Hats & Ladders for Health: Data-driven Decision-Making for Future Health Citizens and Professionals

项目摘要 尽管对卫生保健工作者的需求不断增长，而且有证据表明，多样化的卫生工作者队伍对 在公共福祉方面，大多数年轻人缺乏对卫生职业选择以及如何追求这些选择的认识。窄 职业接触，建议不足，缺乏鼓励追求STEM科目，缺乏一致性 导师是黑人和拉丁美洲/x青年的重要障碍，这两个群体的代表性一直不足 在卫生专业中。该项目将帮助这些青少年克服障碍， 健康身份，使他们对自己承担具有挑战性的健康职业道路的能力更有信心， 做出明智的健康决定。为此，一个来自帽子和梯子公司的联合团队，在医学指导， 德克萨斯大学奥斯汀分校人类生态学学院，CareerVillage和应用课程研究将 设计，开发和测试健康的帽子和梯子：未来健康公民的数据驱动决策 专业人士（HLH）。这种混合数字体验的目标是9年级和10年级的学生和教育工作者， 一般职业和健康教育计划，并将包括一个数字游戏化的应用程序，基于项目 活动，现场健康职业小组，近同行辅导会议，以及一个强大的教学工具包与培训 视频、进度报告、课程和其他教育者支持，为学生提供准确、可操作的 反馈HLH的数据驱动，基于调查和包容性干预的总体结果可能 广泛的公共卫生影响，并（1）增加学生对他们追求的能力的信心 挑战健康职业道路并解决沿着问题;（2）提高他们发现， 理解并利用信息做出与健康相关的决定;（3）培养教育者的能力， 提供高质量的健康职业指导和健康素养教育。旨在加强我们组织的 对高中青年的影响，我们的干预将带来一系列新的互动-正如我们的要求， 现有用户-并利用它们在2010年期间深化与卫生职业和扫盲有关的探究式学习。 高中早期的关键阶段。 在第一阶段，H&L研发团队将从协调的医疗保健专业人员那里收集、分析和输入数据。 我们将把它整合到HLH应用程序中。为了收集数据，我们将开发， 和相关性测试，一项针对500名种族和专业多样化受访者的在线调查， CareerVillage的社区由3，000名卫生专业人员（52% BIPOC）和1，500多名医学导师组成 志愿者25-30名受访者将参加视频访谈。调查数据和视频 片段将被标记元数据并输入数据库，使我们能够推荐真实的， 相关的健康内容，以共享的人口和职业属性的学生。我们将测试可用性， 应用程序设计和原型的可行性与学生在小组或二人组，以及应用程序和仪表板 使用深度访谈与教育工作者的组件。我们还将调整两项学生成果指标， 青少年健康素养和职业决策自我效能量表的评估，使用专家 回顾和认知访谈的学生，然后测试的措施与样本的400名学生。所有 参与者将从纽约市青年和社区发展部的180+网络中招募 与纽约市高中合作的社区组织。在第二阶段，我们会研究及发展一套 接近最终产品，将在纽约市的五个教室进行试点测试，以进一步探索可用性、可行性和支持 从教育者。在试点测试之后，在第二阶段的第二年，我们将实施混合方法， 随机对照试验（RCT），以测试已完成的HLH创新对学生的影响的有效性 职业效能和健康素养。RCT由Applied Curriculum的外部评估团队领导 研究，将有助于我们确定HLH的整体有效性，以提高学生的健康职业效能感 和健康素养。

PROJECT SUMMARY Despite a growing demand for health care workers and evidence that a diverse health workforce is vital for public wellbeing, most young people lack awareness of health career options and how to pursue them. Narrow career exposure, insufficient advising, lack of encouragement to pursue STEM subjects, and lack of concordant mentors are significant barriers for Black and Latino/x youth—two groups consistently under-represented across health professions. This project will help these adolescents to overcome barriers and develop positive health identities so they are more confident in their ability to undertake challenging health career pathways and to make informed health decisions. To do so, a joint team from Hats & Ladders, Inc., Mentoring in Medicine, the University of Texas at Austin School of Human Ecology, CareerVillage and Applied Curiosity Research will design, develop, and test Hats & Ladders for Health: Data-driven Decision-Making for Future Health Citizens and Professionals (HLH). This blended digital experience targets 9th- and 10th-grade students and educators in general career and health education programs, and will consist of a digital gamified app, project-based activities, live health career panels, near-peer mentoring sessions, and a robust instructional toolkit with training videos, progress reports, lessons and other educator supports for providing accurate, actionable student feedback. The overall outcomes of HLH’s data-driven, inquiry-based, and inclusive intervention could have broad reaching public health impact, and are to (1) increase students’ confidence in their ability to pursue challenging health career pathways and solve problems along the way; (2) increase their ability to find, understand, and use information to make health-related decisions; and, (3) develop educators’ capacity to provide quality health career guidance and health literacy instruction. Designed to strengthen our organization’s impact on high school youth, our intervention will bring a novel set of interactions––as requested by our existing users––and use them to deepen inquiry-based learning related to health careers and literacy during the critical stage of early high school. In Phase I, the H&L R&D team will collect, analyze and input data from concordant healthcare professionals into a new health career database that we will integrate into the HLH app. To gather the data, we will develop, and test for relevance, an online survey targeting 500 racially and professionally diverse respondents through CareerVillage’s community of 3,000 health professionals (52% BIPOC) and 1,500+ Mentoring in Medicine volunteers. A subset of 25-30 survey respondents will participate in video interviews. Survey data and video snippets will be tagged with metadata and inputted into the database enabling us to recommend authentic and relevant health content to students with shared demographic and career attributes. We will test usability and feasibility of app designs and prototypes with students in small groups or dyads, and both app and dashboard components with educators using in-depth interviews. We will also adapt two student outcome measures, the Assessment of Adolescent Health Literacy and the Career Decision-Making Self Efficacy Scale, using expert reviews and cognitive interviews with students, and then test the measures with a sample of 400 students. All participants will be recruited from NYC Department of Youth and Community Development’s network of 180+ community-based organizations that work with NYC high schools. In Phase II, we will iterate and develop a near final product to pilot test in five NYC classrooms to further explore the usability, feasibility, and support from educators. Following the pilot test, in year two of Phase II we will implement a mixed-methods randomized controlled trial (RCT) to test the efficacy of the completed HLH innovation to impact students’ career efficacy and health literacy. The RCT, led by the External Evaluation team at Applied Curiosity Research, will help us determine the overall effectiveness of HLH to increase students’ health career efficacy and health literacy.