TY - JOUR
T1 - Optimal Emotional Profiles for Peak Performance in Strength and Conditioning
AU - Cooper, Jonathan
AU - Johnson, Matt
AU - Radcliffe, Jon
AU - Fisher, James
PY - 2018/10/5
Y1 - 2018/10/5
N2 - This study investigated athletes’ performance-related emotions and emotional profiles for optimal performance in strength and conditioning (S&C). It is suggested that the identification and control of emotions associated with successful and unsuccessful performances are essential for achieving peak psychological states and optimal performance in sports-related tasks. The Individual Zone of Optimal Functioning (IZOF) model outlines an idiographic and comprehensive conceptual framework of interrelated dimensions that describe the structure and dynamics of subjective emotional experiences and performance-related psychobiological states. With institutional ethics approval, 13 competitive-elite athletes (male, n = 7; female, n = 6: mean age = 21.7 ± 4.0 years) completed IZOF-based emotion profiling, in which participants were asked to recall their perceived best and worst S&C session, outlining emotions and intensity within four global emotional categories. A significant difference was evidenced between best ever and worst ever performance within positive functional emotions (p < 0.001, d = 3.63) and negative dysfunctional emotions (p< 0.001, d = 4.92). Initial findings suggest that perceived peak performance states within S&C are associated with a high intensity of positive functional emotions (confident, motivated and energetic) and a low intensity of negative dysfunctional emotions (worn out, sluggish, annoyed and discouraged). Whilst future research is necessary to fully understand this area, the present data suggests that, in order to assist athletes in achieving perceived peak performance states within S&C, psychological skills and strategies should be informed and developed in collaboration with Sport Psychologists, with the aim of achieving an optimal emotional profile.
AB - This study investigated athletes’ performance-related emotions and emotional profiles for optimal performance in strength and conditioning (S&C). It is suggested that the identification and control of emotions associated with successful and unsuccessful performances are essential for achieving peak psychological states and optimal performance in sports-related tasks. The Individual Zone of Optimal Functioning (IZOF) model outlines an idiographic and comprehensive conceptual framework of interrelated dimensions that describe the structure and dynamics of subjective emotional experiences and performance-related psychobiological states. With institutional ethics approval, 13 competitive-elite athletes (male, n = 7; female, n = 6: mean age = 21.7 ± 4.0 years) completed IZOF-based emotion profiling, in which participants were asked to recall their perceived best and worst S&C session, outlining emotions and intensity within four global emotional categories. A significant difference was evidenced between best ever and worst ever performance within positive functional emotions (p < 0.001, d = 3.63) and negative dysfunctional emotions (p< 0.001, d = 4.92). Initial findings suggest that perceived peak performance states within S&C are associated with a high intensity of positive functional emotions (confident, motivated and energetic) and a low intensity of negative dysfunctional emotions (worn out, sluggish, annoyed and discouraged). Whilst future research is necessary to fully understand this area, the present data suggests that, in order to assist athletes in achieving perceived peak performance states within S&C, psychological skills and strategies should be informed and developed in collaboration with Sport Psychologists, with the aim of achieving an optimal emotional profile.
KW - IZOF Model
KW - Functional
KW - Dysfunctional
KW - Emotion
KW - Peak Performance State
U2 - 10.1519/JSC.0000000000002832
DO - 10.1519/JSC.0000000000002832
M3 - Article
SN - 1064-8011
JO - Journal of Strength and Conditioning Research
JF - Journal of Strength and Conditioning Research
ER -