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The gender-affirmative model of care has proven unsuccessful in many cases of gender dysphoria. There is a pressing need to continue research and develop and implement alternative models of care. Personalised models of care need to replace the standardised ones to reflect the unique nature of internal issues that exist within every individual. A holistic care model that includes Physical, Mental, Emotional, Social, and Spiritual (PMESS) aspects of a person’s wellbeing indicates an effective way forward. Such a multidimensional model enables a greater understanding of complex relationships between different factors and their effects on health and overall wellbeing. Empowered by intelligent technologies, such as data mining and Artificial Intelligence (AI), the PMESS model can systematically capture, analyse, and evaluate data across the multiple dimensions of the holistic model of care. It can help identify patterns within the data, generate useful insights, and support the development of effective prevention and personalized treatment strategies. The PMESS-AI model supports the collaboration between multiple stakeholders, and the machine learning aspects of it can usher in the discovery of new knowledge and breakthroughs in research.
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