow-up study, the conversion rate to first-episode psychosis was studied in 246 outpatients of an early detection of psychosis service (FETZ); thereby, the association between conversion, and the combined and singular use of UHR criteria and COGDIS was compared. RESULTS Patients that met UHR criteria and COGDIS (n=127) at baseline had a significantly higher risk of conversion (hr=0.66 at month 48) and a shorter time to conversion than patients that met only UHR criteria (n=37; hr=0.28) or only COGDIS (n=30; hr=0.23). Furthermore, the risk of conversion was higher for the combined criteria than for UHR criteria (n=164; hr=0.56 at month 48) and COGDIS (n=158; hr=0.56 at month 48) when considered irrespective of each other. CONCLUSIONS Our findings support the merits of considering both COGDIS and UHR criteria in the early detection of persons who are at high risk of developing a first psychotic episode within 48months. Applying both sets of criteria improves sensitivity and individual risk estimation, and may thereby support the development of stage-targeted interventions. Moreover, since the combined approach enables the identification of considerably more homogeneous at-risk samples, it should support both preventive and basic research.

Head movement synchrony in social interactions of patients with schizophrenia indicates symptoms, cognition and social functioning

Background: Disturbed interpersonal communication is a core problem in schizophrenia. Patients with schizophrenia often appear disconnected and "out of sync" when interacting with others. This may involve perception, cognition, motor behavior, and nonverbal expressiveness. Although well-known from clinical observation, mainstream research has neglected this area. Corresponding theoretical concepts, statistical methods, and assessment were missing. In recent research, however, it has been shown that objective, video-based measures of nonverbal behavior can be used to reliably quantify nonverbal behavior in schizophrenia. Newly developed algorithms allow for a calculation of movement synchrony. We found that the objective amount of movement of patients with schizophrenia during social interactions was closely related to the symptom profiles of these patients (Kupper et al., 2010). In addition and above the mere amount of movement, the degree of synchrony between patients and healthy interactants may be indicative of various problems in the domain of interpersonal communication and social cognition. Methods: Based on our earlier study, head movement synchrony was assessed objectively (using Motion Energy Analysis, MEA) in 378 brief, videotaped role-play scenes involving 27 stabilized outpatients diagnosed with paranoid-type schizophrenia. Results: Lower head movement synchrony was indicative of symptoms (negative symptoms, but also of conceptual disorganization and lack of insight), verbal memory, patients’ self-evaluation of competence, and social functioning. Many of these relationships remained significant even when corrected for the amount of movement of the patients. Conclusion: The results suggest that nonverbal synchrony may be an objective and sensitive indicator of the severity of symptoms, cognition and social functioning.