Interpreting doping prevalence estimates generated through indirect estimation models
(IEMs) remains challenging for sport policy and governance due to the wide variation
in reported rates and methodological complexity. In this study, we combined a critical
appraisal of the methodological and epistemic developments of IEM applications to
doping prevalence with a bibliometric analysis of publication trends, citation patterns,
and collaboration networks, using a convergent parallel mixed-methods design. Across
52 records published between 2002 and 2026, this study maps the scientific landscape
of IEM-based doping prevalence research. Findings show that IEM-based prevalence research
is methodologically sophisticated yet institutionally dispersed and largely Eurocentric,
reflecting a field still consolidating its standards and disciplinary identity. Over
time, the focus has shifted from reporting prevalence rates to methodological critique
and re-analysis of existing datasets. Reported prevalence estimates, ranging from
0 to 57.1%, are highly sensitive to modelling assumptions about athlete behaviour
in complex survey environments. While this trend strengthens rigour, it also complicates
evidence synthesis for policy actors and risks undermining trust in IEM-based estimates
if poorly communicated. Anti-doping organisations and researchers should treat IEM-derived
prevalence as bounded indicators rather than definitive rates and integrate prevalence
evidence with contextual data for transparent policy and public communication.
