IDEAS home Printed from https://ideas.repec.org/a/eee/cysrev/v128y2021ics0190740921002267.html
   My bibliography  Save this article

Behaviour associated with the presence of a school sports ground: Visual information for policy makers

Author

Listed:
  • Vala, Roman
  • Valova, Marie
  • Drazdilova, Pavla
  • Krömer, Pavel
  • Platos, Jan

Abstract

The planning and development of sports infrastructure is a complex process that has a broad and long-term impact on health and well-being in communities. It involves many different stake- holders and usually requires significant public or private investments. Its framework is outlined by policies that define the general social goals of such development. To ensure the maximum alignment between the goals and the development activities, it is important to support the policy making process by high-quality information based on real-world data and presented in a clear and focused way. This work introduces a new pipeline of methods for processing and interpretation of data on physical activity and lifestyle in adolescents. The data is extracted from the Health Behaviour in School-aged Children (HBSC) study and analyzed by modern machine learning methods. We identify behavioural patterns associated with the presence and absence of a school sports ground in different sex and age groups of adolescent in the Czech Republic. The patterns are presented by concise graphical models that ease their use by stake- holders without expert knowledge in sociology, statistics, mathematical modelling, etc. They enable intuitive visual assessment of situation in different regions and highlight the specific similarities and differences among them. Together, the proposed methods contribute towards objective evidence-based policy making in sports management and development.

Suggested Citation

  • Vala, Roman & Valova, Marie & Drazdilova, Pavla & Krömer, Pavel & Platos, Jan, 2021. "Behaviour associated with the presence of a school sports ground: Visual information for policy makers," Children and Youth Services Review, Elsevier, vol. 128(C).
  • Handle: RePEc:eee:cysrev:v:128:y:2021:i:c:s0190740921002267
    DOI: 10.1016/j.childyouth.2021.106150
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0190740921002267
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.childyouth.2021.106150?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dendup, Tashi & Putra, I Gusti Ngurah Edi & Dorji, Tandin & Tobgay, Tashi & Dorji, Gampo & Phuntsho, Sonam & Tshering, Pandup, 2020. "Correlates of sedentary behaviour among Bhutanese adolescents: Findings from the 2016 Global School-based health survey," Children and Youth Services Review, Elsevier, vol. 119(C).
    2. Gérard Biau & Erwan Scornet, 2016. "A random forest guided tour," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(2), pages 197-227, June.
    3. Dagmar Sigmundová & Erik Sigmund & Riki Tesler & Kwok W. Ng & Zdenek Hamrik & Frida Kathrine Sofie Mathisen & Jo Inchley & Jens Bucksch, 2019. "Vigorous physical activity in relation to family affluence: time trends in Europe and North America," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 64(7), pages 1049-1058, September.
    4. James Skinner & Dwight H. Zakus & Jacqui Cowell, 2008. "Development through Sport: Building Social Capital in Disadvantaged Communities," Sport Management Review, Taylor & Francis Journals, vol. 11(3), pages 253-275, September.
    5. McLean, Lavinia & Penco, Rebecca, 2020. "Physical activity: Exploring the barriers and facilitators for the engagement of young people in residential care in Ireland," Children and Youth Services Review, Elsevier, vol. 119(C).
    6. Gérard Biau & Erwan Scornet, 2016. "Rejoinder on: A random forest guided tour," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(2), pages 264-268, June.
    7. Sandu, Petru & Chereches, Razvan M. & Baba, Catalin O. & Revnic, Radu N. & Mocean, Floarea, 2018. "Environmental influences on physical activity – Romanian youths' perspectives," Children and Youth Services Review, Elsevier, vol. 95(C), pages 71-79.
    8. Zieff, Susan G. & Chaudhuri, Anoshua & Musselman, Elaine, 2016. "Creating neighborhood recreational space for youth and children in the urban environment: Play(ing in the) Streets in San Francisco," Children and Youth Services Review, Elsevier, vol. 70(C), pages 95-101.
    9. Tim Althoff & Rok Sosič & Jennifer L. Hicks & Abby C. King & Scott L. Delp & Jure Leskovec, 2017. "Large-scale physical activity data reveal worldwide activity inequality," Nature, Nature, vol. 547(7663), pages 336-339, July.
    10. Skinner, James & Zakus, Dwight H. & Cowell, Jacqui, 2008. "Development through Sport: Building Social Capital in Disadvantaged Communities," Sport Management Review, Elsevier, vol. 11(3), pages 253-275, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hou, Lei & Elsworth, Derek & Zhang, Fengshou & Wang, Zhiyuan & Zhang, Jianbo, 2023. "Evaluation of proppant injection based on a data-driven approach integrating numerical and ensemble learning models," Energy, Elsevier, vol. 264(C).
    2. Ma, Zhikai & Huo, Qian & Wang, Wei & Zhang, Tao, 2023. "Voltage-temperature aware thermal runaway alarming framework for electric vehicles via deep learning with attention mechanism in time-frequency domain," Energy, Elsevier, vol. 278(C).
    3. Patrick Krennmair & Timo Schmid, 2022. "Flexible domain prediction using mixed effects random forests," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1865-1894, November.
    4. Manuel J. García Rodríguez & Vicente Rodríguez Montequín & Francisco Ortega Fernández & Joaquín M. Villanueva Balsera, 2019. "Public Procurement Announcements in Spain: Regulations, Data Analysis, and Award Price Estimator Using Machine Learning," Complexity, Hindawi, vol. 2019, pages 1-20, November.
    5. Kuang-Hua Hu & Fu-Hsiang Chen & Gwo-Hshiung Tzeng, 2016. "Evaluating the Improvement of Sustainability of Sports Industry Policy Based on MADM," Sustainability, MDPI, vol. 8(7), pages 1-21, June.
    6. Sachin Kumar & Zairu Nisha & Jagvinder Singh & Anuj Kumar Sharma, 2022. "Sensor network driven novel hybrid model based on feature selection and SVR to predict indoor temperature for energy consumption optimisation in smart buildings," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(6), pages 3048-3061, December.
    7. Escribano, Álvaro & Wang, Dandan, 2021. "Mixed random forest, cointegration, and forecasting gasoline prices," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1442-1462.
    8. Yigit Aydede & Jan Ditzen, 2022. "Identifying the regional drivers of influenza-like illness in Nova Scotia with dominance analysis," Papers 2212.06684, arXiv.org.
    9. Siyoon Kwon & Hyoseob Noh & Il Won Seo & Sung Hyun Jung & Donghae Baek, 2021. "Identification Framework of Contaminant Spill in Rivers Using Machine Learning with Breakthrough Curve Analysis," IJERPH, MDPI, vol. 18(3), pages 1-26, January.
    10. Yan, Ran & Wang, Shuaian & Du, Yuquan, 2020. "Development of a two-stage ship fuel consumption prediction and reduction model for a dry bulk ship," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    11. Hanna Nałęcz & Łukasz Skrok & Dawid Majcherek & Elżbieta Biernat, 2020. "Through Sport to Innovation: Sustainable Socio-Economic Development in European Countries," Sustainability, MDPI, vol. 12(24), pages 1-16, December.
    12. Yi Cao & Xue Li, 2022. "Multi-Model Attention Fusion Multilayer Perceptron Prediction Method for Subway OD Passenger Flow under COVID-19," Sustainability, MDPI, vol. 14(21), pages 1-16, November.
    13. Ying Yan & Abdol Aziz Shahraki, 2023. "Exploring the Mutual Relationships between Public Space and Social Satisfaction with Case Studies," Sustainability, MDPI, vol. 15(9), pages 1-15, May.
    14. Filmer,Deon P. & Nahata,Vatsal & Sabarwal,Shwetlena, 2021. "Preparation, Practice, and Beliefs : A Machine Learning Approach to Understanding Teacher Effectiveness," Policy Research Working Paper Series 9847, The World Bank.
    15. Ho Fai Chan & David A. Savage & Benno Torgler, 2021. "Sport as a Behavioral Economics Lab," CREMA Working Paper Series 2021-20, Center for Research in Economics, Management and the Arts (CREMA).
    16. Daniel Boller & Michael Lechner & Gabriel Okasa, 2021. "The Effect of Sport in Online Dating: Evidence from Causal Machine Learning," Papers 2104.04601, arXiv.org.
    17. Jorge Antunes & Peter Wanke & Thiago Fonseca & Yong Tan, 2023. "Do ESG Risk Scores Influence Financial Distress? Evidence from a Dynamic NDEA Approach," Sustainability, MDPI, vol. 15(9), pages 1-32, May.
    18. Seung Pil Lee, 2020. "Sustainable Reciprocity Mechanism of Social Initiatives in Sport: The Mediating Effect of Gratitude," Sustainability, MDPI, vol. 12(21), pages 1-18, November.
    19. Lyudmyla Kirichenko & Tamara Radivilova & Vitalii Bulakh, 2018. "Machine Learning in Classification Time Series with Fractal Properties," Data, MDPI, vol. 4(1), pages 1-13, December.
    20. Martino Corazza & Jen Dyer, 2017. "A New Model for Inclusive Sports? An Evaluation of Participants’ Experiences of Mixed Ability Rugby," Social Inclusion, Cogitatio Press, vol. 5(2), pages 130-140.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:cysrev:v:128:y:2021:i:c:s0190740921002267. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/childyouth .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.