Abstract
Identification and Incidence of Mood Profile Clusters Among Sport Participants
Journal of Science and Medicine in Sport, Vol.22(Supplement 2), p.S100
ASICS Sports Medicine Australia Conference, 2019 (Sunshine Coast, Australia, 23-Oct-2019–26-Oct-2019)
2019
Abstract
Researchers show persistent interest in mood responses among athletes and exercisers. Mood profiling has often focused on antecedents and behavioural consequences associated with the iceberg (Morgan, 1980) and inverse iceberg profiles (Terry,1995). The iceberg profile (high vigour, low tension, depression, anger, fatigue, confusion) is associated with positive mental health and superior performance. The inverse iceberg profile (low vigour, high tension, depression, anger, fatigue, confusion) is associated with risk of psychopathology and used as a diagnostic criterion for overtraining syndrome. Four novel and theoretically meaningful mood profiles, termed the inverse Everest, shark fin, submerged, and surface profiles, were identified recently in the general population (Parsons-Smith, Terry, & Machin, 2017). In the present study, we investigated whether these six mood profiles are also evident in an athletic population.
Details
- Title
- Identification and Incidence of Mood Profile Clusters Among Sport Participants
- Authors
- Peter C Terry (Author) - University of Southern QueenslandRenee L Parsons-Smith (Author) - University of the Sunshine Coast
- Publication details
- Journal of Science and Medicine in Sport, Vol.22(Supplement 2), p.S100
- Conference details
- ASICS Sports Medicine Australia Conference, 2019 (Sunshine Coast, Australia, 23-Oct-2019–26-Oct-2019)
- Publisher
- Elsevier Australia
- Date published
- 2019
- DOI
- 10.1016/j.jsams.2019.08.129
- ISSN
- 1440-2440; 1440-2440
- Organisation Unit
- School of Social Sciences - Legacy; University of the Sunshine Coast, Queensland; School of Law and Society; School of Health and Behavioural Sciences - Legacy
- Language
- English
- Record Identifier
- 99451409002621
- Output Type
- Abstract
Metrics
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