Evidence map›Paper›PMID 29340268›Full record

ArticlePreventive medicine reports2018

Out with the old, in with the new: Assessing change in screen time when measurement changes over time.

Katie E Gunnell, Jennifer Brunet, Mathieu Bélanger

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Methodology to Derive Objective Screen-State from Smartphones: A SMART Platform Study.International journal of environmental research and public health · 2019
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Katie E GunnellDepartment of Psychology, Carleton University, Canada.
Jennifer BrunetSchool of Human Kinetics, University of Ottawa, Canada.
Mathieu BélangerDepartment of Family Medicine, Université de Sherbrooke, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AdolescentsComputersInvarianceLongitudinalMeasurementScreen timeShifting indicatorsTechnology

Identifiers

PMID29340268
PMCPMC5766751

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.