IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2019i1p39-d299698.html
   My bibliography  Save this article

Physical Activity-Related Health Competence, Physical Activity, and Physical Fitness: Analysis of Control Competence for the Self-Directed Exercise of Adolescents

Author

Listed:
  • Stephanie Haible

    (Institute of Sport Science, University of Tübingen, Wilhelmstr. 124, D-72074 Tübingen, Germany)

  • Carmen Volk

    (Institute of Sport Science, University of Tübingen, Wilhelmstr. 124, D-72074 Tübingen, Germany)

  • Yolanda Demetriou

    (Department of Sport and Health Sciences, Technical University of Munich, Georg-Brauchle-Ring 60/62, D-80992 Munich, Germany)

  • Oliver Höner

    (Institute of Sport Science, University of Tübingen, Wilhelmstr. 124, D-72074 Tübingen, Germany)

  • Ansgar Thiel

    (Institute of Sport Science, University of Tübingen, Wilhelmstr. 124, D-72074 Tübingen, Germany)

  • Gorden Sudeck

    (Institute of Sport Science, University of Tübingen, Wilhelmstr. 124, D-72074 Tübingen, Germany)

Abstract

(1) Background: Individuals have to effectively manage their physical activity in order to optimize the associated physical and psychological health benefits. Control competence allows the individual to structure and pace physical activity in a health-enhancing way. The concept was developed within a model of physical activity-related health competence, and is related to the concepts of health literacy and physical literacy. Therefore, the study firstly aimed to validate a self-report scale to measure the physical and psychological facets of control competence in adolescents. Secondly, relationships between control competence and its basic elements, knowledge and motivation, as well as between control competence, sport activity, and fitness, were investigated. (2) Methods: In two cross-sectional studies, ninth grade adolescents (study A: n = 794, 51% female; study B: n = 860, 52% female) were tested using self-report scales (study A and B), a test for health-related fitness knowledge (study B), and cardiovascular and muscular fitness tests (study B). (3) Results: Confirmatory factor analyses confirmed the two-factor structure of the self-report scale for control competence in studies A and B. In addition, the results of structural equation modeling in study B showed a relationship between motivation (via control competence) and sport activity, and a relationship between control competence and fitness. (4) Conclusion: The questionnaire extends the ability to assess control competence in adolescents. Moreover the findings support the importance of control competence in order to achieve health benefits through physical activity.

Suggested Citation

  • Stephanie Haible & Carmen Volk & Yolanda Demetriou & Oliver Höner & Ansgar Thiel & Gorden Sudeck, 2019. "Physical Activity-Related Health Competence, Physical Activity, and Physical Fitness: Analysis of Control Competence for the Self-Directed Exercise of Adolescents," IJERPH, MDPI, vol. 17(1), pages 1-15, December.
  • Handle: RePEc:gam:jijerp:v:17:y:2019:i:1:p:39-:d:299698
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/1/39/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/17/1/39/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Thomas Warm, 1989. "Weighted likelihood estimation of ability in item response theory," Psychometrika, Springer;The Psychometric Society, vol. 54(3), pages 427-450, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gabriella Nagy-Pénzes & Ferenc Vincze & János Sándor & Éva Bíró, 2020. "Does Better Health-Related Knowledge Predict Favorable Health Behavior in Adolescents?," IJERPH, MDPI, vol. 17(5), pages 1-12, March.
    2. Gerd Schmitz, 2020. "Moderators of Perceived Effort in Adolescent Rowers During a Graded Exercise Test," IJERPH, MDPI, vol. 17(21), pages 1-10, November.

    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. repec:zbw:rwidps:0002 is not listed on IDEAS
    2. Dahmann, Sarah C., 2017. "How does education improve cognitive skills? Instructional time versus timing of instruction," Labour Economics, Elsevier, vol. 47(C), pages 35-47.
    3. Torberg Falch & Justina AV Fischer, 2008. "Does a generous welfare state crowd out student achievement? Panel data evidence from international student tests," TWI Research Paper Series 31, Thurgauer Wirtschaftsinstitut, Universität Konstanz.
    4. Steger, Diana & Schroeders, Ulrich & Wilhelm, Oliver, 2019. "On the dimensionality of crystallized intelligence: A smartphone-based assessment," Intelligence, Elsevier, vol. 72(C), pages 76-85.
    5. Janna Niens & Lisa Richter-Beuschel & Tobias C. Stubbe & Susanne Bögeholz, 2021. "Procedural Knowledge of Primary School Teachers in Madagascar for Teaching and Learning towards Land-Use- and Health-Related Sustainable Development Goals," Sustainability, MDPI, vol. 13(16), pages 1-36, August.
    6. Michela Battauz & Ruggero Bellio, 2011. "Structural Modeling of Measurement Error in Generalized Linear Models with Rasch Measures as Covariates," Psychometrika, Springer;The Psychometric Society, vol. 76(1), pages 40-56, January.
    7. Xiang Liu & James Yang & Hui Soo Chae & Gary Natriello, 2020. "Power Divergence Family of Statistics for Person Parameters in IRT Models," Psychometrika, Springer;The Psychometric Society, vol. 85(2), pages 502-525, June.
    8. Chun Wang, 2015. "On Latent Trait Estimation in Multidimensional Compensatory Item Response Models," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 428-449, June.
    9. Marko Böhm & Jan Barkmann & Sabina Eggert & Claus H. Carstensen & Susanne Bögeholz, 2020. "Quantitative Modelling and Perspective Taking: Two Competencies of Decision Making for Sustainable Development," Sustainability, MDPI, vol. 12(17), pages 1-32, August.
    10. repec:zbw:rwidps:0023 is not listed on IDEAS
    11. Hammon, Angelina & Zinn, Sabine, 2020. "Multiple imputation of binary multilevel missing not at random data," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 69(3), pages 547-564.
    12. Schmidt, Christoph & Fertig, Michael, 2002. "The Role of Background Factors for Reading Literacy: Straight National scores in the Pisa 2000 Study," CEPR Discussion Papers 3544, C.E.P.R. Discussion Papers.
    13. Yang Liu & Jan Hannig & Abhishek Pal Majumder, 2019. "Second-Order Probability Matching Priors for the Person Parameter in Unidimensional IRT Models," Psychometrika, Springer;The Psychometric Society, vol. 84(3), pages 701-718, September.
    14. Robitzsch, Alexander, 2020. "About Still Nonignorable Consequences of (Partially) Ignoring Missing Item Responses in Large-scale Assessment," OSF Preprints hmy45, Center for Open Science.
    15. Haruhiko Ogasawara, 2013. "Asymptotic properties of the Bayes modal estimators of item parameters in item response theory," Computational Statistics, Springer, vol. 28(6), pages 2559-2583, December.
    16. Fertig, Michael, 2003. "Educational Production, Endogenous Peer Group Formation and Class Composition - Evidence From the PISA 2000 Study," RWI Discussion Papers 2, RWI - Leibniz-Institut für Wirtschaftsforschung.
    17. Elina Tsigeman & Sebastian Silas & Klaus Frieler & Maxim Likhanov & Rebecca Gelding & Yulia Kovas & Daniel Müllensiefen, 2022. "The Jack and Jill Adaptive Working Memory Task: Construction, Calibration and Validation," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-29, January.
    18. Seonghoon Kim, 2012. "A Note on the Reliability Coefficients for Item Response Model-Based Ability Estimates," Psychometrika, Springer;The Psychometric Society, vol. 77(1), pages 153-162, January.
    19. Falch, Torberg & Justina, Fischer, 2016. "Welfare state generosity and student performance: Evidence from international student tests 1980-2003," MPRA Paper 74553, University Library of Munich, Germany.
    20. Xiao Li & Hanchen Xu & Jinming Zhang & Hua-hua Chang, 2023. "Deep Reinforcement Learning for Adaptive Learning Systems," Journal of Educational and Behavioral Statistics, , vol. 48(2), pages 220-243, April.
    21. Martin Biehler & Heinz Holling & Philipp Doebler, 2015. "Saddlepoint Approximations of the Distribution of the Person Parameter in the Two Parameter Logistic Model," Psychometrika, Springer;The Psychometric Society, vol. 80(3), pages 665-688, September.
    22. Piero Veronese & Eugenio Melilli, 2021. "Confidence Distribution for the Ability Parameter of the Rasch Model," Psychometrika, Springer;The Psychometric Society, vol. 86(1), pages 131-166, March.

    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:gam:jijerp:v:17:y:2019:i:1:p:39-:d:299698. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.