Using models to understand community interventions for improving public health and food systems

Hennessy, Erin; Calancie, Larissa; Economos, Christina D.

doi:10.1016/b978-0-12-822112-9.00012-6

Cited by 2 publications

(2 citation statements)

References 62 publications

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“…Other model examples include urban energy systems, logistics models, sponge models, and water demand models [33]. Agent-based modelling (ABM) is a computational tool which models the actions or interaction of "agents" and allows for the exploration of dynamic mechanisms which link autonomous behaviour to overall outcomes among populations [34]. ABM is categorised under the social simulation trend of demography, whereby application of novel modelling techniques to specific populations or simulations is executed.…”

Section: Various Modelling Attempts Have Been Made By Global Urban Sc...mentioning

confidence: 99%

Report on the E-TEMS 2023 Doctoral Workshop

Kaiser,

Ntanda,

Beck

et al. 2023

2023 IEEE European Technology and Engineering Management Summit (E-Tems)

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The doctoral workshop is a crucial element of the IEEE E-TEMS conference series, aiming to engage researchers in the early stages of their research work. This report discusses the implementation of the workshop in 2023, which was the first on-site workshop in the conference series. The submitted and presented research projects are presented, addressing the following topics: "Restorative Social Justice through Digital Transformation in South African Metropolitan Cities", "Understanding the Future Role of Energy Communities in Renewable System Integration", "Developing a framework for analysis of Virtual District Models for planning and operation of district energy systems", "Digital twins to improve Social Sustainability in Smart Cities", "An integrated digital twin for city resources consumption optimisation", and "Automated Technology adoption to accelerate technology adoption". These thematic areas provide a foundation for collaborative discussions and knowledge exchange among the workshop participants, fostering interdisciplinary exploration and potential synergies. At the end, all participants give a short reflection on their experience of the workshop.

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Section: Various Modelling Attempts Have Been Made By Global Urban Sc...mentioning

confidence: 99%

Report on the E-TEMS 2023 Doctoral Workshop

Kaiser,

Ntanda,

Beck

et al. 2023

2023 IEEE European Technology and Engineering Management Summit (E-Tems)

View full text Add to dashboard Cite

show abstract

“…We previously developed the Stakeholder-driven Community Diffusion (SDCD) theory (Fig. 1 ), which posits that a multi-sector group can diffuse knowledge and engagement across both existing and new relationship networks, thus facilitating changes in policies, systems, and environments that influence obesity [ 21 – 23 ]. SDCD was informed by Community-based Participatory Research [ 24 ], Community Coalition Action Theory [ 25 ], Diffusion of Innovations [ 26 ], and systems science [ 27 ].…”

Section: Introductionmentioning

confidence: 99%

Community coalition efforts to prevent childhood obesity: two-year results of the Shape Up Under 5 study

et al. 2023

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Background Cross-sector collaborations and coalitions are promising approaches for childhood obesity prevention, yet there is little empirical evidence about how they affect change. We hypothesized that changes in knowledge of, and engagement with, childhood obesity prevention among coalition members can diffuse through social networks to influence policies, systems, and environments. Methods We studied a community coalition (N = 16, Shape Up Under 5 “SUU5 Committee”) focused on early childhood obesity prevention in Somerville, MA from 2015–17. Knowledge, engagement, and social network data were collected from Committee members and their network contacts (n = 193) at five timepoints over two years. Policy, systems, and environment data were collected from the SUU5 Committee. Data were collected via the validated COMPACT Stakeholder-driven Community Diffusion survey and analyzed using regression models and social network analysis. Results Over 2 years, knowledge of (p = 0.0002), and engagement with (p = 0.03), childhood obesity prevention increased significantly among the SUU5 Committee. Knowledge increased among the Committee’s social network (p = 0.001). Significant changes in policies, systems, and environments that support childhood obesity prevention were seen from baseline to 24 months (p = 0.003). Conclusion SUU5 had positive effects on “upstream” drivers of early childhood obesity by increasing knowledge and engagement. These changes partially diffused through networks and may have changed “midstream” community policies, systems, and environments.

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Using models to understand community interventions for improving public health and food systems

Cited by 2 publications

References 62 publications

Report on the E-TEMS 2023 Doctoral Workshop

Report on the E-TEMS 2023 Doctoral Workshop

Community coalition efforts to prevent childhood obesity: two-year results of the Shape Up Under 5 study

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