Call to increase statistical collaboration in sports science, sport and exercise medicine and sports physiotherapy

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Author(s)
Sainani, Kristin L
Borg, David N
Caldwell, Aaron R
Butson, Michael L
Tenan, Matthew S
Vickers, Andrew J
Vigotsky, Andrew D
Warmenhoven, John
Nguyen, Robert
Lohse, Keith R
Knight, Emma J
Bargary, Norma
Griffith University Author(s)
Year published
2020
Metadata
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Statistical errors are common in many biomedical fields.1–5 We believe the nature and impact of these errors to be great enough in sports science and medicine to warrant special attention.6–14 Poor methodological and statistical practices have led to calls for change in other fields, such as psychology.15–18 We believe that a similar call to action is needed in sports science and medicine. Specifically, we see two pressing needs: (1) to increase collaboration between researchers and statisticians, and (2) to increase statistical training within the exercise science/medicine/physiotherapy (PT) discipline. Our call to action ...
View more >Statistical errors are common in many biomedical fields.1–5 We believe the nature and impact of these errors to be great enough in sports science and medicine to warrant special attention.6–14 Poor methodological and statistical practices have led to calls for change in other fields, such as psychology.15–18 We believe that a similar call to action is needed in sports science and medicine. Specifically, we see two pressing needs: (1) to increase collaboration between researchers and statisticians, and (2) to increase statistical training within the exercise science/medicine/physiotherapy (PT) discipline. Our call to action extends the work of those who have previously called for increased statistical collaboration in sports medicine and sports injury research.19–21 Though some academic sports science and medicine studies employ statisticians, such collaborations are an exception rather than the norm. To determine the extent of collaboration, we performed a systematic review of articles published in quartile one sports science journals in 2019 (see online supplementary file 1 for methods and online supplementary file 2 for data). The initial extraction included 8970 articles; of the 400 articles selected at random, 299 were deemed eligible and included in the review (figure 1). We found that only 13.3% (95% CI: 9.5% to 17.2%) of papers had at least one coauthor affiliated with a biostatistics, statistics, data science, data analytics, epidemiology, maths, computer science or economics department (figure 2). It should be noted that we included a broad set of methodological departments because we recognise that individuals from these fields may possess considerable statistical expertise. When we use the term ‘statistician’ in this paper, we broadly include individuals from other methods-focussed disciplines if they have extensive statistical training and experience.
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View more >Statistical errors are common in many biomedical fields.1–5 We believe the nature and impact of these errors to be great enough in sports science and medicine to warrant special attention.6–14 Poor methodological and statistical practices have led to calls for change in other fields, such as psychology.15–18 We believe that a similar call to action is needed in sports science and medicine. Specifically, we see two pressing needs: (1) to increase collaboration between researchers and statisticians, and (2) to increase statistical training within the exercise science/medicine/physiotherapy (PT) discipline. Our call to action extends the work of those who have previously called for increased statistical collaboration in sports medicine and sports injury research.19–21 Though some academic sports science and medicine studies employ statisticians, such collaborations are an exception rather than the norm. To determine the extent of collaboration, we performed a systematic review of articles published in quartile one sports science journals in 2019 (see online supplementary file 1 for methods and online supplementary file 2 for data). The initial extraction included 8970 articles; of the 400 articles selected at random, 299 were deemed eligible and included in the review (figure 1). We found that only 13.3% (95% CI: 9.5% to 17.2%) of papers had at least one coauthor affiliated with a biostatistics, statistics, data science, data analytics, epidemiology, maths, computer science or economics department (figure 2). It should be noted that we included a broad set of methodological departments because we recognise that individuals from these fields may possess considerable statistical expertise. When we use the term ‘statistician’ in this paper, we broadly include individuals from other methods-focussed disciplines if they have extensive statistical training and experience.
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Journal Title
British Journal of Sports Medicine
Copyright Statement
© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
Subject
Engineering
Medical and Health Sciences
Education