HCI-ML Work In Wellbeing of Mental Health and Pilot Study to Detect Depression and Anxiety among Students during COVID

Abstract

Introduction: Suicidal thoughts and suicide cases are increasing amongst youth in the current COVID-19 pandemic situation. Depression and anxiety are common, disabling, and costly mental disorders. Interdisciplinary research efforts in the field of Human Computer Interaction (HCI) have increased dramatically in the mental health area. The literature survey is performed to find the role of HCI and Machine Learning (ML) in the wellbeing of mental health. HCI and ML need more adequacies in the development of online mental health interventions.

Aims: The pilot study to detect level of depression and anxiety along with relationship with each other, among engineering college students during COVID-19 pandemic situation and correlation with year of study.

Methods: Randomized controlled trial study using PHQ-9 and GAD-7 conducted in the early phase of COVID-19 pandemic situation. The statistical analysis is done using Excel and K-means algorithm.

Results: The study shows that second and third year engineering students are majorly in mild and moderate level of depression and anxiety during this pandemic situation.

Conclusions: There is a need to make mental health awareness amongst youth. The current pandemic situation shows the importance of online therapeutic intervention rather than face to face counselling and intervention. The HCI and ML research has major challenges in online therapeutic intervention starting from enrolling users in the program, minimum dropout rate, more engagement and highest accuracy.