Abstract
Understanding the burden and pattern of mental disorders as well as mapping the existing resources for delivery of mental health services in India, has been a felt need over decades. Recognizing this necessity, the Ministry of Health and Family Welfare, Government of India, commissioned the National Mental Health Survey (NMHS) in the year 2014–15. The NMHS aimed to estimate the prevalence and burden of mental health disorders in India and identify current treatment gaps, existing patterns of health-care seeking, service utilization patterns, along with an understanding of the impact and disability due to these disorders. This paper describes the design, steps and the methodology adopted for phase 1 of the NMHS conducted in India. The NMHS phase 1 covered a representative population of 39,532 from 12 states across 6 regions of India, namely, the states of Punjab and Uttar Pradesh (North); Tamil Nadu and Kerala (South); Jharkhand and West Bengal (East); Rajasthan and Gujarat (West); Madhya Pradesh and Chhattisgarh (Central) and Assam and Manipur (North East). The NMHS of India (2015–16) is a unique representative survey which adopted a uniform and standardized methodology which sought to overcome limitations of previous surveys. It employed a multi-stage, stratified, random cluster sampling technique, with random selection of clusters based on Probability Proportionate to Size. It was expected that the findings from the NMHS 2015–16 would reveal the burden of mental disorders, the magnitude of the treatment gap, existing challenges and prevailing barriers in the mental-health delivery systems in the country at a single point in time. It is hoped that the results of NMHS will provide the evidence to strengthen and implement mental health policies and programs in the near future and provide the rationale to enhance investment in mental health care in India. It is also hoped that the NMHS will provide a framework for conducting similar population based surveys on mental health and other public health problems in low and middle-income countries.
Highlights
Robust and good quality data is an essential pre-requisite to plan, develop, implement, monitor, evaluate and strengthen mental health services globally and especially in Low- and Middle-Income countries (LMICs) like India
This paper describes the design, steps and the methodology adopted for phase 1 of the National Mental Health Survey (NMHS) conducted in India
The Ministry of Health and Family Welfare, Government of India, commissioned the National Mental Health Survey (NMHS) during the year 2014–15 to be implemented by the National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru [17, 18]
Summary
Robust and good quality data is an essential pre-requisite to plan, develop, implement, monitor, evaluate and strengthen mental health services globally and especially in Low- and Middle-Income countries (LMICs) like India. Earlier epidemiological surveys of mental disorders in India have methodological problems due to wide differences in study designs, sampling methods, instruments used, case definitions, cultural adaptations, data collection methods and statistical interpretations. The World Mental Health Survey, undertaken across 29 countries included India; the published details of the study which sampled populations from only 11 sites across India are limited to a few centers[15, 16]. To this end, a large scale nationally representative study of the prevalence and characteristics of mental disorders in India, was imperative.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.