Development and initial psychometric evaluation of the Body Image Matrix of Thinness and Muscularity - Female Bodies
Development and initial psychometric evaluation of the Body Image Matrix of Thinness and Muscularity - Female Bodies
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2020
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Journal of Eating Disorders ; 8 (2020). - 75. - BioMed Central. - eISSN 2050-2974
Abstract
Background
Despite evidence that thinness and muscularity are part of the female body ideal, there is not yet a reliable figure rating scale measuring the body image of women which includes both of these dimensions. To overcome this shortcoming, the Body Image Matrix of Thinness and Muscularity - Female Bodies (BIMTM-FB) was developed.
Methods
The objective of this study is to analyze the psychometric properties of this measure. Nā=ā607 non-clinical women and Nā=ā32 women with eating disorders answered the BIMTM-FB as well as instruments assessing eating disorder symptoms and body image disturbance in order to test the convergent validity of the BIMTM-FB. To assess test-retest reliability, a two-week interval was determined.
Results
The results indicated that the body-fat dimension of the BIMTM-FB correlates significantly with the Contour Drawing Rating-Scale, the Drive for Leanness Scale (DLS) and the Body Appreciation Scale, while the muscularity dimension of the BIMTM-FB was significantly associated with the DLS and the Drive for Muscularity Scale, proving the convergent validity of the BIMTM-FB. High coefficients of test-retest reliability were found. Moreover, the BIMTM-FB differentiated between the clinical sample and the non-clinical controls.
Conclusions
The BIMTM-FB is a figure rating scale assessing both thinness and muscularity as part of the female body ideal. Due to its high reliability and validity, the BIMTM-FB can be recommended in research and practice.
Despite evidence that thinness and muscularity are part of the female body ideal, there is not yet a reliable figure rating scale measuring the body image of women which includes both of these dimensions. To overcome this shortcoming, the Body Image Matrix of Thinness and Muscularity - Female Bodies (BIMTM-FB) was developed.
Methods
The objective of this study is to analyze the psychometric properties of this measure. Nā=ā607 non-clinical women and Nā=ā32 women with eating disorders answered the BIMTM-FB as well as instruments assessing eating disorder symptoms and body image disturbance in order to test the convergent validity of the BIMTM-FB. To assess test-retest reliability, a two-week interval was determined.
Results
The results indicated that the body-fat dimension of the BIMTM-FB correlates significantly with the Contour Drawing Rating-Scale, the Drive for Leanness Scale (DLS) and the Body Appreciation Scale, while the muscularity dimension of the BIMTM-FB was significantly associated with the DLS and the Drive for Muscularity Scale, proving the convergent validity of the BIMTM-FB. High coefficients of test-retest reliability were found. Moreover, the BIMTM-FB differentiated between the clinical sample and the non-clinical controls.
Conclusions
The BIMTM-FB is a figure rating scale assessing both thinness and muscularity as part of the female body ideal. Due to its high reliability and validity, the BIMTM-FB can be recommended in research and practice.
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Subject (DDC)
150 Psychology
Keywords
Body image, Body fat, Eating disorders, Figure rating scale, Women, Muscularity
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STEINFELD, Beate, Andrea S. HARTMANN, Manuel WALDORF, Silja VOCKS, 2020. Development and initial psychometric evaluation of the Body Image Matrix of Thinness and Muscularity - Female Bodies. In: Journal of Eating Disorders. BioMed Central. 8, 75. eISSN 2050-2974. Available under: doi: 10.1186/s40337-020-00345-wBibTex
@article{Steinfeld2020-12-01Devel-55263, year={2020}, doi={10.1186/s40337-020-00345-w}, title={Development and initial psychometric evaluation of the Body Image Matrix of Thinness and Muscularity - Female Bodies}, volume={8}, journal={Journal of Eating Disorders}, author={Steinfeld, Beate and Hartmann, Andrea S. and Waldorf, Manuel and Vocks, Silja}, note={Article Number: 75} }
RDF
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