STUDY ON NEWER PSYCHIATRIC CASES VISITING OPD AFTER ONSET OF PANDEMIC COVID-19

2021 ◽  
pp. 11-12
Author(s):  
Krishna Mishra ◽  
Priyash Jain
Keyword(s):  
Mental Health ◽  
Major Depressive Disorder ◽  
Health Status ◽  
General Population ◽  
Depressive Disorder ◽  
Mental Hospital ◽  
Major Depressive ◽  
Classi Cation ◽  
The Impact

Introduction : It is predicted by the experts that there will be a steep rise in the number of psychiatric cases post covid-19 pandemic. It is important to gauge the situation of mental health in population to be able to provide mental health services in a better way. Objective: The aim of this study is to determine the impact of the pandemic and other factors contingent to the pandemic on the mental health status of general population. Materials and method: The study was done over a period of 1 month after the lockdown. Study was done on 160 patients visiting Psychiatry OPD th in Mental Hospital, Indore for the rst time. Patients were diagnosed using International classication of diseases- 10 edition. Results: In our study we found that a majority of 45 of the 160 patients were suffering from Major Depressive Disorder followed by 24 patients of 160 suffering from nonorganic unspecied psychosis. Conclusion: It is important to assess the number of psychiatry patients visiting OPD to be able to cater to the needs of general population. It is also important to assess any role of psychosocial factors operating during pandemic being responsible for any rise in number of psychiatric cases.

scholarly journals Knowledge of and attitudes to major depressive disorder and its treatment in a sample of the general population in Serbia

2020 ◽  
Vol 148 (1-2) ◽  
pp. 94-99
Author(s):  
Ivona Milacic-Vidojevic ◽  
Marija Colic ◽  
Branka Draskovic
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Major Depressive Disorder ◽  
Health Literacy ◽  
General Population ◽  
Depressive Disorder ◽  
Mental Health Literacy ◽  
Structured Interview ◽  
Major Depressive ◽  
People With Mental Illness

Introduction/Objective. The objective of this paper was to examine the mental health literacy of the general population in Serbia and their attitudes towards persons with a mental illness. Methods. This was a cross-sectional study with structured interview using the vignette of a person with major depressive disorder (MDD). The attitudes towards people with mental illness were assessed by the Department of Health Attitudes to Mental Illness Questionnaire. A convenient sample consisted of 504 participants. Results. A total of 72% of the sample recognized the presence of some sort of mental health problem, of which 40.9% correctly labeled the symptoms as MDD. The majority of participants believed that MDD was caused more by stress than by biological factors. A psychologist, a close friend, and a psychiatrist were often rated as helpful for the person described by the vignette. Vitamins and healing herbs were rated as the most helpful remedy. Antidepressants were considered both helpful and harmful. The attitudes towards people with mental illness were moderately positive. Conclusion. Mental health literacy in Serbia is moderate. Risk factors for negative attitudes included older age and lower education.

scholarly journals Obesity, food insecurity, and depression among females

2020 ◽  
Vol 78 (1) ◽  
Author(s):  
Manik Ahuja ◽  
Thiveya Sathiyaseelan ◽  
Rajvi J. Wani ◽  
Praveen Fernandopulle
Keyword(s):  
Mental Health ◽  
Logistic Regression ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Food Insecurity ◽  
Mental Health Problems ◽  
Major Depressive ◽  
Logistic Regression Models ◽  
Increased Risk ◽  
The Impact

Abstract Background Nutritional psychiatry is an emerging field of research and it is currently exploring the impact of nutrition and obesity on brain function and mental illness. Prior studies links between obesity, nutrition and depression among women. However, less is known how food insecurity may moderate that relationship. Methods Data were employed from the Collaborative Psychiatric Epidemiology Surveys (CPES), 2001–2003. Two logistic regression models were Logistic regression was used to determine the association between obesity, gender, food insecurity, and past year Major Depressive Disorder (MDD). We then stratified by gender, and tested the association between obesity and past year MDD, and if food insecurity moderated the association. Results Obesity was associated with an increased risk for past year Major Depressive Disorder (MDD) among females (AOR = 1.35; 95% CI 1.17–1.55) and was not associated among males (AOR = 1.07; 95% CI, 0.86–1.32). Women who reported that reported both obesity and food insecurity reported higher odds of past year MDD episode (AOR = 3.16; 95% CI, 2.36–4.21, than women who did not report food insecurity (AOR = 1.08; 95% CI, 1.02–1.38). Conclusion With rising rates of mental health problems, females should be closely monitored to understand how poor diets, food insecurity, and obesity play a role in mental health outcomes. It is recommended that clinicians and treatment providers consider the patient’s diet and access to nutritious foods when conducting their assessment.

Recurrence of major depressive disorder and its predictors in the general population: results from The Netherlands Mental Health Survey and Incidence Study (NEMESIS)

2012 ◽  
Vol 43 (1) ◽  
pp. 39-48 ◽  
Author(s):  
F. Hardeveld ◽  
J. Spijker ◽  
R. De Graaf ◽  
W. A. Nolen ◽  
A. T. F. Beekman
Keyword(s):  
Mental Health ◽  
Major Depressive Disorder ◽  
General Population ◽  
Depressive Disorder ◽  
Depressive Episode ◽  
Major Depressive ◽  
Time To Recurrence ◽  
Younger Age ◽  
Mental Health Survey

BackgroundKnowledge of the risk of recurrence after recovery from major depressive disorder (MDD) in the general population is scarce.MethodData were derived from 687 subjects in the general population with a lifetime DSM-III-R diagnosis of MDD but without a current major depressive episode (MDE) or dysthymia. Participants had to be at least 6 months in remission, and were recruited from The Netherlands Mental Health Survey and Incidence Study (NEMESIS), using the Composite International Diagnostic Interview (CIDI). Recency and severity of the last MDE were assessed retrospectively at baseline. Recurrence of MDD was measured prospectively during the 3-year follow-up. Kaplan–Meier survival curves were used to measure time to recurrence. Determinants of time to recurrence were analyzed using proportional hazard models.ResultsThe estimated cumulative recurrence of MDD was 13.2% at 5 years, 23.2% at 10 years and 42.0% at 20 years. In bivariate analysis, the following variables predicted a shorter time to recurrence: younger age, younger age of onset, higher number of previous episodes, a severe last depressive episode, negative youth experiences, ongoing difficulties before recurrence and high neuroticism. Multivariably, younger age, a higher number of previous episodes, a severe last depressive episode, negative youth experiences and ongoing difficulties remained significant.ConclusionsIn this community sample, the long-term risk of recurrence was high, but lower than that found in clinical samples. Subjects who had had an MDE had a long-term vulnerability for recurrence. Factors predicting recurrence included illness- and stress-related factors.

Depression – Let’s Talk - Role of Aashwasan Chikitsa

2017 ◽  
Vol 2 (3) ◽  
Author(s):  
Priya Vishal Naik ◽  
Prachi Datta Dalvi U.
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Positive Attitude ◽  
Medical Intervention ◽  
Medical Illness ◽  
Suicidal Tendency ◽  
Major Depressive ◽  
Curative Therapy ◽  
Personal Interaction

The WHO theme for the year 2017 is Depression. Depression (major depressive disorder) is a common and serious medical illness that negatively affects how a person feels, thinks and behaves. Psychotherapy if incorporated along with medications can be of substantial help in depression. It is also called ‘talking therapy’ and is based on personal interaction with the patient. Patients suffering from this disorder do not easily accept it and hence do not feel the need to seek medical intervention or counselling. In this process the symptoms might get aggravated and suicidal tendency (which is the worst effect of this disease) may develop. So it is extremely essential for the patient, family and society to accept, talk, discuss and seek treatment for this disease. This ‘talking therapy’ is of utmost importance in today’s life where concept of privacy is taking its toll. This therapy is mentioned in Ayurveda as Aashwasan Chikitsa. Aashwasan Chikitsa consists of good, pleasing and benevolent thoughts, spiritual ideas, positive attitude, ethics and communication with near ones. So in the treatment of psychological disorders, along with medications counselling therapy plays a very important role. Finally counselling can act as a part of preventive, curative therapy and also aids to avoid recurrence in the patients of depression.

scholarly journals The Role of Dynorphin and the Kappa Opioid Receptor in Schizophrenia and Major Depressive Disorder: A Translational Approach

2020 ◽  
Author(s):  
Samuel David Clark
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Healthy Volunteers ◽  
Opioid Receptor ◽  
Clinical Data ◽  
Potential Role ◽  
Kappa Opioid Receptor ◽  
Kappa Opioid ◽  
Major Depressive

AbstractThe kappa opioid receptor (KOR) and its endogenous ligands dynorphins (DYN) have been implicated in the development or symptomatology of a variety of neuropsychiatric disorders. This review covers a brief history of the development of KOR agonists and antagonists, their effects in healthy volunteers, and the potential role of DYN/KOR dysfunction in schizophrenia and major depressive disorder from a translational perspective. The potential role of DYN/KOR dysfunction in schizophrenia is based on several lines of evidence. Selective KOR agonists induce affective states in healthy volunteers with similarities to the symptoms of schizophrenia. Studies have shown increased DYN in patients with schizophrenia, although the data have been mixed. Finally, meta-analytic data have shown that opioid antagonists are associated with reductions in the symptoms of schizophrenia. The potential role of DYN/KOR dysfunction in major depressive disorder is also based on a combination of preclinical and clinical data. Selective KOR agonists have shown pro-depressive effects in human volunteers, while selective KOR antagonists have shown robust efficacy in several preclinical models of antidepressant activity. Small studies have shown that nonselective KOR antagonists may have efficacy in treatment-resistant depression. Additionally, recent clinical data have shown that the KOR may be an effective target for treating anhedonia, a finding relevant to both schizophrenia and depression. Finally, recommendations are provided for translating preclinical models for schizophrenia and major depressive disorder into the clinic.

scholarly journals Cognition and Its Association with Psychosocial and Occupational Functioning during Treatment with Escitalopram in Patients with Major Depressive Disorder: A CAN-BIND-1 Report: La Cognition Et Son Association Avec Le Fonctionnement Psychosocial Et Professionnel Durant Le Traitement Par Escitalopram Chez Des Patients Souffrant De Trouble Dépressif Majeur: Une Étude Can-Bind-1

2020 ◽  
pp. 070674372097482
Author(s):  
Shane J. McInerney ◽  
Trisha Chakrabarty ◽  
Malgorzata Maciukiewicz ◽  
Benicio N. Frey ◽  
Glenda M. MacQueen ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Cognitive Functioning ◽  
Symptom Severity ◽  
Cognitive Change ◽  
Cognitive Domain ◽  
Depression Symptom ◽  
Major Depressive ◽  
Occupational Functioning ◽  
The Impact

Objectives: Major depressive disorder (MDD) is associated with impairments in both cognition and functioning. However, whether cognitive deficits significantly contribute to impaired psychosocial and occupational functioning, independent of other depressive symptoms, is not well established. We examined the relationship between cognitive performance and functioning in depressed patients before and after antidepressant treatment using secondary data from the first Canadian Biomarker Integration Network in Depression-1 study. Methods: Cognition was assessed at baseline in unmedicated, depressed participants with MDD ( n = 207) using the Central Nervous System Vital Signs computerized battery, psychosocial functioning with the Sheehan Disability Scale (SDS), and occupational functioning with the Lam Employment Absence and Productivity Scale (LEAPS). Cognition ( n = 181), SDS ( n = 175), and LEAPS ( n = 118) were reassessed after participants received 8 weeks of open-label escitalopram monotherapy. A series of linear regressions were conducted to determine (1) whether cognitive functioning was associated with psychosocial and occupational functioning prior to treatment, after adjusting for overall depressive symptom severity and (2) whether changes in cognitive functioning after an 8-week treatment phase were associated with changes in psychosocial and occupational functioning, after adjusting for changes in overall symptom severity. Results: Baseline global cognitive functioning, after adjusting for depression symptom severity and demographic variables, was associated with the SDS work/study subscale (β = −0.17; P = 0.03) and LEAPS productivity subscale (β = −0.17; P = 0.05), but not SDS total (β = 0.19; P = 0.12) or LEAPS total (β = 0.41; P = 0.17) scores. Although LEAPS and SDS scores showed significant improvements after 8 weeks of treatment ( P < 0.001), there were no significant associations between changes in cognitive domain scores and functional improvements. Conclusion: Cognition was associated with occupational functioning at baseline, but changes in cognition were not associated with psychosocial or occupational functional improvements following escitalopram treatment. We recommend the use of more comprehensive functional assessments to determine the impact of cognitive change on functional outcomes in future research.

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.

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