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Use-of-time and health-related quality of life in 10- to 13-year-old children: not all screen time or physical activity minutes are the same

Overview of attention for article published in Quality of Life Research, July 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

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1 blog
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9 X users
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2 Facebook pages

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193 Mendeley
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Title
Use-of-time and health-related quality of life in 10- to 13-year-old children: not all screen time or physical activity minutes are the same
Published in
Quality of Life Research, July 2017
DOI 10.1007/s11136-017-1639-9
Pubmed ID
Authors

Margarita D. Tsiros, Michelle G. Samaras, Alison M. Coates, Timothy Olds

Abstract

To investigate associations between aspects of time use and health-related quality of life (HRQoL) in youth. 239 obese and healthy-weight 10- to 13-year-old Australian children completed the Pediatric Quality of Life Inventory (PedsQL™) quantifying their health-related quality of life. Time use was evaluated over four days using the Multimedia Activity Recall for Children and Adolescents (MARCA), a validated 24 h recall tool. The average number of minutes/day spent in physical activity (divided into sport, active transport and play), screen time (divided into television, videogames and computer use), and sleep were calculated. Percent fat was measured using dual-energy X-ray absorptiometry, Tanner stage by self-report, and household income by parental report. Sex-stratified analysis was conducted using Partial Least Squares regression, with percent fat, Tanner stage, household income, and use-of-time as the independent variables, and PedsQL™ total, physical and psychosocial subscale scores as the dependent variables. For boys, the most important predictors of HRQoL were percent fat (negative), videogames (negative), sport (positive), and Tanner stage (negative). For girls, the significant predictors were percent fat (negative), television (negative), sport (positive), active transport (negative), and household income (positive). While body fat was the most significant correlate of HRQoL, sport was independently associated with better HRQoL, and television and videogames with poorer HRQoL. Thus, parents and clinicians should be mindful that not all physical activity and screen-based behaviours have equivocal relationships with children's HRQoL. Prospective research is needed to confirm causation and to inform current activity guidelines.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 193 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 193 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 29 15%
Student > Master 26 13%
Student > Ph. D. Student 22 11%
Researcher 15 8%
Student > Doctoral Student 10 5%
Other 32 17%
Unknown 59 31%
Readers by discipline Count As %
Sports and Recreations 23 12%
Nursing and Health Professions 20 10%
Medicine and Dentistry 20 10%
Social Sciences 20 10%
Psychology 17 9%
Other 23 12%
Unknown 70 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 17 August 2018.
All research outputs
#2,136,381
of 22,985,065 outputs
Outputs from Quality of Life Research
#143
of 2,911 outputs
Outputs of similar age
#42,984
of 313,820 outputs
Outputs of similar age from Quality of Life Research
#4
of 84 outputs
Altmetric has tracked 22,985,065 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,911 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done particularly well, scoring higher than 95% of its peers.
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 313,820 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 84 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.