Evidence map›Paper›PMID 41171831›Full record

ArticlePloS one2025

Homogenized and stigmatized: A discourse analysis of Asian sub-ethnic medical school aspirants.

Salman H Choudhry, Keegan D'Mello, George Kim, Robin Mackin, Amrit Kirpalani

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Salman H ChoudhrySchulich School of Medicine & Dentistry, Western University, London, Ontario, Canada.
Keegan D'MelloLawson Health Research Institute, London, Ontario, Canada.
George KimSchulich School of Medicine & Dentistry, Western University, London, Ontario, Canada.
Robin MackinSchulich School of Medicine & Dentistry, Western University, London, Ontario, Canada.
Amrit KirpalaniSchulich School of Medicine & Dentistry, Western University, London, Ontario, Canada.ORCID https://orcid.org/0000-0001-7567-9052

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The study examines the influence of Asian sub-ethnic identity on the experiences of pre-medical students in the United States and Canada, aiming to understand how early interactions with the medical education system shape their pursuit of medicine. The researchers analyzed 132 discussion threads from popular online premedical school forums between June 2018 and 2023. The Asian Critical Theory framework guided the analysis along with cyclical inductive coding. Two major themes emerged: the homogenization of diverse Asian sub-ethnicities and external pressure related to sociocultural values. Terms like "over-represented minorities" contributed to the perception of Asians as a monolithic group, while expressions such as "Asian Parents" highlighted unique familial expectations. Non-Asian users often dismissed these barriers, reinforcing the model minority myth. The study emphasizes the negative consequences of framing Asians as a homogenous group in medical school admissions policies, perpetuating stereotypes, and overlooking the diversity within Asian sub-ethnic communities. The term "overrepresented" is critiqued for its role in homogenizing Asian identities and undermining the complexity of their experiences. These findings highlight the need for greater recognition of the nuanced challenges faced by Asian sub-ethnic medical trainees and the importance of dismantling stereotypes in medical education.

Indexed as

AsianAsian PeopleSchools, MedicalStudents, MedicalCanadaFemaleHumansMaleStereotypingUnited States

Identifiers

PMID41171831
PMCPMC12578164

What OpenQuestion holds

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LicenceCC BY
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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.