Assessment of the representation of black, indigenous and people of colour in dermatology clinical practice guidelines

Pan, C.; Yang, Kevin; Nambudiri, Vinod E.

doi:10.1111/bjd.21273

Cited by 2 publications

(3 citation statements)

References 6 publications

(20 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the field of dermatology, skin color has long been recognized as a key component of the assessment, which is necessary to correctly diagnose dermatologic findings. 1 However, nursing, although progressing, still lacks in providing culturally aware and sensitive care in the appropriate assessment of patients with ranging variations of skin tone.…”

Section: Ethics and Equity In Neonatal Carementioning

confidence: 99%

“…The inclusion of differences in assessment findings for Black, Indigenous, and people of color (BIPOC) in the nurse physical assessment has long been ignored and misconceptions about how BIPOC people may present in a physical assessment are passed down from one nursing generation to another instead of being evidence-based. In the field of dermatology, skin color has long been recognized as a key component of the assessment, which is necessary to correctly diagnose dermatologic findings 1. However, nursing, although progressing, still lacks in providing culturally aware and sensitive care in the appropriate assessment of patients with ranging variations of skin tone.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Color Does Matter

Carter,

Newberry,

Leonard

2023

Advances in Neonatal Care

View full text Add to dashboard Cite

Background: The observation of color is an integral part of the nursing assessment. However, the current understanding of individual skin qualities and pigmentation has not yet been integrated thoroughly into foundational assessment courses, clinical education, simulation, and textbooks. Evidence Acquisition: Literature is scarce regarding racial groups, skin color, and physical assessment for patients across the lifespan, but even more so for the neonatal population. Historically, many nursing textbooks did not provide visual pictures or observational assessment strategies for the assessment of the Black, Indigenous, and people of color (BIPOC) population. This is improving in some nursing textbooks; however, the descriptors of and visual differences and anticipated assessment findings for the BIPOC population are not comprehensive. Results: Evidence-based assessment findings, which may occur in newborns with varying skin tones/pigmentations, are presented. Implications for Practice and Research: The most essential step to having an accurate assessment is acknowledging the importance of color awareness. Color blindness, while thought to support inclusivity, only contributes to exclusion of one of the most important components of a person's being—their color.

show abstract

Section: Ethics and Equity In Neonatal Carementioning

confidence: 99%

mentioning

confidence: 99%

Color Does Matter

Carter,

Newberry,

Leonard

2023

Advances in Neonatal Care

View full text Add to dashboard Cite

show abstract

“…Current article summarizes the data on bias in AI in the cosmetic skincare industry, as to the best of our knowledge, this topic has been poorly researched. This problem is particularly prevalent in dermatological and cosmetic literature, including dermatology textbooks, where a racial bias is reflected in the underrepresentation of images of minorities compared to the general population, which can lead to inequalities in skin health care [19,20]. In parallel, the skincare industry has focused its clinical testing mainly on pale or white skin, known as Fitzpatrick skin types I-III [21].…”

Section: Introductionmentioning

confidence: 99%

How artificial intelligence adopts human biases: the case of cosmetic skincare industry

Georgievskaya,

Tlyachev,

Danko

et al. 2023

AI Ethics

View full text Add to dashboard Cite

The cosmetic skincare industry is a growing market that extends to different regions and customer groups. In addition to scientific advances and technological developments, state-of-the-art digital approaches, including machine learning and other artificial intelligence (AI)-based techniques, are being applied at different stages of the value chain. The objectives of these efforts include optimizing the supply chain, developing high-quality, effective and safe products and personalization at every step of the customer journey. However, the use of digital technologies comes with risks and undesirable effects. These include a lack of transparency and accountability, compromised fairness and a general deficiency in data governance, all of which are critical at every customer touchpoint. This dark side of digital transformation is recognized by both businesses and governments. In this paper, we explain the concept of bias leading to unfairness for beauty technology applications. Based on published data we identified potential sources of AI bias in the cosmetic skincare industry and/or beauty tech. They were classified by the stage of the AI lifecycle: biases related to target setting, to acquisition and annotation, to modeling, to validation and evaluation, and to deployment and monitoring. We aim to create awareness of such phenomena among readers, whether executives, managers, developers or potential end-users.

show abstract

Assessment of the representation of black, indigenous and people of colour in dermatology clinical practice guidelines

Cited by 2 publications

References 6 publications

Color Does Matter

Color Does Matter

How artificial intelligence adopts human biases: the case of cosmetic skincare industry

Contact Info

Product

Resources

About