Exploring the emergence and evolution of population patterns of leisure-time physical activity through agent-based modelling

Garcia, Leandro Martin Totaro; Roux, Ana V. Diez; Martins, André C. R.; Yang, Yong; Florindo, Alex Antônio

doi:10.1186/s12966-018-0750-9

Cited by 13 publications

(15 citation statements)

References 49 publications

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“…This intention for physical activity was updated each week based on the person's past behavior, the behavior of their personal network, and the broader community. 66,67 If the person decided to engage in recreational physical activity during a given week, a weekly frequency was assigned (see Supplementary Section 3.3.4.2 [available online] for further details).…”

Section: Modeling Changes In Cities and People Over Timementioning

confidence: 99%

“…Weights assigned to capture the importance of each factor considered in the persons' decision-making process for recreational physical activity were derived from Garcia et al 68 Specifically, a person's past behavior and the quality and accessibility of spaces for physical activity were assumed to have the greatest influence on decision making, followed by the behavior of the personal network and then that of the community at large. For travel behavior, the same weight was assigned to each factor.…”

Section: Modeling Changes In Cities and People Over Timementioning

confidence: 99%

See 1 more Smart Citation

Physical Activity Promotion and the United Nations Sustainable Development Goals: Building Synergies to Maximize Impact

Salvo¹,

Garcia²,

Reis³

et al. 2021

Journal of Physical Activity and Health

127

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Background: Many of the known solutions to the physical inactivity pandemic operate across sectors relevant to the United Nations Sustainable Development Goals (SDGs). Methods: The authors examined the contribution of physical activity promotion strategies toward achieving the SDGs through a conceptual linkage exercise, a scoping review, and an agent-based model. Results: Possible benefits of physical activity promotion were identified for 15 of the 17 SDGs, with more robust evidence supporting benefits for SDGs 3 (good health and well-being), 9 (industry, innovation, and infrastructure), 11 (sustainable cities and communities), 13 (climate action), and 16 (peace, justice, and strong institutions). Current evidence supports prioritizing at-scale physical activity-promoting transport and urban design strategies and community-based programs. Expected physical activity gains are greater for low-and middle-income countries. In high-income countries with high car dependency, physical activity promotion strategies may help reduce air pollution and traffic-related deaths, but shifts toward more active forms of travel and recreation, and climate change mitigation, may require complementary policies that disincentivize driving. Conclusions: The authors call for a synergistic approach to physical activity promotion and SDG achievement, involving multiple sectors beyond health around their goals and values, using physical activity promotion as a lever for a healthier planet.

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Section: Modeling Changes In Cities and People Over Timementioning

confidence: 99%

Section: Modeling Changes In Cities and People Over Timementioning

confidence: 99%

Physical Activity Promotion and the United Nations Sustainable Development Goals: Building Synergies to Maximize Impact

Salvo¹,

Garcia²,

Reis³

et al. 2021

Journal of Physical Activity and Health

127

View full text Add to dashboard Cite

show abstract

“…Simulation modelling was used in 10 of the 25 articles. Three subtypes were applied: five used agent-based modelling (ABM) [ 34 – 38 ], four used system dynamics modelling (SDM) [ 39 – 42 ] and one described a cross impact analysis [ 43 ] (Table 1 ). ABM can be defined as developing ‘computational models that simulate complex social systems by representing agents that interact with one another and with the environment in which they live according to predefined rules’ [ 34 ] (p. 2).…”

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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“…Examples include the evolution of cooperation based on familiarity (Son & Rojas, 2011), similarities (Hadzibeganovic et al, 2018) or trust (Bravo et al, 2012;Growiec et al, 2018;Laifa et al, 2018). Additionally, a social environment can provide existential security (Gore et al, 2018) or can support people to promote an activity (Garcia et al, 2018).…”

Section: Social Integrationmentioning

confidence: 99%

Combining social network analysis and agent-based modelling to explore dynamics of human interaction: A review

Will

Groeneveld

Frank

et al. 2020

SESMO

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Agent-based modelling (ABM) and social network analysis (SNA) are both valuable tools for exploring the impact of human interactions on a broad range of social and ecological patterns. Integrating these approaches offers unique opportunities to gain insights into human behaviour that neither the evaluation of social networks nor agent-based models alone can provide. There are many intriguing examples that demonstrate this potential, for instance in epidemiology, marketing or social dynamics. Based on an extensive literature review, we provide an overview on coupling ABM with SNA and evaluating the integrated approach. Building on this, we identify current shortcomings in the combination of the two methods. The greatest room for improvement is found with regard to (i) the consideration of the concept of social integration through networks, (ii) an increased use of the co-evolutionary character of social networks and embedded agents, and (iii) a systematic and quantitative model analysis focusing on the causal relationship between the agents and the network. Furthermore, we highlight the importance of a comprehensive and clearly structured model conceptualization and documentation. We synthesize our findings in guidelines that contain the main aspects to consider when integrating social networks into agent-based models.

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Exploring the emergence and evolution of population patterns of leisure-time physical activity through agent-based modelling

Cited by 13 publications

References 49 publications

Physical Activity Promotion and the United Nations Sustainable Development Goals: Building Synergies to Maximize Impact

Physical Activity Promotion and the United Nations Sustainable Development Goals: Building Synergies to Maximize Impact

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

Combining social network analysis and agent-based modelling to explore dynamics of human interaction: A review

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