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Systematic and Quantitative Comparisons of Diagnostic Areas
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Scientific Reports | (2021) 11:14451 | https://doi.org/10.1038/s41598-021-93865-7
www.nature.com/scientificreports/
should be interpreted with caution. While more research is needed into systematic and quantitative comparisons of diagnostic areas related to different body representations, our findings were largely consistent with more time- and effort-intensive methods such as eye tracking, offering up a relatively easy and cost-effective alternative.
Conclusion In the current study, we explored the relationship between real and perceived body size (hip width) when asked about one’s own abstract, ideal, and own concrete body using visual depictions of implicit body representations by means of a data-driven method. In the own concrete body condition only, which referred to the body participants thought looked most like the body they would choose for online clothes shopping, we observed a negative relationship between real and perceived hip width.
These results suggest that a relationship between real and perceived body measurements is only present when participants are asked to contextualize their body representations in a real-life environment. The inverse relationship, however, indicates that implicit offline full body representations, much like their explicit counterparts1–4, are not necessarily accurate. Furthermore, these implicit body representations were differently influenced by personality traits, attitudes towards body weight, and participants’ tendency to under- versus over-estimate their body size. Additionally, we did not observe a relationship between the three different body representations, suggesting that the implicit representation of one’s body size/shape in a practical context is not related to the own or ideal implicit body representation in abstract environments. These findings have clinical and practical implications, suggesting that the implicit mental rep- resentations of our own body depend on the situational context.
Material and methods Participants. Sample size was determined following a Bayesian approach using JASP111. Based on previous research26, we initially scheduled 40 participants, and planned to check the Bayes Factor (BF; prior based on a Cauchy distribution, default scale of 0.707, zero-centered) after data collection for this group of participants. If a stopping criterion had not been reached, we would repeat this procedure after every additional five partici- pants. The stopping criteria included: 1) the BF reached the threshold for moderate evidence to either support (BF10 < 1/3) or reject (BF10 > 3) the null hypothesis when correlating real with perceived hip width for all con- ditions (see below), 2) a maximum of 60 participants had been tested, 3) the end date (31/05/2020) had been reached. The experiment was terminated due to reaching the latter criterion.
55 adults (age in years: range = 18–26, M = 21.44, SD = 1.85), all female (to exclude gender differences112) and residing in Spain, participated in the study in exchange for a gift card of 10 euros. Participants were recruited through a local subject pool, consisting of adults taking part in research studies during the preceding year and who had agreed to be contacted to participate in future research studies. Real body measurements of all participants were available from previous studies, including weight, height, hip width, waist width, and chest width.
Only participants whose real body measurements were not obtained more than six months before the start of the current study were considered. The study was conducted in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and was granted ethical approval by the local ethics committee at Universidad Carlos III de Madrid. All participants provided informed written consent beforehand. BMI in our sample ranged from 17 to 30.7 (M = 21.83, SD = 3.00), with five participants classified as underweight (BMI < 18.5), 43 as normal weight (18.5 < BMI < 24.9), five as overweight (25 < BMI < 29.9), and two participants as obese (BMI > 30). Only including participants within the normal weight range category did not change the results.
Stimuli and apparatus. Stimuli for the reverse correlation task consisted of 400 pairs of randomly distorted images of bodies. These pairs of images were created using the ‘rcicr’ package in R69, which generates sinusoidal noise patterns that are superimposed on a base image. For each pair of images, a noise pattern and its inverted noise pattern are created, which distort the resulting images in perceptually opposing ways (as described in pre- vious research26). All images (including the base image) were 512 × 512 pixels in size.
The base image consisted of a 3D female body in a T-pose (see Fig. 6a) based on a large database of young Spanish women113 (10.141 women grouped into 10 ages ranges; measurements from the age group 20–24 years were used, which was the age group closest to the age range of the participants in the current study).
First, a set of average measurements was extracted from this study. The most important body measurements extracted were as follows: height = 161.3 cm, chest circumference = 88 cm, waist circumference = 77 cm, hips circumference = 96.9 cm. Second, we created an avatar using skinned multi-person linear parametric modeling (SMPL)114, which allows for the modification of several parameters that affect the pose (e.g. moving arms and legs) and shape of the avatar (e.g. modifying fatness and height).
Third, a 3D version of the measurements was created and attached to the surface of the parametric SMPL avatar, acting as body landmarks whose length changed accordingly when varying the shape parameters of the avatar.
For example, by increasing the parameters usually related to fatness, a corresponding enlargement of the most relevant measurement (in this case primarily around the waist) could be observed. A custom non-linear optimization algorithm was used to automatically detect the SMPL shape parameters that defined a 3D body with measurements that were most similar to the aforementioned target measurements of the ‘average Spanish young female’.
Using this method, the obtained 3D surface is a plausible estimation because the deformation space of the SMPL model is constrained to real humans, since it was learnt from variations of thousands of scanned bodies. We used the default SMPL pose values (T-pose) since it allows for the silhouette of the avatar to be observed from the front without any occlusions. The final result of this process was the closest 3D avatar mesh to the average Spanish female measurements set. To avoid bias produced by the presence of a face, the geometry in the face area was smoothed manually. Furthermore, the avatar material (matte) was chosen to avoid specular reflections. Finally, lightning was adjusted to create uniform
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Systematic and Quantitative Comparisons of Diagnostic Areas |
Systematic and Quantitative Comparisons of Diagnostic Areas