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Clothing functions and use of clothing to alter mood

Authors: Ju-Young M. Kang; Kim K.P. Johnson; Jieun Kim;

Clothing functions and use of clothing to alter mood

Abstract

The purpose of our study was to examine the antecedents to use of clothing to alter mood by identifying personality traits, social appearance anxiety, clothing in relation to self as structure (CSS), and clothing functions. Undergraduate women participated (n=310) in the study. Path analysis using structural equation modelling was used to test our hypothesised model. Perfectionism was related to social appearance anxiety and CSS. Neuroticism was related to social appearance anxiety. Individuals who experienced social appearance anxiety tended to select clothing for its ability to provide comfort, camouflage flaws in appearance, and provide assurance. Individuals who felt a close connection between clothing and the self (CSS) tended to select clothing for its ability to camouflage flaws in appearance and provide assurance, fashionability, and individuality. CSS in combination with the camouflage clothing function played the most important role in predicting the use of clothing to alter mood.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
21
Top 10%
Top 10%
Average
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