STUDENT COMPANION: EARLY INTERVENTION SYSTEM FOR STUDENTS MENTAL HEALTH

Abstract

Pakistani students' mental health is in crisis. Students are under academic stress, Competition, expectations from family and society, and all this, while going through a cultural image. In countries where mental health care is highly stigmatized. The results are: untreated distress has led to student suicides across provinces. Current support is based on students They don't many of them, but they seek help themselves.  Our system recommends an AI based early intervention program, Student Companion, which can detect signs of mental health issues, challenges students face prior to entering crisis without the student being in crisis to make an initial move. It operates on the basis of a two parallel data source, using the multimodal approach. First, students fill in the completed and validated questionnaire. Second, the system analyzes live facial expressions to capture emotional cues that may not be captured in self-report, through their device camera. Combining both inputs creates a more complete picture of the student's psychological state. Finally, a customized report is created and assessed against psychologist criteria to determine the level of severity of the student's condition and to introduce the student to a virtual therapy assistant that can offer unique coping strategies and guidance. Student Companion is not meant to substitute clinical care. Rather, it plugs the gap between quiet misery and professional assistance creating a less intrusive, earlier mental health assistance. Technology is not a replacement to human care in this case, but rather a tool of making sure that more students receive the necessary assistance in a timely fashion before their situation worsens.

Keywords: Mental health, AI, Facial expression recognition, Early intervention, Pakistan, NLP