Evidence map›Paper›PMID 30794204›Full record

ArticleJournal of medical Internet research2019

Understanding Youths' Ability to Interpret 3D-Printed Physical Activity Data and Identify Associated Intensity Levels: Mixed-Methods Study.

Sam Graeme Morgan Crossley, Melitta Anne McNarry, Michael Rosenberg, Zoe R Knowles, Parisa Eslambolchilar, Kelly Alexandra Mackintosh

Abstract read
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Article in Journal of medical Internet research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. 3D-Printing Physical Activity in Youth: An Autotopographical Approach to Behaviour Change.International journal of environmental research and public health · 2023
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  3. Article
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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

6 authors.

Sam Graeme Morgan Crossley *Applied Sports Science Technology and Medicine Research Centre (A-STEM), Swansea University, Swansea, United Kingdom.ORCID 0000-0002-2792-919X
Melitta Anne McNarry *Applied Sports Science Technology and Medicine Research Centre (A-STEM), Swansea University, Swansea, United Kingdom.ORCID 0000-0003-0813-7477
Michael RosenbergSchool of Human Sciences, The University of Western Australia, Crawley, Australia.ORCID 0000-0002-9950-5775
Zoe R Knowles *Physical Activity Exchange, School of Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, United Kingdom.ORCID 0000-0003-1129-2275
Parisa EslambolchilarSchool of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom.ORCID 0000-0003-4610-1643
Kelly Alexandra Mackintosh *Applied Sports Science Technology and Medicine Research Centre (A-STEM), Swansea University, Swansea, United Kingdom.ORCID 0000-0003-0355-6357

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA significant proportion of youth in the United Kingdom fail to meet the recommended 60 minutes of moderate-to-vigorous physical activity every day. One of the major barriers encountered in achieving these physical activity recommendations is the perceived difficulty for youths to interpret physical activity intensity levels and apply them to everyday activities. Personalized physical activity feedback is an important method to educate youths about behaviors and associated outcomes. Recent advances in 3D printing have enabled novel ways of representing physical activity levels through personalized tangible feedback to enhance youths' understanding of concepts and make data more available in the everyday physical environment rather than on screen.

objectiveThe purpose of this research was to elicit youths' (children and adolescents) interpretations of two age-specific 3D models displaying physical activity and to assess their ability to appropriately align activities to the respective intensity.

methodsTwelve primary school children (9 boys; mean age 7.8 years; SD 0.4 years) and 12 secondary school adolescents (6 boys; mean age 14.1 years; SD 0.3 years) participated in individual semistructured interviews. Interview questions, in combination with two interactive tasks, focused on youths' ability to correctly identify physical activity intensities and interpret an age-specific 3D model. Interviews were transcribed verbatim, content was analyzed, and outcomes were represented via tables and diagrammatic pen profiles.

resultsYouths, irrespective of age, demonstrated a poor ability to define moderate-intensity activities. Moreover, children and adolescents demonstrated difficulty in correctly identifying light- and vigorous-intensity activities, respectively. Although youths were able to correctly interpret different components of the age-specific 3D models, children struggled to differentiate physical activity intensities represented in the models.

conclusionsThese findings support the potential use of age-specific 3D models of physical activity to enhance youths' understanding of the recommended guidelines and associated intensities.

Indexed as

AdolescentChildExerciseFemaleHumansMalePrinting, Three-Dimensional3D printingadolescentchildcomprehensioneducationmental recallunderstanding

Identifiers

PMID30794204
PMCPMC6406232

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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.