IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0241013.html
   My bibliography  Save this article

Using the situational characteristics of the DIAMONDS taxonomy to distinguish sports to more precisely investigate their relation with psychologically relevant variables

Author

Listed:
  • Sophia Terwiel
  • John F Rauthmann
  • Maike Luhmann

Abstract

The continuous development and evolvement of sports provide a challenge for researchers who study psychological correlates and consequences of sports, as no single study can include all sports and results cannot easily be generalized across different sports. In this preregistered study, we present a new way of distinguishing sports based on the eight DIAMONDS situational characteristics: Duty, Intellect, Adversity, Mating, pOsitivity, Negativity, Deception, and Sociality. In a cross-sectional online survey, athletes were asked to judge the sport they perform on the eight DIAMONDS dimensions. 138 sports were rated by N = 7,835 athletes using the 24-item version of the S8*questionnaire measuring the DIAMONDS. Descriptive and cluster analyses were performed, and situational characteristics profiles were computed. The sport-specific profiles and identified clusters resemble existing sport categorizations but add relevant information based on the situational characteristics of sports, especially regarding their relation with psychologically relevant variables.

Suggested Citation

  • Sophia Terwiel & John F Rauthmann & Maike Luhmann, 2020. "Using the situational characteristics of the DIAMONDS taxonomy to distinguish sports to more precisely investigate their relation with psychologically relevant variables," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-15, October.
    • Handle: RePEc:plo:pone00:0241013
    DOI: 10.1371/journal.pone.0241013
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0241013
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0241013&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0241013?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
    ---><---

    References listed on IDEAS

    as
    1. Christian Hennig & Tim F. Liao, 2013. "How to find an appropriate clustering for mixed-type variables with application to socio-economic stratification," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(3), pages 309-369, May.
    2. Hallmann, Kirstin & Giel, Thomas, 2018. "eSports – Competitive sports or recreational activity?," Sport Management Review, Elsevier, vol. 21(1), pages 14-20.
    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. Elvira Pelle & Roberta Pappadà, 2021. "A clustering procedure for mixed-type data to explore ego network typologies: an application to elderly people living alone in Italy," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(5), pages 1507-1533, December.
    2. Roberto Mari & Roberto Rocci & Stefano Antonio Gattone, 2020. "Scale-constrained approaches for maximum likelihood estimation and model selection of clusterwise linear regression models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(1), pages 49-78, March.
    3. Fernández, D. & Arnold, R. & Pledger, S., 2016. "Mixture-based clustering for the ordered stereotype model," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 46-75.
    4. Layal Christine Lettry, 2023. "Clustering the Swiss Pension Register," FSES Working Papers 529, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    5. Goodrich, Brittney K. & Goodhue, Rachael E., 2020. "Are All Colonies Created Equal? The Role of Honey Bee Colony Strength in Almond Pollination Contracts," Ecological Economics, Elsevier, vol. 177(C).
    6. Marcel Raab & Anette Fasang & Aleksi Karhula & Jani Erola, 2014. "Sibling Similarity in Family Formation," Demography, Springer;Population Association of America (PAA), vol. 51(6), pages 2127-2154, December.
    7. Salvatore Ingrassia & Antonio Punzo & Giorgio Vittadini & Simona Minotti, 2015. "Erratum to: The Generalized Linear Mixed Cluster-Weighted Model," Journal of Classification, Springer;The Classification Society, vol. 32(2), pages 327-355, July.
    8. Raoofpanah, Iman & Zamudio, César & Groening, Christopher, 2023. "Review reader segmentation based on the heterogeneous impacts of review and reviewer attributes on review helpfulness: A study involving ZIP code data," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    9. Weisheng Chiu & Thomas Chun Man Fan & Sang-Back Nam & Ping-Hung Sun, 2021. "Knowledge Mapping and Sustainable Development of eSports Research: A Bibliometric and Visualized Analysis," Sustainability, MDPI, vol. 13(18), pages 1-17, September.
    10. Andrew Gelman & Christian Hennig, 2017. "Beyond subjective and objective in statistics," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(4), pages 967-1033, October.
    11. Cunningham, George B. & Fairley, Sheranne & Ferkins, Lesley & Kerwin, Shannon & Lock, Daniel & Shaw, Sally & Wicker, Pamela, 2018. "eSport: Construct specifications and implications for sport management," Sport Management Review, Elsevier, vol. 21(1), pages 1-6.
    12. Frano Giakoni-Ramírez & Eugenio Merellano-Navarro & Daniel Duclos-Bastías, 2022. "Professional Esports Players: Motivation and Physical Activity Levels," IJERPH, MDPI, vol. 19(4), pages 1-13, February.
    13. Jean-Patrick Baudry & Margarida Cardoso & Gilles Celeux & Maria Amorim & Ana Ferreira, 2015. "Enhancing the selection of a model-based clustering with external categorical variables," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 9(2), pages 177-196, June.
    14. Giachino, Chiara & Nirino, Niccolò & Leonidou, Erasmia & Glyptis, Loukas, 2023. "eSport in the digital era: Exploring the moderating role of perceived usefulness on financial behavioural aspects within reward-crowdfunding," Journal of Business Research, Elsevier, vol. 155(PB).
    15. Hollebeek, Linda D. & Abbasi, Amir Zaib & Schultz, Carsten D. & Ting, Ding Hooi & Sigurdsson, Valdimar, 2022. "Hedonic consumption experience in videogaming: A multidimensional perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    16. Michael R. Ward & Alexander D. Harmon, 2019. "ESport Superstars," Journal of Sports Economics, , vol. 20(8), pages 987-1013, December.
    17. Andrea Cerasa, 2016. "Combining homogeneous groups of preclassified observations with application to international trade," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(3), pages 229-259, August.
    18. Bettina Grün & Sara Dolnicar, 2016. "Response style corrected market segmentation for ordinal data," Marketing Letters, Springer, vol. 27(4), pages 729-741, December.
    19. Francesco Dotto & Alessio Farcomeni & Luis Angel García-Escudero & Agustín Mayo-Iscar, 2017. "A fuzzy approach to robust regression clustering," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(4), pages 691-710, December.
    20. Goodrich, Brittney K. & Yu, Jisang, 2018. "Risk Preferences and the Participation Pattern of Rainfall Index Insurance," 2018 Annual Meeting, August 5-7, Washington, D.C. 273879, Agricultural and Applied Economics Association.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0241013. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.