AI and Mental Health: Developing Predictive Models for Stress, Anxiety, and Depression

This study focuses on employing artificial intelligence (AI) in the diagnosis of mental health conditions including, stress, anxiety, and depression, under the quantitative approach. One hundred participants completed surveys through social media posts, and wore physical activity monitors as well as devices that recorded their heart rate and the quality and quantity of their sleep. For behavioural, textual and physiological data of the patients, we utilized machine learning techniques such as SVM and Random Forest. From the Rubrics perspective, the AI models achieved high forecast precision, indicating possible ways to detect and treat mental health disorders on time. Data privacy issues, ethical issues, and the ability to incorporate the apps in clinical practice were considered as the most important challenges. It is therefore clear that there is need for further improvement on the AI models as well as uptake of ethical issues to make the AI technique more responsible in enhancing mental health care.