労働者のメンタルヘルスを改善するための身体活動促進 : 深層学習を用いたモバイルヘルス介入

Abstract

There is clear scientific evidence that physical activity helps to prevent depression and anxiety. Utilizing mobile health (mHealth) technologies to enable physical activity is promising, but the evidence of the effectiveness of mHealth interventions on physical activity and mental health is inconsistent. We recently developed a native smartphone app to prevent depression and anxiety by promoting physical activity. One of the app's strengths is that it adopts a deep-learning model and automatically estimates psychological distress from users' physical activity patterns. We conducted a single-arm, 1-month feasibility trial to examine the implementation of the app and its effectiveness in promoting physical activity and improving depression and anxiety. As a result, we did not observe any significant improvement in physical activity or psychological distress. For implementation aspects, the participants used the app less. The conclusion of the presentation is that mHealth interventions are promising for the improvement of physical activity and mental health among workers, but, at this stage, their effectiveness is unclear. There are challenges to be addressed, especially in implementation.