Profiling Movement Quality Characteristics of Children (9-11y) During Recess

Authors

  • Cain Craig Truman Clark Sport, Exercise and Well-Being Research Arena, University Centre Hartpury, Gloucestershire, England, GL19 3BE., and; Engineering Behaviour Analytics in Sport and Exercise (E-BASE) Research group, College of Engineering, Bay Campus, Swansea University, Fabian Way, Swansea, Wales, SA1 8EN.
  • Claire Marie Barnes Applied Sports Science Technology and Medicine Research Centre (A-STEM), College of Engineering, Bay Campus, Swansea University, Fabian Way, Swansea, Wales, SA1 8EN., and; Engineering Behaviour Analytics in Sport and Exercise (E-BASE) Research group, College of Engineering, Bay Campus, Swansea University, Fabian Way, Swansea, Wales, SA1 8EN
  • Huw D Summers Applied Sports Science Technology and Medicine Research Centre (A-STEM), College of Engineering, Bay Campus, Swansea University, Fabian Way, Swansea, Wales, SA1 8EN., and; Engineering Behaviour Analytics in Sport and Exercise (E-BASE) Research group, College of Engineering, Bay Campus, Swansea University, Fabian Way, Swansea, Wales, SA1 8EN
  • Kelly Mackintosh Applied Sports Science Technology and Medicine Research Centre (A-STEM), College of Engineering, Bay Campus, Swansea University, Fabian Way, Swansea, Wales, SA1 8EN., and; Engineering Behaviour Analytics in Sport and Exercise (E-BASE) Research group, College of Engineering, Bay Campus, Swansea University, Fabian Way, Swansea, Wales, SA1 8EN
  • Gareth Stratton Applied Sports Science Technology and Medicine Research Centre (A-STEM), College of Engineering, Bay Campus, Swansea University, Fabian Way, Swansea, Wales, SA1 8EN., and; Engineering Behaviour Analytics in Sport and Exercise (E-BASE) Research group, College of Engineering, Bay Campus, Swansea University, Fabian Way, Swansea, Wales, SA1 8EN

Abstract

Introduction. Frequency spectrum characteristics derived from raw accelerometry, such as spectral purity, have the potential to reveal detailed information about children’s movement quality, but remain unexplored in children’s physical activity. The aim of this study was to investigate and profile children’s recess physical activity and movement quality using a novel analytical approach. Materials and Methods. A powered sample of twenty-four children (18 boys) (10.5±0.6y, 1.44±0.09m, 39.6±9.5kg, body mass index; 18.8±3.1 kg.m2) wore an ankle-mounted accelerometer during school recess, for one school-week. Hierarchical clustering, Spearman’s rho and the Mann-Whitney U test were used to assess relationships between characteristics, and to assess inter-day differences. Results. There were no significant inter-day differences found for overall activity (P>0.05), yet significant differences were found for spectral purity derived movement quality (P<0.001). Overall activity was hierarchically clustered, and positively correlated, with spectral purity (P<0.05). Discussion. This is the first study to report spectral purity derived movement quality of children’s physical activity in an uncontrolled setting and our results highlight potential for future research.

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Author Biography

Cain Craig Truman Clark, Sport, Exercise and Well-Being Research Arena, University Centre Hartpury, Gloucestershire, England, GL19 3BE., and; Engineering Behaviour Analytics in Sport and Exercise (E-BASE) Research group, College of Engineering, Bay Campus, Swansea University, Fabian Way, Swansea, Wales, SA1 8EN.

Dr. Cain C. T. Clark is an early career researcher in the field of physical activity and health, in addition to programme managing BSc Sport & Exercise Sciences at University Centre Hartpury. Dr. Clark is a member of the Global Active Healthy Kids Alliance and a Fellow of the Royal Society of Public Health.

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2018-01-15

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