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Three models of community mental health services In low-income countries

DOI: 10.1186/1752-4458-5-3

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Abstract:

Primary and secondary data collected before, during, and after site visits to mental health programs in Nigeria, the Philippines, and India.Qualitative case study methodology.Data were collected through interviews and observations during site visits to the programs, as well as from reviews of documentary evidence.A set of narrative topics and program indicators were used to compare and contrast three community mental health programs in low-income countries. This allowed us to identify a diversity of service delivery models, common challenges, and the strengths and weaknesses of each program. More definitive evaluations will require the establishment of data collection methods and information systems that provide data about the clinical and social outcomes of clients, as well as their use of services.Community mental health programs in low-income countries face a number of challenges. Using a case study methodology developed for this purpose, it is possible to compare programs and begin to assess the effectiveness of diverse service delivery models.Global Mental Health has emerged as a significant field in public health [1], as evidenced by series in The Lancet [2-7] and PLoS Medicine [8-14], as well as by the establishment of the WHO mental health Gap Action Programme [15] and the development of intervention guidelines for the treatment of mental, neurological and substance use disorders in non-specialized settings [16]. However, a major obstacle to the goal of improving and expanding mental health services in low-income countries (LIC) is the comparative lack of evidence about how mental health services in LIC function in actual practice [17]. The Case Studies Project at the London School of Hygiene and Tropical Medicine was established with the objective of developing a methodology to address this deficiency. In this paper, we compare and contrast three models of community mental health services in low-income settings, based on information gathered according to a

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