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Network Analysis of Competitive State Anxiety
Richard Mullen1, Eleri Sian Jones2
1Division of Sport, Health and Exercise Sciences, Brunel University London, London, United Kingdom.
Frontiers in Psychology
|January 28, 2021
Summary
This study re-examined competitive state anxiety in athletes using a network approach. Findings suggest network analysis effectively maps anxiety symptoms, aiding assessment and intervention strategies for sports performance.
Area of Science:
- Sports Psychology
- Psychometric Measurement
- Network Analysis
Background:
- Competitive state anxiety is crucial for sports performance, yet its measurement remains debated.
- Existing methods may not fully capture the complex interplay of anxiety symptoms.
- A network approach offers a novel perspective on understanding anxiety as a system.
Purpose of the Study:
- To apply network analysis to competitive state anxiety measurement in athletes.
- To explore the structure and interconnections of anxiety symptoms.
- To identify potential targets for improved assessment and intervention.
Main Methods:
- Utilized a dataset of 485 competitive athletes from the United Kingdom.
- Employed network analysis, including graphical LASSO, node predictability, and exploratory graph analysis.
- Reduced data to 15 items from the modified Three Factor Anxiety Inventory.
Main Results:
- A network structure of 15 anxiety-related items was estimated.
- Community detection identified three distinct symptom clusters.
- Several network nodes were found to bridge these communities, indicating interconnectedness.
Conclusions:
- Network analysis provides a valuable framework for understanding competitive state anxiety.
- The identified network structure and bridging nodes can inform more nuanced assessment strategies.
- This approach may lead to more effective, targeted interventions for athletes experiencing anxiety.
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