Evidence map›Paper›PMID 36149654›Full record

ArticleJAMA network open2022

Representation of Asian American Populations in Medical School Curricula.

Peter Sang Uk Park, Eda Algur, Sweta Narayan, William B Song, Matthew D Kearney, Jaya Aysola

Abstract read
In one paragraph

Article in JAMA network open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

6 authors.

Peter Sang Uk ParkPerelman School of Medicine, University of Pennsylvania, Philadelphia.
Eda AlgurPerelman School of Medicine, University of Pennsylvania, Philadelphia.
Sweta NarayanPerelman School of Medicine, University of Pennsylvania, Philadelphia.
William B SongPerelman School of Medicine, University of Pennsylvania, Philadelphia.
Matthew D KearneyDepartment of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia.
Jaya AysolaPenn Medicine Center for Health Advancement, Perelman School of Medicine, University of Pennsylvania, Philadelphia.

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM007170 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI BRASS, LAWRENCE F · 1985 to 2022
$54.0M
NIGMS NIH HHS T32 GM007170
6 · The paper itself

Abstract

Importance: Despite being one of the fastest-growing populations in the US, the Asian American population is often misrepresented in and omitted from health research and policy debate. There is a current lack of understanding of how Asian American populations are portrayed in medical school curricula. Objective: To assess how Asian American populations and their subgroups are represented in medical school curricula. Design, Setting, and Participants: In this qualitative study, the content of 632 lectures from all 19 courses of the preclinical curriculum at a single US institution from the academic year 2020 to 2021 was analyzed to identify and characterize unique mentions of race and ethnicity as well as granular ethnicity. Among the 632 lectures, we identified 256 nonrepetitive, unique mentions of race and ethnicity or granular ethnicity. These unique mentions were coded and analyzed for emerging patterns of use. Main Outcomes and Measures: Study outcomes included (1) the frequency of specific racial and ethnic categories mentioned in the curriculum, (2) the relative proportion of mentions of race and ethnicity that involved or included Asian American data by courses and context, and (3) key themes representing emerging patterns found from qualitative analysis of curriculum content for mentions of Asian American populations or lack thereof. Results: Among the 632 lectures, 256 nonrepetitive mentions of race and ethnicity or granular ethnicity were identified; of these, Asian American populations and/or their subgroups were mentioned in 79 of the instances (30.9%). The most common terms used to denote Asian American populations were Asian, with 36 mentions (45.6%); followed by Japanese, with 10 mentions (12.7%); and Chinese, with 8 mentions (10.1%). Overall, there were 26 mentions (10.2%) of American Indian or Alaska Native populations, 12 mentions (4.7%) of Asian and Pacific Islander or Asian American and Pacific Islander populations, 67 mentions (26.2%) of Asian or Asian American populations, 143 mentions (55.9%) of Black or African American populations, 62 mentions (24.2%) of Hispanic or Latino populations, 4 mentions (1.6%) of Native Hawaiian or Pacific Islander populations, and 154 mentions (60.2%) of White populations. During the analysis of the curriculum for representation of Asian American populations, the following 5 key themes emerged from the data: (1) omission, (2) aggregation, (3) inconsistent categorization, (4) misidentification of granular ethnicity, and (5) association of race and ethnicity with disease. Conclusions and Relevance: This qualitative study suggests that the curriculum from a single US medical school largely mirrors the inappropriate use of race and ethnicity found in published health literature and clinical guidelines. Solutions with long-term results will require collaboration among diverse groups of interest to adopt inclusive research programs and design. Such solutions could better equip students in combating race-based medicine and could promote community outreach programs built based on trust.

Indexed as

AsianSchools, MedicalCurriculumEthnicityHispanic or LatinoHumans

Identifiers

PMID36149654
PMCPMC9508660

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.