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01.12.2012 | Research article | Ausgabe 1/2012 Open Access

BMC Health Services Research 1/2012

Information seeking for making evidence-informed decisions: a social network analysis on the staff of a public health department in Canada

BMC Health Services Research > Ausgabe 1/2012
Reza Yousefi-Nooraie, Maureen Dobbins, Melissa Brouwers, Patricia Wakefield
Wichtige Hinweise

Electronic supplementary material

The online version of this article (doi:10.​1186/​1472-6963-12-118) contains supplementary material, which is available to authorized users.

Competing interests

No financial and non-financial competing interests.

Authors’ contributions

Conception and design: RYN, MD, MB, PW; Performing analyses: RYN; interpretation of data: RYN, MD, MB, PW; drafting the manuscript: RYN; critical revising the manuscript for important intellectual content: RYN, MD, MB, PW; final approval of the version to be published: RYN, MD, MB, PW. All authors read and approved the final manuscript.



Social network analysis is an approach to study the interactions and exchange of resources among people. It can help understanding the underlying structural and behavioral complexities that influence the process of capacity building towards evidence-informed decision making. A social network analysis was conducted to understand if and how the staff of a public health department in Ontario turn to peers to get help incorporating research evidence into practice.


The staff were invited to respond to an online questionnaire inquiring about information seeking behavior, identification of colleague expertise, and friendship status. Three networks were developed based on the 170 participants. Overall shape, key indices, the most central people and brokers, and their characteristics were identified.


The network analysis showed a low density and localized information-seeking network. Inter-personal connections were mainly clustered by organizational divisions; and people tended to limit information-seeking connections to a handful of peers in their division. However, recognition of expertise and friendship networks showed more cross-divisional connections. Members of the office of the Medical Officer of Health were located at the heart of the department, bridging across divisions. A small group of professional consultants and middle managers were the most-central staff in the network, also connecting their divisions to the center of the information-seeking network. In each division, there were some locally central staff, mainly practitioners, who connected their neighboring peers; but they were not necessarily connected to other experts or managers.


The methods of social network analysis were useful in providing a systems approach to understand how knowledge might flow in an organization. The findings of this study can be used to identify early adopters of knowledge translation interventions, forming Communities of Practice, and potential internal knowledge brokers.
Additional file 1: Codes of actors with the highest centrality and brokerage measures according to various definitions (job title, division).(DOC 36 KB)
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