Objective: The aim of this study was to analyze the acceptable values of female and male smile attractiveness based on different amounts of gingival display and buccal corridor widths, as judged by dental professionals and laypersons.
Methods: The frontal smile photographs of a male and female model were modified to create seven different smile photographs of the same individual with different amounts of gingival display and buccal corridor widths. Overall, 249 evaluators in four groups (Group 1=orthodontists, Group 2=prosthodontists, Group 3=oral surgeons, and Group 4=laypersons) evaluated 28 images of different smiles with a visual analogue scale. Significant statistical differences were found among the evaluator's scores (p<0.05).
Results: For female smiles, the highest scores were obtained for 12% and 0% buccal corridor width. For male smiles, the highest scores were obtained for 4%, 0%, 12%, and 16% buccal corridor width for Groups 1, 2, 3, and 4 respectively. The highest scores were obtained for +2 mm and -3 mm of gingival display for female smiles.
Conclusion: The amount of gingival display, the buccal corridor width, and the knowledge in the field affects the perceptions of smile attractiveness. Thus, 3 mm of gingival display and buccal corridor width larger than 16% should be avoided for esthetic reasons during dental treatment.
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http://dx.doi.org/10.5152/TurkJOrthod.2017.17021 | DOI Listing |
Cureus
January 2025
Department of Orthodontics, School of Dental Sciences, University Sains Malaysia, Kota Bharu, MYS.
Background: Soft tissue specifications and facial values vary depending on the underlying skeletal structures. To achieve the ideal treatment result and patient satisfaction, one must know the attractive soft tissue specifications compatible with each type of malocclusion. This study aims to analyze the facial measurements that contribute to perceived facial attractiveness in patients with vertical growth patterns and skeletal class I malocclusion, focusing on gender-specific differences.
View Article and Find Full Text PDFJ Esthet Restor Dent
December 2024
Head Prosthodontics, Akademie für Orale Implantologie (Academy for Oral Implantology), Vienna, Austria.
Statement Of Problem: Esthetic dental features, especially the maxillary anterior teeth, significantly influence perceived attractiveness. Gingival recessions can negatively affect smile esthetics, particularly when asymmetrical.
Purpose: This study aimed to investigate the perception of dentists and non-professionals regarding subtle variations in the apically displaced soft tissue surrounding a lateral or central incisor.
Emotion
December 2024
Department of Psychology, Ben Gurion University of the Negev.
Dyadic affective processes are key determinants of romantic relationship quality. One such process termed emotional synchrony (i.e.
View Article and Find Full Text PDFJ R Soc N Z
February 2024
Discipline of Orthodontics, Faculty of Dentistry, University of Otago, Dunedin, New Zealand.
The desire for an attractive smile is a major reason people seek orthodontic and other forms of cosmetic dental treatment. An understanding of the features of a smile is important for dental diagnosis and treatment planning. The common methods of smile analysis rely on the visual analysis of smile aesthetics using posed photographs, and videos and gathering information about smiles through patient questionnaires and diaries.
View Article and Find Full Text PDFHeliyon
October 2024
Chungbuk National University, Department of Computer Engineering, Cheongju, 28644, South Korea.
Pre-trained chemical language models (CLMs) have attracted increasing attention within the domains of cheminformatics and bioinformatics, inspired by their remarkable success in the natural language processing (NLP) domain such as speech recognition, text analysis, translation, and other objectives associated with language. Furthermore, the vast amount of unlabeled data associated with chemical compounds or molecules has emerged as a crucial research focus, prompting the need for CLMs with reasoning capabilities over such data. Molecular graphs and molecular descriptors are the predominant approaches to representing molecules for property prediction in machine learning (ML).
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!