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Out with the old, in with the new: Assessing change in screen time when measurement changes over time
We examined if screen time can be assessed over time when the measurement protocol has changed to reflect advances in technology. Beginning in 2011, 929 youth (9–12 years at time one) living in in New Brunswick (Canada) self-reported the amount of time spent watching television (cycles 1–13), using...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5766751/ https://www.ncbi.nlm.nih.gov/pubmed/29340268 http://dx.doi.org/10.1016/j.pmedr.2017.12.008 |
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author | Gunnell, Katie E. Brunet, Jennifer Bélanger, Mathieu |
author_facet | Gunnell, Katie E. Brunet, Jennifer Bélanger, Mathieu |
author_sort | Gunnell, Katie E. |
collection | PubMed |
description | We examined if screen time can be assessed over time when the measurement protocol has changed to reflect advances in technology. Beginning in 2011, 929 youth (9–12 years at time one) living in in New Brunswick (Canada) self-reported the amount of time spent watching television (cycles 1–13), using computers (cycles 1–13), and playing video games (cycles 3–13). Using longitudinal invariance to test a shifting indicators model of screen time, we found that the relationships between the latent variable reflecting overall screen time and the indicators used to assess screen time were invariant across cycles (weak invariance). We also found that 31 out of 37 indicator intercepts were invariant, meaning that most indicators were answered similarly (i.e., on the same metric) across cycles (partial strong invariance), and that 28 out of 37 indicator residuals were invariant indicating that similar sources of error were present over time (partial strict invariance). Overall, across all survey cycles, 76% of indicators were fully invariant. Whereas issues were noted when new examples of screen-based technology (e.g., iPads) were added, having established partial invariance, we suggest it is still possible to assess change in screen time despite having changing indicators over time. Although it is not possible to draw definitive conclusions concerning other self-report measures of screen time, our findings may assist other researchers considering modifying self-report measures in longitudinal studies to reflect technological advancements and increase the precision of their results. |
format | Online Article Text |
id | pubmed-5766751 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-57667512018-01-16 Out with the old, in with the new: Assessing change in screen time when measurement changes over time Gunnell, Katie E. Brunet, Jennifer Bélanger, Mathieu Prev Med Rep Regular Article We examined if screen time can be assessed over time when the measurement protocol has changed to reflect advances in technology. Beginning in 2011, 929 youth (9–12 years at time one) living in in New Brunswick (Canada) self-reported the amount of time spent watching television (cycles 1–13), using computers (cycles 1–13), and playing video games (cycles 3–13). Using longitudinal invariance to test a shifting indicators model of screen time, we found that the relationships between the latent variable reflecting overall screen time and the indicators used to assess screen time were invariant across cycles (weak invariance). We also found that 31 out of 37 indicator intercepts were invariant, meaning that most indicators were answered similarly (i.e., on the same metric) across cycles (partial strong invariance), and that 28 out of 37 indicator residuals were invariant indicating that similar sources of error were present over time (partial strict invariance). Overall, across all survey cycles, 76% of indicators were fully invariant. Whereas issues were noted when new examples of screen-based technology (e.g., iPads) were added, having established partial invariance, we suggest it is still possible to assess change in screen time despite having changing indicators over time. Although it is not possible to draw definitive conclusions concerning other self-report measures of screen time, our findings may assist other researchers considering modifying self-report measures in longitudinal studies to reflect technological advancements and increase the precision of their results. Elsevier 2017-12-24 /pmc/articles/PMC5766751/ /pubmed/29340268 http://dx.doi.org/10.1016/j.pmedr.2017.12.008 Text en © 2018 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Regular Article Gunnell, Katie E. Brunet, Jennifer Bélanger, Mathieu Out with the old, in with the new: Assessing change in screen time when measurement changes over time |
title | Out with the old, in with the new: Assessing change in screen time when measurement changes over time |
title_full | Out with the old, in with the new: Assessing change in screen time when measurement changes over time |
title_fullStr | Out with the old, in with the new: Assessing change in screen time when measurement changes over time |
title_full_unstemmed | Out with the old, in with the new: Assessing change in screen time when measurement changes over time |
title_short | Out with the old, in with the new: Assessing change in screen time when measurement changes over time |
title_sort | out with the old, in with the new: assessing change in screen time when measurement changes over time |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5766751/ https://www.ncbi.nlm.nih.gov/pubmed/29340268 http://dx.doi.org/10.1016/j.pmedr.2017.12.008 |
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