Mental Health during Medical Transition in a US and Canadian Sample of Early Socially Transitioned Transgender Youth

Purpose: This study aimed to shed light on the mental health of a unique group of medically transitioning transgender adolescents: those who had made a binary social transition during childhood and who, in general, had not experienced substantial gender-incongruent puberty. Methods: Study participants were part of a broader longitudinal study comprising 3 groups: transgender youth, their cisgender siblings, and unrelated cisgender peers. Using multilevel models, we compared self-reported and parent-reported levels of anxiety and depressive symptoms among transgender youth at 3 stages: before youth had begun puberty blockers; after they had begun blockers; and after they had begun hormone therapy. We also compared age-based mental health trajectories in transgender and cisgender youth. Results: In this sample of transgender youth who sought and received gender-affirming medical care, participants experienced stable and relatively low levels of psychological distress across stages of medical transition and across time. There was one exception: transgender girls showed increased, followed by decreased, parent-reported depressive symptoms over time. In contrast, cisgender girls showed increases in internalizing symptomatology (with the exception of parent- reported anxiety) as they got older, and cisgender boys showed decreased self-reported anxiety and increased, followed by decreased, parent-reported depressive symptoms. By mid-adolescence, levels of anxiety and depressive symptoms among transgender girls and transgender boys generally fell between those of cisgender girls and cisgender boys. Discussion: Results demonstrate that transgender youth who are socially and medically supported in their gender identity can experience stable and positive mental health throughout the notoriously challenging developmental period of adolescence. (c) 2024 Society for Adolescent Health and Medicine. All rights are reserved, including those for text and data mining, AI training, and similar technologies.