Related Experiment Video
Updated: May 8, 2026

11:18
Using the Threat Probability Task to Assess Anxiety and Fear During Uncertain and Certain Threat
Published on: September 12, 2014
The interrelationships between anxiety, motor performance and electromyography
1a Psychology Department Kinesiology Department , University of California , Los Angeles.
Journal of Motor Behavior
|August 23, 2013
Summary
High-anxious individuals exhibit poorer motor performance and less efficient neuromuscular energy expenditure compared to low-anxious individuals. This study differentiates between anxiety states and traits, focusing on movement quality over mere performance outcomes.
Area of Science:
- Psychology
- Neuroscience
- Kinesiology
Background:
- Anxiety research often conflates transitory (state) and stable (trait) anxiety.
- Focus on motor act outcomes overlooks the quality of movement and energy organization.
Purpose of the Study:
- To differentiate between state-anxiety and trait-anxiety subjects.
- To investigate qualitative differences in motor behavior using electromyography.
- To analyze the efficiency of neuromuscular energy expenditure in relation to anxiety levels.
Main Methods:
- State-Trait Anxiety Inventory administered to classify subjects.
- Electromyography (EMG) used to measure muscle activity and energy expenditure.
- Comparison of motor performance and energy use between high-anxious and low-anxious groups.
Main Results:
- High-anxious subjects demonstrated significantly poorer motor performance.
- High-anxious subjects exhibited increased energy expenditure before, during, and after motor tasks.
- Qualitative differences in movement patterns and energy organization were observed.
Conclusions:
- Distinguishing between state and trait anxiety is crucial for understanding anxiety's impact on motor behavior.
- Anxiety influences the efficiency of neuromuscular energy expenditure during motor acts.
- Future research should focus on movement quality and energy organization to better understand anxiety and motor behavior links.

