Developing a Scientific Workforce Analysis and Modeling Framework

开发科学的劳动力分析和建模框架

• 批准号: 7952813
• 负责人: Joshua Hawley
• 金额: $ 28.47万
• 依托单位: OHIO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2014-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7952813
• 关键词: Academia; Accounting; Achievement; Affect; Area; Behavior; Biological Models; Characteristics; Communities; Complex; Consultations; Data; Data Collection; Data Set; Decision Making; Economics; Ecosystem; Education; Feedback; Funding; Future; Goals; Health Sciences; Industry; Institution; International; Internet; Intervention; Knowledge; Literature; Longitudinal Surveys; Mathematics; Medical; Medicine; Methods; Modeling; Pattern; Performance; Policies; Policy Maker; Population; Principal Investigator; Process; Publishing; Research; Research Personnel; Resolution; Running; Science; Societal Factors; Staging; Structure; Students; System; Talents; Time; United States National Institutes of Health; Universities; career; collected works; design; driving force; flexibility; innovation; insight; interest; model development; models and simulation; network models; programs; public health relevance; science education; simulation; sound; stem; technological innovation; tool; trend

DESCRIPTION (provided by applicant): This research proposes to develop a layered, extensible system modeling framework representing the diverse, complex, and interdependent institutions and policies that influence the quality and availability of the U.S. academic medicine/health sciences (M/HS) workforce. This approach avoids the tendency to "lock in" to a single model that may be appropriate only for certain types of analysis by developing multiple models at different levels of resolution, using a variety of modeling tools. Model development will be an iterative and recursive process, starting with top-down modeling to develop the key insights needed and guide data collection, which will in turn suggest the detailed model structure required to make sense of the empirical findings. The choice of system domains and behaviors to model will be guided by consultations with subject-matter experts and coordination with other efforts funded under this solicitation. Quantitative associations will be established through review of the published literature and examination of extant datasets, including a number of large-scale longitudinal surveys not heretofore available to modelers. Selected issues and policy scenarios will be investigated via simulation runs. Model interfaces will be developed that align with the needs and capacities of key stakeholders, such as NIH managers and policymakers. The long-term goal of this research is to encourage the use of integrated simulation modeling tools within the M/HS community to support the establishment of sound policies and practices for workforce improvement and beneficial interventions in education, recruitment and retention. Such models have the potential to enhance decision-making processes by allowing leaders to (a) account for historical patterns in the M/HS education systems, (b) examine what might have occurred under other historical conditions, (c) explore what may happen in a variety of future scenarios, (d) identify methods and/or points of intervention with higher leverage (stronger influence) over system behavior, (e) characterize the time constants applicable to various actions or changes, and (f) identity the most critical areas for future research and data collection. PUBLIC HEALTH RELEVANCE: Patterns and trends in U.S. student science and mathematics abilities and career selections raise concern about the future supply of well-prepared people entering the nation's medical and health sciences workforce. This project will rigorously model the complex web of factors influencing these patterns and trends and develop tools to assist national leaders in designing more effective policies and programs aimed at assuring this vital flow of talent.

描述（由申请人提供）：本研究建议开发一个分层的、可扩展的系统建模框架，代表影响美国学术医学/健康科学（M/HS）劳动力质量和可用性的多样化、复杂且相互依赖的机构和政策。这种方法通过开发不同分辨率级别的多个模型，避免了“锁定”单个模型的趋势，该模型可能仅适用于某些类型的分析。 各种建模工具。模型开发将是一个迭代和递归的过程，从自上而下的建模开始，以开发所需的关键见解并指导数据收集，这反过来又会提出理解实证结果所需的详细模型结构。系统域和建模行为的选择将通过与主题专家的协商以及与本次招标资助的其他工作的协调来指导。将通过审查已发表的文献和检查现有数据集来建立定量关联，包括建模者迄今为止无法进行的一些大规模纵向调查。将通过模拟运行来调查选定的问题和政策情景。将开发符合关键利益相关者（例如 NIH 管理者和政策制定者）​​需求和能力的模型接口。这项研究的长期目标是鼓励在 M/HS 社区内使用集成模拟建模工具，以支持制定健全的政策和实践，以改善劳动力以及在教育、招聘和保留方面进行有益的干预。这些模型有可能增强决策过程，让领导者能够（a）解释 M/HS 教育系统的历史模式，（b）检查在其他历史条件下可能发生的情况，（c）探索可能发生的情况在各种未来场景中，（d）确定对系统行为具有更高影响力（更强影响力）的方法和/或干预点，（e）描述适用于各种行动或变化的时间常数，以及（f）识别最重要的未来研究和数据收集的关键领域。 公共卫生相关性：美国学生科学和数学能力以及职业选择的模式和趋势引起了人们对未来进入国家医疗和健康科学劳动力队伍做好充分准备的人员的担忧。该项目将严格模拟影响这些模式和趋势的复杂因素网络，并开发工具来协助国家领导人设计更有效的政策和计划，以确保这一重要的人才流动。