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Intelligence-based doping control planning improves testing effectiveness: Perspectives from a national anti-doping

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Anti-doping efforts show low violation rates, especially in elite sports. An intelligence-led approach to doping control significantly increases the detection of anti-doping rule violations (ADRVs).

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Area of Science:

  • Sports Science
  • Anti-Doping
  • Doping Control

Background:

  • Anti-doping programs aim to detect, deter, and prevent doping in sports.
  • Current testing strategies, primarily sample collection, face scrutiny for efficiency.
  • Understanding doping practices and optimizing testing is crucial for effective deterrence.

Purpose of the Study:

  • To evaluate 17 years of doping test statistics and Anti-Doping Rule Violations (ADRVs).
  • To analyze the effectiveness of different doping test strategies from a national anti-doping organization's perspective.
  • To identify factors associated with increased ADRVs.

Main Methods:

  • Analysis of 48,709 doping samples collected between 2003-2019.
  • Examination of 216 Anti-Doping Rule Violations (ADRVs) recorded.
  • Statistical comparison of sample collection numbers, ADRVs, and testing strategies.

Main Results:

  • An average sample-to-ADRV rate of 0.44% was observed.
  • Most ADRVs involved male athletes in national/recreational ball, team, or strength sports.
  • ADRVs were infrequent in elite athletes and high-risk sports, despite extensive testing.
  • ADRV numbers did not correlate with sample collection volume.
  • Intelligence-led testing planning was associated with a significant increase in ADRVs.

Conclusions:

  • Current doping control strategies may not be optimally efficient.
  • An intelligence-led approach to test planning is more effective in detecting ADRVs.
  • Anti-doping organizations should enhance target testing capabilities and adopt intelligence-driven strategies.