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SCIENTIFIC LITERATURE · PPR

Using Bivariate Latent Growth Model to Better Understand the Anxiety Symptom in Parkinson's Patients

· 2024-10-14

DOI: 10.21203/rs.3.rs-4925629/v1

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Abstract Objective This study utilizes the Bivariate Latent Growth Model to explore the developmental trajectories of trait anxiety and state anxiety, as well as the interrelationships between the trait anxiety and state anxiety. Methods We obtained six-year follow-up data from 475 Parkinson's disease patients through the Parkinson's Progression Markers Initiative. We employed latent growth models to explore the trajectories of anxiety, trait anxiety, and state anxiety. Subsequently, we used the Bivariate Latent Growth Model to investigate the longitudinal relationships between state anxiety and trait anxiety. Results The trajectories of anxiety, trait anxiety, and state anxiety were best described by a linear growth model. The intercept and slope of each were significantly correlated with the intercept, and the variance of both intercepts and the correlation between them were all significant (P 

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