Utilizing a Data-to-Action Approach to Cultivate Policy Research and Advocacy Skills in Community-Engaged Health Promotion Courses

IF 1.1 Q3 EDUCATION & EDUCATIONAL RESEARCH
Ameena Batada, Audrey E. Thomas, D. Holtz
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引用次数: 2

Abstract

Community-engaged (or service) learning is a common approach in health promotion and undergraduate education and can provide students with an opportunity to learn about the social determinants of health and policy change and advocacy. Students can support organizations with policy advocacy to promote more equitable resource allocation in communities close to campus and take these skills into their future professions. This article presents an overview of and the lessons learned from a “data-to-action” approach, as well as a summary of students’ perceptions on being part of a class taking this approach. In partnership with community organizations advocating for policy change, a data-to-action approach engages and guides students in primary and/or secondary data collection, analysis, and reporting. Through the projects described in this article, students observed how policy change can affect the social determinants of health, and they contributed to advocacy efforts for policy change, such as extending bus routes, reducing the marketing and sales of tobacco, and prioritizing resources for people who are houseless. Overall, students reported that they gained familiarity with local communities and with research and other professional skills. A data-to-action approach has the potential to benefit both students and community organizations’ local advocacy efforts.
利用数据到行动的方法在社区参与的健康促进课程中培养政策研究和宣传技能
社区参与(或服务)学习是健康促进和本科教育的一种常见方法,可以为学生提供了解健康和政策变化和宣传的社会决定因素的机会。学生可以支持政策倡导组织,促进校园附近社区更公平的资源分配,并将这些技能应用到他们未来的职业中。本文概述了从“数据到行动”方法中学到的经验教训,并总结了学生对采用这种方法的班级的看法。与倡导政策变革的社区组织合作,采用数据到行动的方法,让学生参与并指导他们进行初级和/或二级数据的收集、分析和报告。通过本文所述的项目,学生们观察到政策变化如何影响健康的社会决定因素,他们为政策变化的宣传工作做出了贡献,例如延长公共汽车路线,减少烟草的营销和销售,以及优先为无家可归者提供资源。总体而言,学生们报告说,他们熟悉了当地社区,掌握了研究和其他专业技能。从数据到行动的方法有可能使学生和社区组织在当地的宣传工作受益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.10
自引率
33.30%
发文量
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