ArticlePloS one2017
UV imaging reveals facial areas that are prone to skin cancer are disproportionately missed during sunscreen application.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed.
- Optimal sunscreen use, during a sun holiday with a very high ultraviolet index, allows vitamin D synthesis without sunburn.The British journal of dermatology · 2019Trial
- In vivo evaluation of sunscreen application by multispectral imaging: A new tool for educating sunscreen users.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) · 2023Article
- In search of the perfect tan: Chemical activity, biological effects, business considerations, and consumer implications of dihydroxyacetone sunless tanning products.Journal of cosmetic dermatology · 2023Review
- Assessing Sunscreen Protection Using UV Photography: Descriptive Study.JMIR dermatology · 2021Article
- Application of SPF moisturisers is inferior to sunscreens in coverage of facial and eyelid regions.PloS one · 2019Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Application of sunscreen is a widely used mechanism for protecting skin from the harmful effects of UV light. However, protection can only be achieved through effective application, and areas that are routinely missed are likely at increased risk of UV damage. Here we sought to determine if specific areas of the face are missed during routine sunscreen application, and whether provision of public health information is sufficient to improve coverage. To investigate this, 57 participants were imaged with a UV sensitive camera before and after sunscreen application: first visit; minimal pre-instruction, second visit; provided with a public health information statement. Images were scored using a custom automated image analysis process designed to identify areas of high UV reflectance, i.e. missed during sunscreen application, and analysed for 5% significance. Analyses revealed eyelid and periorbital regions to be disproportionately missed during routine sunscreen application (median 14% missed in eyelid region vs 7% in rest of face, p<0.01). Provision of health information caused a significant improvement in coverage to eyelid areas in general however, the medial canthal area was still frequently missed. These data reveal that a public health announcement-type intervention could be effective at improving coverage of high risk areas of the face, however high risk areas are likely to remain unprotected therefore other mechanisms of sun protection should be widely promoted such as UV blocking sunglasses.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.