Global mental health and the DIADA project.

The DIADA project, understood as a mental healthcare implementation experience in the context of a middle-income country like Colombia, promotes a necessary discussion about its role in the global mental health framework. The following article outlines the main points by which this relationship occurs, understanding how the project contributes to global mental health and, at the same time, how global mental health nurtures the development of this project. It reflects on aspects like the systematic screening of patients with mental illness, the use of technology in health, the adoption of a collaborative model, the investigation on implementation, a collaborative learning and the Colombian healthcare system. These are all key aspects when interpreting the feedback cycle between the individual and the global. The analysis of these components shows how collaborative learning is a central axis in the growth of global mental health: from the incorporation of methodologies, implementation of models, assessment of outcomes and, finally, the dissemination of results to local, regional and international stakeholders.

Technology-based mental healthcare models: A systematic review of the literature.

INTRODUCTION: This systematic review summarises the existing evidence on the implementation of technology-based mental healthcare models in the primary care setting. METHODS: A systematic search was conducted (MEDLINE, Embase, CENTRAL) in August 2019 and studies were selected according to predefined eligibility criteria. The main outcomes were clinical effectiveness, adherence to primary treatment and cost of implementation. SELECTION CRITERIA: Studies with an experimental or quasi-experimental design that evaluated the implementation of technology-based mental healthcare models were included. RESULTS: Five articles met the inclusion criteria. The models included technological devices such as tablets, cellphones and computers, with programs and mobile apps that supported decision-making in the care pathway. These decisions took place at different times, from the universal screening phase to the follow-up of patients with specific conditions. In general, the studies showed a decrease in the reported symptoms. However, there was great heterogeneity in both the health conditions and the outcomes, which hindered a quantitative synthesis. The assessment of risk of bias showed low quality of evidence. CONCLUSION: There is not enough evidence to support the implementation of a technology-based mental healthcare model. High quality studies that focus on implementation and effectiveness outcomes are needed to evaluate the impact of technology-based mental healthcare models in the primary care setting.