How Does Variation in the Body Composition of Both Stimuli and Participant Modulate Self-Estimates of Men's Body Size?

Allowed response time and estimated average body size influence visual body size estimates

Studies show that body size estimates exhibit a contraction bias wherein participants with a lower-than-average BMI overestimate their bodies while participants with a higher-than-average BMI underestimate. We attempted to replicate this effect and test its relationship to allowed response time and estimates of average body size. Neurotypical female Dutch participants (n = 277) estimated their body size using a forced-choice task, which we modified to modulate allowed response time, and a method-of-adjustment task. They also estimated the average body size (for their age and gender) and their ideal size. We found no direct evidence of a contraction bias in either task. However, estimates of average body size predicted misestimation of own body size (consistent with a contraction bias). Finally, we found that greater allowed response time caused greater body size overestimation amongst participants with higher BMIs (in our forced-choice task). Our results support the context-sensitive nature of the contraction bias and the influence of allowed response time on visual body size misestimation.

Testing the validity of online psychophysical measurement of body image perception

This body image study tests the viability of transferring a complex psychophysical paradigm from a controlled in-person laboratory task to an online environment. 172 female participants made online judgements about their own body size when viewing images of computer-generated female bodies presented in either in front-view or at 45-degrees in a method of adjustment (MOA) paradigm. The results of these judgements were then compared to the results of two laboratory-based studies (with 96 and 40 female participants respectively) to establish three key findings. Firstly, the results show that the accuracy of online and in-lab estimates of body size are comparable, secondly that the same patterns of visual biases in judgements are shown both in-lab and online, and thirdly online data shows the same view-orientation advantage in accuracy in body size judgements as the laboratory studies. Thus, this study suggests that that online sampling potentially represents a rapid and accurate way of collecting reliable complex behavioural and perceptual data from a more diverse range of participants than is normally sampled in laboratory-based studies. It also offers the potential for designing stratified sampling strategies to construct a truly representative sample of a target population.

The degree to which the cultural ideal is internalized predicts judgments of male and female physical attractiveness

We used attractiveness judgements as a proxy to visualize the ideal female and male body for male and female participants and investigated how individual differences in the internalization of cultural ideals influence these representations. In the first of two studies, male and female participants judged the attractiveness of 242 male and female computer-generated bodies which varied independently in muscle and adipose. This allowed us to map changes in attractiveness across the complete body composition space, revealing single peaks for the attractiveness of both men and women. In the second study, we asked our participants to choose the most attractive male and female bodies in a method of adjustment task in which they could independently vary muscle and adipose to create the most attractive body. We asked whether individual differences in internalization of cultural ideals, drive for muscularity, eating disorder symptomatology and depressive symptoms could systematically shift the location of peak attractiveness in body composition space. We found a clear preference by both genders for a male body with high muscle and low adipose, and a toned, low adipose female body. The degree of internalization of cultural ideals predicted large individual differences in the composition of the most attractive bodies.

EXPRESS: The Influence of Three-Dimensional Cues on Body Size Judgements

Research has shown that body size judgements are frequently biased, or inaccurate. Critically, judgement biases are further exaggerated for individuals with eating disorders, a finding that has been attributed to difficulties integrating body features into a perceptual whole. However, current understanding of which body features are integrated when judging body size is lacking. In this study, we examine whether individuals integrate three-dimensional (3D) cues to body volume when making body size judgements. Computer-generated body stimuli were presented in a 3D Virtual Reality (VR) environment. Participants (N = 412) were randomly assigned to one of two conditions: in one condition the to-be-judged body was displayed binocularly (containing 3D cues to body volume), in the other, bodies were presented monocularly (2D cues only). Across 150 trials, participants were required to make a body size judgement of a target female body from a third-person point of view using an unmarked visual analogue scale (VAS). It was found that 3D cues significantly influenced body size judgements. Namely, thin 3D bodies were judged smaller, and overweight 3D bodies were judged larger, than their 2D counterpart. Furthermore, to reconcile these effects, we present evidence that the two perceptual biases, regression to the mean and serial dependence, were reduced by the additional 3D feature information. Our findings increase our understanding of how body size is perceptually encoded and creates testable predictions for clinical populations exhibiting integration difficulties.

Beyond BMI for self-estimates of body size and shape: A new method for developing stimuli correctly calibrated for body composition

Accurate self-assessment of body shape and size plays a key role in the prevention, diagnosis, and treatment of both obesity and eating disorders. These chronic conditions cause significant health problems, reduced quality of life, and represent a major problem for health services. Variation in body shape depends on two aspects of composition: adiposity and muscularity. However, most self-assessment tools are unidimensional. They depict variation in adiposity only, typically quantified by the body mass index. This can lead to substantial, and clinically meaningful, errors in estimates of body shape and size. To solve this problem, we detail a method of creating biometrically valid body stimuli. We obtained high-resolution 3D body shape scans and composition measures from 397 volunteers (aged 18-45 years) and produced a statistical mapping between the two. This allowed us to create 3D computer-generated models of bodies, correctly calibrated for body composition (i.e., muscularity and adiposity). We show how these stimuli, whose shape changes are based on change in composition in two dimensions, can be used to match the body size and shape participants believe themselves to have, to the stimulus they see. We also show how multivariate multiple regression can be used to model shape change predicted by these 2D outcomes, so that participants' choices can be explained by their measured body composition together with other psychometric variables. Together, this approach should substantially improve the accuracy and precision with which self-assessments of body size and shape can be made in obese individuals and those suffering from eating disorders.