Openly accessible

Collaboration in complex systems: multilevel network analysis for community-based obesity prevention interventions

McGlashan, Jaimie, de la Haye, Kayla, Wang, Peng and Allender, Steven 2019, Collaboration in complex systems: multilevel network analysis for community-based obesity prevention interventions, Scientific Reports, vol. 9, no. 1, pp. 1-10, doi: 10.1038/s41598-019-47759-4.

Attached Files
Name Description MIMEType Size Downloads

Title Collaboration in complex systems: multilevel network analysis for community-based obesity prevention interventions
Author(s) McGlashan, JaimieORCID iD for McGlashan, Jaimie orcid.org/0000-0003-4543-7161
de la Haye, Kayla
Wang, Peng
Allender, StevenORCID iD for Allender, Steven orcid.org/0000-0002-4842-3294
Journal name Scientific Reports
Volume number 9
Issue number 1
Article ID 12599
Start page 1
End page 10
Total pages 10
Publisher Nature
Place of publication London, Eng.
Publication date 2019
ISSN 2045-2322
Keyword(s) Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
PERFORMANCE
MODELS
Summary © 2019, The Author(s). Community-based systems interventions represent a promising, but complex approach to the prevention of childhood obesity. Existing studies suggest that the implementation of multiple actions by engaged community leaders (steering committees) is of critical importance to influence a complex system. This study explores two key components of systems interventions: (1) steering committees; and (2) causal loop diagrams (CLDs), used to map the complex community-level drivers of obesity. The interactions between two components create an entangled, complex process difficult to measure, and methods to analyse the dependencies between these two components in community-based systems interventions are limited. This study employs multilevel statistical models from social network analysis to explore the complex interdependencies between steering committee collaboration and their actions in the CLD. Steering committee members from two communities engaged in obesity prevention interventions reported on their collaborative relationships with each other, and where their actions are situated in a locally developed CLD. A multilevel exponential random graph model (MERGM) was developed for each community to explore the structural configurations of the collaboration network, actions in the CLD, and cross-level interactions. The models showed the tendency for reciprocated and transitive collaboration among committee members, as well as some evidence of more complex multilevel configurations that may indicate integrated solutions and collective action. The use of multilevel network analysis represents a step toward unpacking the complexities inherent in community-based systems interventions for obesity prevention.
Language eng
DOI 10.1038/s41598-019-47759-4
Indigenous content off
HERDC Research category C1 Refereed article in a scholarly journal
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30129646

Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 88 Abstract Views, 0 File Downloads  -  Detailed Statistics
Created: Fri, 06 Sep 2019, 08:28:17 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.