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Stenling, Andreas
Publications (5 of 5) Show all publications
Ivarsson, A. & Stenling, A. (2019). Prediction of injury risk in sports. In: N. Balakrishnan, Theodore Colton, Brian Everitt, Walter Piegorsch, Fabrizio Ruggeri & Jozef L. Teugels (Ed.), Wiley StatsRef: Statistics Reference Online. John Wiley & Sons
Open this publication in new window or tab >>Prediction of injury risk in sports
2019 (English)In: Wiley StatsRef: Statistics Reference Online / [ed] N. Balakrishnan, Theodore Colton, Brian Everitt, Walter Piegorsch, Fabrizio Ruggeri & Jozef L. Teugels, John Wiley & Sons, 2019Chapter in book (Refereed)
Abstract [en]

Sport injuries are a major problem associated with sport participation. To develop preventive strategies and programs, it is important to identify factors that will increase the likelihood of sport injuries. In most sport injury risk factor research, statistical analyses are performed; however, many of the most common statistical analyses provide limited information about predictors of sport injury risk. The common analyses used in previous studies do not acknowledge the complexity associated with investigating risk factors for sport injuries. To better capture this complexity, suggested in most theoretical frameworks, more appropriate of statistical approaches should be used. In this article we present how latent profile analysis, latent change score analysis, and latent growth curve analysis can be used to overcome some of the limitations with more traditional analyses. Lastly, we also elaborate on future directions for analyses in sport injury risk factor research. More specifically, we present how advanced statistical models, such as classification and regression trees (CART) analysis and random forest analysis, can be used to provide researchers and clinicians with results that are more clinically meaningful.

Place, publisher, year, edition, pages
John Wiley & Sons, 2019
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:hh:diva-38528 (URN)10.1002/9781118445112.stat08141 (DOI)9781118445112 (ISBN)
Available from: 2018-12-09 Created: 2018-12-09 Last updated: 2019-05-16Bibliographically approved
Stenling, A., Ivarsson, A., Lindwall, M. & Gucciardi, D. F. (2018). Exploring longitudinal measurement invariance and the continuum hypothesis in the Swedish version of the Behavioral Regulation in Sport Questionnaire (BRSQ): An exploratory structural equation modeling approach. Psychology of Sport And Exercise, 36, 187-196
Open this publication in new window or tab >>Exploring longitudinal measurement invariance and the continuum hypothesis in the Swedish version of the Behavioral Regulation in Sport Questionnaire (BRSQ): An exploratory structural equation modeling approach
2018 (English)In: Psychology of Sport And Exercise, ISSN 1469-0292, E-ISSN 1878-5476, Vol. 36, p. 187-196Article in journal (Refereed) Published
Abstract [en]

Objectives

The aims of the present study were to: (a) examine longitudinal measurement invariance in the Swedish version of the Behavioral Regulations in Sport Questionnaire (BRSQ) and (b) examine the continuum hypothesis of motivation as postulated within self-determination theory.

Design

Two-wave survey.

Method

Young competitive athletes (N = 354) responded to the BRSQ early in the season (November) and at the end of the athletic season (April). Data were analyzed using exploratory structural equation modeling (ESEM) and bifactor ESEM.

Results

We found support for strict longitudinal measurement invariance in the BRSQ. Latent mean comparisons showed an increase in external regulation and amotivation across the season. The latent factor correlations indicated some deviations from a simplex pattern related to amotivation, external regulation, and introjected regulation. In the bifactor model, intrinsic motivation items had negative factor loadings on the global factor, identified regulation items had factor loadings approaching zero, and introjected and external regulation and amotivation items all had moderate to strong positive factor loadings.

Conclusion

The present study adds longitudinal measurement invariance to the psychometric evidence of the BRSQ. Research on why the latent means of the behavioral regulations changed over the athletic season is warranted. The continuum hypothesis was partially supported. Latent factor correlations and factor loadings on the global factor in the bifactor ESEM highlighted that the discriminant validity of the controlled regulations and amotivation needs further investigation. © 2018 Elsevier Ltd

Place, publisher, year, edition, pages
Amsterdam: Elsevier, 2018
Keywords
Latent mean changes, Motivation continuum, Self-determination theory, Temporal stability
National Category
Applied Psychology
Identifiers
urn:nbn:se:hh:diva-36388 (URN)10.1016/j.psychsport.2018.03.002 (DOI)2-s2.0-85043782981 (Scopus ID)
Note

Funding: Andreas Stenling was supported by grants from Umeå School of Sport Sciences (Dnr: IH 5.3-12-2017) and the Swedish National Centre for Research in Sports (CIF), grant numbers P2014-0043 and P2015-0114. Daniel F. Gucciardi is supported by a Curtin Research Fellowship.

Available from: 2018-03-06 Created: 2018-03-06 Last updated: 2018-04-12Bibliographically approved
Clement, D., Ivarsson, A., Tranaeus, U., Johnson, U. & Stenling, A. (2018). Investigating the influence of intra-individual changes in perceived stress symptoms on injury risk in soccer. Scandinavian Journal of Medicine and Science in Sports, 28(4), 1461-1466
Open this publication in new window or tab >>Investigating the influence of intra-individual changes in perceived stress symptoms on injury risk in soccer
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2018 (English)In: Scandinavian Journal of Medicine and Science in Sports, ISSN 0905-7188, E-ISSN 1600-0838, Vol. 28, no 4, p. 1461-1466Article in journal (Refereed) Published
Abstract [en]

Research has shown that high levels of stress and stress responsivity can increase the risk of injuries. However, most of the research that has supported this notion has focused on between-person relationships, ignoring the relationships at the within-person level. As a result, the objective of this study was to investigate if within-person changes in perceived stress symptoms over a 1-month time period could predict injury rates during the subsequent 3 months. A prospective design with two measurement points (Time 1—at the beginning of the season and Time 2—1 month into the season) was utilized. A total of 121 competitive soccer players (85 males and 36 females; Mage = 18.39, SD = 3.08) from Sweden and the United States completed the Kessler Psychological Distress Scale (KPDS) and a demographic sheet at Time 1. The KPDS was also completed at Time 2, and all acute injuries that occurred during the subsequent 3-month period were recorded. A Bayesian latent change scores model was used to determine whether within-person changes in stress symptoms could predict the risk of injury. Results revealed that there was a credible positive effect of changes in stress symptoms on injury rates, indicating that an increase in reported stress symptoms was related to an increased risk for injury. This finding highlights the importance of creating caring and supportive sporting environments and relationships and teaching stress management techniques, especially during the earlier portion of competitive seasons, to possibly reduce the occurrence of injuries. © 2018 John Wiley & Sons A/S.

Place, publisher, year, edition, pages
Chichester: Wiley-Blackwell Publishing Inc., 2018
Keywords
athletes, psychological predictors, sport injury, stress management
National Category
Psychology
Identifiers
urn:nbn:se:hh:diva-36307 (URN)10.1111/sms.13048 (DOI)2-s2.0-85041201109 (Scopus ID)
Available from: 2018-02-16 Created: 2018-02-16 Last updated: 2018-07-05Bibliographically approved
Li, C., Ivarsson, A., Stenling, A. & Wu, Y. (2018). The dynamic interplay between burnout and sleep among elite blind soccer players. Psychology of Sport And Exercise, 37, 164-169
Open this publication in new window or tab >>The dynamic interplay between burnout and sleep among elite blind soccer players
2018 (English)In: Psychology of Sport And Exercise, ISSN 1469-0292, E-ISSN 1878-5476, Vol. 37, p. 164-169Article in journal (Refereed) Published
Abstract [en]

The dynamic pattern between burnout and sleep among athletes is unknown. This longitudinal survey examined the interplay between burnout and sleep among blind elite soccer players. China national blind soccer team players (n = 10) completed measures on burnout and sleep quality through interview at baseline (month 1), and followed at months 2, 3, 4, and 5. The results of dynamic p-technique analysis, using Bayesian estimation, showed a credible relationship between burnout and sleep quality. Also, burnout had a credible lagged effect on subsequent sleep quality whereas sleep quality did not have a credible lagged effect on burnout. The results suggest that burnout and sleep are not reciprocally related and burnout may be a risk factor of sleep problems among athletes. © 2017 Elsevier Ltd.

Place, publisher, year, edition, pages
Amsterdam: Elsevier, 2018
Keywords
Bayesian estimation, Disability sport, p-technique analysis, Sleep quality
National Category
Applied Psychology Sport and Fitness Sciences
Identifiers
urn:nbn:se:hh:diva-35017 (URN)10.1016/j.psychsport.2017.08.008 (DOI)2-s2.0-85028377538 (Scopus ID)
Note

Funding: the China Disabled Persons’ Federation [6*CLRIO&010].

Available from: 2017-09-19 Created: 2017-09-19 Last updated: 2018-07-03Bibliographically approved
Stenling, A., Ivarsson, A., Johnson, U. & Lindwall, M. (2015). Bayesian Structural Equation Modeling in Sport and Exercise Psychology. Journal of Sport & Exercise Psychology (JSEP), 37, 410-420
Open this publication in new window or tab >>Bayesian Structural Equation Modeling in Sport and Exercise Psychology
2015 (English)In: Journal of Sport & Exercise Psychology (JSEP), ISSN 0895-2779, E-ISSN 1543-2904, Vol. 37, p. 410-420Article in journal (Refereed) Published
Abstract [en]

Bayesian statistics is on the rise in mainstream psychology, but applications in sport and exercise psychology research are scarce. In this article, the foundations of Bayesian analysis are introduced, and we will illustrate how to apply Bayesian structural equation modeling in a sport and exercise psychology setting. More specifically, we contrasted a confirmatory factor analysis on the Sport Motivation Scale II estimated with the most commonly used estimator, maximum likelihood, and a Bayesian approach with weakly informative priors for cross-loadings and correlated residuals. The results indicated that the model with Bayesian estimation and weakly informative priors provided a good fit to the data, whereas the model estimated with a maximum likelihood estimator did not produce a well-fitting model. The reasons for this discrepancy between maximum likelihood and Bayesian estimation are discussed as well as potential advantages and caveats with the Bayesian approach. © 2015 Human Kinetics, Inc.

Place, publisher, year, edition, pages
Champaign, IL: Human Kinetics, 2015
Keywords
Bayesian analysis, confirmatory factor analysis, informative priors, maximum likelihood, Sport Motivation Scale II
National Category
Psychology
Identifiers
urn:nbn:se:hh:diva-28392 (URN)10.1123/jsep.2014-0330 (DOI)000363091900005 ()26442771 (PubMedID)2-s2.0-84945902927 (Scopus ID)
Note

The first author was supported by grants from Umeå School of Sport Sciences and the Swedish National Centre for Research in Sports (CIF), grant number P2014-0043.

Available from: 2015-06-03 Created: 2015-06-03 Last updated: 2018-07-05Bibliographically approved

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