Knowledge Integration in Quitlines: Networks that Improve Cessation

描述（由申请人提供）：戒烟热线中的知识整合：改善戒烟的网络（KIQ NIC）摘要在美国，每五例死亡中就有一例与烟草使用有关，它仍然是过早死亡的主要可预防原因。鉴于烟草使用作为一种公共健康威胁的高度复杂性，国家癌症研究所支持了一项倡议和最近出版的一本烟草控制专著，旨在说明以何种方式（系统思维）可以改善烟草控制工作。在该专著中，NCI确定了社会网络分析和与个人和群体之间沟通有关的因素，认为这些因素对于理解和改进烟草控制等复杂适应系统的组织内最佳做法的传播和实施至关重要（NCI，2007年）。该调查小组是NCI倡议和专著的核心，拟议的研究是该倡议的直接延伸。拟议的研究旨在更好地了解网络和沟通机制，通过这些机制，现有和定义明确的烟草控制网络}北美戒烟联盟（NAQC）}中的利益相关者进行互动，分享新证据，就如何以及何时实施新知识做出决定，并实际采用他们认为将改善戒烟结果的做法。NAQC由NCI，CDC和其他组织资助，作为一种独特的研究实践合作，以支持基于电话的戒烟。截至2006年，每一个美国。S.州（包括哥伦比亚特区）加拿大的每个省都实施了戒烟热线，因此将有62个戒烟热线的人群纳入拟议的研究。在研究人员和NAQC成员之间的仪器开发和团队建设形成一年之后，将实施三波社交网络和决策分析，以分析采用和实施新证据和知识的过程。此外，将分析实际的戒烟线操作，以跟踪新做法的实施，多变量建模将评估网络，决策的相对影响，以及其他潜在的影响，采用新的戒烟线的做法。这些结果有望增加我们对如何弥合研究人员，服务组织，提供者和客户之间的差距的理解，并探索如何在NAQC内传播，实施和整合新知识，特别是新的科学证据。公共卫生相关性：在美国，每五例死亡中就有一例与烟草使用有关，它仍然是导致过早死亡的主要可预防原因。幸运的是，美国和加拿大的每个州和省现在都有免费的戒烟热线，帮助吸烟者戒烟。不幸的是，我们对如何在这些退出线上实施最佳实践和创新知之甚少。拟议的研究旨在更好地了解戒烟热线网络如何实施最佳做法和创新。将实施三波社交网络和决策分析，以分析新证据和知识的采用和实施过程，并分析实际退出线操作，以跟踪新实践的实施。

DESCRIPTION (provided by applicant): Knowledge Integration in Quitlines: Networks that Improve Cessation (KIQ NIC) Abstract One in every five deaths in the U.S. is related to tobacco use, and it remains the leading preventable cause of premature death. Given the highly complex nature of tobacco use as a public health threat, the National Cancer Institute supported an initiative and a recently published tobacco control monograph designed to describe in what ways (systems thinking) might improve tobacco control efforts. In that monograph, NCI identified social network analysis and factors related to communication between individuals and groups as critical to understanding and improving the dissemination and implementation of best practices within organizations that are part of a complex adaptive system such as tobacco control (NCI, 2007). This investigative team was central to the NCI initiative and Monograph, and the proposed study is a direct extension of that initiative. The proposed study is designed to better understand the network and communications mechanisms by which stakeholders in an existing and well-defined tobacco control network } the North American Quitline Consortium (NAQC) } interact, share new evidence, make decisions on how and when to implement new knowledge, and actually adopt practices that they believe will improve quitline outcomes. The NAQC is funded by NCI, CDC and other organizations as a unique research-to-practice collaboration to support telephone- based tobacco cessation. As of 2006, every U. S. state (including D.C.) and every Canadian province had implemented a smoking cessation quitline, thus resulting in a population of 62 quitlines that will be included in the proposed study. Following a formative year of instrument development and team building between the researchers and NAQC members, three waves of social network and decision-making analyses will be implemented to analyze processes of adoption and implementation of new evidence and knowledge. In addition, actual quitline operations will be analyzed in order to track implementation of new practices, and multivariate modeling will assess the relative influences of network, decision-making, and other potential influences on adoption of new quitline practices. The results are expected to increase our understanding of how to bridge the gaps between researchers, services organizations, providers, and clients, and to explore how new knowledge} especially new scientific evidence} is disseminated, implemented, and integrated within the NAQC. PUBLIC HEALTH RELEVANCE: One in every five deaths in the U.S. is related to tobacco use, and it remains the leading preventable cause of premature death. Fortunately, every state and Province in the U.S. and Canada, respectively, now has a free telephone quitline to help smokers quit. Unfortunately, we know little about how best practices and innovations are implemented in those quitlines. The proposed study is designed to better understand how the network of quitlines implements best practices and innovations. Three waves of social network and decision-making analyses will be implemented to analyze processes of adoption and implementation of new evidence and knowledge, and actual quitline operations will be analyzed in order to track implementation of new practices.