Logic model of the Recreovía: a community program to promote physical activity in Bogota

Ríos, Ana Paola; Páez, Diana; Pinzón, Edwin; Fermino, Rogério César; Sarmiento, Olga L.

doi:10.12820/rbafs.v.22n2p206-211

Cited by 6 publications

(12 citation statements)

References 5 publications

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“…(3) Global supply chain project network: an e-mail network between project team roles of a global supply chain project 36 . (4) Recreovia Facebook friendship network: an online friendship network of stakeholders in a physical activity program in Colombia 37 . And (5) School children friendship network: a friendship network of a primary school in Colombia 38 .…”

Section: Resultsmentioning

confidence: 99%

“…(4) Recreovía facebook friendship network: an online friendship network of stakeholders in a physical activity program in Colombia. This program aims to promote physical activity, health habits, and social equity through musicalized and directed group classes in Bogota, Colombia 37 . In this network, nodes represent Facebook friends of the Recreovia account, and edges represent a mutual friendship between the nodes.…”

Section: Methodsmentioning

confidence: 99%

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Benchmarking seeding strategies for spreading processes in social networks: an interplay between influencers, topologies and sizes

Montes

Jaramillo

Meisel

et al. 2020

Sci Rep

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The explosion of network science has permitted an understanding of how the structure of social networks affects the dynamics of social contagion. In community-based interventions with spill-over effects, identifying influential spreaders may be harnessed to increase the spreading efficiency of social contagion, in terms of time needed to spread all the largest connected component of the network. Several strategies have been proved to be efficient using only data and simulation-based models in specific network topologies without a consensus of an overall result. Hence, the purpose of this paper is to benchmark the spreading efficiency of seeding strategies related to network structural properties and sizes. We simulate spreading processes on empirical and simulated social networks within a wide range of densities, clustering coefficients, and sizes. We also propose three new decentralized seeding strategies that are structurally different from well-known strategies: community hubs, ambassadors, and random hubs. We observe that the efficiency ranking of strategies varies with the network structure. In general, for sparse networks with community structure, decentralized influencers are suitable for increasing the spreading efficiency. By contrast, when the networks are denser, centralized influencers outperform. These results provide a framework for selecting efficient strategies according to different contexts in which social networks emerge.Information, behaviors, diseases, emotions, and even the adoption of technological innovations spread through social networks 1-5 . Recently, the explosion of network science across disciplines has produced many important advances in understanding how the structure of social networks affects the dynamics of social contagion. Specifically, the study of social networks has provided an opportunity to potentiate interventions with spill-over effects aimed to increase population well-being. For example, several studies have examined the spreading processes efficiency related to the topological properties of networks 4,6-8 . Other studies have analyzed the role of homophily in spreading processes 9-11 , while others have focused on identifying influential spreaders in networks and how they may be harnessed to increase the efficiency of public health and poverty reduction interventions [12][13][14][15] .A key point for designing interventions with spill-over effects is to allocate resources for the intervention targeting in a wisely way. Thus, it is crucial to have an appropriate methodological framework for selecting seednodes with the best spreading ability. Several complex networks studies have proposed selecting seednodes by ranking network nodes based on centrality measures 12,15-28 . Particularly, nodes with high degree, closeness, and betweenness coefficients have been identified as influential or high-risk individuals during a spreading process 16,23,29 . Furthermore, there are random-walk based seeding strategies, such as Page-Rank, that have been shown more efficient than ce...

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Benchmarking seeding strategies for spreading processes in social networks: an interplay between influencers, topologies and sizes

Montes

Jaramillo

Meisel

et al. 2020

Sci Rep

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“…The Recreovía program of Bogotá started in 1995 as a program providing free recreational activities, especially for socioeconomically vulnerable residents ( Rios et al, 2017 ). The Recreovía program offers free physical activity classes led by trained physical activity instructors on weekdays, Sundays, and holidays.…”

Section: Methodsmentioning

confidence: 99%

Social cohesion emerging from a community-based physical activity program: A temporal network analysis

Jaramillo

Montes

Sarmiento³

et al. 2020

Net Sci

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Community-based physical activity programs, such as the Recreovía, are effective in promoting healthy behaviors in Latin America. To understand Recreovías’ challenges and scalability, we characterized its social network longitudinally while studying its participants’ social cohesion and interactions. First, we constructed the Main network of the program’s Facebook profile in 2013 to determine the main stakeholders and communities of participants. Second, we studied the Temporal network growth of the Facebook profiles of three Recreovía locations from 2008 to 2016. We implemented a Time Windows in Networks algorithm to determine observation periods and a scaling model of cities’ growth to measure social cohesion over time. Our results show physical activity instructors as the main stakeholders (20.84% nodes of the network). As emerging cohesion, we found: (1) incremental growth of Facebook users (43–272 nodes), friendships (55–2565 edges), clustering coefficient (0.19–0.21), and density (0.04–0.07); (2) no preferential attachment behavior; and (3) a social cohesion super-linear growth with 1.73 new friendships per joined user. Our results underscore the physical activity instructors’ influence and the emergent cohesion in innovation periods as a co-benefit of the program. This analysis associates the social and healthy behavior dimensions of a program occurring in natural environments under a systemic approach.

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“…O modelo lógico foi desenvolvido de acordo com as diretrizes propostas pelo Centers of Disease Control 11 , que prevê a avaliação de programas de promoção da atividade física com a descrição sistemática dos recursos, atividades, produtos e metas a curto, médio e longo prazo. Ainda, a versão final do modelo lógico foi estruturada com base em documentos similares de outros programas de atividade física a nível comunitário desenvolvido em cidades da América Latina [6][7][8][9] .…”

Section: Métodosunclassified

“…Na América Latina, as experiências de alguns programas foram documentadas na literatura 3,[6][7][8][9] . No Brasil, a Política Nacional de Promoção da Saúde guia as ações e a inserção de programas para a promoção da atividade física na comunidade 10 , sendo esta conside-rada uma estratégia promissora, a qual pode contribuir para a prevenção de doenças crônicas, o desenvolvimento do capital social, aumento da qualidade de vida, entre outros cobenefícios 3,4,10 .…”

Section: Introductionunclassified

Modelo lógico do “Programa Cidade Ativa, Cidade Saudável” de São José dos Pinhais, Paraná

Silva

Santos

Rodriguez-Añez

et al. 2021

Rev Bras Ativ Fís Saúde

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O objetivo deste estudo foi desenvolver o modelo lógico do “Programa Cidade Ativa, Cidade Saudável” da cidade de São José dos Pinhais, Paraná. Trinta e seis gestores forneceram parte das informações e o modelo lógico foi elaborado conforme as diretrizes do Centers for Disease Control and Prevention. Foram identificadas 163 pessoas responsáveis por elaborar, gerenciar, coordenar, apoiar e ministrar diversas ações de atividades físicas, esportivas e lúdicas para a população, sob responsabilidade das divisões de “lazer e eventos populares”, “esportes populares” e “esportes de rendimento”. O modelo lógico possibilitou a identificação ordenada dos recursos, atividades, produtos e metas do programa. Estes dados poderão auxiliar a reestruturação do Programa frente a possíveis demandas de gestão. Futuros estudos podem utilizar estas informações para avaliar a efetividade e a eficácia do Programa nos indicadores de saúde da população.

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Logic model of the Recreovía: a community program to promote physical activity in Bogota

Cited by 6 publications

References 5 publications

Benchmarking seeding strategies for spreading processes in social networks: an interplay between influencers, topologies and sizes

Benchmarking seeding strategies for spreading processes in social networks: an interplay between influencers, topologies and sizes

Social cohesion emerging from a community-based physical activity program: A temporal network analysis

Modelo lógico do “Programa Cidade Ativa, Cidade Saudável” de São José dos Pinhais, Paraná

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