Introduction: Anxiety disorders (ADs) impact the quality of life and productivity at an individual level and result in substantial loss of national income. Representative epidemiological studies estimating the burden of ADs are limited in India. National Mental Health Survey (NMHS) 2016 of India aimed to strengthen mental health services across India assessed the prevalence and pattern of public health priority mental disorders for mental health-care policy and implementation. This article focuses on the current prevalence, sociodemographic correlates, disability, and treatment gap in ADs in the adult population of NMHS 2016. Materials and Methods: NMHS 2016 was a nationally representative, multicentered study across 12 Indian states during 2014–2016. Diagnosis of ADs (generalized AD, panic disorder, agoraphobia, and social AD) was based on Mini-International Neuropsychiatric Interview 6.0.0. Disability was by Sheehan’s Disability Scale. Results: The current weighted prevalence of ADs was 2.57% (95% confidence interval: 2.54–2.60). Risk factors identified were female gender, 40–59 age group, and urban metro dwellers. Around 60% suffered from the disability of varying severity. The overall treatment gap for ADs was 82.9%. Conclusions: The burden of AD is similar to Depressive disorders, and this article calls for the immediate attention of policymakers to institute effective management plans in existing public health programs.

There is a dearth of published research on uptake and utility of mental health apps in India, despite a rising global trend in the application of technology in the field of mental health. We describe the development and pilot testing of a self-help intervention for depression, PUSH-D (Practice and Use Self-Help for Depression) for urban Indians. This guided self-help app, with essential and optional zone sections, was developed to provide a comprehensive coverage of therapeutic strategies drawn from cognitive behavior therapy, interpersonal therapy, supportive psychotherapy, and positive psychology. Pilot testing was carried out using a single group pre-, post- and follow-up design in 78 eligible participants. Participants were typically young adults with major depression or dysthymia and significant impairment in functioning. Almost two-thirds of the participants had never sought professional mental health help. Significant reductions in depression and improvement in the functioning and well-being were notedon standardized measures in participants completing all 10 essential zone sections. These gains were maintained at follow-up. The results were similar for partial completers, who completed fiveout of the 10 essential sections. PUSH-D is one of the first indigenously developed self-help apps for depression and it shows promise in reducing the treatment gap for depression in India.

Context: In 2010, nearly 37 lakh Indians have been estimated to be suffering from dementia. Estimated costs of care in published literature do not reflect the actual expenses of individual households. Hence, a household budget approach was undertaken to arrive at the costs of dementia care in India. Materials and Methods: We identified and listed the different components of care, classified the applicability of care for the different components with respect to mild, moderate, and severe cases. This framework was utilized to assign costs of care and arrive at the household costs of care for a Person with Dementia (PwD) in both urban and rural areas. Results: The total expense was similar to that reported by individual households. The annual household cost of caring for a person with dementia in India, depending on the severity of the disease, ranged between INR 45,600 to INR 2,02,450 in urban areas and INR 20,300 to INR 66,025 in rural areas. Costs increased with increasing severity of the disease process. The costs of informal care contributed to nearly half of the total costs either in rural or urban area. With increasing severity, proportion of medical costs decreased while social cost increased. Medical costs in rural areas were nearly one-third of the total costs as against less than one-fifth in urban areas. Conclusion: The household budget model realistically estimated the household costs of care. It is hoped that the comprehensive and generic framework would prompt health professionals, researchers, and policy makers in India to catalyze geriatric health services, particularly for care for PwD.

Background: About 14% of the global mental health burden is contributed by India. However, there exists a disparity in mental health patterns, utilization, and prioritization among various Indian states. The state of Madhya Pradesh is a low performer among Indian states, ranking lower than the national average on the Human Development Index, Hunger Index, and Gross Domestic Product (GDP). The state also performes poorly on other health-related indicators. Objectives of Study: To estimate the prevalence and patterns of mental illnesses in the state of Madhya Pradesh, India. Material and Methods: This study used the multistage, stratified, random cluster sampling technique, with selection probability proportionate to size at each stage. A total of 3240 individuals 18 years and older were interviewed. The mixed-method study that was employed had both quantitative and qualitative components. The Mini International Neuropsychiatric Interview along with 10 other instruments were used. Results: The overall weighted prevalence for any mental illness was 13.9%, with 16.7% over the lifetime. The treatment gap for all of the mental health problems is very high (91%), along with high suicidal risk and substance use in the state. Conclusions: This study provides evidence of the huge burden of mental, behavioral, and substance use disorders as well as the treatment gap in Madhya Pradesh. This information is crucial for developing an effective prevention and control strategy. The high treatment gap in the state calls for coordinated efforts from all stakeholders, including policy makers, political leaders, health care professionals, and the society at large to give mental health care its due priority. These findings also highlight the need for multi-pronged interventions rooted in health policy directed at reducing the treatment gap in the short term and disease burden in the long run.

Background: Partners of heavy drinking individuals can be detrimentally affected as a result of their partner’s drinking. Objectives: The aim of this study was to identify the proportion of heterosexual intimate partner relationships with a heavy drinking male that resulted in reported alcohol-related harm and to investigate the impact of this on well-being in 9 countries. Methods: This study used survey data from the Gender and Alcohol’s Harm to Others (GENAHTO) Project on Alcohol’s Harm to Others in 9 countries (10,613 female respondents, 7,091 with intimate live-in partners). Respondents were asked if their partners drinking had negatively affected them as well as questions on depression, anxiety, and satisfaction with life. Results: The proportion of partnered respondents that reported having a harmful heavy drinking partner varied across countries, from 4% in Nigeria and the US to 33% in Vietnam. The most consistent correlate of experiencing harm was being oneself a heavy episodic drinker, most likely as a proxy measure for the acceptability of alcohol consumption in social circles. Women with a harmful heavy drinking partner reported significantly lower mean satisfaction with life than those with a partner that did not drink heavily. Conclusions: Harms to women from heavy drinking intimate partners appear across a range of subgroups and impact on a wide range of women, at least demographically speaking. Women living with a heavy drinking spouse experience higher levels of anxiety and depression symptoms and lower satisfaction with life.