Comparisons of psychological characteristics between schizophrenia, bipolar disorder and depressive disorder patients

2016 ◽  
Vol 33 (S1) ◽  
pp. S534-S534
Author(s):  
M.S. Shin
Keyword(s):  
Bipolar Disorder ◽  
Depressive Disorder ◽  
Scoring System ◽  
Psychological Characteristics ◽  
Bipolar Group ◽  
Schizophrenic Group ◽  
Social Discomfort ◽  
Competing Interest ◽  
Depressive Patients ◽  
Depressive Group

Introduction and objectivesThis study was conducted to examine the psychological characteristics of the schizophrenia (n = 20), bipolar disorder (n = 20) and depressive disorder (n = 13) patients on MMPI-2 and Rorschach responses.MethodsMMPI-2 and Rorschach was individually administered to all patients, and their Rorschach responses were scored by Exner's comprehensive scoring system. The means of T scores of MMPI-2 subscales and Rorschach scores were compared among the three groups.ResultsThe schizophrenic and bipolar disorder groups showed significantly higher scores on the MMPI-2 K scale than the depressive group, while the depressive group showed significantly higher score on MMPI-2 Si scale than the schizophrenic and bipolar groups. In Rorschach responses, the bipolar and depressive groups obtained significantly higher scores on two variables (FM + m, m) than the schizophrenic group. The bipolar group obtained significantly higher scores on three variables (es, CP, a), suggesting hyperactivity and mood dysregulation.ConclusionsThese results suggested that patients with depressive disorder might subjectively suffer from more severe emotional and social discomfort than patients with the schizophrenia and bipolar disorder, while patients with bipolar disorder and schizophrenia would be more defensive than the depressive patients.Disclosure of interestThe author has not supplied his/her declaration of competing interest.

Partial psychiatric hospitalization and differences in clinical outcome

2016 ◽  
Vol 33 (S1) ◽  
pp. S195-S195
Author(s):  
J. Vázquez Bourgon ◽  
F. Hoyuela Zatón ◽  
E. Gómez-Ruiz ◽  
E. Cortazar Lopez ◽  
B. Agüeros Perez ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Personality Disorder ◽  
Clinical Outcome ◽  
Depressive Disorder ◽  
Psychiatric Hospitalization ◽  
Clinical Severity ◽  
Partial Hospitalization ◽  
Significant Difference ◽  
Competing Interest ◽  
Clinical Resource

IntroductionIntensive treatment in partial hospitalization unit may represent an efficient alternative to traditional inward hospitalization. However, there is evidence suggesting that this clinical resource may not be equally effective for every psychiatric disorder.ObjectivesWe aimed to study possible differences in the effectiveness of treatment in a partial hospitalization regime for different psychiatric disorders.MethodsThree hundred and thirty-one patients were admitted to the Valdecilla acute psychiatric day hospital between January 2013 and January 2015. Clinical severity was assessed using BPRS-E and HoNOS scales at admission and discharge. Other relevant clinical and socio-demographic variables were recorded. For statistical comparisons, patients were clustered into 4 wide diagnostic groups (non-affective psychosis; bipolar disorder; depressive disorder; personality disorder).ResultsWe observed a significant difference in the status of discharge (χ2 = 12.227; P = 0.007). Thus, depressive patients were more frequently discharged because of clinical improvement, while patients with a main diagnose of personality disorder abandoned the treatment more frequently (23% vs. 4,0%)When analysing the clinical outcome at discharge, we found that patients with a diagnosis of bipolar disorder showed greater improvement in BPRS (F = 5.305; P = 0.001) than those diagnosed of psychosis or depressive disorder. Interestingly, we found no significant differences between diagnoses in hospital re-admission in the following 6 months after being discharged.ConclusionsOur results suggest that acute treatment in partial hospitalization regime may be more effective for bipolar and depressive disorder, and particularly less effective for those patients with a personality disorder.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Volumetric MRI measurements in bipolars compared with schizophrenics and healthy controls

1994 ◽  
Vol 24 (3) ◽  
pp. 689-699 ◽  
Author(s):  
I. Harvey ◽  
R. Persaud ◽  
M. A. Ron ◽  
G. Baker ◽  
R. M. Murray
Keyword(s):  
Bipolar Disorder ◽  
Healthy Controls ◽  
Volumetric Mri ◽  
Psychotic Illness ◽  
Cortical Volume ◽  
Bipolar Group ◽  
Schizophrenic Group ◽  
Mri Measurements

SynopsisTwenty-six patients with RDC bipolar disorder were compared with a previously reported group of 48 RDC schizophrenics and 34 healthy controls, using volumetric MRI measurements of cerebral, cortical and sulcal volumes. The bipolar group appeared no different from the controls, and both of these groups had significantly larger cerebral and cortical volumes than the schizophrenics. Our previous report of a significantly reduced cortical volume in the schizophrenic group, with a corresponding increase in the volume of sulcal fluid is, therefore, not a generalized feature of psychotic illness but may be more specific to schizophrenia.

scholarly journals The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rona J. Strawbridge ◽  
Keira J. A. Johnston ◽  
Mark E. S. Bailey ◽  
Damiano Baldassarre ◽  
Breda Cullen ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
European Ancestry ◽  
Cardiometabolic Disease ◽  
Metabolic Profiles ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Major Depressive ◽  
Increased Risk

AbstractUnderstanding why individuals with severe mental illness (Schizophrenia, Bipolar Disorder and Major Depressive Disorder) have increased risk of cardiometabolic disease (including obesity, type 2 diabetes and cardiovascular disease), and identifying those at highest risk of cardiometabolic disease are important priority areas for researchers. For individuals with European ancestry we explored whether genetic variation could identify sub-groups with different metabolic profiles. Loci associated with schizophrenia, bipolar disorder and major depressive disorder from previous genome-wide association studies and loci that were also implicated in cardiometabolic processes and diseases were selected. In the IMPROVE study (a high cardiovascular risk sample) and UK Biobank (general population sample) multidimensional scaling was applied to genetic variants implicated in both psychiatric and cardiometabolic disorders. Visual inspection of the resulting plots used to identify distinct clusters. Differences between these clusters were assessed using chi-squared and Kruskall-Wallis tests. In IMPROVE, genetic loci associated with both schizophrenia and cardiometabolic disease (but not bipolar disorder or major depressive disorder) identified three groups of individuals with distinct metabolic profiles. This grouping was replicated within UK Biobank, with somewhat less distinction between metabolic profiles. This work focused on individuals of European ancestry and is unlikely to apply to more genetically diverse populations. Overall, this study provides proof of concept that common biology underlying mental and physical illness may help to stratify subsets of individuals with different cardiometabolic profiles.

Predictors of conversion of major depressive disorder to bipolar disorder

2021 ◽  
pp. 113939
Author(s):  
Satish Suhas ◽  
Abha Thakurdesai ◽  
Amal Jolly Joseph ◽  
Chittaranjan Andrade
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Major Depressive

scholarly journals Response Processes to Looming Appetitive and Aversive Cues in Euthymic Bipolar Patients and Their First-Degree Relatives: An Exploratory Study

2020 ◽  
pp. 025371762097528
Author(s):  
Velprashanth Venkatesan ◽  
Christoday R J Khess ◽  
Umesh Shreekantiah ◽  
Nishant Goyal ◽  
K. K. Kshitiz
Keyword(s):  
Bipolar Disorder ◽  
Healthy Controls ◽  
Sensitivity To Reward ◽  
Bipolar Group ◽  
First Degree Relatives ◽  
Vulnerability Model ◽  
Increased Sensitivity ◽  
Appetitive Cues ◽  
Spectrum Disorders ◽  
Bipolar Patients

Background: Patients with bipolar disorder demonstrate increased sensitivity to appetitive/rewarding stimuli even during euthymia. On presentation of arousing pictures, they show a peculiar response, suggesting heightened vigilance. While responding to looming arousing cues, studies show subjects with anxiety spectrum disorders exhibit increased reaction time (RT), explained by the “looming-vulnerability model.” This study aimed to investigate the responses to looming arousing cues in euthymic bipolar patients and their first-degree relatives, as compared to healthy controls. Method: A looming appetitive and aversive cue paradigm was designed for assessing the RT of patients to process appetitive and aversive cues. The behavioral inhibition/activation and sensitivity to reward/punishment amongst the groups were also assessed. Results: The bipolar group showed significantly longer RT to process appetitive cues irrespective of the looming condition. Aversive cues elicited significantly longer RT in both the bipolar group and in first-degree relatives, but only when presented with the looming condition. Significant looming bias was elicited in the bipolar group which suggested a particular cognitive style to looming cues. A composite measure of RT along with sensitivity to reward/punishment distinguishes the bipolar group and their first-degree relatives from the healthy controls. Conclusion: The looming vulnerability model may provide important insights for future exploration of cognitive endophenotypes in bipolar disorder.

scholarly journals A machine learning algorithm to differentiate bipolar disorder from major depressive disorder using an online mental health questionnaire and blood biomarker data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jakub Tomasik ◽  
Sung Yeon Sarah Han ◽  
Giles Barton-Owen ◽  
Dan-Mircea Mirea ◽  
Nayra A. Martin-Key ◽  
...  
Keyword(s):  
Mental Health ◽  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Diagnostic Algorithm ◽  
Health Questionnaire ◽  
Major Depressive ◽  
Blood Biomarker ◽  
Mental Health Questionnaire ◽  
Biomarker Data

AbstractThe vast personal and economic burden of mood disorders is largely caused by their under- and misdiagnosis, which is associated with ineffective treatment and worsening of outcomes. Here, we aimed to develop a diagnostic algorithm, based on an online questionnaire and blood biomarker data, to reduce the misdiagnosis of bipolar disorder (BD) as major depressive disorder (MDD). Individuals with depressive symptoms (Patient Health Questionnaire-9 score ≥5) aged 18–45 years were recruited online. After completing a purpose-built online mental health questionnaire, eligible participants provided dried blood spot samples for biomarker analysis and underwent the World Health Organization World Mental Health Composite International Diagnostic Interview via telephone, to establish their mental health diagnosis. Extreme Gradient Boosting and nested cross-validation were used to train and validate diagnostic models differentiating BD from MDD in participants who self-reported a current MDD diagnosis. Mean test area under the receiver operating characteristic curve (AUROC) for separating participants with BD diagnosed as MDD (N = 126) from those with correct MDD diagnosis (N = 187) was 0.92 (95% CI: 0.86–0.97). Core predictors included elevated mood, grandiosity, talkativeness, recklessness and risky behaviour. Additional validation in participants with no previous mood disorder diagnosis showed AUROCs of 0.89 (0.86–0.91) and 0.90 (0.87–0.91) for separating newly diagnosed BD (N = 98) from MDD (N = 112) and subclinical low mood (N = 120), respectively. Validation in participants with a previous diagnosis of BD (N = 45) demonstrated sensitivity of 0.86 (0.57–0.96). The diagnostic algorithm accurately identified patients with BD in various clinical scenarios, and could help expedite accurate clinical diagnosis and treatment of BD.

Attention-deficit/hyperactivity disorder and other neurodevelopmental disorders in offspring of parents with depression and bipolar disorder

2021 ◽  
pp. 1-8
Author(s):  
L. Propper ◽  
A. Sandstrom ◽  
S. Rempel ◽  
E. Howes Vallis ◽  
S. Abidi ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Attention Deficit Hyperactivity Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Mood Disorder ◽  
Attention Deficit ◽  
Neurodevelopmental Disorders ◽  
Autism Spectrum ◽  
Major Depressive ◽  
Hyperactivity Disorder

Abstract Background Offspring of parents with major mood disorders (MDDs) are at increased risk for early psychopathology. We aim to compare the rates of neurodevelopmental disorders in offspring of parents with bipolar disorder, major depressive disorder, and controls. Method We established a lifetime diagnosis of neurodevelopmental disorders [attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, communication disorders, intellectual disabilities, specific learning disorders, and motor disorders] using the Kiddie Schedule for Affective Disorders and Schizophrenia, Present and Lifetime Version in 400 participants (mean age 11.3 + s.d. 3.9 years), including 93 offspring of parents with bipolar disorder, 182 offspring of parents with major depressive disorder, and 125 control offspring of parents with no mood disorder. Results Neurodevelopmental disorders were elevated in offspring of parents with bipolar disorder [odds ratio (OR) 2.34, 95% confidence interval (CI) 1.23–4.47, p = 0.010] and major depressive disorder (OR 1.87, 95% CI 1.03–3.39, p = 0.035) compared to controls. This difference was driven by the rates of ADHD, which were highest among offspring of parents with bipolar disorder (30.1%), intermediate in offspring of parents with major depressive disorder (24.2%), and lowest in controls (14.4%). There were no significant differences in frequencies of other neurodevelopmental disorders between the three groups. Chronic course of mood disorder in parents was associated with higher rates of any neurodevelopmental disorder and higher rates of ADHD in offspring. Conclusions Our findings suggest monitoring for ADHD and other neurodevelopmental disorders in offspring of parents with MDDs may be indicated to improve early diagnosis and treatment.

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