In plain language
Many people feel dissatisfied with how their bodies look—so many that researchers call it “normative discontent.” But some people manage to stay committed to what matters to them in life even while having negative thoughts about their bodies. This capacity is called body image flexibility, and it is usually measured with a 12-item questionnaire, the Body Image-Acceptance and Action Questionnaire (BI-AAQ). Long questionnaires are a burden in large studies and clinical settings, so this study set out to create a much shorter version without losing measurement quality.
The researchers used a fully automated machine-learning technique based on genetic algorithms—a method that mimics natural selection to find the best small subset of items—on data from an American community sample of 538 adults. The result was a 5-item short form, the BI-AAQ-5, which was then validated in an independent sample of 762 adults. The short form captured 96% of the variance in the original measure and showed a near-perfect correlation with it.
The BI-AAQ-5 behaved almost identically to the full scale in its relationships with body image dissatisfaction, stigma, internalization of societal appearance standards, self-compassion, and poor mental health. Importantly, body image flexibility predicted these outcomes even after accounting for body image dissatisfaction itself, showing that how people respond to body dissatisfaction matters over and above the dissatisfaction they feel. The BI-AAQ-5 offers researchers and clinicians a quick, valid alternative to the full measure.
Key findings
- A genetic-algorithm procedure reduced the 12-item BI-AAQ to a 5-item short form (BI-AAQ-5) that explained 96% of the variance in the original measure and correlated almost perfectly with it.
- In an independent validation sample of 762 American adults, the short and long forms showed comparable factor structure and near-identical correlations with body image dissatisfaction, stigma, internalization of thin and muscular appearance ideals, self-compassion, and poor mental health.
- Both versions of the BI-AAQ were uniquely associated with stigma, internalization of appearance norms, and self-compassion over and above body image dissatisfaction, gender, age, and BMI—evidence of discriminant validity.
- Model fit and explanatory power were virtually indistinguishable between forms (average differences in fit indices of .006-.008 and in variance explained of .006).
- Body image flexibility and body image dissatisfaction were strongly negatively correlated, yet each contributed uniquely, indicating they are related but distinct constructs.
- The study adds to evidence that genetic algorithms are a fast, fully automated, and effective method for abbreviating psychological questionnaires.
How to cite
APA
Basarkod, G., Sahdra, B., & Ciarrochi, J. (2017). Body Image-Acceptance and Action Questionnaire-5: An abbreviation using genetic algorithms. Behavior Therapy. https://doi.org/10.1016/j.beth.2017.09.006
BibTeX
@article{basarkod2017body,
author = {Basarkod, Geetanjali and Sahdra, Baljinder and Ciarrochi, Joseph},
title = {Body Image-Acceptance and Action Questionnaire-5: An abbreviation using genetic algorithms},
journal = {Behavior Therapy},
year = {2017},
doi = {10.1016/j.beth.2017.09.006}
}
Related work
- All publications by Joseph Ciarrochi (searchable, with free PDFs)
- Process-Based Therapy & Idionomic Analysis
Author: Joseph Ciarrochi (ORCID 0000-0003-0471-8100). Free copy hosted with permission for scholarly use. Please cite the published version via the DOI above.