Evidence map›Paper›PMID 42647456›Full record

SynthesisPloS one2026

Global prevalence of impostor phenomenon in medical students: A systematic review and meta-analysis.

Víctor Juan Vera-Ponce, Christian Humberto Huaman-Vega, Fiorella E Zuzunaga-Montoya, César Iván Guerrero Uceda, Darwin A León-Figueroa, Oriana Rivera-Lozada, Edwin Aguirre-Milachay, Carmen Inés Gutierrez De Carrillo, Mario J Valladares-Garrido

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in PloS one, 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

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Víctor Juan Vera-PonceInstituto de Investigación de enfermedades Tropicales, Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas (UNTRM), Amazonas, Perú.
Christian Humberto Huaman-VegaInstituto de Investigación de enfermedades Tropicales, Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas (UNTRM), Amazonas, Perú.
Fiorella E Zuzunaga-MontoyaUniversidad Continental, Lima, Perú.
César Iván Guerrero UcedaEscuela de Medicina Humana, Universidad Señor de Sipán, Chiclayo, Peru.
Darwin A León-FigueroaUnidad de Posgrado y Especialización, Tecnologías Avanzadas para la Salud con enfoque en Inteligencia Artificial, Bioinformática y TIC, Universidad Peruana Cayetano Heredia, Lima, Peru.
Oriana Rivera-LozadaEscuela de Medicina Humana, Universidad Señor de Sipán, Chiclayo, Peru.
Edwin Aguirre-MilachayHospital Nacional Almanzor Aguinaga Asenjo, EsSalud, Chiclayo, Peru.
Carmen Inés Gutierrez De CarrilloInstituto de Investigación de enfermedades Tropicales, Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas (UNTRM), Amazonas, Perú.ORCID https://orcid.org/0000-0002-4711-7201
Mario J Valladares-GarridoEscuela de Medicina Humana, Universidad Señor de Sipán, Chiclayo, Peru.ORCID https://orcid.org/0000-0003-0839-2419

Funding

University of California Launching Future Leaders in Global Health Research Training ProgramD43TW009343 · FIC · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CRAIG R COHEN, Sung-Jae Lee · 2017 to 2026
$14.7M
FIC NIH HHS D43 TW009343
6 · The paper itself

Abstract

introductionImpostor phenomenon (IP) is a psychological phenomenon in which successful individuals fail to internalize their achievements and fear being exposed as "incompetent." Medical students may be particularly vulnerable to IP because medical training combines repeated high-stakes assessment, competitive peer comparison, hierarchical clinical supervision, and rapid professional identity transition, potentially affecting psychological well-being and academic performance.

objectiveTo estimate the global prevalence of IP in pre-licensure medical students and analyze differences by sex, academic stage, and geographic region.

methodsA systematic search was conducted in MEDLINE/PubMed, Scopus, Web of Science, and EMBASE, including studies published between January 1, 2000, and June 30, 2025. Observational studies reporting IP prevalence in pre-licensure medical students using validated instruments were selected. Pooled prevalences were calculated using random-effects meta-analysis, with subgroup analyses and meta-regression by publication year.

resultsThirty-five studies were included for qualitative synthesis, with 26 studies (n = 9,110 students) employing the Clance Impostor Phenomenon Scale (CIPS) included in the primary meta-analysis. The global CIPS-based prevalence was 54.2% (95% CI: 47.0%-61.3%) with high heterogeneity (I² = 98%). Studies using probabilistic sampling (n = 4) reported 36.5% prevalence, while non-probabilistic sampling (n = 22) yielded 57.5%. Prevalence was similar between women (50.5%) and men (47.1%), and between preclinical (48.9%) and clinical (46.8%) students. The highest rates were observed in the United Arab Emirates (89.5%), Canada (75.8%), and the United Kingdom (66.0%), while Peru presented the lowest estimate among CIPS studies (30.6%). Meta-regression showed no significant temporal trend from 2018-2024 (β = 0.0221, p = 0.1747).

conclusionsIP was frequent among pre-licensure medical students, although pooled estimates should be interpreted cautiously because heterogeneity was substantial and prevalence varied by sampling method and geographic context. These findings support the need for standardized measurement, probabilistic sampling when feasible, longitudinal research, and rigorously evaluated interventions addressing both individual coping and institutional educational practices.

Indexed as

Students, MedicalAnxiety DisordersFemaleHumansMalePrevalenceSelf Concept

Identifiers

PMID42647456
PMCPMC13514014

What OpenQuestion holds

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Registered trials

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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.