ArticleScientific reports2023
Exploring the influence of personal factors on physiological responses to mental imagery in sport.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Mapping the use of mental imagery for stress management in athletes: a scoping review.Frontiers in psychology · 2026Pooled it
- Mental imagery and stress: the mediating role of self-efficacy in competitive martial arts athletes.Frontiers in psychology · 2025Article
- Explicit Motor Imaging Abilities Are Similar in Complex Regional Pain Syndrome, Chronic Limb Pain and Healthy Individuals: A Cross-Sectional Study.Journal of pain research · 2025Article
- The benefits of guided imagery on athletic performance: a mixed-methods approach.Frontiers in psychology · 2025Article
- Psychophysiological strategies for enhancing performance through imagery-skin conductance level analysis in guided vs. self-produced imagery.Scientific reports · 2024Article
- Repetition and practice. Developing mental training with young violinists: a collaboration.Frontiers in psychology · 2024Article
- Developing and validating a Japanese version of the Plymouth Sensory Imagery Questionnaire.Frontiers in psychology · 2023Article
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Authors and funding
10 authors.
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Abstract
Imagery is a well-known technique in mental training which improves performance efficiency and influences physiological arousal. One of the biomarkers indicating the amount of physiological arousal is skin conductance level (SCL). The aim of our study is to understand how individual differences in personality (e.g. neuroticism), general imagery and situational sport anxiety are linked to arousal measuring with SCL in situational imagery. Thirty participants aged between 14 and 42 years (M = 22.93; SD = 5.24), with sport experience ranging between 2 and 20 years (M = 10.15; SD = 4.75), took part in our study. Participants listened to each previously recorded script and then were asked to imagine the scene for a minute. During the task SCL was monitored using the Biofeedback Expert 2000. Machine learning predictive models based on artificial neural networks have been trained for prediction of physiological response, as a function of selected psychological tests. We found an association among neuroticism, prestart anxiety, and general tendency to use imagery with SCL. From a practical point of view our results may help athletes, coaches, and psychologists to be more aware of the role of individual differences in sport.
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