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Exploring the symptom patterns of depression and anxiety among teachers during COVID-19: A latent profile analysis
Zekai Lu1, Rongqin Yuan2, Zelin Liu1
1Center for Brain and Cognitive Sciences, School of Education, Guangzhou University.
Objective:
The present study used the latent profile analysis (LPA) approach to explore the symptom patterns of depression and anxiety among Chinese teachers during COVID-19 and its relationship with fear of COVID-19 and suicidal ideation.
Method:
A sample of 6,121 teachers from primary and secondary schools in a district-level administrative unit in southern China was used. The LPA was employed to identify different symptom patterns of depression and anxiety. We subsequently used logistic regression to analyze the effects of demographic variables on the different profiles. The Bolck-Croon-Hagenaars method assessed the relationships between each profile and fear of COVID-19 and suicidal ideation.
Results:
The study identified five significant latent profiles and two subtypes in the moderate psychological disorder group. We also found that gender, professional title, and age significantly influenced the distribution of the profiles. The risk for both fear of COVID-19 and suicidal ideation was highest in the severe psychological disorder group. The high anxiety subtype had a significantly greater fear of the new coronavirus epidemic than the high depression subtype, which had a significantly higher level of suicidal ideation than the high anxiety subtype.
Conclusion:
The profiles we identified have distinct features that confirm their unique patterns of symptom endorsement. Our study may have important implications for early warning and intervention in teacher mental health. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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