Cornelissen, K. K., McCarty, K., Cornelissen, P. L. and Tovee, M. J. (2017) Body size estimation in women with anorexia nervosa and healthy controls using 3D avatars. Scientific Reports, 7 . p. 15773. ISSN 2045-2322
Full content URL: https://doi.org/10.1038/s41598-017-15339-z
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Cornelissen_et_al-2017-Scientific_Reports.pdf - Whole Document Available under License Creative Commons Attribution 4.0 International. 2MB |
Item Type: | Article |
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Item Status: | Live Archive |
Abstract
A core feature of anorexia nervosa is an over-estimation of body size. However, quantifying this over-estimation has been problematic as existing methodologies introduce a series of artefacts and inaccuracies in the stimuli used for judgements of body size. To overcome these problems, we have: (i) taken 3D scans of 15 women who have symptoms of anorexia (referred to henceforth as anorexia spectrum disorders, ANSD) and 15 healthy control women, (ii) used a 3D modelling package to build avatars from the scans, (iii) manipulated the body shapes of these avatars to reflect biometrically accurate, continuous changes in body mass index (BMI), (iv) used these personalized avatars as stimuli to allow the women to estimate their body size. The results show that women who are currently receiving treatment for ANSD show an over-estimation of body size which rapidly increases as their own BMI increases. By contrast, the women acting as healthy controls can accurately estimate their body size irrespective of their own BMI. This study demonstrates the viability of combining 3D scanning and CGI techniques to create personalised realistic avatars of individual patients to directly assess their body image perception.
Keywords: | Anorexia Nervosa, body size, body image, body estimation, body mass index, BMI |
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Subjects: | C Biological Sciences > C810 Applied Psychology C Biological Sciences > C800 Psychology C Biological Sciences > C850 Cognitive Psychology C Biological Sciences > C841 Health Psychology C Biological Sciences > C840 Clinical Psychology |
Divisions: | College of Social Science |
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ID Code: | 29648 |
Deposited On: | 20 Nov 2017 10:31 |
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