Mustapha Alhassan, Ivis King, Youseung Kim, Kenya Jones, Shena Brown, Eboni Dotson
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引用次数: 0
Abstract
Data science refers to the connections among different disciplines, including physics, statistics, engineering, mathematics, and the social sciences. Data science can significantly affect how social work students collect and use data. Data science tools and methodology can provide effective strategies for social work students to explore, analyze, visualize, and understand social problems. This article aims to present the findings of the Social Work Data Corps (SWDC) project. The SWDC project was implemented in the summer of 2022 to introduce social work students to data science. The SWDC project mentored Bachelor of Social Work (BSW) and Master of Social Work (MSW) data science scholars who explored health disparities of marginalized communities in the United States using secondary data. The data science scholars addressed a wide range of issues, including cancer, pregnancy, Covid-19, trauma, veterans' issues, autism, reproductive care, and the impact of the opioid crisis on Native Americans in their research projects.
期刊介绍:
Social Work in Public Health (recently re-titled from the Journal of Health & Social Policy to better reflect its focus) provides a much-needed forum for social workers and those in health and health-related professions. This crucial journal focuses on all aspects of policy and social and health care considerations in policy-related matters, including its development, formulation, implementation, evaluation, review, and revision. By blending conceptual and practical considerations, Social Work in Public Health enables authors from many disciplines to examine health and social policy issues, concerns, and questions.