Evidence map›Paper›PMID 41355359›Full record

ArticleJournal of genetic counseling2025

Representation of skin tone: The use of medical imagery in the genetic counseling profession.

Lawri Sanders, Karen Mary Davalos, Iman Kashmola-Perez, Ian M MacFarlane, Heewon Lee

Abstract read
In one paragraph

Article in Journal of genetic counseling, 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.

Lawri SandersDepartment of Genetics, Cell Biology, and Development, University of Minnesota, Minneapolis, Minnesota, USA.ORCID 0009-0004-3154-653X
Karen Mary DavalosDepartment of Chicano and Latinx Studies, University of Minnesota, Minneapolis, Minnesota, USA.ORCID 0009-0008-2471-547X
Iman Kashmola-PerezVariantyx, Inc, Framingham, Massachusetts, USA.ORCID 0009-0006-7862-4915
Ian M MacFarlaneDepartment of Genetics, Cell Biology, and Development, University of Minnesota, Minneapolis, Minnesota, USA.ORCID 0000-0002-0896-1952
Heewon LeeDepartment of Genetics, Cell Biology, and Development, University of Minnesota, Minneapolis, Minnesota, USA.ORCID 0000-0001-7930-8857

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The utilization of medical imagery featuring human bodies is a common practice in educational settings and patient interactions. However, these images predominantly depict white bodies and lighter skin tones, raising questions about their inclusivity and representation. This cross-sectional quantitative study addressed this gap by assessing the diversity of medical imagery in the genetic counseling field. Participants (n = 103) completed a 43-item survey where they responded to prompts about their experiences with medical imagery, depicting Black, Indigenous, People of Color (BIPOC) bodies and white bodies within their genetic counseling (GC) role, their genetic counseling program instructor role, and during their time as genetic counseling students. In their GC role, participants were significantly more likely to see (p < 0.001) and use (p = 0.02) white imagery compared to BIPOC imagery. In both their GC and instructor roles, participants found it more difficult to find BIPOC imagery (p < 0.001) and had to put more effort into finding it (p

Indexed as

Genetic CounselingSkin PigmentationAdultCross-Sectional StudiesFemaleHumansMaleSurveys and QuestionnairesDEIJdiverse imageryeducationgenetic counselingmedical imageryraceracismtextbook

Identifiers

PMID41355359
PMCPMC12683219

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.