Evidence map›Paper›PMID 34340596›Full record

ArticleJournal of cutaneous medicine and surgery

Novel Education Modules Addressing the Underrepresentation of Skin of Color in Dermatology Training.

Christa Slaught, Pamela Madu, Aileen Y Chang, Victoria L Williams, Masego B Kebaetse, Oathokwa Nkomazana, Onkabetse Julia Molefe-Baikai, Negussie A Bekele, Bernard Omech, Philip J Kellman and 2 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of cutaneous medicine and surgery. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.8field-weighted citation impact, top 24% of its field
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

8 citing papers in PubMed, 21 citations in OpenAlex.

  1. Health Implications of Colorism: A Narrative Review of the Literature.Journal of racial and ethnic health disparities · 2026
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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

12 authors at 8 institutions in 3 countries.

Christa Slaught78843 Department of Dermatology, Oregon Health and Sciences University, Portland, OR, USA.ORCID https://orcid.org/0000-0002-0757-9524
Pamela Madu12223 Department of Dermatology, Keck School of Medicine of University of Southern California, Los Angeles, CA, USA.
Aileen Y Chang8785 Department of Dermatology, University of California San Francisco School of Medicine, CA, USA.
Victoria L Williams14640 Botswana University of Pennsylvania Partnership, Gaborone, Botswana.
Masego B Kebaetse54547 Department of Medical Education, Faculty of Medicine, University of Botswana, Gaborone, Botswana.ORCID https://orcid.org/0000-0001-8987-7017
Oathokwa Nkomazana54547 Department of Surgery, Faculty of Medicine, University of Botswana, Gaborone, Botswana.
Onkabetse Julia Molefe-Baikai54547 Department of Internal Medicine, Faculty of Medicine, University of Botswana, Gaborone, Botswana.ORCID https://orcid.org/0000-0002-3371-4611
Negussie A Bekele54547 Department of Internal Medicine, Faculty of Medicine, University of Botswana, Gaborone, Botswana.
Bernard Omech487455 Faculty of Health Sciences, Lira University, Uganda.
Philip J Kellman8783 Department of Psychology, University of California, Los Angeles, CA, USA.
Sally Krasne12222 Department of Physiology, David Geffen School of Medicine, Los Angeles, CA, USA.
Carrie L Kovarik14640 Department of Dermatology, Perelman School of Medicine at the University of Pennsylvania, PA, USA.
University of Botswana · BWUniversity of California, Los Angeles · USLira Hospital · UGMerck & Co., Inc., Rahway, NJ, USA (United States) · USOregon Health & Science University · USUniversity of California, San Francisco · USUniversity of Pennsylvania · USUniversity of Southern California · US

Funding

Perceptual and Adaptive Learning in Cancer Image InterpretationR01CA236791 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI KELLMAN, PHILIP J · 2019 to 2022
$2.0M
NCI NIH HHS R01 CA236791
6 · The paper itself

Abstract

backgroundRepresentative images of pathology in patients with skin of color are lacking in most medical education resources. This particularly affects training in dermatology, which relies heavily on the use of images to teach pattern recognition. The presentation of skin pathology can vary greatly among different skin tones, and this lack of representation of dark skin phototypes challenges providers' abilities to provide quality care to patients of color.In Botswana and other countries in sub-Saharan Africa, this challenge is further compounded by limited resources and access to dermatologists. There is a need for improved and accessible educational resources to train medical students and local medical providers in basic skin lesion description and diagnosis.

objectivesWe examined whether online Perceptual and Adaptive Learning Modules (PALMs) composed of representative dark skin images could efficiently train University of Botswana medical students to more accurately describe and diagnose common skin conditions in their community.

methodsYear 4 and 5 medical students voluntarily completed PALMs that teach skin morphology, configuration, and distribution terminology and diagnosis of the most common dermatologic conditions in their community. Pre-tests, post-tests and delayed-tests assessed knowledge acquisition and retention.

resultsPALMs training produced statistically significant (

conclusionsOverall, population-specific PALMs are a useful tool for efficient development of pattern recognition in skin disease description and diagnosis.

Indexed as

DermatologyEducation, Medical, UndergraduateSkin DiseasesBotswanaCurriculumEthnic and Racial MinoritiesHumansacnedermatitisdermatologyHIVinfectious disease

Identifiers

PMID34340596
PMCPMC8742749
OpenAlexW3190348963

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.