Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
October 3, 2025Early Intervention in Psychiatry

Longitudinal Trajectories of Depression and Anxiety Among Chinese Adolescents in the Later Stage of the COVID‐19 Pandemic

View Full Paper
Ask AI
Bookmark
Share

Authors

HLHuolian LiXZXiangting ZhangLBLuowei Bu

Discussion

Loading...

Member takes

Overview

Longitudinal analysis shows three distinct trajectories of depression and anxiety among adolescents, indicating varied predictors.

Key Points

  • Three distinct trajectories of depression and anxiety were identified, highlighting significant variations among participants.
  • The resilience group had the highest prevalence, accounting for approximately 55.6% of participants, indicating a strong positive outcome.
  • Latent Growth Mixture Modelling was utilized to explore the various trajectories, with logistic regression identifying key predictors.
  • Individualized interventions are essential to address the different predictors for varying trajectories of mental health.

Cite This Study

Li et al. (2025) studied this question.

synapsesocial.com/papers/68e02f2cf0e39f13e7fa1dd8https://doi.org/10.1111/eip.70090
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Trajectories of Depressive Symptom Among College Students in China During the COVID‐19 Pandemic: Association With Suicidal Ideation and Insomnia Symptoms2025
  2. 2Trend of Chinese adolescent anxiety symptoms before and after <scp>COVID</scp>‐19: A cross‐temporal meta‐analysis with segmented regression2025 · 1 citations
  3. 3Adolescent Depressive Symptom Trajectories From Before to After the COVID-19 Pandemic2025 · 5 citations
  4. 4Anxiety and depressive symptoms of young children during the COVID-19 pandemic: Developmental trajectories and risk factors.2025 · 2 citations
  5. 5Mental health longitudinal trajectories and predictors in medical students: Latent growth mixture model analysis2025