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http://hdl.handle.net/10362/182100
Title: | Self-representation of People with Disabilities on Instagram |
Author: | Mañas-Viniegra, L Llorente-Barroso, Carmen Ferreira, I Viñarás-Abad, M |
Keywords: | Body Image Disability Eye Tracking Neuroscience Self-representation |
Issue Date: | Mar-2024 |
Abstract: | The physical appearance of many people with disabilities leads them to feel stigmatised for not conforming to socially imposed ideals of beauty. These aesthetic standards convey lifestyles on Instagram that attract the attention of young audiences. In this regard, previous research has pointed out that people with disabilities also post self-representative images that are leading to new stereotypes of beauty with a potential impact on users without impairments. The aim of this research was to measure the attention and emotional intensity generated by a selection of posts on Instagram made by people with disabilities, in which they display their body image for aesthetic purposes, both in terms of beauty and fashion. Two neurocommunication techniques, eye tracking and galvanic skin response, were used on a sample of 120 Spanish and Portuguese university students who are regular Instagram users. The results indicate that young people without disabilities focus their attention on aspects of the image that clearly show a person’s disability, especially regarding specific features, yet there were no appreciable changes in emotional intensity. The findings also highlight the need to integrate heightened awareness and sensitivity regarding the image of people with disabilities by using a cross-curricular approach in the educational system in order to promote full inclusion |
Description: | UIDB/05021/2020 UIDP/05021/2020 |
Peer review: | yes |
URI: | http://hdl.handle.net/10362/182100 |
DOI: | https://doi.org/10.58262/V32I78.15 |
ISSN: | 1134-3478 |
Appears in Collections: | FCSH: ICNOVA - Artigos em revista nacional com arbitragem científica |
Files in This Item:
File | Description | Size | Format | |
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15-ID-115152_texto_final_Preprint-78.ING.pdf | 1,14 MB | Adobe PDF | View/Open |
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