ArticleClinical, cosmetic and investigational dermatology2021
Aesthetic Delusions: An Investigation into the Role of Rapid Visual Adaptation in Aesthetic Practice.
Article in Clinical, cosmetic and investigational dermatology, 2021. 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
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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.
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Who cites it
5 citing papers in PubMed, 12 citations in OpenAlex.
- Facial Overfilled Syndrome: A Narrative Clinical Review.Clinical, cosmetic and investigational dermatology · 2026Review
- The Influence of Image Exposure Duration on Facial Perception-Why It Matters.Journal of cosmetic dermatology · 2025Article
- Beyond the Algorithm: A Perspective on Tackling Bias and Cultural Sensitivity in AI-Guided Aesthetic Standards for Cosmetic Surgery in the Middle East and North Africa (MENA) Region.Clinical, cosmetic and investigational dermatology · 2025Article
- Lip Augmentation with Soft Tissue Fillers: Social Media, Perceptual Adaptation, and Shifting Beauty Trends beyond Golden Standard Ideals.Plastic and reconstructive surgery. Global open · 2024Article
- About the Need for a More Adequate Way to Get an Understanding of the Experiencing of Aesthetic Items.Behavioral sciences (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo date, the process of adaptation in the setting of aesthetic medicine has not been investigated. The combination of complex advanced feedback in the current intense social media milieu, in conjunction with easily accessible and effective aesthetic treatments, has produced pockets of overtreated patients and over-zealous practitioners. We examine whether aesthetic assessments of attractiveness and what appears natural can be distorted by the cognitive process of adaptation.
methodsForty-eight female participants were exposed to photographs of female faces in whom lip fullness had been strongly under- or over-exaggerated, while remaining within the bounds of natural appearing lips. Before and after evaluation of the exaggerated images, participants were asked to rate an alternative set of faces in terms of attractiveness (reflecting direct assessment of effective beauty impression) and naturalness (reflecting indirect assessment of beauty norms). The evaluation set consisted of six base faces that had been digitally altered to create a systematically varying 11 step set of lip sizes from extremely thin, to the original version, to very full.
resultsSecond-order polynomial fits indicated clear shifts of the subjects' facial aesthetic assessments towards the specific lip fullness of the adaptors. In contrast, such adaptions were not found for ratings of face naturalness. In contrast to research demonstrating mathematical foundations and unchanging rules governing perceptions of beauty, we show that simple viewing of exaggerated feature morphologies can rapidly result in recalibration of a person's assessment of attractiveness.
conclusionThis paper provides evidence that facial attractiveness is fluid, and that there are psychological mechanisms that cause an aesthetic bias. Over-exposure to exaggerated features can lead to significant changes to a person's ideas of attractiveness.
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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.