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Different conceptual constructs for modelling sedentary behaviour and physical activity: the impact on the correlates of behaviour

Overview of attention for article published in BMC Research Notes, December 2014
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  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

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Title
Different conceptual constructs for modelling sedentary behaviour and physical activity: the impact on the correlates of behaviour
Published in
BMC Research Notes, December 2014
DOI 10.1186/1756-0500-7-921
Pubmed ID
Authors

Nana Kwame Anokye, Emmanuel Stamatakis

Abstract

Research on the correlates of physical activity (PA) and sedentary behaviour (SB) to date has used independent prediction equations for each behaviour, without considering that they are both part of the same continuum of movement. This assumption of independence might lead to inaccurate estimates because common underlying latent variables may simultaneously influence the propensity to engage in PA and SB. This study tests empirically the interdependent nature of PA and SB by comparing independent equations (current approach in the literature), and joint estimators (a novel but unexplored approach). Using Health Survey for England 2008 data, accelerometry-accessed PA and SB were separately modelled (using ordinary least squared regressions - OLS) and then jointly (using seemingly unrelated regressions -SUR). We tested for diagonality, specification, and goodness of fit.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 8%
Japan 1 4%
Unknown 23 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 31%
Researcher 6 23%
Lecturer 1 4%
Student > Bachelor 1 4%
Other 1 4%
Other 4 15%
Unknown 5 19%
Readers by discipline Count As %
Medicine and Dentistry 9 35%
Social Sciences 3 12%
Psychology 2 8%
Computer Science 2 8%
Economics, Econometrics and Finance 1 4%
Other 2 8%
Unknown 7 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 22 January 2015.
All research outputs
#16,048,318
of 25,374,917 outputs
Outputs from BMC Research Notes
#2,139
of 4,514 outputs
Outputs of similar age
#200,299
of 360,783 outputs
Outputs of similar age from BMC Research Notes
#44
of 107 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,514 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one is in the 49th percentile – i.e., 49% 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 360,783 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 107 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.