Measuring the LINKS Model for Knowledge Sharing Using Social Network Analysis
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Abstract
Background: Knowledge Translation plays a vital role in the modern health care community, facilitating the movement of new evidence into practice. The Leveraging Internet for Knowledge Sharing (LINKS) model provides the tools for enabling knowledge translation between clinicians using web 2.0 tools. This model has been implemented in a pediatric pain discussion forum in Thailand, linking practitioners from nine different hospitals and allowing them to communicate electronically in a secure forum.
Objective: The goals of this project are (a) to summarize the implementation of the LINKS model and develop a formal LINKS evaluation framework; and (b) to analyze the communication patterns that evolved out of the discussion forum using social network analysis methods.
Methods: The LINKS model was formally analyzed and deconstructed into its composite parts, which were then connected to specific implementation activities performed by the team that designed the Thai discussion forum. Summary statistics provide a broad overview of the communication patterns in the network, and Social network analysis provides the tools to delve deeper into communication patterns of the network. User-level centrality measures help identify those members that are most active within the community, and provide a broad overview of the health of the community. Core-Periphery analysis helps identify a set of users (and threads) that are at the centre of the traffic within the community. Finally, group-level centrality measures can provide insight into how different groups of users (both professional and geographical groupings) interact with users outside their community.
Results: The summary of the LINKS model has resulted in an implementation checklist that can be used to guide the deployment of web 2.0 tools designed for knowledge translation. This checklist can be used to both guide the development of an intervention and be used to evaluate the project during its use and at the end of the project. The social network analysis discovered a healthy network with strong communication patterns, while identifying which users are at the centre of the community in terms of facilitating communication. The group-level analysis suggests that there is strong inter-professional and inter-regional communication, but a dearth of non-nurse participants has been identified as a shortcoming. Specific social network analysis methods have been identified as tools to evaluate the components of the LINKS model.
Conclusion: The checklist developed through this project provides a valuable resource to the knowledge translation community. The results of the social network analysis suggest that the discussion forum is being used by the community, and that, though few, the inter-community ties are strong. Future work should be on connecting more analytic techniques directly to components of the implementation checklist, providing a complete analytical framework to accompany the LINKS model, and on testing the checklist on a new web-based knowledge translation tool.
Objective: The goals of this project are (a) to summarize the implementation of the LINKS model and develop a formal LINKS evaluation framework; and (b) to analyze the communication patterns that evolved out of the discussion forum using social network analysis methods.
Methods: The LINKS model was formally analyzed and deconstructed into its composite parts, which were then connected to specific implementation activities performed by the team that designed the Thai discussion forum. Summary statistics provide a broad overview of the communication patterns in the network, and Social network analysis provides the tools to delve deeper into communication patterns of the network. User-level centrality measures help identify those members that are most active within the community, and provide a broad overview of the health of the community. Core-Periphery analysis helps identify a set of users (and threads) that are at the centre of the traffic within the community. Finally, group-level centrality measures can provide insight into how different groups of users (both professional and geographical groupings) interact with users outside their community.
Results: The summary of the LINKS model has resulted in an implementation checklist that can be used to guide the deployment of web 2.0 tools designed for knowledge translation. This checklist can be used to both guide the development of an intervention and be used to evaluate the project during its use and at the end of the project. The social network analysis discovered a healthy network with strong communication patterns, while identifying which users are at the centre of the community in terms of facilitating communication. The group-level analysis suggests that there is strong inter-professional and inter-regional communication, but a dearth of non-nurse participants has been identified as a shortcoming. Specific social network analysis methods have been identified as tools to evaluate the components of the LINKS model.
Conclusion: The checklist developed through this project provides a valuable resource to the knowledge translation community. The results of the social network analysis suggest that the discussion forum is being used by the community, and that, though few, the inter-community ties are strong. Future work should be on connecting more analytic techniques directly to components of the implementation checklist, providing a complete analytical framework to accompany the LINKS model, and on testing the checklist on a new web-based knowledge translation tool.
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