Longitudinal relationships between cognitive emotion regulation strategies and depressive symptoms: a cross-lagged panel network analysis
1
School of Medicine, Xizang Minzu University, Xianyang, China
2
Clinical Medical Research Centre for Plateau Gastroenterological Disease of Xizang Autonomous Region, Xizang Minzu University, Xianyang, China
3
Key Laboratory of High-Altitude Hypoxia Environment and Life Health, Xizang Minzu University, Xianyang, China
Popul. Med. 2026;8(Supplement Supplement 1):A2202
ABSTRACT
INTRODUCTION:
Cognitive emotion regulation strategies (CERS) are significantly correlated with depressive symptoms, but much of the research on the relationship between depression and cognitive emotion regulation has focused on cross-sectional studies, where most of the focus has been on correlations and correlation coefficients between different cluster nodes only. There are relatively few longitudinal studies on the relationship between CERS and depressive symptoms. To explore the bidirectional dynamic association between the use of cognitive emotion regulation strategies (CERS) and depression, a cross-lagged panel network (CLPN) was used.
METHODS:
From June to December 2021, the cluster sampling method was applied to 3919 students from two universities in Xizang, China. The Chinese version of the Cognitive Emotion Regulation Questionnaire (CERQ-C) was used to collect information on the use of CERS, and the Patient Health Questionnaire-9 (PHQ-9) was used to assess the participants' depression symptoms.
RESULTS:
The strongest positive cross-lagged edge between depression and cognitive emotion regulation was guilt, which predicted self-blame, and the strongest negative cross-lagged edge between depression and cognitive emotion regulation was suicidal ideation, which predicted positive reappraisal. The CLPN centrality estimates across time and network clusters show that suicide has the greatest influence and lowest predictability and, put into perspective, has both lower influence and higher predictability.
CONCLUSIONS:
The nodes of the depression cluster have a greater influence on cognitive emotion regulation, supporting the scar theory of depression. These findings provide a basis for the improvement of college students' depression and the selection of cognitive emotional strategies.
Cognitive emotion regulation strategies (CERS) are significantly correlated with depressive symptoms, but much of the research on the relationship between depression and cognitive emotion regulation has focused on cross-sectional studies, where most of the focus has been on correlations and correlation coefficients between different cluster nodes only. There are relatively few longitudinal studies on the relationship between CERS and depressive symptoms. To explore the bidirectional dynamic association between the use of cognitive emotion regulation strategies (CERS) and depression, a cross-lagged panel network (CLPN) was used.
METHODS:
From June to December 2021, the cluster sampling method was applied to 3919 students from two universities in Xizang, China. The Chinese version of the Cognitive Emotion Regulation Questionnaire (CERQ-C) was used to collect information on the use of CERS, and the Patient Health Questionnaire-9 (PHQ-9) was used to assess the participants' depression symptoms.
RESULTS:
The strongest positive cross-lagged edge between depression and cognitive emotion regulation was guilt, which predicted self-blame, and the strongest negative cross-lagged edge between depression and cognitive emotion regulation was suicidal ideation, which predicted positive reappraisal. The CLPN centrality estimates across time and network clusters show that suicide has the greatest influence and lowest predictability and, put into perspective, has both lower influence and higher predictability.
CONCLUSIONS:
The nodes of the depression cluster have a greater influence on cognitive emotion regulation, supporting the scar theory of depression. These findings provide a basis for the improvement of college students' depression and the selection of cognitive emotional strategies.
| eISSN: | 2654-1459 |
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