Development and Validation of the Female Muscularity Scale View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-01

AUTHORS

Rachel F. Rodgers, Debra L. Franko, Meghan E. Lovering, Stephanie Luk, Wendy Pernal, Atsushi Matsumoto

ABSTRACT

Socially promoted physical appearance ideals for women place increasing importance on muscularity, resulting in growing muscularity concerns among traditional college-age women. To date, however, instruments for assessing the type of muscularity concerns reported by women are lacking. The aim of the present study was therefore to develop such a scale and examine its psychometric properties among a sample of young women. Findings from an exploratory factor analysis (n = 235) and a confirmatory factor analysis (n = 130) revealed a two-factor structure, including a five-item Attitudes subscale (α = .89) and a five-item Behaviors subscale (α = .90), which were moderately correlated, r = .50. In addition, the scale demonstrated good 2-week test-retest reliability (r = .76), and the subscales revealed moderate-to-large associations with body image concerns, drive for thinness, and exercise engagement, indicating concurrent validity. Thus the new Female Muscularity Scale is a useful and promising tool for assessing muscularity concerns among young women, and it may help toward understanding the role of pressures to achieve a toned body in the development of body image, eating, and exercise disorders. More... »

PAGES

18-26

Journal

TITLE

Sex Roles

ISSUE

1-2

VOLUME

78

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11199-017-0775-6

DOI

http://dx.doi.org/10.1007/s11199-017-0775-6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1085091040


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s11199-017-0775-6'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s11199-017-0775-6'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11199-017-0775-6'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11199-017-0775-6'


 

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