Abstract
Public awareness of the diversity of experiences of gender identities has climbed sharply. The specific issues
of those with gender dysphoria (GD) related to self-identity, body image, and medical interventions are
challenges for the 21st century, particularly given the high risk of suicide. Gender identity is tightly linked to
one’s bodily features, particularly readily observable sexual characteristics. For transgender and nonbinary
individuals with GD, the incongruence between their body associated with their birth-assigned sex – what they
see in the mirror before any treatment – and the internalized representation of their gender-identified body is a
key defining part of their experience and contributes to their dysphoria. Currently, no clinical or research tool
exists to capture and quantify the diverse experiences of one’s current body and one’s gender-identified body
(which may be distinct from their current body), across a range of gender identities. Measuring the internalized
representation of one’s body could be facilitated by technology to visually represent this on a three-dimensional
avatar. The technology needed to scan and analyze the human figure is now available and cost efficient. It is
now possible to scan individuals to create personalized 3D visualizations, or “avatars,” with which they can
interact on mobile and desktop devices to represent internal representation of their bodies. This can allow
individuals to see and manipulate their own 3D avatar with a high degree of flexibility. The goal of this project is
to create a novel, visually based digital tool to measure, understand, and quantify individuals’ experiences of
their bodies. We will develop, validate, and test in transgender, nonbinary, and cisgender adults a personalized
avatar tool to represent internalized gender-identified bodies in order to quantify incongruence between this
and one’s current body. This tool – “GD Somatomap” – will be an advancement over existing self-report
questionnaires to capture visual representations of internalized body image, cross-sectionally and dynamically
over time. It will be flexible enough to characterize the heterogenous experiences of a range of gender
identities including binary transgender, gender fluid, nonbinary, and cisgender. It can be used in clinical and
clinical research applications to track outcomes of cross-hormone and gender-affirming surgical treatments. It
can potentially improve clinical outcomes by identifying specific sets of body parts as targets for treatments to
improve body congruence. Further, it will provide a unique means to measure own-body perceptual accuracy;
understanding differences in perceptual accuracy and what potentially modifiable factors contribute to this may
have prognostic significance for treatments to address body incongruence. It could also be used in future
studies to investigate functional and structural neurobiological correlates of body perception and internal body
representation, and at what point in neurodevelopment these emerge for those with different gender identities.
