Developing an online educational curriculum to enhance parent-supervised driving

描述（由申请人提供）：机动车碰撞是青少年死亡和受伤的主要原因，每年造成3000多人死亡，受伤人数是车祸的100倍，相关费用超过140亿美元。美国疾病控制与预防中心已经将交通事故和相关伤害确定为公共卫生的首要任务。缺乏经验是青少年新手驾驶事故的主要原因，但积累必要的经验，成为一个安全的司机可能需要很多年。幸运的是，来自驾驶和其他领域的证据表明，通过基于场景的培训可以增加经验知识。目前为青少年提供练习的方法侧重于父母监督驾驶。然而，家长们并没有准备好承担这个角色，许多人只关注驾驶技术、法律和一般的安全建议。很少有父母讨论驾驶决策方面的问题，甚至可能传递不准确的信息。许多父母限制了青少年接触驾驶情况的范围，错误地认为这增加了安全，而不是危险地限制了青少年积累重要驾驶经验的能力。我们的长期目标是设计和验证一种创新的工具，旨在加速青少年司机获得关键的安全知识。我们建议通过开发适合父母使用的场景来扩展我们团队过去的工作，以指导他们没有经验的青少年司机。这些场景将成为在线教育课程的一部分，旨在帮助父母在青少年学习驾驶时为他们提供指导练习。该在线工具将基于场景的培训与机器学习技术的创新应用相结合，以评估场景响应，并提供量身定制的反馈，其中包含实用的、适合发展的策略，以提高安全性，并为父母监督的道路实践提供建议。第一阶段将解决这些具体目标：1)进行基础研究，通过对15-18岁青少年司机的半结构化访谈，确定新手青少年司机经常遇到的现实情况。2)收集不同驾驶经验水平的青少年和成人对场景的代表性反应，以确定知识的进展，并确定适合发展的策略作为反馈。3)创建机器学习算法，根据对场景的反应提供量身定制的反馈，并推荐上路驾驶体验。4)开发在线系统原型。第二阶段将侧重于其他具体目标：5)将第一阶段的概念证明发展成一个完整的在线课程，并使用完善的算法。6)通过焦点小组评估在线课程的可用性，接受度，以及通过驾驶模拟器实验和有限的青少年新手现场试验评估在线课程的有效性。拟议的产品代表了青少年驾驶员培训方法的重大转变，通过第三阶段的传播，它将填补以证据为基础的家长教导的驾驶员教育的关键需求。

DESCRIPTION (provided by applicant): Motor vehicle crashes are the leading cause of death and injury for teens, accounting annually for over 3000 deaths, 100 times as many injuries, and over 14 billion dollars in associated costs. The CDC has identified traffic crashes and associated injuries as a top public health priority. Inexperience is the leading cause of crashes among novice teen drivers, but accumulating the necessary experiences to become a safe driver can take many years. Fortunately, evidence from driving and other domains suggests that it is possible to increase experiential knowledge through scenario-based training. Current methods for providing teens with practice focus on parent-supervised driving. However, parents are ill-prepared to handle this role, with many focusing only on the mechanics of driving, laws and general safety advice. Few parents discuss decision-making aspects of driving and may even pass on inaccurate information. Many parents limit the range of driving situations teens are exposed to mistakenly believing that this increases safety rather than dangerously limiting teens' ability to accumulate important driving experience. Our long-term objective is to design and validate an innovative tool that aims to accelerate the acquisition of critical safety knowledge for teen drivers. We propose to extend our team's past work by developing scenarios appropriate for parents to use to mentor their inexperienced teen drivers. The scenarios will be part of an online educational curriculum designed to help parents provide teens with guided practice as they learn how to drive. The online tool will combine scenario- based training with innovative applications of machine learning technology to evaluate scenario responses and provide tailored feedback containing practical, developmentally appropriate strategies for improving safety as well as recommendations for parent-supervised on-the-road practice. Phase I will address these specific aims: 1) Conduct foundational research to identify realistic scenarios commonly encountered by novice teen drivers through semi-structured interviews with teen drivers aged 15-18. 2) Collect representative responses to scenarios from teens with different levels of driving experience and adults to identify the progression of knowledge and identify developmentally appropriate strategies to use as feedback. 3) Create machine learning algorithms to provide tailored feedback and recommend on-the-road driving experiences based on responses to the scenarios. 4) Develop prototype online system. Phase II will focus on additional specific aims: 5) Develop the Phase I proof of concept into a complete online curriculum with refined algorithms. 6) Evaluate the online curriculum for usability, acceptance via focus groups, and effectiveness via a driving simulator experiment and limited field trial with novice teen drivers. The proposed product represents a significant shift in trainig approaches for teen drivers and through Phase III dissemination it will fill a critical need for evidence- based parent-taught driver's education. PUBLIC HEALTH RELEVANCE: Motor vehicle crashes are the leading cause of death and injury for teens, accounting annually for over 3000 deaths, 100 times as many injuries, and over 14 billion dollars in associated costs; despite this, many teens' primary source of driver's education is their parents. In Phase I we propose to extend our past work for teaching experiential knowledge and develop a prototype online educational curriculum that allows parents to provide teens with guided practice by utilizing innovative machine learning technologies, while Phase II will allow us to complete the prototype and evaluate its effectiveness. The proposed application represents a significant shift in training approaches that has the potential, through Phase III dissemination, to improve teen driving safety.