Mental Toughness Explains Rowing Performance: A Mixed Model Analysis.

PURPOSE: In the quest to enhance rowing performance, coaches and athletes are seeking ways to gain acompetitive edge. One potential catalyst that has emerged in this pursuit is the concept of mental toughness(MT). Despite its potential significance, the sport of rowing has remained notably underrepresented in MTresearch, predominantly relying on cross-sectional study designs. Collegiate rowing, a sport demanding bothphysical and mental prowess, employs the 2 K time trial as a pivotal benchmark for evaluating rowers’performance. Therefore, the purpose of this study was whether MT is a significant factor in explaining 2Krowing performance utilizing a repeated subjects’ design. METHODS: Drawing from an observational andhypothesis-generating framework, a total of 12 Division II female collegiate rowers participated in this study.They completed the Mental Toughness Index (MTI) on four occasions preceding their respective 2 K time trials,integrated into their annual performance evaluation. Analysis employed a linear mixed model utilizing theGAMLj module in Jamovi version 2.4.8, with a significance level set at p < 0.05. MT was considered a fixedfactor, while athlete, MT, and Athlete*MT interaction served as random factors to account for possibleindividual variations. RESULTS: Analysis revealed three mixed models in which MT was found to besignificant and negatively related to 2 K performance: Model #1, MT with Athlete Intercept: F 1 = 7.58, p = 0.009, β = -0.93, 95%CI [-1.58, -0.27], p = 0.009; Model #2, MT with MT Intercept: F 1 = 5.88, p = 0.019, β = -0.98, 95%CI [-1.77, -0.19], p = 0.019; and Model #3, MT with Athlete and MT Intercept: F 1 = 5.34, p = 0.029,β = -0.81, 95%CI [-1.50, -0.12], p = 0.029. CONCLUSIONS: Collectively, these models demonstrate thesignificance of MT in explaining rowing performance, whether considered independently, accounting forathlete-specific differences, or factoring in the baseline level of MT. Findings suggest the potential practicalapplication of MT-oriented interventions within rowing. However, it is essential to acknowledge the study’ssmall sample size. Future investigations should explore larger participant cohorts and delve deeper into theimpact of MT interventions on the dynamics of rowing performance.

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Publication Details

Journal
Medicine & Science in Sports & Exercise
Published
2024-09-16
DOI
https://doi.org/10.1249/01.mss.0001055164.49475.86
Primary Topic
Personality Traits and Psychology
Type
article
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article

Mental Toughness Explains Rowing Performance: A Mixed Model Analysis.

Zacharias Papadakis, Claire Egret, Tal Amasay, Andreas Stamatis et al.
Medicine & Science in Sports & Exercise
Personality Traits and Psychology
article

Mental Toughness Explains Rowing Performance: A Mixed Model Analysis.

Zacharias Papadakis, Claire Egret, Tal Amasay, Andreas Stamatis, Samuel X. Norwood, Charlotte Armstrong
article en

Abstract

PURPOSE: In the quest to enhance rowing performance, coaches and athletes are seeking ways to gain acompetitive edge. One potential catalyst that has emerged in this pursuit is the concept of mental toughness(MT). Despite its potential significance, the sport of rowing has remained notably underrepresented in MTresearch, predominantly relying on cross-sectional study designs. Collegiate rowing, a sport demanding bothphysical and mental prowess, employs the 2 K time trial as a pivotal benchmark for evaluating rowers’performance. Therefore, the purpose of this study was whether MT is a significant factor in explaining 2Krowing performance utilizing a repeated subjects’ design. METHODS: Drawing from an observational andhypothesis-generating framework, a total of 12 Division II female collegiate rowers participated in this study.They completed the Mental Toughness Index (MTI) on four occasions preceding their respective 2 K time trials,integrated into their annual performance evaluation. Analysis employed a linear mixed model utilizing theGAMLj module in Jamovi version 2.4.8, with a significance level set at p < 0.05. MT was considered a fixedfactor, while athlete, MT, and Athlete*MT interaction served as random factors to account for possibleindividual variations. RESULTS: Analysis revealed three mixed models in which MT was found to besignificant and negatively related to 2 K performance: Model #1, MT with Athlete Intercept: F 1 = 7.58, p = 0.009, β = -0.93, 95%CI [-1.58, -0.27], p = 0.009; Model #2, MT with MT Intercept: F 1 = 5.88, p = 0.019, β = -0.98, 95%CI [-1.77, -0.19], p = 0.019; and Model #3, MT with Athlete and MT Intercept: F 1 = 5.34, p = 0.029,β = -0.81, 95%CI [-1.50, -0.12], p = 0.029. CONCLUSIONS: Collectively, these models demonstrate thesignificance of MT in explaining rowing performance, whether considered independently, accounting forathlete-specific differences, or factoring in the baseline level of MT. Findings suggest the potential practicalapplication of MT-oriented interventions within rowing. However, it is essential to acknowledge the study’ssmall sample size. Future investigations should explore larger participant cohorts and delve deeper into theimpact of MT interventions on the dynamics of rowing performance.

Medicine & Science in Sports & ExerciseVol. 56(10S)
University of Louisville (US), Barry University (US), Florida International University (US), Kentuckiana Pulmonary Associates (US)
Openalex Percentile: Top 78%
Personality Traits and Psychology
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