Sebastian Ruiz's Github repository for Data 150 at WIlliam and Mary
Sebastian Ruiz
Developing countries in Latin America suffer disproportionately from untreated mental illness. This problem drove my central research question: do mental health coverage gaps in developing Latin American countries have a disproportionate impact on impoverished individuals and can this be reliably modeled? People in Latin America are more susceptible to mental illness due to rapid urbanization and higher rates of poverty, alcoholism, crime, and gender-based violence (Elsey et Al.) Furthermore, the vast majority of mental health services in Latin America are concentrated in cities only accessible to privileged people that can afford them. Untreated mental illness has devastating effects on the lifespan, education, and economic wellbeing of marginalized populations in Latin America. During my research, I noticed a gap in literature concerning a dearth of data on mentally ill individuals in developing Latin American countries as well as a lack of studies that attempt to use existing data to model mental health care inequities in Latin America. The lack of data can be attributed to the fact that government surveys in developing Latin American countries, such as official censuses, tend to leave out questions about non-communicable diseases like depression and overlook the needs of populations that are all more susceptible to mental health treatment gaps including indigenous, rural, impoverished individuals.
In order to address this gap in literature, I am proposing a research project where I will use sociodemographic data from household surveys and satellite data from government data bases to run a machine learning model that highlights mental Health Inequalities and can improve and expand data collection in Latin America on mental illness. Additionally, the study will offer insight into how surveys can ask effective and appropriate questions about mental illness. Improved data collection could show governments and humanitarian organizations how many people are suffering from mental illness and would lead to increased funding and availability of mental health services and applications in Latin America. The roll out of low-cost mental health applications, such as apps that connect users to therapists, in rural and impoverished regions in Latin America improves data collection even more by allowing users to input their information safely and anonymously.
References:
Elsey H, Poudel AN, Ensor T, et alImproving household surveys and use of data to address health inequities in three Asian cities: protocol for the Surveys for Urban Equity (SUE) mixed methods and feasibility studyBMJ Open 2018;8:e024182. doi: 10.1136/bmjopen-2018-024182
Jiménez-Molina Á, Franco P, Martínez V, Martínez P, Rojas G and Araya R (2019) Internet-Based Interventions for the Prevention and Treatment of Mental Disorders in Latin America: A Scoping Review. Front. Psychiatry 10:664. doi: 10.3389/fpsyt.2019.00664
Martínez V, Rojas G, Martínez P, Gaete J, Zitko P, Vöhringer PA and Araya R (2019) Computer-Assisted Cognitive-Behavioral Therapy to Treat Adolescents With Depression in Primary Health Care Centers in Santiago, Chile: A Randomized Controlled Trial. Front. Psychiatry 10:552. doi: 10.3389/fpsyt.2019.00552
Poor mental health, an obstacle to development in Latin America. (2015, July 13). World Bank. https://www.worldbank.org/en/news/feature/2015/07/13/bad-mental-health-obstacle- development-latin-america
Rathod, S., Pinninti, N., Irfan, M., Gorczynski, P., Rathod, P., Gega, L., & Naeem, F. (2017). Mental Health Service Provision in Low- and Middle-Income Countries. Health Services Insights. https://doi.org/10.1177/1178632917694350