Analysis of Anxiety and Depression in Gaming Individuals

摘要

Mental Health is very important and having a healthy state of mind is often ignored in today’s world. People have many ways they pass time when they are not working which may include following their Hobbies, reading a book or something just as simple as playing a game. Playing games is a good way to relieve stress but it may affect some people’s mental health adversely. This may happen by playing games for a long amount of time. Following paper focuses on applying machine learning techniques to predict anxiety and depression in individuals who play games. Towards this we conducted a survey in which major participants were students and included some responses from working professionals who practice gaming. Machine learning techniques were applied to train and test our models after pre-processing of data. To evaluate the accuracy of the trained models different parameters like Accuracy, F1 score, Mean Absolute Error(MAE) and Mean Squared Error(MSE). K- Nearest Neighbor (KNN) came up with the highest accuracy among all the models implemented. With these results we were able to predict anxiety and depression. With this people who play games can take necessary steps in order to prevent anxiety and depression.