| dc.description.abstract | Garage2020 is planning to develop the G-Moji application for youngsters in youth care with the aim to improve their mental health. This app will be able to predict the mood of users by collecting passive (your location, phone status, charging) and active (social interaction, sleep, physical exercise) data. In order to develop this predictive app, 35 youngsters are testing a research app for three months. This research app is not able yet to predict the emotional state of the user. Everyday users are asked to choose an emoticon that suits their mood. This thesis is the result of a three-and-a-half month ethnographic research at Garage2020, answering the question How are risk and resilience related to the datafication of health experienced by users of the G-Moji app and approached by organisations providing this care? I interviewed 11 experts who are involved in the pilot and 10 youngsters who are receiving youth care or psychiatry and testing the research app. In my research I will reflect on the G-Moji app as well as mobile health applications in general. Since 2017, 325000 mobile health application where downloadable worldwide and this number is increasing every year. However, many of these apps are not scientific validated, might be unreliable and lack privacy policies. On the other hand, mobile health technologies have the potential to offer great opportunities, regarding to an increase of self-awareness and autonomy. Therefore, it is of great importance to examine resilience-based aspect and risk-based effects of mobile health technologies, in understanding their possible benefits and pitfalls. | |
