"My biggest learning curve:" an interpretive phenomenological analysis of coaches` experiences of working with athletes who experience a menstrual cycle
("Meine größte Lernkurve": eine interpretative phänomenologische Analyse der Erfahrungen von Trainern in der Arbeit mit Sportlerinnen, die einen Menstruationszyklus erleben)
The purpose of this interpretative phenomenological analysis was to describe and interpret coaches` experiences working with athletes who experience a menstrual cycle (MC). Participants included 15 high-performance coaches (11 women, 4 men) involved at the national or international level in a variety of winter and summer sports. Coaches participated in online, semi-structured one-on-one interviews. Data were analysed using an interpretative phenomenological analysis approach, and coaches` experiences are represented by four main themes: (a) `Make them feel safe` - facilitating a culture of trust, empathy, and support; (b) `It will be different` - recognising athletes` unique and personal experiences; (c) `Find strategies that allow them to participate` - managing training and performance; and (d) `Make it more normalised` - reducing stigma, barriers, and awkwardness. Our study advances MC-research in sport by highlighting the need to take athlete-centred approaches to understand athletes` unique MC experiences, as well as coaching-education and practices for progressing and supporting women athletes. In addition, we provide recommendations for future research and evidence-informed practices that can support athletes who experience a MC.
© Copyright 2025 Qualitative Research in Sport, Exercise and Health. Taylor & Francis. Alle Rechte vorbehalten.
| Schlagworte: | |
|---|---|
| Notationen: | Trainingswissenschaft Sozial- und Geisteswissenschaften |
| Veröffentlicht in: | Qualitative Research in Sport, Exercise and Health |
| Sprache: | Englisch |
| Veröffentlicht: |
2025
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| Online-Zugang: | https://doi.org/10.1080/2159676X.2025.2495012 |
| Jahrgang: | 17 |
| Heft: | 5 |
| Seiten: | 365-381 |
| Dokumentenarten: | Artikel |
| Level: | hoch |