ArticleCureus2023
Investigation of the Chemical Content and User Comments on Facial Cleansing Products.
Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed, 4 citations in OpenAlex.
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe goal of skin cleansing is to reduce sebum and exogenous pollutants and control the skin microbiome. Surfactants in cleansers dissolve hydrophobic substances in an aqueous phase and allow them to move away from the skin's surface. The negative effect of surfactants on the skin barrier can be reduced by changing the solution properties. As a dermatologist in the group of patients we encounter in our clinical dermatology practice who recommends face wash products, we thought of conducting this research in order to determine the product contents to identify the products with the highest user satisfaction so that we can easily make the selection of the right product and direct the patients correctly. MATERIALS AND
methodsWe planned to conduct cross-sectional research. Ten facial cleansing products sold on the most popular website that sells dermo-cosmetic products online in our country were selected. In the selection of the website, the criterion of having the most Internet traffic was sought. Internet traffic data was obtained from www.similarweb.com. The classification of the identified key ingredients according to their chemical properties was used on https://cosmeticanalysis.com. Reviews for each of the ten products in total were examined from the most recent date to the oldest.
resultsWe detected 87 different chemicals in ten different products. These basically consisted of surfactants, emollients (moisturizers), emulsifiers (cleansers), buffering (denaturators), herbal ingredients-antioxidants, solvents, and moisturizers. A total of 30 different surfactants were identified as the main cleaning ingredient in the examined products. Counterfeit product reporting was especially high on expensive products. No correlation was found between the number of surfactants in the products and the positive effects, such as cleansing and acne reduction and increase, and the negative effects, such as dryness, redness, burning, and smoothing/softening (p>0.05). There was a negative correlation between the cleansing effect of the products and the improvement and worsening of acne (p<0.05, p<0.001, respectively).
conclusionThe bottom line is that a good facial cleansing product doesn't have to contain a lot of chemicals and surfactants. It should be kept in mind that expensive products may be counterfeit and should question whether the product is original or not on the local product detection system from the barcode number.
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.