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ORIGINAL RESEARCH article

Front. Psychol.
Sec. Sport Psychology
Volume 15 - 2024 | doi: 10.3389/fpsyg.2024.1518468
This article is part of the Research Topic Online Assessment in Health and Sport Psychology View all 7 articles

Data mining for psychological profile study of track and field athletes and runners

Provisionally accepted
Cristina Sanz-Fernández Cristina Sanz-Fernández 1*Jose Luis Pastrana-Brincones Jose Luis Pastrana-Brincones 2Julen Castellano Julen Castellano 3Rafael E. Reigal Rafael E. Reigal 2Diego A. Arvizu Diego A. Arvizu 4Antonio Hernández-Mendo Antonio Hernández-Mendo 2Verónica Morales-Sánchez Verónica Morales-Sánchez 5
  • 1 University of La Rioja, Logroño, La Rioja, Spain
  • 2 University of Malaga, Málaga, Andalusia, Spain
  • 3 Department of Physical Education and Sports, University of the Basque Country, Vitoria-Gasteiz, Spain
  • 4 Autonomous University of Nuevo León, San Nicolás de los Garza, Nuevo León4, Mexico
  • 5 Aula del Mar Málaga, Málaga, Andalusia, Spain

The final, formatted version of the article will be published soon.

    Psychological factors in sport have been widely studied in scientific literature. However, just a few research has used data mining techniques for athletic profile analyzing. The main goal of this study was to analyze motivation, self-confidence, flow and psychological skills in athletics in order to build differentiated profiles trough clustering techniques. Sample size was 470 participants (age: from 14 to 70 years old; M = 32.1; SD = 13.5). Sport Motivation Scale (SMS), Task and Ego Orientation in Sport Questionnaire (TEOSQ), Self-Confidence in Sport Questionnaire (CACD), Flow Dispositional Scale-2 (FDS-2) and Psychological Inventory of Sport Performance (IPED) were used to analyze the psychological profile of the sample. A clustering analysis of data was carried out to check the study purpose. Results show different behavior patterns according to specific profiles. Likewise, it has been found differences between male and female, as well as online and in face-to-face participants, federated athletes and runners, categories or sport disciplines. In conclusion, the understanding of each athlete psychological profile is essential to improve his/her performance. The results of this study could be used to implement changes and adjustments in athlete psychological training, in order to run several interventions programs, focus on each group needs.

    Keywords: Track and Field, Data Mining, clustering, mixed method, specialties

    Received: 28 Oct 2024; Accepted: 24 Dec 2024.

    Copyright: © 2024 Sanz-Fernández, Pastrana-Brincones, Castellano, Reigal, Arvizu, Hernández-Mendo and Morales-Sánchez. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Cristina Sanz-Fernández, University of La Rioja, Logroño, 26006, La Rioja, Spain

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.