Evidence map›Paper›PMID 42806410›Full record

ArticleBMC psychology2026

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

Nader Salari, Seyed Hamidreza Hashemian, Amin Hosseinian-Far, Amirreza Fallahi, Pegah Heidarian, Shabnam Rasoulpoor, Masoud Mohammadi

Abstract readLetterComment
In one paragraph

Article in BMC psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Nader SalariDepartment of Biostatistics, School of Health, Kermanshah University of Medical Sciences, Kermanshah, Iran.
Seyed Hamidreza HashemianStudent Research Committee, Kermanshah University of Medical Sciences, Kermanshah, Iran.
Amin Hosseinian-FarDepartment of Business Analytics & Systems, University of Hertfordshire, Hatfield, AL10 9EU, UK.
Amirreza FallahiStudent Research Committee, Kermanshah University of Medical Sciences, Kermanshah, Iran.
Pegah HeidarianStudent Research Committee, Kermanshah University of Medical Sciences, Kermanshah, Iran.
Shabnam RasoulpoorDepartment of Nursing, School of Nursing and Midwifery, Urmia University of Medical Sciences, Nursing, Urmia, Iran.
Masoud MohammadiResearch Center for Social Determinants of Health, Jahrom University of Medical Sciences, Jahrom, Iran. Masoud.mohammadi1989@yahoo.com.ORCID 0000-0002-5722-8300

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Anxiety DisordersSelf ConceptHumansMeta-Analysis as TopicPrevalenceSystematic Reviews as TopicHeterogenicityImpostor PhenomenonMeta-analysisPrevalenceThresholds

Identifiers

PMID42806410
PMCPMC13621757

What OpenQuestion holds

Textmetadata
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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.