12 research outputs found
Prevalence and profile of depressive mixed state in patients with autism spectrum disorder
Purpose: The present study aimed to clarify prevalence and profile of depressive mixed state (DMX) in depressed individuals with autism spectrum disorder (ASD).
Patients and methods: The Quick Inventory of Depressive Symptomatology Self-Report Japanese version (QIDS-SR-J) and global assessment of functioning (GAF) were administered to 182 consecutive patients (36 ASD and 146 non-ASD subjects) with a major depressive episode (MDE). DMX was categorically diagnosed according to the criteria for mixed depression (MD) by Benazzi and mixed features (MF) specifier by DSM-5. Severity of DMX was assessed by the self-administered 12-item questionnaire for DMX (DMX-12). Clinical backgrounds and incidence/severity of DMX were compared between the ASD and non-ASD groups.
Results: ASD patients showed higher prevalence of MD than non-ASD patients (36.1% versus 18.5%). Mood lability, distractibility, impulsivity, aggression, irritability, dysphoria and risk-taking behavior as mixed symptoms were more prevalent in ASD patients than those in non-ASD patients, together with higher scores of total DMX-12 and its disruptive emotion/behavior cluster. Multiple regression analysis revealed significant contribution of ASD to the disruptive emotion/behavior symptoms.
Conclusion: Careful monitoring and management of potential DMX are warranted in depressed ASD individuals
Development of a 20-item questionnaire for drinking behavior pattern (DBP-20) toward personalized behavioral approaches for alcohol use disorder
Although screening tools are available for alcohol use disorders (AUD), such as the Alcohol Use Disorders Identification Test (AUDIT), these tools do not directly characterize individual drinking behavior for patients with AUD. Therefore, the aim of this study was to develop a new self-report questionnaire to identify the characteristics of drinking behavior patterns in patients with AUD. The study team developed a self-administered 20-item questionnaire for drinking behavior pattern (DBP-20) based on semistructured interviews of patients with AUD. The DBP-20 and AUDIT were administered to 232 patients with AUD and 222 normal drinkers (1 ≤ AUDIT <20) as controls. Exploratory factor analysis of the DBP-20 was conducted for patients with AUD, followed by comparisons of its item and subscale scores between patients with AUD and controls. Correlations of AUDIT with total and subscale scores of the DBP-20 were also analyzed. Receiver operating characteristic (ROC) analyses for the DBP-20 and its subscales were performed to distinguish patients with AUD from controls. Exploratory factor analysis revealed a multidimensional 4-factor model of the DBP-20: coping with negative affect, automaticity, enhancement, and social use. Significant differences in DBP-20 total and subscale scores were observed for patients with AUD versus controls for all factors, except the social use subscale. Both the coping with negative affect and automaticity subscale scores as well as total DBP-20 scores were highly correlated with AUDIT scores. Total DBP-20 scores showed the greatest sensitivity, negative predictive value, and area under the ROC curve to distinguish patients with AUD from normal drinkers. Drinking as a means of coping with negative affect and automaticity may be specific for patients with AUD. DBP-20 may help patients with AUD to be aware of their own targeted problematic drinking behaviors and to seek their personalized behavioral approaches in a collaborative relationship with therapists
Development of the 12-item questionnaire for quantitative assessment of depressive mixed state (DMX-12)
Background: Conventional categorical criteria have limitations in assessing the prevalence and severity of depressive mixed state (DMX). Thus, we have developed a new scale for screening and quantification of DMX and examined the symptomatological structure and severity of DMX in individuals with major depressive episode (MDE). Methods: Subjects were 154 patients with MDE (57 males and 97 females; age 13–83 years). Our original Japanese version of the self-administered 12-item questionnaire to assess DMX (DMX-12), together with the Quick Inventory of Depressive Symptomatology Self- Report Japanese version (QIDS-SR-J) and global assessment of functioning, were administered to each participant. The symptomatological structure of the DMX-12 was examined by exploratory factor analysis. Multiple regression analyses were used to analyze factors contributing to the DMX-12 scale. The relationships of this scale with categorical diagnoses (mixed depression by Benazzi and mixed features by DSM-5) were also investigated. Results: A three-factor model of the DMX-12 was extracted from exploratory factor analysis, namely, “spontaneous instability”, “vulnerable responsiveness”, and “disruptive emotion/behavior”. Multiple regression analyses revealed that age was negatively correlated with total DMX-12 score, while bipolarity and the QIDS-SR-J score were positively correlated. A higher score on the disruptive emotion/behavior subscale was observed in patients with mixed depression and mixed features. Conclusion: The DMX-12 seems to be useful for screening DMX in conjunction with conventional categorical diagnoses. Severely depressed younger subjects with potential bipolarity are more likely to develop DMX. The disruptive emotion/behavior subscale of the DMX-12 may be the most helpful in distinguishing patients with DMX from non-mixed patients.博士(医学)琉球大
Diagnosis & treatment of mixed depression
Although the definition of depressive mixed state, more commonly known as mixed depression, is still controversial, about one-third of major depressive episodes are held to contain mixed components. The most frequent manifestations of mixed depression are irritability, distractibility and psychomotor agitation, although these symptoms are not included in the mixed features during a major depressive episode according to the DSM-5 criteria, which is therefore unlikely to cover the full scope of mixed depression in real-world settings. Mixed depression often accompanies risky behavior including impulsive suicide attempts. The early detection and treatment of these unstable conditions is therefore necessary. Also, sufficiently sensitive and specific screening methods for depressive mixed state are needed to avoid both under- and over-diagnosis. Antidepressants should be avoided since these drugs often worsen irritability, agitation and impulsivity, and increase risky behavior. Instead, combination therapy with mood stabilizer(s) to prevent the relapse of the depressive mixed state and atypical antipsychotics for rapid stabilization in the acute phase should be considered. Because there is very little evidence for effective pharmacotherapy in mixed depression, the efficacy of various mood-stabilizing agents, either as monotherapy or in combination therapies, should be extensively examined in the future using quantitative assessments of the psychopathology of mixed depression in patients with confirmed diagnoses of mixed depression
Development of the 12-item questionnaire for quantitative assessment of depressive mixed state (DMX-12)
Background: Conventional categorical criteria have limitations in assessing the prevalence and severity of depressive mixed state (DMX). Thus, we have developed a new scale for screening and quantification of DMX and examined the symptomatological structure and severity of DMX in individuals with major depressive episode (MDE).
Methods: Subjects were 154 patients with MDE (57 males and 97 females; age 13-83 years). Our original Japanese version of the self-administered 12-item questionnaire to assess DMX (DMX-12), together with the Quick Inventory of Depressive Symptomatology Self-Report Japanese version (QIDS-SR-J) and global assessment of functioning, were administered to each participant. The symptomatological structure of the DMX-12 was examined by exploratory factor analysis. Multiple regression analyses were used to analyze factors contributing to the DMX-12 scale. The relationships of this scale with categorical diagnoses (mixed depression by Benazzi and mixed features by DSM-5) were also investigated.
Results: A three-factor model of the DMX-12 was extracted from exploratory factor analysis, namely, "spontaneous instability", "vulnerable responsiveness", and "disruptive emotion/behavior". Multiple regression analyses revealed that age was negatively correlated with total DMX-12 score, while bipolarity and the QIDS-SR-J score were positively correlated. A higher score on the disruptive emotion/behavior subscale was observed in patients with mixed depression and mixed features.
Conclusion: The DMX-12 seems to be useful for screening DMX in conjunction with conventional categorical diagnoses. Severely depressed younger subjects with potential bipolarity are more likely to develop DMX. The disruptive emotion/behavior subscale of the DMX-12 may be the most helpful in distinguishing patients with DMX from non-mixed patients
Aberrant Large-Scale Network Interactions Across Psychiatric Disorders Revealed by Large-Sample Multi-Site Resting-State Functional Magnetic Resonance Imaging Datasets
Background and Hypothesis
Dynamics of the distributed sets of functionally synchronized brain regions, known as large-scale networks, are essential for the emotional state and cognitive processes. However, few studies were performed to elucidate the aberrant dynamics across the large-scale networks across multiple psychiatric disorders. In this paper, we aimed to investigate dynamic aspects of the aberrancy of the causal connections among the large-scale networks of the multiple psychiatric disorders.
Study Design
We applied dynamic causal modeling (DCM) to the large-sample multi-site dataset with 739 participants from 4 imaging sites including 4 different groups, healthy controls, schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BD), to compare the causal relationships among the large-scale networks, including visual network, somatomotor network (SMN), dorsal attention network (DAN), salience network (SAN), limbic network (LIN), frontoparietal network, and default mode network.
Study Results
DCM showed that the decreased self-inhibitory connection of LIN was the common aberrant connection pattern across psychiatry disorders. Furthermore, increased causal connections from LIN to multiple networks, aberrant self-inhibitory connections of DAN and SMN, and increased self-inhibitory connection of SAN were disorder-specific patterns for SCZ, MDD, and BD, respectively.
Conclusions
DCM revealed that LIN was the core abnormal network common to psychiatric disorders. Furthermore, DCM showed disorder-specific abnormal patterns of causal connections across the 7 networks. Our findings suggested that aberrant dynamics among the large-scale networks could be a key biomarker for these transdiagnostic psychiatric disorders