Exploring the impact of co-experiencing stressor events for teens stress forecasting

Abstract

Nowadays increasingly severe psychological stress becomes a major threat to adolescents’ health development. Accurate and timely stress forecast is of great significance for understanding adolescents’ mental health status. State-of-the-art microblog-based stress prediction utilizes only explicit self expression and behavior as cues, which may suffer from the problem of data sparsity: what if the user performs not so actively in microblog? As teenagers with similar background exhibit similar coping mechanism under co-experiencing stressor events, in this paper, we try to leverage the intra-group impact of co-experiencing stressor events to supplement sparse individual stress series and thus help improve individual stress prediction. Jointly considering stress response details, posting habit and individual profile, we quantify teenagers’ stress coping similarity under co-experiencing stressors using K-medoids model and represent the impact of co-experiencing stressors. Afterward, a cluster-based NARX recurrent neural network is constructed to combine intra-group impact of co-experiencing stressor events and individual stress series for stress prediction. Experiments upon the real dataset of 124 high school students demonstrate the effectiveness of our forecasting model. It is also proved that leveraging the impact of co-experiencing stressors significantly improves individual stress prediction.