Development of a police officer stress algorithm to prevent adverse events: A mixed-methods approach

开发警官压力算法以防止不良事件：混合方法

• 批准号: 9788173
• 负责人: Katelyn K Jetelina
• 金额: $ 10.37万
• 依托单位: UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9788173
• 关键词: Development; police; officer; stress; algorithm

PROJECT SUMMARY Dr. Katelyn Jetelina is a postdoctoral Research Associate in the Department of Epidemiology at the University of Texas, School of Public Health. She is seeking three years of funding through the Mentored Research Scientist Development Award (K01). Dr. Jetelina conducts research in examining the acute and chronic stresses of law enforcement by evaluating the effects reactive outcomes, like coping mechanisms and excessive use-of-force, on officer health and safety. This area of study is significant due to the recent, highly visible concern that has largely framed reactive outcomes as police mismanagement rather than occupational health and safety. Dr. Jetelina’s long-term career goals are to become an independent investigator and a mixed- methods expert, and to develop a system-level intervention to reduce rates of police officer and citizen injury. In the current proposal, Dr. Jetelina outlines five short-term goals to be achieved throughout the award period that are intended to link her quantitative skills to new methodological techniques. These are: 1) to accumulate a strong knowledge base in qualitative methodology; 2) to gain formal training in mixed-methods design; 3) to learn the appropriate techniques and processes for stakeholder engagement; 4) to extend her current knowledge of officer health to community police based training; and 5) to orient herself with the science of team science. These goals will be achieved through a combination of mentoring by a multi- disciplinary team of established researchers, attendance at national workshops and conferences, focused coursework, and the proposed study. The proposed research plan seeks to contribute to the NORA Sector: Public Safety, Cross-sector: Traumatic Injury Prevention, and Strategic Goal 5: Evaluate information sources collected by stakeholders that may be enhanced to conduct effective occupational health and safety surveillance among law enforcement workers. This study will identify predisposing multi-dimensional factors that converge to create high-stress calls for Dallas Police Department (DPD) officers using a mixed-methods design. Specifically, the aims are: 1) To identify themes associated with consecutive high-stress calls and current stress decompression techniques through structured observations, focus groups, and distributing a stress survey among DPD officers; 2) To build a multi-level database that will classify calls for service on a stress continuum scale by triangulating new and pre-existing data from multiple DPD sources; and 3) To test the predictive capability of the integrated database, by evaluating statistical relationships between multi-level factors and adverse events (e.g. injury). Identifying predictors that contribute the greatest to high-stress calls is instrumental to inform a R01 application where Dr. Jetelina will develop a new computer-assisted dispatch system, which would take into account compound stress of a police officer’s shift and evaluate whether it reduces the likelihood of officer (and citizen) injury.

项目摘要 Katelyn Jetelina博士是纽约大学流行病学系的博士后研究助理。 德克萨斯大学公共卫生学院。她正在寻求三年的资金，通过指导 研究科学家发展奖（K 01）。Jetelina博士进行了检查急性和 通过评估应对机制等反应性结果的影响， 过度使用武力，危及军官健康和安全这一领域的研究是重要的，由于最近，高度 一个明显的关切，在很大程度上将反应性结果框定为警察管理不善，而不是职业 健康安全Jetelina博士的长期职业目标是成为一名独立调查员和一名混合- 方法专家，并制定一个系统级的干预措施，以减少警察和公民受伤率。 在目前的提案中，Jetelina博士概述了在整个奖项中要实现的五个短期目标 这一时期旨在将她的定量技能与新的方法技术联系起来。它们是：1） 在定性方法学方面积累了坚实的知识基础; 2）获得混合方法的正式培训 设计; 3）学习利益相关者参与的适当技术和流程; 4）扩展她的 目前的知识官员健康的社区警察为基础的培训;和5）定位自己与 团队科学这些目标将通过多方面的指导来实现， 由知名研究人员组成的学科小组，出席国家讲习班和会议， 课程作业和拟议的研究。 拟议的研究计划旨在为诺拉部门做出贡献：公共安全、跨部门：创伤 战略目标5：评估利益相关者收集的信息来源， 对执法人员进行有效的职业健康和安全监督。这项研究将确定 诱发多维因素，汇聚在一起，为达拉斯警察局创造高压力的电话 (DPD)使用混合方法设计的人员。具体而言，目标是：1）确定与以下方面有关的主题： 通过结构化观察，连续的高压力呼叫和当前的压力减压技术， 焦点小组，并在警察司官员中分发压力调查表; 2）建立一个多层次的数据库， 通过三角测量来自多个区域的新的和预先存在的数据， DPD来源;以及3）通过评估统计数据来测试综合数据库的预测能力 多水平因素与不良事件（如损伤）之间的关系。确定预测因素， 贡献最大的高压力电话是有用的通知R 01应用程序，其中博士Jetelina将 开发新的计算机辅助调度系统，该系统将考虑到警察的复合压力 检查官员的轮班情况，并评估其是否降低了官员（和公民）受伤的可能性。