Evidence map›Paper›PMID 32099724›Full record

ArticleJournal of sport and health science2020

Analysis of doping control test results in individual and team sports from 2003 to 2015.

Millán Aguilar-Navarro, Jesús Muñoz-Guerra, María Del Mar Plara, Juan Del Coso

Open access · diamondAbstract read
In one paragraph

Article in Journal of sport and health science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
7.4field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 22 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. The purpose and effectiveness of doping testing in sport.Frontiers in sports and active living · 2024
    Article
  6. Article
  7. Article
  8. Moral Identity and Attitudes towards Doping in Sport: Whether Perception of Fair Play Matters.International journal of environmental research and public health · 2021
    Article
  9. Article
  10. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Millán Aguilar-NavarroExercise Physiology Laboratory, Camilo José Cela University, Madrid, 28692, Spain; Faculty of Education, Francisco de Vitoria University, Madrid, 28223, Spain.
Jesús Muñoz-GuerraDepartment for Doping Control, Spanish Agency for Health Protection in Sport, Madrid, 28016, Spain.
María Del Mar PlaraDepartment of Education, Spanish Agency for Health Protection in Sport, Madrid, 28016, Spain.
Juan Del CosoExercise Physiology Laboratory, Camilo José Cela University, Madrid, 28692, Spain. Electronic address: juan.delcoso@urjc.es.
Camilo José Cela University · ESUniversidad Francisco de Vitoria · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Determining the prevalence of doping in sport might be useful for anti-doping authorities to gauge the effectiveness of anti-doping policies implemented to prevent positive attitudes toward doping. Using questionnaires and personal interviews, previous investigations have found that the prevalence of doping might be different among different sports disciplines; however, there is no sport-specific information about the proportion of adverse and atypical findings (AAF) in samples used for doping control. The aim of the present investigation was to assess the differences in the frequency of adverse analytical and atypical findings among sports using the data made available by the World Anti-Doping Agency. Methods: The data included in this investigation were gathered from the Testing Figures Reports made available annually from 2003 to 2015 by the World Anti-Doping Agency. These Testing Figures Reports include information about the number of samples analyzed, the number of AAFs reported, and the most commonly found drugs in the urine and blood samples analyzed. A total of 1,347,213 samples were analyzed from the individual sports selected for this investigation, and 698,371 samples were analyzed for disciplines catalogued as team sports. Results: In individual sports, the highest proportions of AAF were 3.3% ± 1.0% in cycling, 3.0% ± 0.6% in weightlifting, and 2.9% ± 0.6% in boxing. In team sports, the highest proportions of AAF were 2.2% ± 0.5% in ice hockey, 2.0% ± 0.5% in rugby, and 2.0% ± 0.5% in basketball. Gymnastics and skating had the lowest proportions at (≤1.0%) for individual sports, and field hockey, volleyball and football had the lowest proportions for team sports (≤1.4%). Conclusion: As suggested by the analysis, the incidence of AAF was not uniform across all sports disciplines, with the different proportions pointing to an uneven use of banned substances depending on the sport. This information might be useful for increasing the strength and efficacy of anti-doping policies in those sports with the highest prevalence in the use of banned substances.

Indexed as

Team SportsBasketballBicyclingBoxingDoping in SportsFootballHockeyHumansIncidencePerformance-Enhancing SubstancesPrevalenceWeight LiftingPerformance-Enhancing SubstancesAnti-dopingAttitudeBanned drugsElite athleteType of sport

Identifiers

PMID32099724
PMCPMC7031807
OpenAlexW2961818911

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.