ArticlePreventive medicine reports2018
Out with the old, in with the new: Assessing change in screen time when measurement changes over time.
Article in Preventive medicine reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- A Canadian longitudinal study of the associations between weight control status and lifestyle behaviors during adolescence.Preventive medicine reports · 2023Article
- Adolescents' psychosocial well-being one year after the outbreak of the COVID-19 pandemic in Norway.Nature human behaviour · 2022Article
- One size does not fit all: identifying clusters of physical activity, screen time, and sleep behaviour co-development from childhood to adolescence.The international journal of behavioral nutrition and physical activity · 2020Article
- Methodology to Derive Objective Screen-State from Smartphones: A SMART Platform Study.International journal of environmental research and public health · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
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