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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Jun 7, 2018
Open Peer Review Period: Jun 12, 2018 - Aug 7, 2018
Date Accepted: Dec 10, 2018
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

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

Crossley SGM, McNarry MA, Rosenberg M, Knowles ZR, Eslambolchilar P, Mackintosh KA

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

J Med Internet Res 2019;21(2):e11253

DOI: 10.2196/11253

PMID: 30794204

PMCID: 6406232

Understanding Youth’s Ability to Interpret 3D Printed Physical Activity Data and Identify Associated Intensity Levels

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

ABSTRACT

Background:

A significant proportion of youth in the UK fail to meet the recommended 60 minutes of moderate-to-vigorous physical activity (MVPA) every day. One of the major barriers encountered in achieving these physical activity (PA) recommendations is the perceived difficulty for youths to interpret PA intensity levels and apply them to everyday activities. Personalised physical activity feedback is regarded as an important method to educate youths about behaviours and associated outcomes. Recent advances in 3D printing have enabled novel ways of representing physical activity levels through personalised tangible feedback to enhance youth’s understanding of concepts and make data more available in the everyday physical environment rather than on-screen.

Objective:

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

Methods:

Twelve primary school children (9 boys; 7.8 ± 0.4 years) and 12 secondary school adolescents (6 boys; 14.1 ± 0.3 years) participated in individual semi-structured interviews. Interview questions, in combination with two interactive tasks, focussed on youths’ ability to correctly identify PA intensities and interpret an age-specific 3D model. Interviews were transcribed verbatim, content analysed, and outcomes represented via tables and diagrammatic pen profiles.

Results:

Youths, 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. Whilst youths were able to correctly interpret different components of the age-specific 3D models, children struggled to differentiate PA intensities represented on the models.

Conclusions:

These findings support the potential use of age-specific 3D models of PA to enhance youths’ understanding of the recommended guidelines and associated intensities.


 Citation

Please cite as:

Crossley SGM, McNarry MA, Rosenberg M, Knowles ZR, Eslambolchilar P, Mackintosh KA

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

J Med Internet Res 2019;21(2):e11253

DOI: 10.2196/11253

PMID: 30794204

PMCID: 6406232

Per the author's request the PDF is not available.

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