ArticleSports (Basel, Switzerland)2026
"Every Woman Has a Different Cycle and Feels Differently": A Qualitative Study of Athlete-Centred Perspectives on Menstrual Cycle Symptoms and Management in Female Endurance Sports.
Article in Sports (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundAlthough menstrual cycle-based training has attracted increasing attention in endurance sports, research has predominantly focused on ergometric parameters. However, the subjective perspectives and lived realities of athletes remain relatively underexamined. Accordingly, this study aimed to explore performance perceptions and self-regulatory experiences of female endurance athletes within real-life training and competitive contexts.
methodsQualitative semi-structured interviews were conducted with twelve female endurance athletes (ages 18-42) across triathlon, running, swimming, cycling, and skiing. Data were analysed inductively using descriptive thematic analysis in MaxQDA.
resultsSix themes emerged related to menstrual cycle experiences: body awareness and cycle-related perceptions; the influence of expectations and self-efficacy on perceived performance; heterogeneous approaches to cycle-based training; training and recovery adjustments; the ambivalent role of digital tracking tools; and communication openness and barriers. Overall, cycle-based training was applied inconsistently and served more as a framework for interpreting physical symptoms than as a means of optimising performance.
conclusionsIn this sample of endurance athletes, cycle-related effects on performance and symptom perceptions were primarily shaped by biopsychosocial factors rather than physiological considerations alone. The menstrual cycle supported self-regulation, but rigid interpretations may risk reinforcing negative expectancies. These insights extend existing work by foregrounding athlete-centred, flexible approaches over deterministic training models.
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