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Mapping the growing discipline of dissemination and implementation science in health

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The field of dissemination and implementation (D&I) research in health has grown considerably in the past decade. Despite the potential for advancing the science, limited research has focused on mapping the field. We administered an online survey to individuals in the D&I field to assess participants’ demographics and expertise, as well as engagement with journals and conferences, publications, and grants. A combined roster-nomination method was used to collect data on participants’ advice networks and collaboration networks; participants’ motivations for choosing collaborators was also assessed. Frequency and descriptive statistics were used to characterize the overall sample; network metrics were used to characterize both networks. Among a sub-sample of respondents who were researchers, regression analyses identified predictors of two metrics of academic performance (i.e., publications and funded grants). A total of 421 individuals completed the survey, representing a 30.75% response rate of eligible individuals. Most participants were White (n = 343), female (n = 284, 67.4%), and identified as a researcher (n = 340, 81%). Both the advice and the collaboration networks displayed characteristics of a small world network. The most important motivations for selecting collaborators were aligned with advancing the science (i.e., prior collaborators, strong reputation, and good collaborators) rather than relying on human proclivities for homophily, proximity, and friendship. Among a sub-sample of 295 researchers, expertise (individual predictor), status (advice network), and connectedness (collaboration network) were significant predictors of both metrics of academic performance. Network-based interventions can enhance collaboration and productivity; future research is needed to leverage these data to advance the field.

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American Psychological Association


American Public Health Association


Dissemination and Implementation


Health Maintenance Organization


Institute for Healthcare Improvement


Implementation Research Institute


Mentored Training in Dissemination and Implementation Research in Cancer


National Cancer Institute


National Institutes of Health


National Institute of Mental Health


Quality Enhancement Research Initiative


Training in Dissemination and Implementation Research in Health


United States


Veterans Affairs


  • Barabási, A.-L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286, 509–512.

    Article  MathSciNet  MATH  Google Scholar 

  • Brass, D. J. (2003). A social network perspective on human resources management. In R. Cross, A. Parker & L. Sasson (Eds.), Networks in the knowledge economy (pp. 283–323). Oxford: Oxford University Press.

    Google Scholar 

  • Brownson, R. C. (2013). Mentored training for dissemination and implementation research in cancer. National Cancer Institute.

  • Carrington, P. J., Scott, J., & Wasserman, S. (Eds.). (2005). Models and methods in social network analyses (Vol. 28). Cambridge: Cambridge University Press.

  • Ceci, S. J., & Williams, W. M. (2011). Understanding current causes of women’s underrepresentation in science. Proceedings of the National Academy of Sciences, 108, 3157–3162.

    Article  Google Scholar 

  • Certificate Program in Implementation Science: Translating Evidence into Practice, Policy and Public Health .

  • Chambers, D. A., & Norton, W. E. (2016). The adaptome: Advancing the science of intervention adaptation. American Journal of Preventive Medicine, 51, S124–S131.

    Article  Google Scholar 

  • Eccles, M. P., Foy, R., Sales, A., Wensing, M., & Mittman, B. (2012). Implementation science six years on–our evolving scope and common reasons for rejection without review. Implementation Science, 7, 71.

    Article  Google Scholar 

  • Eccles, M. P., & Mittman, B. S. (2006). Welcome to implementation science. Implementation Science, 1, 1.

    Article  Google Scholar 

  • Estabrooks, C. A., Derksen, L., Winther, C., Lavis, J. N., Scott, S. D., Wallin, L., et al. (2008). The intellectual structure and substance of the knowledge utilization field: A longitudinal author co-citation analysis, 1945 to 2004. Implementation Science, 3, 49.

    Article  Google Scholar 

  • Estabrooks, C. A., Winther, C., & Derksen, L. (2004). Mapping the field: A bibliometric analysis of the research utilization literature in nursing. Nursing Research, 53, 293–303.

    Article  Google Scholar 

  • Falk-Krzesinski, H. J., Borner, K., Contractor, N., Fiore, S. M., Hall, K. L., Keyton, J., et al. (2010). Advancing the science of team science. Clinical and Translational Science, 3, 263–266.

    Article  Google Scholar 

  • Global Implementation Conference .

  • Global Implementation Society .

  • Hawe, P., Webster, C., & Shiell, A. (2004). A glossary of terms for navigating the field of social network analysis. Journal of Epidemiology and Community Health, 58, 971–975.

    Article  Google Scholar 

  • Health Implementation Science .

  • Herrera, M., Roberts, D. C., & Gulbahce, N. (2010). Mapping the evolution of scientific fields. PLoS ONE, 5, e10355.

    Article  Google Scholar 

  • Hood, W., & Wilson, C. (2001). The literature of bibliometrics, scientometrics, and informetrics. Scientometrics, 52, 291–314.

    Article  Google Scholar 

  • Implementation Science Research Webinar Series .

  • KT Canada Summer Institute on Knowledge Translation .

  • Lewis, C. C., Fischer, S., Weiner, B. J., Stanick, C., Kim, M., & Martinez, R. G. (2015). Outcomes for implementation science: An enhanced systematic review of instruments using evidence-based rating criteria. Implementation Science, 10, 155.

    Article  Google Scholar 

  • Lungeanu, A., & Contractor, N. S. (2015). The effects of diversity and network ties on innovations: The emergence of a new scientific field. American Behavioral Scientist, 59, 548–564.

    Article  Google Scholar 

  • Lungeanu, A., Huang, Y., & Contractor, N. S. (2014). Understanding the assembly of interdisciplinary teams and its impact on performance. Journal of Informetrics, 8, 59–70.

    Article  Google Scholar 

  • McFadden, D. (1973). Conditional logit analysis of qualitative choice behavior. In P. Zarembka (Ed.), Frontiers in econometrics (pp. 105–142). New York: Academic Press.

    Google Scholar 

  • McKibbon, K. A., Lokker, C., Wilczynski, N. L., Ciliska, D., Dobbins, M., Davis, D. A., et al. (2010). A cross-sectional study of the number and frequency of terms used to refer to knowledge translation in a body of health literature in 2006: A Tower of Babel? Implementation Science, 5, 16.

    Article  Google Scholar 

  • Merrill, J. A., Keeling, J. W., Wilson, R. V., & Chen, T. V. (2011). Growth of a scientific community of practice public health services and systems research. American Journal of Preventive Medicine, 41, 100–104.

    Article  Google Scholar 

  • Merton, R. K. (1968). The Matthew effect in science. Science, 159, 56–63.

    Article  Google Scholar 

  • Meissner, H. I., Glasgow, R. E., Vinson, C. A., Chambers, D., Brownson, R. C., Green, L. W., et al. (2013). The U.S. training institute for dissemination and implementation research in health. Implementation Science, 8, 12.

    Article  Google Scholar 

  • Milgram, S. (1967). The small world problem. Psychology Today, 2, 60–67.

    Google Scholar 

  • Monge, P. R., & Contractor, N. S. (2003). Theories of communication networks. Oxford: Oxford University Press.

    Google Scholar 

  • Neta, G., Sanchez, M. A., Chambers, D. A., Phillips, S. M., Leyva, B., Cynkin, L., et al. (2015). Implementation science in cancer prevention and control: A decade of grant funding by the National Cancer Institute and future directions. Implementation Science, 10, 4.

    Article  Google Scholar 

  • Niven, D. J., Mrklas, K. J., Holodinsky, J. K., Straus, S. E., Hemmelgarn, B. R., Jeffs, L. P., et al. (2015). Towards understanding the de-adoption of low-value clinical practices: A scoping review. BMC Medicine, 13, 255.

    Article  Google Scholar 

  • Norton, W. E., Harris, R., Kramer, B. K. (2016). De-implementation: Exploring multi-level strategies for reducing overdiagnosis and overtreatment. In Preventing Overdiagnosis Conference. Barcelona, Spain.

  • Proctor, E. K. (2014). Implementation Research Institute. NIH.

  • Proctor, E. K., Landsverk, J., Baumann, A. A., Mittman, B. S., Aarons, G. A., Brownson, R. C., et al. (2013). The implementation research institute: Training mental health implementation researchers in the United States. Implementation Science, 8, 105.

    Article  Google Scholar 

  • Purtle, J., Peters, R., & Brownson, R. C. (2016). A review of policy dissemination and implementation research funded by the National Institutes of Health, 2007–2014. Implementation Science, 11, 1.

    Article  Google Scholar 

  • QUERI Implementation Seminar Series. (2015).

  • Rabin, B. A., Lewis, C. C., Norton, W. E., Neta, G., Chambers, D., Tobin, J. N., et al. (2016). Measurement resources for dissemination and implementation research in health. Implementation Science, 11, 42.

    Article  Google Scholar 

  • Rabin, B. A., Purcell, P., Naveed, S., Moser, R. P., Henton, M. D., Proctor, E. K., et al. (2012). Advancing the application, quality and harmonization of implementation science measures. Implementation Science, 7, 119.

    Article  Google Scholar 

  • Society for Implementation Research Collaboration .

  • Stamatakis, K. A., Norton, W. E., Stirman, S. W., Melvin, C., & Brownson, R. C. (2013). Developing the next generation of dissemination and implementation researchers: Insights from initial trainees. Implementation Science, 8, 29.

    Article  Google Scholar 

  • Tinkle, M., Kimball, R., Haozous, E. A., Shuster, G., & Meize-Grochowski, R. (2013). Dissemination and implementation research funded by the US National Institutes of Health, 2005–2012. Nursing Research and Practice, 2013, 909606.

    Article  Google Scholar 

  • Valente, T. W. (2010). Social networks and health: Models, methods, and applications. Oxford: Oxford University Press.

    Book  Google Scholar 

  • Valente, T. W. (2012). Network interventions. Science, 337, 49–53.

    Article  Google Scholar 

  • Vanni, T., Mesa-Frias, M., Sanchez-Garcia, R., Roesler, R., Schwartsmann, G., Goldani, M. Z., et al. (2014). International scientific collaboration in HIV and HPV: A network analysis. PLoS ONE, 9, e93376.

    Article  Google Scholar 

  • Waimey, K. E., Duncan, F. E., Su, H. I., Smith, K., Wallach, H., Jona, K., et al. (2013). Future directions in oncofertility and fertility preservation: A report from the 2011 oncofertility consortium conference. Journal of Adolescent Young Adult Oncology, 2, 25–30.

    Article  Google Scholar 

  • Wald, A. (1943). Tests of statistical hypotheses concerning several parameters when the number of observations is large. Transactions of the American Mathematical society, 54, 426–482.

    Article  MathSciNet  MATH  Google Scholar 

  • Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications (Vol. 8). Cambridge: Cambridge University Press.

    Book  MATH  Google Scholar 

  • Watts, D. J. (2004). Six degrees: The science of a connected age. New York: WW Norton & Company.

    Google Scholar 

  • Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of ‘small-world’networks. Nature, 393, 440–442.

    Article  Google Scholar 

  • Wuchty, S., Jones, B. F., & Uzzi, B. (2007). The increasing dominance of teams in production of knowledge. Science, 316, 1036–1039.

    Article  Google Scholar 

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The authors would like to thank everyone who completed the survey and the D&I researchers who graciously donated their time for a 1-h consultation as part of the raffle drawing for participant incentives.


Preparation of this manuscript is supported in part by NIH 5U01GM112623-02. Data collection and analysis was supported in part by discretionary funds provided by UAB to WEN.

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Authors and Affiliations



WEN participated in study development, study design, coordination of data collection, data interpretation, and manuscript writing and editing. AL participated in data analysis, data interpretation, and manuscript writing and editing. DAC participated in data interpretation and manuscript writing and editing. NSC participated in study development, study design, coordination of data collection, data interpretation, and manuscript writing and editing.

Corresponding author

Correspondence to Wynne E. Norton.

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Conflict of interest

NSC is the co-founder and Chairman of Syndio. WEN, AL and DAC have no competing interests.

Ethical approval

The Institutional Review Boards at the University of Alabama at Birmingham and Northwestern University reviewed and approved the study under exempt status.

Informed consent

Individuals listed in Table 3 provided written consent to be named in the manuscript.

Availability of data and material

The datasets generated during and/or analyzed during the current study are not publicly available to maintain privacy and confidentiality associated with social network data.

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Norton, W.E., Lungeanu, A., Chambers, D.A. et al. Mapping the growing discipline of dissemination and implementation science in health. Scientometrics 112, 1367–1390 (2017).

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