UNASSIGNED: Post-traumatic stress disorder (PTSD) is a chronic psychiatric condition associated with significant distress and dysfunction. While worldwide estimates of prevalence range from 3.9% to 24%, little research has been conducted to identify the prevalence of PTSD in the general population of India. This study analyzes data from the National Mental Health Survey 2015-2016, a comprehensive epidemiological study of mental health disorders in India, to explore the unique characteristics and prevalence of PTSD in the Indian population.
UNASSIGNED: The National Mental Health Survey 2015-2016 employed a multiple-stage, stratified, cluster-sampling methodology, covering 39,532 individuals in 12 states of India. The Mini-International Neuropsychiatric Interview (MINI) version 6.0.0 was used to diagnose psychiatric disorders, including PTSD. A detailed analysis of sociodemographic profiles, prevalence patterns, comorbidities, economic and social impact, and treatment-seeking behavior was conducted. Firth penalized logistic regression was employed to identify associated sociodemographic factors.
UNASSIGNED: The study revealed a low prevalence of PTSD in India at 0.2%, significantly lower than global averages. Factors associated with PTSD included female gender, middle age (40-49 years), and urban residence. The study also highlighted a high rate of comorbid mood and anxiety disorders, substantial disability, poor treatment-seeking behavior, and significant suicidal risk among individuals with PTSD.
UNASSIGNED: Our findings underscore the need for culturally informed diagnostic and management programs to accurately identify and address PTSD in the Indian population. Cultural nuances, stigma, and the use of Western-derived diagnostic instruments likely contribute to the underidentification and undertreatment of PTSD in India. The study emphasizes the importance of recognizing and addressing these challenges to improve mental health outcomes in India.

UNASSIGNED: Panic disorder (PD) is one of the most common and debilitating anxiety disorder. Individuals with PD seek frequent healthcare and emergency services leading to frequent work absenteeism and economic burden. However, its prevalence patterns in the Indian context are poorly understood. Hence, this article discusses the epidemiology, disability, and treatment gap from India\'s National Mental Health Survey 2016.
UNASSIGNED: National Mental Health Survey 2016 was a nationally representative epidemiological survey of adult respondents from 12 states of India. Mini International Neuropsychiatric Interview 6.0.0 is used to diagnose psychiatric disorders. Sheehan disability scale was used to assess the disability. The current weighted prevalence of PD was estimated. Association between PD and its sociodemographic correlates was done using Firth penalized logistic regression. The treatment gap and disability in PD were also calculated.
UNASSIGNED: The lifetime and current weighted prevalence of PD was 0.5% (95% confidence interval 0.49-0.52) and 0.3% (95% confidence interval 0.28-0.41), respectively. The male gender and unemployed have significantly lesser odds with current PD. The elderly, Urban metro, and the married/separated group have significantly higher odds with current PD. The most common comorbid psychiatric disorder is agoraphobia (42.3%) and depression (30.9%) followed by Generalized Anxiety Disorder (10%). Among respondents with current PD in the past 1 month across three domains, around 80% had a disability of any severity and 20%-25% had marked disability. The overall treatment gap of current PD is 71.7%.
UNASSIGNED: It is the first study reporting prevalence from a nationally representative sample from the general population of India. The survey has shed light on the epidemiology and the challenges faced by those with PD which emphasizes the urgency of bridging the treatment gap. These findings are paramount to the development of more inclusive and effective mental health policies and interventions to tackle the current burden due to PD.

The National Mental Health Survey 2016 (NMHS 2016) was a large epidemiological study, one of its kind, conducted by the National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru to overcome the shortcomings of the previous surveys. The detailed report of the study is available in two parts- \'mental health systems\' and \'prevalence, pattern and outcomes\'. Though done comprehensively, there are some inevitable limitations. The private sector, a substantial health care provider in the country was not a participant in the survey. Though MINI version 6.0 is a standard and structured instrument, it does not cover many commonly encountered mental illnesses like somatoform disorders. Further, the methodology of the survey makes it difficult for an accurate calculation of the prevalence of individual major psychiatric disorders. The survey has been appraised using a standard checklist for prevalence studies. The detailed qualitative data has not been shared in the report. The contribution of the traditional indigenous systems of healthcare and accessibility of services in rural areas have not been elaborated. Thus, the need for a comprehensive and culturally sensitive assessment tool, involvement of the private sector, and enhancing funding provision to improve the infrastructure are emphasized as future directions for the subsequent phases of the survey.

UNASSIGNED: Generalized anxiety disorder (GAD) is one of the common anxiety disorders leading to impairment and burden. However, GAD remains the least studied anxiety disorder. There is a need for nationally representative epidemiological data of GAD to understand the current burden and plan the mental health policies and programs to attain their unmet needs. Hence, this study focuses on epidemiology, socio-demographic correlates, disability, and treatment gap of GAD from India\'s National Mental Health Survey (NMHS) 2016.
UNASSIGNED: NMHS 2016 was a nationally representative epidemiological survey of adult respondents from 12 states of India. NMHS is a multi-stage, stratified, random cluster sampling with random selection based on probability proportional to size at each stage. The Mini-International Neuropsychiatric Interview 6.0.0 used to diagnose psychiatric disorders. Sheehan disability scale was used to assess the disability. The current weighted prevalence of GAD was estimated. Association between GAD and socio-demographic factors was done using Firth\'s penalized logistic regression. The treatment gap and disability in GAD also calculated.
UNASSIGNED: The current weighted prevalence of GAD is 0.57%. The male gender and higher education groups have significantly lesser odds with current GAD. Urban metro and the married group have significantly higher odds with current GAD. The most common comorbid psychiatric disorders are depression (15.8%) followed by agoraphobia (9.4%). Among respondents with current GAD in the past 6 months across three domains, around 2/5th has mild and moderate disability, 1/10th has a severe disability, and 1/20th has an extreme disability. The overall treatment gap of current GAD is 75.7%.
UNASSIGNED: NMHS 2016 has provided valuable insights into the epidemiology and burden of GAD among the general population. The available findings provide a glimpse of the current scenario in GAD to aid policymakers in targeting interventions.

UNASSIGNED: Schizophrenia spectrum disorders represent a significant global health concern, contributing significantly to the global burden of disease. The National Mental Health Survey (NMHS) of India, conducted between 2015 and 2016, investigated the prevalence and epidemiological correlates of schizophrenia spectrum disorders in India.
UNASSIGNED: The NMHS conducted a population-based cross-sectional study in 12 Indian states from 2015 to 2016, encompassing 34,802 adults. The overall study design of the NMHS was a multistage, stratified, random cluster sampling technique, incorporating random selection based on probability proportion to size at each stage. The Mini-International Neuropsychiatric Interview 6.0 was used for psychiatric diagnoses, disability was assessed using Sheehan\'s disability scale, and the illness-related socioeconomic impact was assessed using a questionnaire based on the World Health Organization Disability Assessment Schedule 2.0. Firth penalized logistic regression was employed to understand the correlates of current schizophrenia spectrum disorder.
UNASSIGNED: The study found a lifetime prevalence of schizophrenia spectrum disorders at 1.41%, with a current prevalence of 0.42%. A substantial treatment gap of 72% existed for current cases, rising to 83.3% in urban non-metro areas. The penalized logistic regression revealed that the age group category of 30-49 years, unemployed status, and lower education level had higher odds of association with schizophrenia spectrum disorders.
UNASSIGNED: The primary finding of this study is a lifetime prevalence of 1.41%, a current prevalence of 0.42%, and a substantial treatment gap of 72%. Addressing this treatment gap and holistic intervention is crucial for reducing the socioeconomic impact of this disorder. Strengthening the National Mental Health Program and implementing community-based rehabilitation are essential first steps in this direction.

The National Mental Health Survey of India (NMHS) was a ground-breaking nationwide study that harnessed a uniform, standardized methodology blending quantitative and qualitative approaches. Covering data from 12 states across diverse regions, its mission was to gauge the prevalence of psychiatric disorders, bridge treatment gaps, explore service utilization, and gauge the socioeconomic repercussions of these conditions. This initiative provided pivotal insights into the intricate landscape of mental health in India. One of the analyses planned for NMHS data was to undertake a logistic regression analysis with an aim to unravel how various sociodemographic factors influence the presence or absence of specific psychiatric disorders. Within this pursuit, two substantial challenges loomed. The first pertained to data separation, a complication that could perturb parameter estimation. The second challenge stemmed from the existence of disorders with lower prevalence rates, which resulted in datasets of limited density, potentially undermining the statistical reliability of our analysis. In response to these data-driven hurdles, NMHS recognized the critical necessity for an alternative to conventional logistic regression, one that could adeptly navigate these complexities, ensuring robust and dependable insights from the collected data. Traditional logistic regression, a widely prevalent method for modeling binary outcomes, has its limitations, especially when faced with limited datasets and rare outcomes. Here, the problem of \"complete separation\" can lead to convergence failure in traditional logistic regression estimations, a conundrum frequently encountered when handling binary variables. Firth\'s penalized logistic regression emerges as a potent solution to these challenges, effectively mitigating analytical biases rooted in small sample sizes, rare events, and complete separation. This article endeavors to illuminate the superior efficacy of Firth\'s method in managing small datasets within scientific research and advocates for its more widespread application. We provide a succinct introduction to Firth\'s method, emphasizing its distinct advantages over alternative analytical approaches and underscoring its application to data from the NMHS 2015-2016, particularly for disorders with lower prevalence.

UNASSIGNED: West Bengal, situated in eastern India, comprising 19 districts as of 2016 and consisting of 9.13 crore population, had been one of the participating states in the National Mental Health Survey, 2015-16.
UNASSIGNED: To estimate the prevalence and pattern of mental disorders in a representative population in West Bengal.
UNASSIGNED: Based upon a multi-stage stratified random cluster sampling with probability proportionate to each stage, 2646 eligible individuals were interviewed. Standard validated instruments in Bengali like socio-demographic profiles and Mini International Neuropsychiatric Interview (MINI) version 6 were used by trained data collectors with quality monitoring as per a standardized protocol.
UNASSIGNED: The current prevalence of mental illness in the state of West Bengal is 13.07% (12.9-13.24 95% CI), which is more than the current national average of 10.56% (10.51-10.61 95% CI). The prevalence of severe mental illness of 2.32% and suicide risk of 1.75% (1.68-1.81 95% CI) is higher than the national average. The common mental illness prevalence is 11.29 (11.13-11.45 95% CI), which is similar to the national weighted average. In West Bengal, severe mental illness is more concentrated in the rural areas in contrast to the national trend. Also, the prevalence of alcohol use disorder is 3.04 (2.96-3.13 95% CI) and epilepsy is 0.03 (0.27-0.29 95% CI), which is less than the national average.
UNASSIGNED: The prevalence of mental disorders in the state of West Bengal is higher than the national average, and for severe mental illness, the prevalence is the highest as compared to the national average.

UNASSIGNED: The National Mental Health Survey was borne out of the felt need for a comprehensive epidemiological survey on mental health to understand the magnitude of psychiatric morbidities in India to aid in mental health policymaking, service planning, and delivery. Kerala was one of the 12 surveyed states, representing southern India.
UNASSIGNED: To estimate the prevalence and pattern of various mental illnesses and substance use disorders in a representative sample from Kerala state.
UNASSIGNED: A household survey using a multi-stage, stratified, random cluster sampling technique, with selection based on probability proportionate to size at each stage.
UNASSIGNED: The community-based survey was carried out by trained field staff on individuals from systematically selected households from three randomly selected districts of Kerala. The instruments used in the survey included M.I.N.I adult version 6.0, a modified version of the Fagerström Nicotine Dependence Scale and questionnaires to screen for epilepsy, intellectual disability, and autism spectrum disorders.
UNASSIGNED: A total of 2479 respondents aged >18 years were interviewed. The lifetime and current prevalence of mental morbidity (excluding tobacco use disorders) was 14.14% and 11.36%, respectively. Neurotic/stress-related disorders and depressive disorders were 5.43% and 2.49%, respectively, while severe mental disorders were prevalent in 0.44% of the sample. The prevalence of high risk for suicide was 2.23%.
UNASSIGNED: The survey revealed high rates of common mental illnesses and suicide risk in the state when compared to national estimates.

UNASSIGNED: Bipolar Affective Disorder (BPAD) merits careful consideration within the medical and healthcare communities, researchers, and policymakers. This is due to its substantial disability burden, elevated prevalence of co-morbidities, heightened lifetime risk of suicidality, and a significant treatment gap. This article focuses on the lifetime and current prevalence, correlates, co-morbidities, associated disabilities, socio-economic impact, and treatment gap for BPAD in the adult population of the National Mental Health Survey (NMHS) 2016.
UNASSIGNED: The NMHS 2016 was a nationally representative study conducted across 12 Indian states between 2014 and 2016. A multi-stage, stratified, random cluster sampling technique based on probability proportionate to size at each stage was used. The diagnosis of BPAD was based on Mini-International Neuropsychiatric Interview 6.0.0. Sheehan\'s Disability Scale was used to assess the disability.
UNASSIGNED: A total of 34,802 adults were interviewed. The overall weighted prevalence of BPAD was 0.3% [95% confidence interval (CI): 0.29-0.31] for current and 0.5% (95% CI: 0.49-0.51) for lifetime diagnosis. Male gender [odds ratio (OR) 1.56] and residence in urban metropolitans (OR 2.43) had a significantly higher risk of a lifetime diagnosis of BPAD. Substantial cross-sectional co-morbidities were noted as per MINI 6.0.0 with the diagnosis of current BPAD such as tobacco use disorder (33.3%), other substance use disorders (14.6%), and anxiety disorders (10.4%). Two-thirds of persons with current BPAD reported disability of varying severity at work (63%), social (59.3%), and family life (63%). The treatment gap for current BPAD was 70.4%.
UNASSIGNED: Most individuals with current BPAD reported moderate-severe disability. There were substantial co-morbidities and a large treatment gap. These warrant concentrated efforts from policymakers in devising effective strategies.

UNASSIGNED: Social anxiety disorder (SAD), also termed as social phobia, is a disabling psychiatric condition with limited epidemiological research on it in India. This study, using data from the National Mental Health Survey (NMHS), 2016, is the first to explore its current prevalence and associated factors in India.
UNASSIGNED: The NMHS in India used a comprehensive population-based study with subjects selected through a multistage stratified random cluster sampling technique across 12 states. The study included 34,802 adults interviewed with the Mini-International Psychiatric Interview 6.0.0. Firth penalized logistic regression (FPLR) was used to estimate covariate odds ratios (ORs), and the treatment gap for SAD and disability measured using Sheehan\'s disability scale was calculated.
UNASSIGNED: The study found a 0.47% prevalence of SAD, with an average age of 35.68 years (standard deviation (SD) = 15.23) among those affected. Factors, such as male gender, unemployment, and living in urban areas, were associated with higher odds of SAD, while the elderly had lower odds. A significant proportion of individuals with SAD experienced disability in work (63%), social life (77%), and family life (68%). They spent a median of ₹ 2500 per month on treatment and had a high rate of comorbid psychiatric disorders (58%). The treatment gap was substantial at 82%.
UNASSIGNED: A considerable portion of India\'s population (approximately >65 lakhs) is affected by SAD. Surprisingly, the NMHS 2016 report indicates a higher risk of SAD among males compared with females, a trend that warrants further investigation. SAD in India is linked to significant disability and a considerable treatment gap, emphasizing the need for innovative approaches to address this large, affected population, especially in light of the scarcity of mental health professionals.