Exploring Doping Prevalence in Sport from Indirect Estimation Models: A Systematic Review and Meta-Bibliometric Analysis

Author:

Sagoe Dominic1ORCID,Cruyff Maarten2,Chegeni Razieh3,Veltmaat Annalena4,Kiss Anna5,Soós Sándor6,de Hon Olivier7,Heijden Peter van der2,Petróczi Andrea8

Affiliation:

1. Department of Psychosocial Science, University of Bergen, Bergen

2. Faculty of Social Sciences, Utrecht University, Utrecht

3. PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo

4. Department of Sport and Exercise Psychology, Institute of Sport and Exercise Sciences, University of Münster, Münster

5. Faculty of Education and Psychology, ELTE Eötvös Loránd University, Budapest

6. Department of Science Policy and Scientometrics, Hungarian Academy of Sciences (MTA), Budapest

7. Doping Authority Netherlands, Capelle aan den IJssel

8. School of Life Sciences, Pharmacy and Chemistry, Faculty of Health, Science, Social Care and Education, Kingston University, London

Abstract

Abstract Background To our knowledge, no previous systematic review and meta-analysis on doping prevalence in sport from Indirect Estimation Models (IEM) exists. We conducted a systematic review and meta-analysis complemented with a bibliometric analysis on empirical IEM-based studies of admitted doping prevalence in sport. Methods We conducted electronic database and ad hoc searches up to December 2023, estimated lifetime and past year prevalence rates, and conducted study quality/risk of bias as well as bibliometric analysis. Results Forty five studies were included in the review (meta-analysis: k = 33, bibliometric analysis: k = 22). The World Anti-Doping Agency’s definition of doping use was applied for data collection in most studies (k = 18) and doping prevalence was mostly assessed as past year/season (k = 20). Studies included in the meta-analysis were mostly conducted in Europe, particularly Germany (k = 10), and applied the Unrelated Question (k = 11) and Forced Response (k = 10) models. The lifetime prevalence rate of doping for competitive athletes was 22.5% (95% CI: 15.3–31.4, k = 10) and 17.2% (95% CI: 10.5–26.0, k = 4) for recreational sportspersons (t = -1.69, p = .100). Additionally, the past year prevalence rate of doping for competitive athletes was 14.3% (95% CI: 9.6–20.3, k = 14) and 10.3% (95% CI: 6.1–16.3, k = 7) for recreational sportspersons (t = -1.69, p = .100). Study participants were mostly multi-sport (k = 22) and competed at diverse levels. Additionally, majority of data (k = 27) were collected outside sport events. Most studies were evaluated as of moderate risk/quality (k = 17). Eight of the 17 journals where the prevalence estimation studies were published target sports readership. The mean normalized citation score is above the international average at 1.48 (range: 0.00–6.26), with two dominant but unconnected author communities. Conclusions One of six competitive athletes and recreational sportspersons in our sample of included studies admitted doping under IEM, exceeding the prevalence obtained via direct questioning and analytical testing. Despite their advantages, considerable internal variation in publication years and stable collaborations within the two identified communities of authors, IEM-based studies of doping prevalence require functional improvement.

Publisher

Research Square Platform LLC

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