Research: Elite female athlete research: stop searching for the ‘magic P ’

Burden, Shill and Bishop 2021: DOI: 10.113/EP089884

In this editorial, the authors discuss the challenges of using traditional statistical measures when researching athletes, especially when the population is elite and female.

"Unfortunately, your findings are limited and lack power due to the small sample size"

A comment I have received MANY times when I am attempting to publish my research. Yes, I have a small sample size, because the sample I have chosen to investigate is small, e.g., elite athletes.

I was reminded of this short editorial by my PhD supervisor Dr Stacy Sims. I love that the authors advocate for more research looking into smaller sample sizes and case studies, observing changes in individuals rather than group means. As mentioned by the authors "…by their very nature, elite athletes are elite precisely because they are statistical outliers." For some, they are likely to be outside of the group average and the realms of the "95% confidence limits". It can be annoying when researchers are fixated on "p<0.05" to make any meaning of research findings.

This editorial poses great questions for future research. You can access the article (for free) by using the link below.

“In recent years, the call for a priority need for research in female athletes has grown louder (Bruinvels et al., 2017). Practitioners, coaches and athletes are crying out for more informed support. Certainly, there are signs of positive change, with a visible increase in female athlete specific publications. Yet, whilst the gap may be closing, it remains significant in elite populations where studies in elite female athletes remain limited. Studies in truly elite female athletes are often statistically underpowered and therefore not considered publication worthy, as peer-review feedback we and others have experienced has suggested. But isn't that the point? The elite population is a limited number – these are the top 5% performers of their sport – but if academia continues to work with a mindset that elite sport requires an evidence-based practice approach, then more often than not this means meeting the magic ‘P < 0.05′ or alternative statistical approval to be considered of publication value. Yet, by their very nature, elite athletes are elite precisely because they are statistical outliers. The nature of elite sport does not easily lend itself to traditional experimental design; the population is very small, and the characteristics of elite sport environments mean researchers have little room for manoeuvre when it comes to delivering interventions and requesting athlete time commitments. Yet, academia appears steadfast in the belief that change in practice still largely relies on published outcomes, which can only come in the form of a cohort study.”

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Read the remainder of the editorial here