Abstract
The dynamics of interdisciplinary collaboration invite further investigation if we are to make this endeavour more rewarding and productive. We are using social network analysis to track the development of a new interdisciplinary collaboration on complex interventions to improve population health. It involves nineteen scholars across four countries. We report the Baseline network of formal relationships among the scholars, along with the impact of the collaboration on these relationships in the first 18 months. We observed statistically significant increases in the density of six types of relationship networks: citing publications by other members of the collaboration, email contact, meeting with each other (outside of the formal annual meeting), visiting one another’s institution, submitting research grants together and working on research projects together. The initial strategic role in the network of key ‘gate keepers’ has not altered substantially (betweenness centralization of the networks), but reciprocity has increased, that is, people are more likely to cite those who have cited them and work together. Increased collaboration is also reflected in the rise in number of subgroups over time and the increase in the average number of subgroup memberships. Use of social network analysis to understand the dynamics of interdisciplinary collaborations is a relatively new field. It invites reflection about what the optimal network structures for interdisciplinary collaborations would look like.
Similar content being viewed by others
Notes
We are grateful to an anonymous reviewer for this suggestion.
References
Aboelela, S. W., Merrill, J. A., Carley, K. M., & Larson, E. (2007). Social network analysis to evaluate an interdisciplinary research center. Journal of Research Administration, 38(1), 61–78.
Aviv, R., Erlich, Z., & Ravid, G. (2008). Analysis of transitivity and reciprocity in online distance learning networks. Connections, 28(1), 27–39.
Borgatti, S. P., Everett, M. G., & Freeman, L. C. (2002). UCINET for windows: Software for social network analysis. Harvard, MA: Analytic Technologies.
Burt, R. (2000). The network structure of social capital. In R. Sutton & B. Straw (Eds.), Research in organizational behavior (pp. 345–423). Greenwich, CT: Elsevier.
Carley, K. (1991). A theory of group stability. American Sociological Review, 56, 331–354.
Cummings, J. N., & Keisler, S. (2005). Collaborative research across disciplinary and organizational boundaries. Social Studies of Science, 35, 703–722.
Freeman, L. C. (1979). Centrality in social networks I: Concept clarification. Social Networks, 1, 215–239.
Hackett, E. J. (2005). Special guest edited issue on scientific collaboration. Social Studies of Science, 35, 667–671.
Hawe, P., Webster, C., & Shiell, A. (2004). A glossary of terms to navigate the field of social network analysis. Journal of Epidemiology and Community Health, 58, 971–975.
Luke, D. A., & Harris, J. K. (2007). Network analysis in public health: History, methods and applications. Annual Review of Public Health, 28, 69–73.
Marsden, P. V. (1990). Network data and measurement. Annual Review of Sociology, 16, 435–463.
Maton, K. I., Altman, D. G., & Kelly, J. G. (2006a). Community-based interdisciplinary research: Introduction to the special issue. American Journal of Community Psychology, 38, 1–7.
Maton, K. I., Perkins, D. D., & Saegert, S. (2006b). Community psychology at the crossroads: prospects for interdisciplinary research. American Journal of Community Psychology, 38, 9–21.
Monge, P. R., & Contractor, N. S. (2003). Theories of Communication Networks. New York: Oxford University Press.
Provan, K. G., Harvey, J., & Guernsey de Zapien, J. (2005). Network structure and attitudes toward collaboration in a community partnership for diabetes control on the US-Mexican border. Journal of Health Organization and Management, 19(6), 504–518.
Rogers, E. M. (1995). Diffusion of innovations. New York: Free Press.
Rosenfield, P. L. (1992). The potential of transdisciplinary research for sustaining and extending the linkages between the health and social sciences. Social Science and Medicine, 35, 1343–1357.
Schensul, J. J., Robison, J., Reyes, C., Radda, K., Gaztambide, S., & Disch, W. (2006). Building interdisciplinary/intersectoral research partnerships for community-based mental health research with older minority adults. American Journal of Community Psychology, 38, 79–93.
Smith-Lovin, L. (1999). Core concepts and common ground: The relational basis of our discipline. Social Forces, 78, 1–23.
Snijders, T. A. B., & Borgatti, S. P. (1999). Non parametric standard errors and test for network statistics. Connections, 22(2), 1–11.
Stokols, D., Fuqua, J., Gress, J., Harvey, R., Phillips, K., Baezconde-Garbanati, L., et al. (2003). Evaluating interdisciplinary science. Nicotine and Tobacco Research, 5, S21–S39.
Susser, M. (1995). The tribulations of trials. American Journal of Public Health, 85(2), 156–158.
Tanjasiri, S. P., Tran, J. H., Palmer, P. H., & Valente, T. W. (2007). Network analysis of an organizational collaboration for Pacific Islander cancer control. Journal of Health Care for the Poor and Underserved, 18(4), 184–196.
Valente, T. W., Chou, C. P., & Pentz, M. A. (2007). Community coalitions as a system: Effects of network change on adoption of evidence-based substance abuse prevention. American Journal of Public Health, 97(5), 880–886.
Wagner, C. S. (2005). Six case studies of international collaboration in science. Scientometrics, 62, 3–26.
Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. New York: Cambridge University Press.
West, E., Barron, D. N., Dowsett, J., & Newton, J. N. (1999). Hierarchies and cliques in the social networks of health care professionals: Implications for the design of dissemination strategies. Social Science and Medicine, 48(5), 633–646.
Acknowledgments
The International Collaboration on Complex Interventions is funded by a grant awarded through the Canadian Institutes of Health Research to the Principal Investigator, Penelope Hawe. The authors thank Alberto Nettel-Aguirre for his advice on the statistical significance testing. We thank our ICCI colleagues for taking part in this study.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Haines, V.A., Godley, J. & Hawe, P. Understanding Interdisciplinary Collaborations as Social Networks. Am J Community Psychol 47, 1–11 (2011). https://doi.org/10.1007/s10464-010-9374-1
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10464-010-9374-1