Prevalence and Factors Associated With Depression among School Going Adolescents in Bengaluru: A Cross-Sectional Study

Introduction:The period of adolescence involves a lot of emotional changes as it is a period of transition to adulthood demanding independence.Adolescents with depression are more likely to have anxiety, disruptive behavior disorder and substance abuse when compared to those who are not depressed. Objective: To estimate the prevalence of depression among school going adolescents.and to assess the factors associated with depression among them. Method: A cross-sectional study was conducted among school going adolescents aged 13-16 years in the urban field practice area of a Medical College. Depression was assessed using Beck’s depression inventory (BDI). Total 896 adolescents were included in this study. Single stage cluster sampling method was done in which schools were considered as clusters and students constituted the sampling units. Schools were selected by simple random sampling technique using lottery method. Results: In this study about 45.2% of the adolescents had depressive disorder, out of which mild depression was reported among 22.2% students, 12.4% moderately depressed and 10.6% severe depression. Factors like mother’s education, lack of communication by father and mother with their children, lack of needs satisfied by the fathers of the adolescents (61.9%), father’s role in adolescents’ life (62%) and domestic violence in family (69.7%) were some of the important reasons for developing depression among adolescents. Adolescent whose parents were having conflict (69.2%) were found be depressed when compared to those adolescents whose parents had no conflicts this difference was statistically significant (p<0.05). Conclusion: The prevalence of depression was found to be 45.2%. Finding of the study emphasizes the need for creating awareness about the early identification of behavioral changes leading to depression among adolescents by the parents and teachers. It is also important to emphasize to the parents on how their relationship and behavior towards the family affects the mental wellbeing of the adolescents

Video Player Using Action Recognition and Convolutional Neural Networks

The whole world, is embracing advanced technology in all areas of life. This is made possible by the interaction between human and Computers (i.e., Human Computer Interaction). In this paper, we are discussing a very innovative way in which this technology of human computer interaction is used to play and control videos. The programmed acknowledgment of human motions from camera pictures is an extremely intriguing point. This technology is now becoming more and more practical as it is being inbuilt into many commercial products. However, here we are dealing with a very different approach in which Convolutional Neural Network (CNN)is used to develop a gesture-controlled video player. The human gestures would be used to control actions likeplay, pause, volume up and volume down. Deep learning techniques can be used to solve the problems that arise in ‘computer vision’ whereas, the parallel nature of CNN, is used to deal with extraction of data sets from images control videos. Convolutional Neural Networks (CNNs) are a type of deep model that can act directly on the raw inputs and they play an important role in the field of Image Recognition and Classification