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Development of a dynamic framework to explain population patterns of leisure-time physical activity through agent-based modeling

Overview of attention for article published in International Journal of Behavioral Nutrition and Physical Activity, August 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (64th percentile)

Mentioned by

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7 X users

Citations

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18 Dimensions

Readers on

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60 Mendeley
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1 CiteULike
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Title
Development of a dynamic framework to explain population patterns of leisure-time physical activity through agent-based modeling
Published in
International Journal of Behavioral Nutrition and Physical Activity, August 2017
DOI 10.1186/s12966-017-0553-4
Pubmed ID
Authors

Leandro M. T. Garcia, Ana V. Diez Roux, André C. R. Martins, Yong Yang, Alex A. Florindo

Abstract

Despite the increasing body of evidences on the factors influencing leisure-time physical activity, our understanding of the mechanisms and interactions that lead to the formation and evolution of population patterns is still limited. Moreover, most frameworks in this field fail to capture dynamic processes. Our aim was to create a dynamic conceptual model depicting the interaction between key psychological attributes of individuals and main aspects of the built and social environments in which they live. This conceptual model will inform and support the development of an agent-based model aimed to explore how population patterns of LTPA in adults may emerge from the dynamic interplay between psychological traits and built and social environments. We integrated existing theories and models as well as available empirical data (both from literature reviews), and expert opinions (based on a systematic expert assessment of an intermediary version of the model). The model explicitly presents intention as the proximal determinant of leisure-time physical activity, a relationship dynamically moderated by the built environment (access, quality, and available activities) - with the strength of the moderation varying as a function of the person's intention- and influenced both by the social environment (proximal network's and community's behavior) and the person's behavior. Our conceptual model is well supported by evidence and experts' opinions and will inform the design of our agent-based model, as well as data collection and analysis of future investigations on population patterns of leisure-time physical activity among adults.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 60 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 14 23%
Researcher 9 15%
Student > Ph. D. Student 6 10%
Student > Doctoral Student 5 8%
Other 3 5%
Other 7 12%
Unknown 16 27%
Readers by discipline Count As %
Sports and Recreations 9 15%
Medicine and Dentistry 9 15%
Social Sciences 6 10%
Nursing and Health Professions 3 5%
Agricultural and Biological Sciences 2 3%
Other 9 15%
Unknown 22 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 February 2024.
All research outputs
#7,336,338
of 23,884,161 outputs
Outputs from International Journal of Behavioral Nutrition and Physical Activity
#1,587
of 2,007 outputs
Outputs of similar age
#111,937
of 320,002 outputs
Outputs of similar age from International Journal of Behavioral Nutrition and Physical Activity
#42
of 46 outputs
Altmetric has tracked 23,884,161 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 2,007 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 29.0. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 320,002 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.
We're also able to compare this research output to 46 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.