Machine learning-enabled mental health risk prediction for youths with stressful life events: A modelling study.

Background: Youths face significant mental health challenges exacerbated by stressful life events, particularly in the context of the COVID-19 pandemic. Immature coping strategies can worsen mental health outcomes.

Methods: This study utilised a two-wave cross-sectional survey design with data collected from Chinese youth aged 14-25 years.

Changes of stressful life events, coping strategies and mental health among youths in the pre- and post-coronavirus 2019 pandemic era: A cross-sectional study.

Background: In the pandemic era, stressful life events (StressLEv) aggravated the impact on mental health. However, youths exhibited different responses to StressLEv because of diverse coping strategies, social support, and emotional intelligence before and after the pandemic.

Aims: To explore the changes in StressLEv and coping strategies before and after the coronavirus 2019 pandemic, as well as report the associations among mental health and related factors in a sample of Chinese youths experiencing the post-pandemic era.