Skip to main navigation Skip to search Skip to main content

Using virtual reality (VR) and eye-tracking to develop students' awareness of the influence of gender on attentional bias

Project: Research

Project Details

Description

Body dissatisfaction is associated with a host of negative health outcomes and problematic personal development. Body image has traditionally been gendered as a feminized concern, and as such the literature is dominated by studies on women; with little thought to the body image concerns of men and how these differ from women. Recent evidence suggests that body image issues emerge during adolescence and young adulthood (Nelson et al., 2018), with reports of negative body appraisals in children as young as six years (Murray & Touyz, 2012). The present study aims to raise awareness of the impact of negative body image among young men and women with the integration of virtual reality and eye-tracking to enhance and development psychology students’ knowledge and skills with psychological equipment whilst simultaneously raising awareness of the influence of gender on attentional bias in relation to body image. Students will receive eye-tracking and VR training before taking part in a body image workshop where students’ eye-movements will be recorded whilst viewing fashion images of men and women. Students will then be embodied into virtual avatars where further fixations will be examined. The proposed project will use VR and eye-tracking to examine gender differences in attentional bias providing students with direct knowledge and raising awareness of the impact of body image concerns. The proposed project also provides students with an opportunity to gain hands-on training and knowledge about utilisation of the eye-tracking device and VR system in empirical research to develop their own professional skill-base.
Project number6000722
Grant typeTDG(CityU)
StatusFinished
Effective start/end date1/06/20 → 30/05/22

Fingerprint

Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.