There is growing international evidence about the importance of mental health as a development issue in countries with low income [1]. This evidence suggests that people with mental conditions constitute a vulnerable population in urgent need of targeting for development assistance. International organizations have subscribed that mental health problems have huge social and economic costs and therefore it is crucial to determine what kind of interventions are needed to break the cycle of poverty and mental illness in these countries [2]. Whether interventions to promote mental health in poor populations should begin with economic intervention to increase financial status or with efforts to improve primary health outcomes (i.e. targeting early detection of symptoms and disabilities associated with mental illness) remains an unsettled question. A recent study indicated that improving health outcomes (intervening in the social drift pathway) and thereby increasing the capabilities of mentally ill patients could be more productive towards bettering their economic outcomes than solely increasing access to financial resources [3]. Although there is robust research questioning whether interventions for early detection and treatment of mental disorders could be sufficiently effective, most of such evidence has been derived from high-income countries [4]. Because of sociocultural and health system differences, the generalizability of such findings are therefore limited.

The present monograph, in two papers, aimed to address ways in which economically scarce settings can provide good research evidence, focusing more specifically on mood disorders detection in low-income primary care settings. The first paper describes how screening tests could outperform typical assessment of mood disorders administered by general practitioners. The second paper reports how an easily applicable clinical predictive score might help physicians at this level of care to detect people with high risk of having a mood disorder. With improved ability to detect the presence of mood disorders, treatment of these disorders could be improved considerably, leading ultimately to greater economic outcomes for these low-income mentally ill patients.