SynthesisSports medicine - open2026
Doping Prevalence in Sport from Indirect Estimation Models: A Systematic Review and Meta-analysis.
Synthesis in Sports medicine - open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed.
- Charting the Scientific Landscape of Indirect Estimation Models in Doping Prevalence Research: A Bibliometric Analysis with Narrative Appraisal.Sports (Basel, Switzerland) · 2026Review
- Health and Performance Challenges in the Era of Human Enhancement: Insights from Sport Medicine Professionals.Sports medicine (Auckland, N.Z.) · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo our knowledge, no previous systematic review and meta-analysis of doping prevalence in sport from indirect estimation models (IEM) exists.
objectiveTo conduct a systematic review and meta-analysis of empirical IEM-based studies of admitted doping prevalence in sport.
methodsWe conducted electronic database and ad hoc searches up to March 2025, and estimated lifetime and past year prevalence rates through a cross-classified model including prevalence (lifetime vs. past year), sample (competitive vs. recreational) and sports (multi-sport vs. single-sport) types.
resultsForty-six records (K) were included in the review (k [subset records included in the meta-analysis] = 30, n [independent studies from the records] = 34). 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 (k = 22) and applied the Unrelated Question (k = 8) and Forced Response with Cheater Detection (k = 6) models. Study participants were mostly multi-sport (k = 20) and competed at diverse levels, and most data (k = 28) was collected outside sport events. The corpus included articles that re-analysed existing data (k = 4). Lifetime prevalence was highest for multi-sport competitive athletes (22.6%) and lowest for single-sport competitive athletes (12.7%), whereas past year prevalence was highest for single-sport recreational sportspersons (15.5%) and lowest for multi-sport recreational sportspersons (8.7%).
conclusionsUnder IEM, about one of five multi-sport competitive athletes admitted to ever doping whereas about one of six of single-sport recreational sportspersons admitted to doping in the past year. Furthermore, multi-sport (vs. single-sport) competitive athletes show relatively higher doping prevalences, whereas single-sport (vs. multi-sport) recreational sportspersons report relatively higher doping prevalences. Secondary (re-)analysis presents a novel methodological challenge for meta-analyses. Registration PROSPERO: CRD42022373691.
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