Evidence map›Paper›PMID 41888934›Full record

ArticleSubstance abuse treatment, prevention, and policy2026

Performance-enhancing drug use in sports: a Bayesian variable selection and profile regression approach to identifying risk factors and estimating prevalence.

Zarina Vakhitova, Claudio Mezzetti, Clair Alston-Knox, Sophia Jowett, Daniel Rhind, Ching-Ying Lin, Po-Ching Huang, Matteo Vergani, Kerry O'Brien

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Article in Substance abuse treatment, prevention, and policy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Zarina VakhitovaSchool of Social Sciences, Monash University, 20 Chancellor's Walk, Melbourne, Victoria, 3800, Australia. zarina.vakhitova@monash.edu.
Claudio MezzettiSchool of Economics, University of Queensland, Sir Fred Schonell Drive, St Lucia, Queensland, 4072, Australia.
Clair Alston-KnoxPredictive Analytics Group, 440 Collins St., Melbourne, Victoria, 3000, Australia.
Sophia JowettSchool of Sports Sciences, Loughborough University, UK, Clyde Williams Building, Epinal Way, Loughborough, LE11 3TU, UK.
Daniel RhindSchool of Sports Sciences, Loughborough University, UK, Clyde Williams Building, Epinal Way, Loughborough, LE11 3TU, UK.
Ching-Ying LinDeakin University, 221 Burwood Highway, Burwood, Victoria, 3125, Australia.
Po-Ching HuangDepartment of Occupational Therapy, College of Medicine, National Cheng Kung University, 1 University Rd., Kaohsiung, 70101, Taiwan.
Matteo VerganiDeakin University, 221 Burwood Highway, Burwood, Victoria, 3125, Australia.
Kerry O'BrienSchool of Social Sciences, Monash University, 20 Chancellor's Walk, Melbourne, Victoria, 3800, Australia. kerrykez@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study has two objectives: (1) to identify the attitudinal and demographic factors most closely associated with performance-enhancing drugs (PED) use in sports; (2) to propose a new method for estimating PED use prevalence that mitigates the limitations of self-report surveys.

methodsWe analyse survey data from a sample of 2113 athletes attending ten UK universities, using a two-step approach. First, Bayesian Variable Selection (BVS) is used to identify the factors most closely associated with PED use. Second, these factors are incorporated into a Bayesian Profile Regression (BPR) model to identify clusters of athletes with similar attitudes toward PEDs. The prevalence of PED use is then estimated by linking these clusters with reported PED use via a logit model.

resultsFour key factors are significantly associated with PED use: being male, believing PED use is necessary to excel in sports, having a perceived estimate of PED use prevalence among elite athletes higher than the sample average, and having a perceived estimate of PED use prevalence among sportspeople in general higher than the sample average. BPR identifies four distinct clusters of athletes: (1) non-users; (2) use-admitters; (3) use-admitters and non-admitters; (4) most likely non-users. Using this new methodology, PED use prevalence is estimated at 13.7%, considerably higher than the 3.4% obtained through direct questioning.

conclusionThe proposed method identifies attitudinal and demographic factors associated with PED use and provides a more accurate estimate of its prevalence, which can inform the development of more effective anti-doping programmes.

Indexed as

AthletesDoping in SportsPerformance-Enhancing SubstancesAdultBayes TheoremFemaleHumansMalePrevalenceRisk FactorsSportsSurveys and QuestionnairesUnited KingdomYoung AdultPerformance-Enhancing SubstancesBayesian profile regressionBayesian variable selectionDoping in sportPerformance-enhancing drugsPrevalenceSelf-report surveys

Identifiers

PMID41888934
PMCPMC13019719

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LicenceCC BY-NC-ND
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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.