DigiMate: Leveraging Large Language Model AI in Geriatric Behavioral Obesity Control Therapy

Obesity is currently classified as a global epidemic that is a primary cause of cardiovascular and other diseases. According to the World Bank, obesity related factors are the second largest cause of mortality in the modern world. Among the primary causes of obesity, environmental factors like fast food consumption and sedentary lifestyle have been identified and the role of health coaches in promoting a healthy lifestyle is now medically established. Behavior modification therapy through guided and encouraging health coaching substantially aids in reducing obesity. Yet, due to costliness and logistical challenges, access to a human health coach is limited to the developed world and the physically agile population. In this project, I create DigiMate, a Web-based application that harnesses the power of large language models to provide digital health coaching customized to the user health requirements. Using a mathematical dynamic general equilibrium model based on lifetime utility maximization, I first trace how behavior modification therapy works through lowering the lifetime health cost of obesity. DigiMate works by utilizing ChatGPT to generate customized health messages based on user inputs to aid behavior modification. Randomized control trial on 63 seniors shows significantly reduced fast food consumption and increased exercise time for continuous DigiMate use for a period of 3 months for the target group as compared to the control group without DigiMate access.