Evidence map›Paper›PMID 35261091›Full record

ArticleSkin 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)2022

Virtual approach of the aesthetical fit between hair colours and skin tones in women of different ethnical origin backgrounds.

Anthony Galliano, Myriam Guerin, Valerie Lambert, Ioanna Favrot, David Seneca, Fabien Lequeux, Frédéric Flament, Anna Sleurs, Berkly Foster, Edmund Phung and 2 more

Open access · hybridAbstract read
In one paragraph

Article in 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), 2022. 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
0.6field-weighted citation impact, top 31% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Observational
  2. Virtual approach of the aesthetical fit between hair colours and skin tones in women of different ethnical origin backgrounds.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) · 2022
    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

12 authors at 2 institutions in 2 countries.

Anthony GallianoL'Oréal Research and Innovation, Centre Charles Zviak, Saint-Ouen, France.
Myriam GuerinL'Oréal Research and Innovation, Centre Charles Zviak, Saint-Ouen, France.
Valerie LambertL'Oréal Research and Innovation, Centre Charles Zviak, Saint-Ouen, France.
Ioanna FavrotL'Oréal Research and Innovation, Centre Charles Zviak, Saint-Ouen, France.
David SenecaL'Oréal Research and Innovation, Centre Charles Zviak, Saint-Ouen, France.
Fabien LequeuxL'Oréal Research and Innovation, Centre Charles Zviak, Saint-Ouen, France.
Frédéric FlamentL'Oréal Research and Innovation, Centre Charles Zviak, Saint-Ouen, France.ORCID https://orcid.org/0000-0003-1128-9535
Anna SleursL'Oréal Paris, Centre Eugene Schueller, Clichy, France.
Berkly FosterModiFace Inc, Toronto, Canada.
Edmund PhungModiFace Inc, Toronto, Canada.
Kyung Moon LeeModiFace Inc, Toronto, Canada.
Jeff HoughtonModiFace Inc, Toronto, Canada.
L'Oréal (France) · FRMarch of Dimes Canada · CA

Funding

L'Oréal Research and Innovation Department
6 · The paper itself

Abstract

objectiveTo determine the aesthetical accordance between a given skin tone and the 11 possible colours of head hairs, covered by a marketed hair colouration product. MATERIAL AND

methodsThe photographs of professional top models, representing several ancestries (non-Hispanic European and Euro-American, East Asian, Hispanic Euro-American, and African-American ancestries), were used to virtually modify skin tones (from light, medium to dark) and hair colour by an artificial intelligence (AI)-based algorithm. Hence, 117 modified photographs were then assessed by five local panels of about 60 women each (one in China, one in France and three in US). The same questionnaire was given to the panels, written in their own language, asking which and how both skin tones and hair colours fit preferentially (or not appreciated), asking in addition the reasons of their choices, using fixed wordings.

resultsAnswers from the five panels differed according to origin or cultural aspects, although some agreements were found among both non-Hispanic European and Euro-American groups. The Hispanic American panel in US globally much appreciated darker hair tones (HTs). Two panels (East Asian in China and African American in US) and part of non-Hispanic European panel in France declared appreciating all HTs, almost irrespective with the skin tone (light, medium and dark). This surprising result is very likely caused by gradings (in %) that differ by too low values, making the establishment of a decisive or significant assessment. By nature highly subjective (culturally and/or fashion driven), the assessments should be more viewed as trends, an unavoidable limit of the present virtual approach. The latter offers nevertheless a full respect of ethical rules as such objective could hardly be conducted in vivo: applying 10 or 11 hair colourations on the same individual is an unthinkable option.

conclusionThe virtual approach developed in the present study that mixes two major facial coloured phenotypes seems at the crossroad of both genetic backgrounds and the secular desire of a modified appearance. Nonetheless, this methodology could afford, at the individual level in total confidentiality, a great help to subjects exposed to some facial skin disorders or afflictions.

Indexed as

Hair ColorSkin PigmentationArtificial IntelligenceAsian PeopleFemaleGenetic BackgroundHumansArtificial Intelligenceconsumer preferencesDiversity of skin toneshair colorInclusivity

Identifiers

PMID35261091
PMCPMC9907600
OpenAlexW4220847200

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.