Coevolution of Information Sharing and Implementation of Evidence-Based Practices Among North American Tobacco Cessation Quitlines.

OBJECTIVES We examined the coevolution of information sharing and implementation of evidence-based practices among US and Canadian tobacco cessation quitlines within the North American Quitline Consortium (NAQC). METHODS Web-based surveys were used to collect data from key respondents representing each of 74 participating funders of NAQC quitlines during the summer and fall of 2009, 2010, and 2011. We used stochastic actor-based models to estimate changes in information sharing and practice implementation in the NAQC network. RESULTS Funders were more likely to share information within their own country and with funders that contracted with the same service provider. Funders contracting with larger service providers shared less information but implemented significantly more practices. Funders connected to larger numbers of tobacco control researchers more often received information from other funders. Intensity of ties to the NAQC network administrative organization did not influence funders' decisions to share information or implement practices. CONCLUSIONS Our findings show the importance of monitoring the NAQC network over time. We recommend increased cross-border information sharing and sharing of information between funders contracting with different and smaller service providers.

[1]  Mark Huisman,et al.  Statistical Analysis of Longitudinal Network Data With Changing Composition , 2003 .

[2]  E. Ferlie,et al.  Interlocking Interactions, the Diffusion of Innovations in Health Care , 2002 .

[3]  Peter R. Monge,et al.  Normative Influences on Network Structure in the Evolution of the Children’s Rights NGO Network, 1977-2004 , 2015, Commun. Res..

[4]  Filip Agneessens,et al.  Where do intra-organizational advice relations come from? The role of informal status and social capital in social exchange , 2012, Soc. Networks.

[5]  Erin K. Ruppel,et al.  Mapping tobacco quitlines in North America: signaling pathways to improve treatment. , 2012, American journal of public health.

[6]  K. Provan,et al.  Awareness of Evidence-Based Practices by Organizations in a Publicly Funded Smoking Cessation Network. , 2013, Journal of public administration research and theory : J-PART.

[7]  Karen Messer,et al.  Smoking cessation rates in the United States: a comparison of young adult and older smokers. , 2008, American journal of public health.

[8]  Jeremy L. Hall,et al.  Evidence-Based Practice and the Use of Information in State Agency Decision-Making , 2012 .

[9]  Kayo Fujimoto,et al.  NETWORK STRUCTURAL INFLUENCES ON THE ADOPTION OF EVIDENCE-BASED PREVENTION IN COMMUNITIES. , 2009, Journal of community psychology.

[10]  Vital signs: current cigarette smoking among adults aged ≥18 years--United States, 2005-2010. , 2011, MMWR. Morbidity and mortality weekly report.

[11]  K. Cummings,et al.  Debunking myths about self-quitting. Evidence from 10 prospective studies of persons who attempt to quit smoking by themselves. , 1989, The American psychologist.

[12]  T. Valente,et al.  Community coalitions as a system: effects of network change on adoption of evidence-based substance abuse prevention. , 2007, American journal of public health.

[13]  René Veenstra,et al.  Actor-based model for network and behavior dynamics , 2012 .

[14]  Jenine K Harris,et al.  Seeing the forest and the trees: using network analysis to develop an organizational blueprint of state tobacco control systems. , 2008, Social science & medicine.

[15]  Robin H. Lemaire,et al.  Core concepts and key ideas for understanding public sector organizational networks: Using research to inform scholarship and practice , 2012 .

[16]  A. Boaz,et al.  The Perilous Road from Evidence to Policy: Five Journeys Compared , 2005, Journal of Social Policy.

[17]  Tom A. B. Snijders,et al.  Introduction to stochastic actor-based models for network dynamics , 2010, Soc. Networks.

[18]  M. Schweinberger Statistical modelling of network panel data: goodness of fit. , 2012, The British journal of mathematical and statistical psychology.

[19]  Indre Maurer,et al.  Dynamics of Social Capital and Their Performance Implications: Lessons from Biotechnology Start-ups , 2006 .

[20]  S. Dube,et al.  Vital signs: Current cigarette smoking among adults aged >=18 years --- United States, 2009 , 2010 .

[21]  K. L. Walker,et al.  Communicating in a Collaborating Group: A Longitudinal Network Analysis , 2012 .

[22]  W. Powell,et al.  Network Dynamics and Field Evolution: The Growth of Interorganizational Collaboration in the Life Sciences1 , 2005, American Journal of Sociology.

[23]  Peter Groenewegen,et al.  An Actor-Oriented Dynamic Network Approach , 2007 .

[24]  Elizabeth A. Graddy,et al.  Influences on the Size and Scope of Networks for Social Service Delivery , 2006 .

[25]  K. Provan,et al.  Modes of Network Governance: Structure, Management, and Effectiveness , 2007 .

[26]  Akbar Zaheer,et al.  Geography, Networks, and Knowledge Flow , 2007, Organ. Sci..

[27]  Ruth M. Ripley,et al.  Manual for RSiena , 2011 .

[28]  T. Snijders The statistical evaluation of social network dynamics , 2001 .

[29]  T. Snijders,et al.  Modeling the Coevolution of Networks and Behavior , 2007 .

[30]  Emmanuel Lazega,et al.  Norms, status and the dynamics of advice networks: A case study , 2012, Soc. Networks.