Gender-Affirming Care and Mental Health (GLOW) investigates the psychological, medical, and social factors that influence the outcomes of gender-affirming care, as well as its impact on mental health, work capacity, and quality of life. Gender dysphoria is defined as the incongruence of a person's experienced gender and sex assigned at birth. In Sweden, the prevalence of gender dysphoria has increased significantly in recent decades. Still there is no consensus on the long-term outcomes ofgender-affirming care. 1. What are the baseline characteristics in individuals seeking gender-affirming care and do any of these predict outcomes of gender-affirmative care?2. Do individuals with gender dysphoria experience improved or reduced quality of life, gender congruence, or functional capacity after gender-affirming care?3. Does gender-affirming care reduce or increase psychiatric symptoms and self-concept clarity?4. What are the effects of gender-affirming care on mortality, work capacity, and healthcare resource utilization as compared to an age and gender matched control group?Data and MethodGLOW targets patients at the Gender Dysphoria Clinic, Region Skåne and Linköping a National Highly Specialized Care unit (NHV). Mixed methods will be used to analyze data from national registries and self-reported assessments.The NHV status ensures standardized high-quality data collection and clinical follow-up, making this project a unique opportunity to evaluate the care given to individuals with gender dysphoria.Societal Relevance and Utility The growing demand for gender-affirming care underscores the need for research to identify the most effective interventions. The results may also help reduce stigma and improve social integration for individuals with genderdysphoria.GLOW is a longitudinal mixed-methods study based at the NHV Gender Dysphoria Clinic in Region Skåne. It includes registry-based, qualitative interviews and repeated self-report measures up to 5 years after baseline assessment. Quantitative analyses will include regression models and Bayesian methods.