Initiatives and partnerships in an Australian metropolitan obesity prevention system: a social network analysis

Blackford, Krysten; Leavy, Justine; Vidler, Abbie-Clare; Chamberlain, Dan; Pollard, Christina; Riley, Therese; Milligan, Megan; Jancey, Jonine

doi:10.1186/s12889-021-11599-7

Cited by 5 publications

(12 citation statements)

References 44 publications

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“…Network analysis was used in four of the 25 articles [ 45 – 48 ] (Table 1 ). All reported on social network analysis methods except for one [ 47 ].…”

Section: Resultsmentioning

confidence: 99%

A scoping review of complex systems methods used in population physical activity research: do they align with attributes of a whole system approach?

Littlejohns

Near

McKee

et al. 2023

Health Res Policy Sys

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Background Complex systems approaches are increasingly used in health promotion and noncommunicable disease prevention research, policy and practice. Questions emerge as to the best ways to take a complex systems approach, specifically with respect to population physical activity (PA). Using an Attributes Model is one way to understand complex systems. We aimed to examine the types of complex systems methods used in current PA research and identify what methods align with a whole system approach as reflected by an Attributes Model. Methods A scoping review was conducted and two databases were searched. Twenty-five articles were selected and data analysis was based upon the following: the complex systems research methods used, research aims, if participatory methods were used and evidence of discussion regarding attributes of systems. Results There were three groups of methods used: system mapping, simulation modelling and network analysis. System mapping methods appeared to align best with a whole system approach to PA promotion because they largely aimed to understand complex systems, examined interactions and feedback among variables, and used participatory methods. Most of these articles focused on PA (as opposed to integrated studies). Simulation modelling methods were largely focused on examining complex problems and identifying interventions. These methods did not generally focus on PA or use participatory methods. While network analysis articles focused on examining complex systems and identifying interventions, they did not focus on PA nor use participatory methods. All attributes were discussed in some way in the articles. Attributes were explicitly reported on in terms of findings or were part of discussion and conclusion sections. System mapping methods appear to be well aligned with a whole system approach because these methods addressed all attributes in some way. We did not find this pattern with other methods. Conclusions Future research using complex systems methods may benefit from applying the Attributes Model in conjunction with system mapping methods. Simulation modelling and network analysis methods are seen as complementary and could be used when system mapping methods identify priorities for further investigation (e.g. what interventions to implement or how densely connected relationships are in systems).

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“…Network analysis was used in four of the 25 articles [ 45 – 48 ] (Table 1 ). All reported on social network analysis methods except for one [ 47 ].…”

Section: Resultsmentioning

confidence: 99%

A scoping review of complex systems methods used in population physical activity research: do they align with attributes of a whole system approach?

Littlejohns

Near

McKee

et al. 2023

Health Res Policy Sys

View full text Add to dashboard Cite

show abstract

“…Identifying informal multisector networks' structures, strengths, and gaps through SNA can inform future informal or formal collaboration for cancer prevention and control (35,(46)(47)(48)(49). Disseminating network findings via summary infographics and interactive platforms can enhance usefulness of SNA to practitioners in rural health and social service agencies.…”

Section: Discussionmentioning

confidence: 99%

“…The exchanging information relationship had a higher average degree than the more time-and resource-intensive activities. In an Australian city, researchers also found a high degree of information exchange and fewer connections for sharing resources and implementing joint programs (49). Held and colleagues (2021) found 48% of the organizations in an Australian urban informal network reported contributing resources to local chronic disease prevention efforts (35).…”

Section: Discussionmentioning

confidence: 99%

“…SNA is a useful tool for practitioners and researchers seeking to control cancer and other chronic conditions (35,(46)(47)(48)(49)57). Crosssectional network analyses of multisector collaborations in health promotion/cancer prevention and control in rural areas can help partnering agencies identify network strengths and gaps, and point to ways to strengthen multisector collaboration.…”

Section: Limitationsmentioning

confidence: 99%

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Mapping the Lay of the Land: Using Interactive Network Analytic Tools for Collaboration in Rural Cancer Prevention and Control

Carothers

Allen

Walsh‐Bailey

et al. 2022

Cancer Epidemiology, Biomarkers &Amp; Prevention

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Background: Cancer mortality rates in the U.S. are higher in rural than urban areas, especially for colorectal cancer. Modifiable cancer risks (e.g. tobacco use, obesity) are more prevalent among U.S. rural than urban residents. Social network analyses are common, yet rural informal collaborative networks for cancer prevention and control and practitioner uses of network findings are less well understood. Methods: In five service areas in rural Missouri and Illinois, we conducted a network survey of informal multisector networks among agencies that address cancer risk (N = 152 individuals). The survey asked about contact, collaborative activities, and referrals. We calculated descriptive network statistics and disseminated network visualizations with rural agencies through infographics and interactive Network Navigator platforms. We also collected feedback on uses of network findings from agency staff (N = 14). Results: Service areas had more connections (average degree) for exchanging information than for more time-intensive collaborative activities of co-developing and sustaining ongoing services and programs, and co-developing and sharing resources. On average, collaborative activities were not dependent on just a few agencies to bridge gaps to hold networks together. Users found the network images and information useful for identifying gaps, planning which relationships to establish or enhance to strengthen certain collaborative activities and cross-referrals, and showing network strengths to current and potential funders. Conclusions: Rural informal cancer prevention and control networks in this study are highly connected and largely decentralized. Impact: Disseminating network findings help ensure usefulness to rural health and social service practitioners who address cancer risks.

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“…To date, several studies have analyzed networks in the context of community obesity prevention interventions [ 2 , 19 , 20 , 21 , 22 , 23 ]. However, the networks often consisted only of stakeholders from higher network levels, such as steering committees, local governments, or institutions delivering obesity prevention initiatives.…”

Section: Introductionmentioning

confidence: 99%

Network Analysis for a Community-Based School- and Family-Based Obesity Prevention Program

et al. 2022

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Rising childhood obesity with its detrimental health consequences poses a challenge to the health care system. Community-based, multi-setting interventions with the participatory involvement of relevant stakeholders are emerging as promising. To gain insights into the structural and processual characteristics of stakeholder networks, conducting a network analysis (NA) is advisable. Within the program “Family+—Healthy Living Together in Families and Schools”, a network analysis was conducted in two rural model regions and one urban model region. Relevant stakeholders were identified in 2020–2021 through expert interviews and interviewed by telephone to elicit key variables such as frequency of contact and intensity of collaboration. Throughout the NA, characteristics such as density, centrality, and connectedness were analyzed and are presented graphically. Due to the differences in the number of inhabitants and the rural or urban structure of the model regions, the three networks (network#1, network#2, and network#3) included 20, 14, and 12 stakeholders, respectively. All networks had similar densities (network#1, 48%; network#2, 52%; network#3, 42%), whereas the degree centrality of network#1 (0.57) and network#3 (0.58) was one-third higher compared with network#2 (0.39). All three networks differed in the distribution of stakeholders in terms of field of expertise and structural orientation. On average, stakeholders exchanged information quarterly and were connected on an informal level. Based on the results of the NA, it appears to be useful to initialize a community health facilitator to involve relevant stakeholders from the education, sports, and health systems in projects and to strive for the goal of sustainable health promotion, regardless of the rural or urban structure of the region. Participatory involvement of relevant stakeholders can have a positive influence on the effective dissemination of information and networking with other stakeholders.

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Initiatives and partnerships in an Australian metropolitan obesity prevention system: a social network analysis

Cited by 5 publications

References 44 publications

A scoping review of complex systems methods used in population physical activity research: do they align with attributes of a whole system approach?

A scoping review of complex systems methods used in population physical activity research: do they align with attributes of a whole system approach?

Mapping the Lay of the Land: Using Interactive Network Analytic Tools for Collaboration in Rural Cancer Prevention and Control

Network Analysis for a Community-Based School- and Family-Based Obesity Prevention Program

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