Literature DB >> 34256541

Anti-doping and other sport integrity challenges during the COVID-19 pandemic.

Giscard Lima1,2, Borja Muniz-Pardos3, Alexander Kolliari-Turner2, Blair Hamilton2,4, Fergus M Guppy2,4, Gerasimos Grivas5, Andrew Bosch6, Paolo Borrione1,7, Alessia DI Gianfrancesco1,7, Chiara Fossati1,7, Fabio Pigozzi8,7,9, Yannis Pitsiladis1,2,9.   

Abstract

The coronavirus disease (COVID-19) pandemic has had an unprecedent impact on the world of sport and society at large. Many of the challenges with respect to integrity previously facing competitive sport have been accentuated further during the pandemic. Threats to the integrity of sporting competition include traditional doping, issues of technological fairness, and integration of transgender and intersex athletes in elite sport. The enforced lull in competitive sport provides an unprecedented opportunity for stakeholders in sport to focus on unresolved integrity issues and develop and implement long-lasting solutions. There needs to be a concerted effort to focus on the many technological innovations accelerated by and perfected during COVID-19 that have enabled us to work from home, such as teaching students on-line, applications for medical advice, prescriptions and referrals, and treating patients in hospitals/care homes via video links and use these developments and innovations to enhance sport integrity and anti-doping procedures. Positive sports integrity actions will require a considered application of all such technology, as well as the inclusion of 'omics' technology, big data, bioinformatics and machine learning/artificial intelligence approaches to modernise sport. Applications include protecting the health of athletes, considered non-discriminative integration of athletes into elite sport, intelligent remote testing to improve the frequency of antidoping tests, detection windows, and the potential combination with omics technology to improve the tests' sensitivity and specificity in order to protect clean athletes and deter doping practices.

Entities:  

Year:  2021        PMID: 34256541     DOI: 10.23736/S0022-4707.21.12777-X

Source DB:  PubMed          Journal:  J Sports Med Phys Fitness        ISSN: 0022-4707            Impact factor:   1.637


  2 in total

1.  Mitigating Bias and Error in Machine Learning to Protect Sports Data.

Authors:  Jie Zhang; Jia Li
Journal:  Comput Intell Neurosci       Date:  2022-05-11

2.  The effects of the COVID-19 pandemic on the use of the performance-enhancing drugs.

Authors:  Francesca Negro; Annagiulia Di Trana; Susanna Marinelli
Journal:  Acta Biomed       Date:  2022-01-19
  2 in total

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