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Published on: July 19, 2017
Dynamic interactions among anxiety, emotional stability, and mindfulness: a cross-lagged panel network analysis
Yuntai Wang1,2, Jiangtao Han3, Yukun Mei1
1Xihua University, Chengdu, China.
Frontiers in Psychology
|August 5, 2026
Summary
Mindfulness techniques like thought acceptance and nonjudgmental awareness can reduce anxiety and improve emotional stability. This study reveals complex, item-level temporal links between these factors, supporting emotion regulation models.
Area of Science:
- Psychology
- Mental Health
- Neuroscience
Background:
- Anxiety is a prevalent global mental health issue, with increased incidence post-COVID-19.
- The process model of emotion regulation suggests mindfulness enhances emotional stability and reduces anxiety.
- Previous research on anxiety, emotional stability, and mindfulness often used cross-sectional designs, limiting understanding of dynamic relationships.
Purpose of the Study:
- To explore the longitudinal, item-level dynamic relationships between anxiety, emotional stability, and mindfulness.
- To construct network models illustrating the temporal interrelations of these constructs.
- To investigate predictive associations at an item level.
Main Methods:
- Data collected from 547 college students across three time points.
- Utilized a cross-lagged panel network (CLPN) approach for item-level temporal dynamics analysis.
- Developed network models to visualize interrelationships.
Main Results:
- Mindfulness items showed higher out-Expected Influence (OEI), while anxiety symptoms had stronger in-Expected Influence (IEI).
- Anxiety and emotional stability demonstrated the strongest bridge effects.
- Specific mindfulness components ('Thought Acceptance,' 'Nonjudgmental Awareness') significantly impacted anxiety and emotional stability, while anxiety symptoms negatively affected emotional stability.
Conclusions:
- This study provides the first item-level longitudinal analysis of anxiety, emotional stability, and mindfulness dynamics.
- Findings offer longitudinal support for the emotion regulation process model.
- Revealed complex temporal and predictive associations, highlighting specific mindfulness facets' impact.
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