Mental disorders are common in athletes, but often go undiagnosed. Although mental health screenings are not routinely conducted in rugby, the Sport Concussion Assessment Tool – Fifth Edition (SCAT-5) is widely performed and measures affective, cognitive, sleep, and physical symptoms. This study investigated the psychometric properties of the SCAT-5 to explore its potential as a mental health screening tool. During preseason for the 2021 Western Province Super League A in South Africa, clinicians conducted mental health assessments of 71 adult male rugby union players. The SCAT-5 Symptom Evaluation, Baron Depression Screener for Athletes (BDSA), Athlete Psychological Strain Questionnaire (APSQ), Center for Epidemiologic Studies–Depression (CES-D), and Generalised Anxiety Disorder-7 (GAD-7) were compared to each other and to fully-structured diagnostic interviews by mental health professionals using the Mini International Neuropsychiatric Interview (MINI) 7.0.2. Lifetime MINI-defined mental disorders were common, being identified in 33.8% (95%CI 22.79 to 46.17%). Only 4.29% of these had a previous diagnosis. Exploratory Factor Analysis indicated a mental health construct of depression/anxiety being measured by the SCAT-5. The SCAT-5 had strong internal consistency ( = 0.94) and showed moderate convergent validity with the CES-D (r = 0.34; p = 0.008) and GAD-7 (r = 0.49; p < 0.0001). The area under the curve for identifying current disorders was 0.87 (p = 0.003). Since the SCAT-5 has the potential to identify depression and anxiety, it may allow mental health screening without the need for additional measures. Follow-up studies should further explore its discriminative ability in larger samples.
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/38207 |
Date | 31 July 2023 |
Creators | Burger, James |
Contributors | Joska, John, Andersen, Lena |
Publisher | Faculty of Health Sciences, Department of Psychiatry and Mental Health |
Source Sets | South African National ETD Portal |
Language | English |
Detected Language | English |
Type | Master Thesis, Masters, MMed |
Format | application/pdf |
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