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School-based intervention on healthy behaviour among Ecuadorian adolescents: effect of a cluster-randomized controlled trial on screen-time

Overview of attention for article published in BMC Public Health, September 2015
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1 tweeter

Citations

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10 Dimensions

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143 Mendeley
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Title
School-based intervention on healthy behaviour among Ecuadorian adolescents: effect of a cluster-randomized controlled trial on screen-time
Published in
BMC Public Health, September 2015
DOI 10.1186/s12889-015-2274-4
Pubmed ID
Authors

Susana Andrade, Maïté Verloigne, Greet Cardon, Patrick Kolsteren, Angelica Ochoa-Avilés, Roosmarijn Verstraeten, Silvana Donoso, Carl Lachat

Abstract

Effective interventions on screen-time behaviours (television, video games and computer time) are needed to prevent non-communicable diseases in low- and middle-income countries. The present manuscript investigates the effect of a school-based health promotion intervention on screen-time behaviour among 12- to 15-year-old adolescents. We report the effect of the trial on screen-time after two stages of implementation. We performed a cluster-randomised pair matched trial in urban schools in Cuenca-Ecuador. Participants were adolescents of grade eight and nine (mean age 12.8 ± 0.8 years, n = 1370, control group n = 684) from 20 schools (control group n = 10). The intervention included an individual and environmental component tailored to the local context and resources. The first intervention stage focused on diet, physical activity and screen-time behaviour, while the second stage focused only on diet and physical activity. Screen-time behaviours, primary outcome, were assessed at baseline, after the first (18 months) and second stage (28 months). Mixed linear models were used to analyse the data. After the first stage (data from n = 1224 adolescents; control group n = 608), the intervention group had a lower increase in TV-time on a week day (β = -15.7 min; P = 0.003) and weekend day (β = -18.9 min; P = 0.005), in total screen-time on a weekday (β = -25.9 min; P = 0.03) and in the proportion of adolescents that did not meet the screen-time recommendation (β = -4 percentage point; P = 0.01), compared to the control group. After the second stage (data from n = 1078 adolescents; control group n = 531), the TV-time on a weekday (β = 13.1 min; P = 0.02), and total screen-time on a weekday (β = 21.4 min; P = 0.03) increased more in adolescents from the intervention group. No adverse effects were reported. A multicomponent school-based intervention was only able to mitigate the increase in adolescents' television time and total screen-time after the first stage of the intervention or in other words, when the intervention included specific components or activities that focused on reducing screen-time. After the second stage of the intervention, which only included components and activities related to improve healthy diet and physical activity and not to decrease the screen-time, the adolescents increased their screen-time again. Our findings might imply that reducing screen-time is only possible when the intervention focuses specifically on reducing screen-time. Clinicaltrials.gov identifier NCT01004367 .

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 143 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Norway 1 <1%
Unknown 142 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 31 22%
Student > Bachelor 18 13%
Student > Ph. D. Student 17 12%
Researcher 16 11%
Student > Doctoral Student 8 6%
Other 32 22%
Unknown 21 15%
Readers by discipline Count As %
Medicine and Dentistry 23 16%
Social Sciences 20 14%
Nursing and Health Professions 20 14%
Sports and Recreations 15 10%
Psychology 8 6%
Other 32 22%
Unknown 25 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 25 September 2015.
All research outputs
#3,016,140
of 6,401,542 outputs
Outputs from BMC Public Health
#4,334
of 6,064 outputs
Outputs of similar age
#108,275
of 201,079 outputs
Outputs of similar age from BMC Public Health
#185
of 262 outputs
Altmetric has tracked 6,401,542 research outputs across all sources so far. This one is in the 29th percentile – i.e., 29% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,064 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one is in the 18th percentile – i.e., 18% 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 201,079 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 262 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.