Related Experiment Video
Updated: Jun 29, 2025

Objectively Assessing Sports Concussion Utilizing Visual Evoked Potentials
Published on: April 27, 2021
Functional Characteristics and Coping Strategies among Rugby Athletes: A Cluster Analysis Approach
Walter Sapuppo1,2, Davide Giacconi1, Vincenzo Monda3
1Department of Psychology, Sigmund Freud University Wien, 20143 Milan, Italy.
Abstract:
The developing domain of mental health in sports has gained much interest, acknowledging its pivotal role in athlete performance and well-being. The aim of this research is to provide a quantitative description concerning the levels of mental health, physical activity, cognitive fusion, cognitive flexibility, and coping strategies that characterize rugby athletes by using a data-driven approach. A total of 92 rugby athletes took part in this study and filled out a set of self-administered questionnaires. A correlational analysis showed that general well-being was positively associated with years spent playing rugby (r = 0.23) and coping mechanisms (r = 0.29). Athletes' well-being was also negatively correlated with cognitive inflexibility (r = -0.41) and cognitive fusion (r = -0.39). A k-means cluster analysis identified two unique groups: group 1, characterized by higher levels of psychological well-being, lower levels of physical activity, greater cognitive flexibility, improved coping techniques, and reduced cognitive fusion, and group 2, which exhibits opposite characteristics. The discrepancies observed in psychological characteristics such as coping strategies, cognitive fusion, and cognitive inflexibility highlight their potential impact on the general health of rugby players. To comprehend the complex interplay between psychological and physical elements in rugby athletes, long-term studies with larger samples are crucial.
Related Concept Videos
Coping Strategies: Problem Focused
For example, consider a student who struggles to understand their...
Coping Strategies: Emotion Focused
Robbers Cave
Comparing the Survival Analysis of Two or More Groups
Cluster Sampling Method
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
Coefficient of Correlation
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the...

