Psychology research and behavior management · 2024
The Relationship Between Cognitive Emotion Regulation Strategy and Mental Health Among University Students During Public Health Emergency: A Network Analysis.
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Li Mengze, Jia Qiannan, Yuan Tifei, Zhang Lin, Wang Huizhong, Ward Jamie, Jin Yinchuan, Yang Qun
Аннотация
BACKGROUND: Public health emergencies pose threats to mental health, and cognitive emotional regulation can be a crucial coping strategy. This study explored the relationship between cognitive emotion regulation strategies and mental health among university students during the COVID-19 pandemic using network analysis.
METHODS: 1100 university students completed questionnaires assessing depression, anxiety, somatization, and cognitive emotion regulation strategies. Network analysis was conducted to identify network structures and bridge symptoms.
RESULTS: (1) In the depression network, the strongest edge is D1 (Little interest)-D2 (Feeling down), while D2 emerged as the node with the highest centrality. C1 (Self-blame), C8 (Catastrophizing), D6 (Feeling bad), and D9 (Suicide) are bridge symptoms. (2) In the anxiety network, A2 (Uncontrollable worrying)-A3 (Worrying too much) were identified as the strongest edge, and A2 exhibiting the highest centrality. C1 (Self-blame), C8 (Catastrophizing), and A6 (Easy annoyance) are bridge symptoms. (3) In the somatization network, the strongest edge is S14 (Fatigue)-S15 (Sleep disturbances) and S9 (Palpitations) exhibited the highest centrality. C1 (Self-blame), C3 (Rumination), C8 (Catastrophizing), S9 (Palpitations), and S14 (Fatigue) are bridge symptoms.
CONCLUSION: Self-blame and catastrophizing are important bridge symptoms for cognitive emotion regulation strategies and mental health networks, so cognitive behavioral therapy, focusing on self-blame and catastrophizing as intervention targets, could most effectively improve mental health during public health emergencies.
METHODS: 1100 university students completed questionnaires assessing depression, anxiety, somatization, and cognitive emotion regulation strategies. Network analysis was conducted to identify network structures and bridge symptoms.
RESULTS: (1) In the depression network, the strongest edge is D1 (Little interest)-D2 (Feeling down), while D2 emerged as the node with the highest centrality. C1 (Self-blame), C8 (Catastrophizing), D6 (Feeling bad), and D9 (Suicide) are bridge symptoms. (2) In the anxiety network, A2 (Uncontrollable worrying)-A3 (Worrying too much) were identified as the strongest edge, and A2 exhibiting the highest centrality. C1 (Self-blame), C8 (Catastrophizing), and A6 (Easy annoyance) are bridge symptoms. (3) In the somatization network, the strongest edge is S14 (Fatigue)-S15 (Sleep disturbances) and S9 (Palpitations) exhibited the highest centrality. C1 (Self-blame), C3 (Rumination), C8 (Catastrophizing), S9 (Palpitations), and S14 (Fatigue) are bridge symptoms.
CONCLUSION: Self-blame and catastrophizing are important bridge symptoms for cognitive emotion regulation strategies and mental health networks, so cognitive behavioral therapy, focusing on self-blame and catastrophizing as intervention targets, could most effectively improve mental health during public health emergencies.