Beauty ideals modulate recognition of filtered images

IF 5.2 1区 心理学 Q1 PSYCHIATRY Body Image Pub Date : 2024-11-29 DOI:10.1016/j.bodyim.2024.101819
Ivonnia M. Flores Bravo , Gastón Saux I , Trinidad B. Speranza , Verónica C. Ramenzoni
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Abstract

Social media has affected how we relate to our body image. Digital makeovers have both reinforced existing beauty ideals and created new ones. This project investigated whether young adults’ recognition of image filters was associated by the beliefs of beauty ideals and gender. Participants completed a visual detection task (forced choice paradigm) where contrast filter correction was assessed for images of female and male bodies that were thin, average, or curvaceous/muscular. Results showed that people respond faster, and accuracy is higher when filters are applied to bodies that represent the historical beauty ideals: thin female bodies and muscular male bodies. These findings suggest that the perception of low-level image features is associated to fit the beliefs about beauty.
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美的理想调节了对过滤图像的识别
社交媒体影响了我们与自己身体形象的关系。数字化化妆既强化了现有的美丽理念,也创造了新的美丽理念。这个项目调查了年轻人对图像过滤器的识别是否与美丽理想和性别的信念有关。参与者完成了一项视觉检测任务(强迫选择范例),其中评估了女性和男性身体图像的对比度过滤器校正,这些图像是瘦的,平均的,或曲线/肌肉发达的。结果表明,当将过滤器应用于代表历史美的理想的身体(苗条的女性身体和肌肉发达的男性身体)时,人们的反应更快,准确性更高。这些发现表明,对低层次图像特征的感知与美的信念相吻合。
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来源期刊
Body Image
Body Image Multiple-
CiteScore
8.70
自引率
28.80%
发文量
174
期刊介绍: Body Image is an international, peer-reviewed journal that publishes high-quality, scientific articles on body image and human physical appearance. Body Image is a multi-faceted concept that refers to persons perceptions and attitudes about their own body, particularly but not exclusively its appearance. The journal invites contributions from a broad range of disciplines-psychological science, other social and behavioral sciences, and medical and health sciences. The journal publishes original research articles, brief research reports, theoretical and review papers, and science-based practitioner reports of interest. Dissertation abstracts are also published online, and the journal gives an annual award for the best doctoral dissertation in this field.
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