India’s efforts towards mental health have long since formalised the incorporation of community mental health into the national policy. However, while efforts have been made towards an accessible, acceptable, decentralised and deinstitutionalized psychosocial model of care, its implementation has missed the mark on these tenets that community mental health is grounded in. The first departure from the dominant institutional frame of mental health in Indian policy began in the 1970s with the wave of decentralisation of these services among developing nations. This led to the development of the landmark National Mental Health Programme (NHMP), first introduced in 1982, which incorporated mental health under the general health care in the community. This program was further expanded and decentralised to aid more effective implementation through its district-level arm introduced in 1996, the District Mental Health Programme (DMHP). While these programmes have certainly made progress, they have suffered from mismanagement and are yet to deliver all they promise.
Moreover, such programs face a severe lack of adequate funding, which, rather than being remedied, are in fact under further strain by the recent allocations of the Union Budget for Mental Health. The previous two years only saw 7% of the budget for mental health allocated to the NMHP which is responsible for 90% of the delivery of mental health services across the nation and instead issued the majority of the funds to the two major institutions in the country, NIMHANS, Bengaluru, and Lokpriya Gopinath Bordoloi Regional Institute of Mental Health, Assam. A digital arm of the NHMP, introduced in 2022 in the wake of the pandemic, aiming to provide free and standardised tele-mental health services to all Indians around the clock, is also being budgeted separately with increased funding this year. While this may look like a step in the right direction on the surface, it also entails essential questions of data protection, quality of care and the actual practicalities of its accessibility. The Union Budget this year has also incorporated the NHMP under the umbrella of the Tertiary Care Programme with no clear-cut budget allocated to it separately. A history of underutilising the allocated funds will make it even more challenging to address the issues with the programme and restructure it to align its aims with its impact.
This is a pressing concern facing the nation as existing data indicates high levels of mental morbidity within the Indian population with a wide treatment gap. Factoring in the socio-demographic correlates contributing to this systemically, it is also important to redress it as a social problem that our national policy has only put into inconsistent effect. However, in the domains where these central large-scale programmes have failed, several local community-based care models carried out by different organisations have entered the scene with their own approaches. Their success opens an avenue for structuring a more effective model that caters to the mental health issue at a national level by endemically serving the specific health needs of the local populations.
Several different community-based intervention programmes have developed exemplary and innovative approaches that would be worth financing and reproducing across other regions. One such recent evidence-based programme is the Atmiyata programme, also featured in the World Health Organization’s recent guidance document on community mental health services. Some of the most effective strategies underlying the success of this model that may benefit from further adaptation are task-sharing, collaboration with existing community resource groups, and localising digital mental health resources to increase accessibility.
Task-shifting is an approach that is being adopted globally to advance health, particularly by lower and middle-income countries that suffer from a lack of adequate financial and human resources, where Primary Care Workers and Community Health Workers (CHWs) are trained to carry out responsibilities traditionally assigned to specialists. While this approach has a strong evidence base for its effectiveness, it has also faced drawbacks in terms of over-burdening the lay health workers (‘task-dumping’ them) without adequate incentivisation and sustainable financing. It has also been criticised for often undermining the localised knowledge of the communities by enforcing rigid Western biomedical models of health on them. The Atmiyata approach, aptly named for ‘shared compassion’ in Marathi, optimises this existing approach by moving towards a model of task-sharing that goes one step beyond the pyramid of service-provision for mental health care. They train ordinary community members to provide basic mental health support and access social benefits from the government. They recruit volunteers from community resource groups with existing strongholds in the community, such as Self-Help Groups and Farmer’s Clubs. Collaboration with these groups allows potential for financial sustainability, community empowerment and localised methods of care. This collaborative model also greatly emphasises accessibility and cultural acceptability as these groups are already embedded into the community and may often cater to more vulnerable groups in society, such as women.
The programme also optimised the digital medium by producing four community films geared towards encouraging discussion (with inbuilt pause points) and promoting knowledge in the local language dealing with commonly experienced social situations such as domestic violence, alcoholism, unemployment and spousal conflict. Volunteers disseminated them in community meetings and made them available for free on YouTube to download and view offline. They also employed a local technical firm to develop a free app accessible even to illiterate people with a list of films along with Bluetooth sharing and emergency contact details of the field-based organisation.
While offering successful and financially sustainable models, programs like these still largely depend on funding to effectively collect data as well as locate, manage, maintain and supervise different regions, particularly the more inaccessible ones. This calls for adequate funding from the government to support and adopt the successful features of these community projects on a larger scale. The funds allocated for the digital mental health branch may also be utilised to optimise these technologies to support these community interventions, creating the potential for accessible and localised apps while providing employment opportunities to local technical talent.
Enas Shauib
