Johnson Kimberly, Quanbeck Andrew, Maus Adam, Gustafson David H, Dearing James W
University of Wisconsin, Madison, WI USA.
Transl Behav Med. 2015 Sep;5(3):260-8. doi: 10.1007/s13142-015-0327-y.
Understanding influence networks among substance abuse treatment clinics may speed the diffusion of innovations. The purpose of this study was to describe influence networks in Massachusetts, Michigan, New York, Oregon, and Washington and test two expectations, using social network analysis: (1) Social network measures can identify influential clinics; and (2) Within a network, some weakly connected clinics access out-of-network sources of innovative evidence-based practices and can spread these innovations through the network. A survey of 201 clinics in a parent study on quality improvement provided the data. Network measures and sociograms were obtained from adjacency matrixes created by UCINet. We used regression analysis to determine whether network status relates to clinics' adopting innovations. Findings suggest that influential clinics can be identified and that loosely linked clinics were likely to join the study sooner than more influential clinics but were not more likely to have improved outcomes than other organizations. Findings identify the structure of influence networks for SUD treatment organizations and have mixed results on how those structures impacted diffusion of the intervention under study. Further study is necessary to test whether use of knowledge of the network structure will have an effect on the pace and breadth of dissemination of innovations.
了解药物滥用治疗诊所之间的影响网络可能会加速创新的传播。本研究的目的是描述马萨诸塞州、密歇根州、纽约州、俄勒冈州和华盛顿州的影响网络,并使用社会网络分析来检验两个预期:(1)社会网络指标可以识别有影响力的诊所;(2)在一个网络中,一些联系薄弱的诊所会获取网络外基于证据的创新实践来源,并能通过该网络传播这些创新。在一项关于质量改进的母研究中,对201家诊所进行的调查提供了数据。网络指标和社会关系图来自UCINet创建的邻接矩阵。我们使用回归分析来确定网络地位是否与诊所采用创新有关。研究结果表明,可以识别出有影响力的诊所,并且联系松散的诊所可能比更有影响力的诊所更早加入研究,但与其他组织相比,其改善结果的可能性并不更高。研究结果确定了物质使用障碍治疗组织影响网络的结构,并且关于这些结构如何影响所研究干预措施的传播有不同结果。有必要进行进一步研究,以检验利用网络结构知识是否会对创新传播的速度和广度产生影响。