Social distancing, also referred to as physical distancing, means creating a safe distance of at least two meters (six feet) between yourself and others. This is a term popularized during the COVID-19 pandemic, as it is one of the most important measures to prevent the spread of this virus. However, the term 'social distancing' can be misleading, as it may imply that individuals should stop socializing. However, socializing in a safe context (i.e. over the phone, video-chat, etc.) is especially important during this time of crisis. Therefore, in this narrative review, we suggest the term 'distant socializing' as more apt expression, to promote physical distancing measures while also highlighting the importance of maintaining social bonds. Further, articles discussing the practice, implementation, measurement, and mental health effects of physical distancing are reviewed. Physical distancing is associated with psychiatric symptoms (such as anxiety and depression), suicidal ideation, and domestic violence. Further, unemployment and job insecurity have significantly increased during COVID-19, which may exacerbate these negative mental health effects. Governments, medical institutions, and public health bodies should therefore consider increasing mental health resources both during and after the pandemic, with a specific focus on frontline workers, COVID-19 survivors, and marginalized communities.
Background: Recognizing the need for good quality, scientific and reliable information for strengthening mental health policies and programmes, the National Mental Health Survey (NMHS) of India was implemented by National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, in the year 2015–2016. Aim: To estimate the prevalence, socio-demographic correlates and treatment gap of mental morbidity in a representative population of India. Methods: NMHS was conducted across 12 Indian states where trained field investigators completed 34,802 interviews using tablet-assisted personal interviews. Eligible study subjects (18+ years) in households were selected by a multi-stage, stratified, random cluster sampling technique. Mental morbidity was assessed using MINI 6. Three-tier data monitoring system was adopted for quality assurance. Weighted and specific prevalence estimates were derived (current and lifetime) for different mental disorders. Mental morbidity was defined as those disorders as per the International Statistical Classification of Diseases, Tenth Revision Diagnostic Criteria for Research (ICD-10 DCR). Multivariate logistic regression was conducted to examine risk for mental morbidity by different socio-demographic factors. Survey was approved by central and state-level institutional ethical committees. Results: The weighted lifetime prevalence of 'any mental morbidity' was estimated at 13.67% (95% confidence interval (CI) = 13.61, 13.73) and current prevalence was 10.56% (95% CI = 10.51, 10.61). Mental and behavioural problems due to psychoactive substance use (F10–F19; 22.44%), mood disorders (F30–F39; 5.61%) and neurotic and stress-related disorders (F40–F48; 3.70%) were the most commonly prevalent mental morbidity in India. The overall prevalence was estimated to be higher among males, middle-aged individuals, in urban-metros, among less educated and in households with lower income. Treatment gap for overall mental morbidity was 84.5%. Conclusion: NMHS is the largest reported survey of mental morbidity in India. Survey estimated that nearly 150 million individuals suffer from one or the other mental morbidity in India. This information is to be used for planning, delivery and evaluating mental health programming in the country.
