Differentiating irritable mood and disruptive behavior in adults.

INTRODUCTION: Irritability has both mood and behavioral manifestations. These frequently co-occur, and it is unclear to what extent they are dissociable domains. We used confirmatory factor analysis and external validators to investigate the independence of mood and behavioral components of irritability. METHODS: The sample comprised 246 patients (mean age 45 years; 63% female) from four outpatient programs (depression, anxiety, bipolar, and schizophrenia) at a tertiary hospital. A clinical instrument rated by trained clinicians was specifically designed to capture irritable mood and disruptive behavior dimensionally, as well as current categorical diagnoses i.e., intermittent explosive disorder (IED); oppositional defiant disorder (ODD); and an adaptation to diagnose disruptive mood dysregulation disorder (DMDD) in adults. Confirmatory factor analysis (CFA) was used to test the best fitting irritability models and regression analyses were used to investigate associations with external validators. RESULTS: Irritable mood and disruptive behavior were both frequent, but diagnoses of disruptive syndromes were rare (IED, 8%; ODD, 2%; DMDD, 2%). A correlated model with two dimensions, and a bifactor model with one general dimension and two specific dimensions (mood and behavior) both had good fit indices. The correlated model had root mean square error of approximation (RMSEA) = 0.077, with 90% confidence interval (90%CI) = 0.071-0.083; comparative fit index (CFI) = 0.99; and Tucker-Lewis index (TLI) = 0.99, while the bifactor model had RMSEA = 0.041; CFI = 0.99; and TLI = 0.99 respectively). In the bifactor model, external validity for differentiation of the mood and behavioral components of irritability was also supported by associations between irritable mood and impairment and clinical measures of depression and mania, which were not associated with disruptive behavior. CONCLUSIONS: Psychometric and external validity data suggest both overlapping and specific features of the mood vs. disruptive behavior dimensions of irritability.

Decoding rumination: A machine learning approach to a transdiagnostic sample of outpatients with anxiety, mood and psychotic disorders.

OBJECTIVE: To employ machine learning algorithms to examine patterns of rumination from RDoC perspective and to determine which variables predict high levels of maladaptive rumination across a transdiagnostic sample. METHOD: Sample of 200 consecutive, consenting outpatient referrals with clinical diagnoses of schizophrenia, schizoaffective, bipolar, depression, anxiety disorders, obsessive compulsive and post-traumatic stress. Machine learning algorithms used a range of variables including sociodemographics, serum levels of immune markers (IL-6, IL-1ß, IL-10, TNF-α and CCL11) and BDNF, psychiatric symptoms and disorders, history of suicide and hospitalizations, functionality, medication use and comorbidities. RESULTS: The best model (with recursive feature elimination) included the following variables: socioeconomic status, illness severity, worry, generalized anxiety and depressive symptoms, and current diagnosis of panic disorder. Linear support vector machine learning differentiated individuals with high levels of rumination from those ones with low (AUC = 0.83, sensitivity = 75, specificity = 71). CONCLUSIONS: Rumination is known to be associated with poor prognosis in mental health. This study suggests that rumination is a maladaptive coping style associated not only with worry, distress and illness severity, but also with socioeconomic status. Also, rumination demonstrated a specific association with panic disorder.

The association between social skills deficits and family history of mood disorder in bipolar I disorder

Objective: To compare social skills and related executive functions among bipolar disorder (BD) patients with a family history of mood disorders (FHMD), BD patients with no FHMD and healthy control (HCs). Methods: We evaluated 20 euthymic patients with FHMD, 17 euthymic patients without FHMD, and 31 HCs using the Social Skills Inventory (SSI) and a neuropsychological battery evaluating executive function, inhibitory control, verbal fluency and estimated intelligence. Results: Both BD groups had lower SSI scores than controls. Scores for one subfactor of the social skills questionnaire, conversational skills and social performance, were significantly lower among patients with FHMD than among patients without FHMD (p = 0.019). Both groups of BD patients exhibited significant deficits in initiation/inhibition, but only BD patients with FHMD had deficits in verbal fluency, both compared to HC. There were no associations between social skills questionnaire scores and measures of cognitive function. Conclusion: Euthymic BD patients have lower social skills and executive function performance than HC. The presence of FHMD among BD patients is specifically associated with deficits in conversational and social performance skills, in addition to deficits in verbal fluency. Both characteristics might be associated with a common genetically determined pathophysiological substrate.

The association between social skills deficits and family history of mood disorder in bipolar I disorder.

OBJECTIVE: To compare social skills and related executive functions among bipolar disorder (BD) patients with a family history of mood disorders (FHMD), BD patients with no FHMD and healthy control (HCs). METHODS: We evaluated 20 euthymic patients with FHMD, 17 euthymic patients without FHMD, and 31 HCs using the Social Skills Inventory (SSI) and a neuropsychological battery evaluating executive function, inhibitory control, verbal fluency and estimated intelligence. RESULTS: Both BD groups had lower SSI scores than controls. Scores for one subfactor of the social skills questionnaire, conversational skills and social performance, were significantly lower among patients with FHMD than among patients without FHMD (p = 0.019). Both groups of BD patients exhibited significant deficits in initiation/inhibition, but only BD patients with FHMD had deficits in verbal fluency, both compared to HC. There were no associations between social skills questionnaire scores and measures of cognitive function. CONCLUSION: Euthymic BD patients have lower social skills and executive function performance than HC. The presence of FHMD among BD patients is specifically associated with deficits in conversational and social performance skills, in addition to deficits in verbal fluency. Both characteristics might be associated with a common genetically determined pathophysiological substrate.