Evidence map›Paper›PMID 41810254›Full record

ArticleHCA healthcare journal of medicine2026

The Efficacy of the Fitzpatrick Scale in Clinical Practice.

Dana Olsen, Cecilia Nguyen, Marshall Hall, Michael Carletti, Stephen E Weis

Abstract readEditorial
In one paragraph

Article in HCA healthcare journal of medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Demographic Reporting and the Absence of Hispanic/Latino Representation in Dermatology Artificial Intelligence: A Scoping Review.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2026
    Article
  2. Review
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.

Dana OlsenUniversity of North Texas Health Science Center, Fort Worth, Texas.
Cecilia NguyenUniversity of North Texas Health Science Center, Fort Worth, Texas.
Marshall HallUniversity of North Texas Health Science Center, Fort Worth, Texas.
Michael CarlettiUniversity of North Texas Health Science Center, Fort Worth, Texas.
Stephen E WeisUniversity of North Texas Health Science Center, Fort Worth, Texas.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Description Many skin diseases can manifest differently depending on the pigment of one's skin. The Fitzpatrick scale is a classification of phototypes (I-VI) that categorizes patients' skin based on its ability to tan and burn. Even though it is a simple questionnaire, the Fitzpatrick scale has numerous criticisms due to its dependence on patients' self-perception, variability in how questions are asked, limited range, and the underestimation of the risk of skin cancers. Alternatives to the Fitzpatrick scale include the melanin index, pigment protection factor, a visual color scale, and using artificial intelligence along with existing or new scales. Having a more accurate and precise tool to measure skin tone is imperative for research, education, and the patient care of individuals with diverse skin tones.

Indexed as

artificial intelligenceFitzpatrick scalephotodermatologyphototypingskin of colorsubjective classification

Identifiers

PMID41810254
PMCPMC12971093

What OpenQuestion holds

Textmetadata
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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.