Levels of work stress among information technology professionals during COVID-19 pandemic in an Indian metropolis.

Introduction: Amid the ongoing Non-Communicable Disease and COVID-19 pandemic, understanding prevalence and characteristics associated with work stress is vital from a health and economic perspective, more so among information technology (IT) professionals. Objective: To estimate the prevalence and factors associated with work stress among IT professionals during the coronavirus disease 2019 (COVID-19) pandemic in Bengaluru, India. Materials and Methods: A cross-sectional study was undertaken on a convenient sample of 356 IT professionals in Bengaluru, India, between September 2020 and March 2021 to assess work stress. The weblink to TAWS-16 (Tool to Assess and classify Work Stress) was provided for IT employees to self-report their experience of work-related stressors and coping abilities in the past 6 months. The prevalence and specific prevalence of work stress were calculated. Multi-variate logistic regression was conducted to identify factors associated with work stress. Ethical clearance was obtained from the Institutional Ethics committee, National Institute of Mental Health and Neurosciences, Bengaluru. Informed consent was obtained from study subjects. Results and Conclusion: The prevalence of work stress among IT professionals was 17.7% during the COVID19 pandemic, with higher rates among employees aged 31 years and above, among female employees, and among employees with 4-7 years of work experience. More than 80% of the professionals experienced deadline pressures, long working hours, regular multi-tasking, and difficulty in maintaining work-life balance. Based on the results, it is recommended to integrate work-stress assessment in periodical medical examination of IT employees from a health promotion and productivity improvement perspective.

Trauma care systems in healthcare facilities of an Indian District: Assessment and future directions.

Introduction: With a long-term vision to strengthen the evidence-based trauma care programme in the Kolar district, an objective assessment and grading of the trauma care system (TCS) in public and private hospitals was undertaken. Methods: This cross-sectional assessment used a specifically developed TCS assessment tool to collect data from all Level 2, 3, and 4 hospitals in the Kolar district using a review of records, observation of facilities, and interviews with stakeholders. Data were collected regarding macro areas, human resources, infrastructure, equipment, and drugs in ER, in an objective manner. TCS was scored and compared against criteria set in WHO essential guidelines for Trauma Care. The functioning of TCS was expressed as 'percentage of expected standards' and graded accordingly. Ethical clearance and informed consent were obtained. Results: All available and eligible Level 2, 3, and 4 hospitals in the district (39 hospitals) covering the public and private sector were assessed. TCS in Level 2 and 3 hospitals was functioning at 56% and 59% of expected standards, respectively. TCS was better in Level 4 hospitals, at 83% of expected standards. Scores were lower for macro areas and human resources. Conclusion: TCS in the district is functioning sub-par to expected standards. There is a need for comprehensive strengthening of TCS in both public and private healthcare facilities, especially in macro areas and human resources. Systematic monitoring and periodical TCS assessments are recommended at district levels throughout the country for improved outcomes in India.

International spinal cord injury socio-demographic basic data set (version 1.0).

STUDY DESIGN: Consensus based on the literature. OBJECTIVE: Create an International Spinal Cord Injury (SCI) Socio-Demographic Basic Data Set (Version 1.0). SETTING: International. METHODS: The development included an iterative process where the authors reviewed existing variables containing socio-demographic variables and created a first dataset draft, which was followed by several revisions through email communications. In addition, the work was conducted in parallel with a similar endeavour within the National Institute of Neurological Disorders and Stroke SCI Common Data Elements project in the United States. Subsequently, harmonization between the two projects was sought. Following this, a review process was initiated, including The International SCI Data Sets Committee, the American Spinal Injury Association (ASIA) Board, and the International Spinal Cord Society (ISCoS) Scientific and Executive Committees, and then by publishing on the respective websites for membership feedback. The draft was sent to about 40 national and international organizations and several interested individuals for feedback. All review comments were discussed in the working group and responded to before the final draft was developed, and finally approved by ASIA Board and the ISCoS Scientific and Executive committees. RESULTS: The final International SCI Socio-Demographic Basic Data Set includes the following variables: Date of data collection, Marital status, Household member count, Years of formal education, and Primary occupation. CONCLUSION: The International SCI Socio-Demographic Basic Data Set will facilitate uniform data collection and reporting of socio-demographic information at the time of injury as well as at post-injury follow-ups to facilitate the evaluation and comparisons across studies.

District-level differences in the distribution of mental and substance use disorders in Assam.

Background: The lifetime prevalence of mental morbidity in Assam is estimated at 8% (NMHS 2015-16). Understanding the distribution patterns of different types of mental disorders among persons with mental morbidity in different districts would facilitate evidence-driven district mental health programming in Assam. Given the varied socio-geopolitical situation across districts in Assam, significant variations in the distribution of mental disorders are expected. Aims: To assess interdistrict differentials in common mental disorders (CMDs), severe mental disorders (SMDs), socioeconomic impact, healthcare utilization, and mental disability across three districts sampled in NMHS in Assam. Materials and Methods: This cross-sectional study used stratified random cluster sampling to identify and study eligible adult participants in Dibrugarh, Barpeta, and Cachar districts. Standardized scales and validated questionnaires were used to assess mental morbidity, disability, socioeconomic impact, and healthcare utilization. The distribution of different mental disorders among persons with mental disorders and their interdistrict differentials were tested using the Chi-square test of significance. Results: Among persons with mental morbidity, the most common disorder was CMDs (79%). The proportional distribution of CMDs among persons with mental morbidity was significantly higher in the Dibrugarh district (79%), whereas the distribution of SMDs was higher in the Cachar district (55%). The distribution of alcohol use disorder was the highest in the Dibrugarh district (71.6%). Significant differences in disability and healthcare utilization were observed between the districts. Conclusions: NMHS 2015-16 Assam indicates significant differentials in the distribution of CMDs and SMDs, healthcare utilization, and associated disability between the three districts. The differentials necessitate further research to understand socio-ethnocultural, religious, geopolitical, and other factors influencing the distribution. These differences need to be accounted for during the implementation of mental health programs in the state.

Nationally representative epidemiological study of social anxiety disorder from India.

Background: 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. Materials and Methods: 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. Results: 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%. Conclusions: 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.

Bipolar affective disorder in India: A multi-site population-based cross-sectional study.

Introduction: 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. Materials and Methods: 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. Results: 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%. Conclusion: 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.

Mental health morbidities in Kerala, India: Insights from National Mental Health Survey, 2015-2016.

Background: 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. Aims: To estimate the prevalence and pattern of various mental illnesses and substance use disorders in a representative sample from Kerala state. Settings and Design: A household survey using a multi-stage, stratified, random cluster sampling technique, with selection based on probability proportionate to size at each stage. Materials and Methods: 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. Results: 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%. Conclusions: The survey revealed high rates of common mental illnesses and suicide risk in the state when compared to national estimates.

Epidemiological analysis of mental health morbidity in Tamil Nadu.

Background: Existing psychiatric epidemiological studies from Tamil Nadu with methodological limitations and variations had under-reported the prevalence of mental morbidity. Robust data from a representative population-based epidemiological study are not readily available to guide mental health programs in Tamil Nadu. Aim: This study aimed to estimate the prevalence, correlates, and treatment gap of mental morbidity in the state of Tamil Nadu using data from National Mental Health Survey (NMHS) of India, 2015-2016. Materials and Methods: NMHS in Tamil Nadu was conducted in 60 clusters of 4 districts (Trichy, Tirunelveli, Thoothukudi, and Namakkal) using a door-to-door survey and multistage sampling proportionate to rural, urban nonmetro, and urban metro population. Mini-International Neuropsychiatric Interview (M.I.N.I version 6) and Fagerstrom nicotine dependence scale were administered on a representative adult (aged ≥18 years) sample to assess the mental morbidity. Prevalence and 95% confidence intervals (CIs) were estimated after weighing the sample for survey design. Results: A total of 3059 adults from 1069 households were interviewed. The overall weighted prevalence of lifetime and current mental morbidity was 19.3% (95% CI: 19.0%-19.6%) and 11.8% (95% CI: 11.6%-12.0%) respectively. Participants who were men (largely contributed by substance-use disorders), aged 40-49 years, from rural areas, and from lower income quintile had higher prevalence of mental morbidity. The treatment gap was 94.2% for any mental health problem. Common mental disorders (depression, anxiety, and substance-use) accounted for most of the morbidity. Conclusion: The burden and treatment gap for mental health morbidity is high in Tamil Nadu. The findings call for urgent policy level and systemic action to strengthen mental health program in Tamil Nadu.

Firth's penalized logistic regression: A superior approach for analysis of data from India's National Mental Health Survey, 2016.

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.

Prevalence and pattern of mental disorders in the state of West Bengal: Findings from the National Mental Health Survey of India 2016.

Background: 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. Aim: To estimate the prevalence and pattern of mental disorders in a representative population in West Bengal. Materials and Methods: 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. Results: 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. Conclusion: 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.

Treatment gap for mental and behavioral disorders in Punjab.

Background and Aims: There is no data on the treatment gap and health care utilization for mental disorders from Punjab. The present study reports on the same by using the data collected during the National Mental Health Survey. Settings and Design: Multisite, multistage, stratified, random cluster sampling study conducted in four districts, namely Faridkot, Moga, Patiala, and Ludhiana (for urban metro areas). Data were collected from October 2015 to March 2016. Materials and Methods: Mini International Neuropsychiatric Interview 6.0.0 and Adapted Fagerstrom Nicotine Dependence Scale were used to diagnose mental and behavioral disorders and tobacco use disorder, respectively. Pathways Interview Schedule of the World Health Organization was applied to persons having any disorder to assess treatment gap and health care utilization. Exploratory focused group discussions (FGDs) were conducted to understand the community perceptions regarding mental and behavioral disorders. Results: The treatment gap for mental and behavioral disorders was 79.59%, and it was higher for common mental disorders than severe mental disorders and higher for alcohol and tobacco use disorders as compared to opioid use disorders. The median treatment lag was 6 months. Only seven patients out of 79 were taking treatment from a psychiatrist, and the average distance traveled by the patient for treatment was 37.61 ± 45.5 km. Many attitudinal, structural, and other barriers leading to high treatment gaps were identified during FGDs in the community, such as stigma, poor knowledge about mental health, deficiency of psychiatrists, and distance from the hospital. Conclusions: Vertical as well as horizontal multisectoral integration is required to reduce the treatment gap and improve healthcare utilization. Increasing mental health literacy, providing high-quality mental health services at the primary-healthcare level and human resources development are the need of the hour.

Exploring the enigma of low prevalence of post-traumatic stress disorder in India.

Introduction: 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. Materials and Methods: 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. Results: 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. Conclusion: 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.

A study of disability and socio-economic impact of mental morbidities from the state of Madhya Pradesh, India.

Background: Disability associated with mental illness has a disproportionate impact on the work, social, and family responsibilities of an individual toward society. The evidence for disability in mental illnesses would help the clinician, caregivers, policymakers, and various stakeholders to come up with sustainable solutions not only to help fill the existing gaps in care but also to develop new avenues as per the specific needs of the population of Madhya Pradesh (MP). Aim: To estimate the burden of disability related to mental illnesses in the state of MP. Materials and Methods: A multi-site cross-sectional study was conducted in 2015-16 as part of National Mental Health Survey among adults above 18 years of age. Samples were selected using multi-stage, stratified, random cluster sampling based on probability proportionate to size. Six tehsils with one urban metro out of four districts from a total of 50 districts were selected in the state of MP. The Sheehan Disability Scale and socio-economic impact of illness (from selected questions from WHO-Disability Assessment Schedule-2.0) were used to assess mental morbidity and the subjective reporting of disability. Results: The weighted prevalence of disability (n = 1011) was found as 10.2%, 13.1%, and 13.9%, respectively, in work/school, social life, and family/home domains. The weighted prevalence of moderate to extreme disability in the same domains was, respectively, 5.1%, 6.7%, and 7.3%. The presence of common mental disorders (CMDs) increases the odds of self-reported disability in work [odds ratio (OR) 2.48, 95% CI 1.35 to 4.59], social life (OR 2.74, 95% CI 1.50 to 5.07), and family domains (OR 3.03, 95% CI1.62 to 5.74). When combined with common mental disorders, tobacco use disorder further escalates the odds of self-reported disability in all three domains [OR 7.10, confidence interval (CI) 3.15 to 16.37; 4.93, CI 2.19 to 11.28; and 7.10, CI 2.78 to 19.25]. Currently, non-working persons had a higher disability in social life and family life domains (P = 0.003 and P = 0.021), respectively. Conclusion: We report a substantial magnitude of disability in social, work, and family life domains. Participants having CMDs, female gender, and those non-working had more disabilities and would require targeted interventions.

Schizophrenia spectrum disorders in India: A population-based study.

Introduction: 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. Materials and Methods: 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. Results: 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. Conclusion: 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.

Current prevalence and determinants of generalized anxiety disorder from a nationally representative, population-based survey of India.

Introduction: 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. Materials and Methods: 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. Results: 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%. Conclusion: 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.

Panic disorder: Epidemiology, disability, and treatment gap from nationally representative general population of India.

Introduction: 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. Materials and Methods: 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. Results: 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%. Conclusion: 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.

Common mental disorders among women in reproductive age group: An analysis of national mental health survey, India 2016.

Background: Common mental disorders (CMDs) have a higher prevalence among women in their reproductive age (WRA) compared to the general population. Large Indian epidemiological studies focusing on the prevalence and socioeconomic correlates of CMDs among WRA are lacking. The associated disability and treatment gap particularly in the women population is unknown. Aim: To estimate the current prevalence, correlates, disability, socioeconomic impact, and treatment gap of CMDs among WRA from a nationally representative sample from India. Materials and Methods: The National Mental Health Survey of India 2016 is a multisite nationwide household survey conducted across India using a uniform methodology. Overall, 39,532 adults were surveyed with a response rate of 88%. The diagnosis was based on Mini International Neuropsychiatric Interview 6.0.0. CMDs among WRA (18-49 years) for this secondary analysis included depression and anxiety disorders. Results: The prevalence of CMDs among WRA in India was 5.83%. Two important risk factors for CMDs included being divorced and living in the urban metro. Nearly 70% of women reported disabilities of varying severity. The overall treatment gap was around 82% (urban nonmetro > metro > rural population). On average, the cost of treatment of CMDs was ₹ 2,000 per month. Conclusion: CMDs are prevalent among WRA groups with significant disabilities and treatment gaps in India. The disability and treatment gap associated with CMDs among WRA can be handled by integrating mental health into general medical/obstetric care.

A bird's eye view of the mental health systems in India.

Background: A staggering 85% of the global population resides in low- and middle-income countries (LAMICs). India stands as an exemplary pioneer in the realm of mental health initiatives among LAMICs, having launched its National Mental Health Program in 1982. It is imperative to effectively evaluate mental health systems periodically to cultivate a dynamic learning model sustained through continuous feedback from mental healthcare structures and processes. Materials and Methods: The National Mental Health Survey (NMHS) embarked on the Mental Health Systems Assessment (MHSA) in 12 representative Indian states, following a pilot program that contextually adapted the World Health Organization's Assessment Instrument for Mental Health Systems. The methodology involved data collection from various sources and interviews with key stakeholders, yielding a set of 15 quantitative, 5 morbidity, and 10 qualitative indicators, which were employed to encapsulate the functional status of mental health systems within the surveyed states by using a scorecard framework. Results: The NMHS MHSA for the year 2015-16 unveiled an array of indices, and the resultant scorecard succinctly encapsulated the outcomes of the systems' evaluation across the 12 surveyed states in India. Significantly, the findings revealed considerable interstate disparities, with some states such as Gujarat and Kerala emerging as frontrunners in the evaluation among the surveyed states. Nevertheless, notable gaps were identified in several domains within the assessed mental health systems. Conclusion: MHSA, as conducted within the framework of NMHS, emerges as a dependable, valid, and holistic mechanism for documenting mental health systems in India. However, this process necessitates periodic iterations to serve as critical indicators guiding the national mental health agenda, including policies, programs, and their impact evaluation.

Profile of Acute Encephalitis Syndrome Patients from South India.

Introduction: Encephalitis is a major public health problem worldwide that causes huge emotional and economic loss to humanity. Encephalitis, being a serious illness, affects people of all ages. The aim is to describe the sociodemographic, clinical, etiological, and neuroimaging profile among 101 acute encephalitis syndrome (AES) patients visiting a tertiary neuro-specialty care hospital in India. Methods: Record review of medical records of all patients attending neurology emergency and outpatient services at NIMHANS Hospital, diagnosed with AES in 2019, was conducted. Data were collected using standardized data collection forms for all cases in the study. Descriptive analyses (mean and standard deviation for continuous variables and proportions for categorical variables) were conducted. The Chi-square test/Fisher's exact test was used for the comparison of independent groups for categorical variables, and t-test for comparing means for continuous variables. Results: About 42.6% of AES patients had viral etiology, while in 57.4%, etiology was not ascertained. Common presenting symptoms were fever (96%), altered sensorium (64.4%), seizures (70.3%), headache (42.6%), and vomiting (27.7%). Herpes simplex was the most common (21.8%) identified viral encephalitis, followed by chikungunya (5%), arboviruses (chikungunya and dengue) (4%), Japanese encephalitis (4%), rabies (3%), dengue (1%), and varicella virus (1%). About 40% of AES patients showed cerebrospinal fluid pleocytosis (44%), increased protein (39.6%), abnormal computed tomography brain (44.6%), and magnetic resonance imaging abnormalities (41.6%). Conclusion: The study highlights the need to ascertain etiology and importance of evidence-based management of AES patients. A better understanding of opportunities and limitations in the management and implementation of standard laboratory and diagnostic algorithms can favor better diagnosis and management of AES.

Health and Lifestyle Issues among Youth: A Record Analysis of Contributing Factors among Beneficiaries Attending Youth Mental Health Promotion Clinics (Yuva Spandana Kendras) in Karnataka, India.

Background: Youth are consideren to be most vulnerable to health and lifestyle issues (HLS) in India. The current study aims to investigate the factors that contribute to health and lifestyle issues among youth attending mental health promotion clinics (YMHP) in Karnataka. Method: Three-year first-visit data from beneficiaries (aged 15-35 years) attending YMHP clinics in Karnataka between 2017 and 2020 were analyzed. Multivariable logistic regression analysis included beneficiaries reporting any HLS issue as the outcome and a host of 57 hypothesized variables as exposures. Results: Overall, 2,615 (25%) beneficiaries reported HLS issues. Years of schooling (AOR 5-7 years = 0.89; 95% confidence interval [CI] =0.60-1.31), (AOR 8-10 years = 0.65; 95% CI = 0.46-0.91), (AOR >10 years = 0.67; 95% CI = 0.49-0.93)], unemployed youth (AOR = 0.52; 95% CI = 0.45-0.61) business and salaried workers (AOR = 1.69; 95% CI = 1.33-2.13), and other occupations (AOR = 2.11; 95% CI = 1.73-2.56), junk food consumption (AOR = 0.76;95% CI = 0.68-0.84), having issues related to relationships with parents (AOR = 3.01; 95% CI = 2.47-3.68) and intergenerational issues (AOR = 1.71; 95% CI = 1.19-2.45), self-development issues (AOR low-self-awareness = 1.57; 95% CI = 1.33-1.85), (AOR low-self-esteem = 1.29; 95% CI = 1.062-1.57), (AOR emotional issues = 1.57; 95% CI = 1.31-1.89), education and academics (AOR = 1.23; 95% CI = 1.09-1.39), safety issues (AOR = 4.11; 95% CI = 3.07-5.50), gender sex and sexuality issues (AOR = 2.44; 95% CI = 1.43-4.15), suicidal ideation (AOR = 1.91; 95% CI = 1.44-2.54), substance use (AOR tobacco chewing = 1.45; 95% CI = 1.09-1.93), (AOR tobacco-smoking = 1.66; 95% CI = 1.18-2.32), (AOR smoking = 4.94; 95% CI = 3.52-6.93) and experiencing emotions (AOR feel anxious = 1.63; 95% CI = 1.41-1.88), (AOR forgetfulness = 1.50; 95% CI = 1.41-1.98), (AOR difficulty in concentration = 1.37; 95% CI = 1.035-1.81), (AOR anger = 1.61; 95% CI = 1.25-2.07), (AOR feel worthless = 2.21; 95% CI = 1.71-2.86) were associated with HLS issues among beneficiaries. Conclusion: This analysis addresses an important but neglected component of HLS issues among youth highlighting the importance of early intervention among youth to prevent the development of diseases later in life. The study has important implications for youth health promotion in India and countries such as India. Health and Lifestyle Issues Among Youth: A record analysis of contributing factors among beneficiaries attending Youth Mental Health promotion clinics (Yuva Spandana Kendras) in Karnataka, India.