Response to: Matters Arising from Salari et al. (2025): Why it is (currently) impossible to estimate accurate prevalence rates of the Impostor Phenomenon

The Impostor Phenomenon (IP) is conceptually a continuous construct on a spectrum, rather than a categorical or definitive diagnosis. Therefore, reference to its ‘prevalence’ in the epidemiological sense may seem to be conceptually incorrect. That said, this does not rule out threshold-based prevalence estimates. There are comparable constructs that are also on a continuum, yet thresholds are used to estimate prevalence. Instances of this include depression (PHQ-9), and anxiety (GAD-7), where empirically derived thresholds are used to provide estimates of prevalence. We would also like to emphasize that our article was a systematic review and meta-analysis. Systematic reviews and meta-analyses are studies that aim to synthesize existing evidence reported within original/primary studies in a specific field and produce a pooled estimate. In primary studies, the percentage or proportion (prevalence) of IP among health service providers was reported. We fully acknowledge that the current cut-offs for the Clance Impostor Phenomenon Scale (CIPS) are inconsistently applied in the existing literature and lack systematic validation. Demonstrating variability across arbitrary thresholds does not invalidate prevalence research and meta-analyses. The inconsistency in operationalization across the literature and not necessarily a flaw in the meta-analysis application. Meta-analysis allows us to quantify this problem and to highlight how different thresholds, samples, and instruments contribute to variance. Without such a synthesis, the field would lack a systematic appreciation of how widely prevalence estimates diverge.