Latent growth curve modeling for improvement of clinical symptoms on depression / 中华流行病学杂志

ABSTRACT

To explore the improvement of clinical symptoms after treatment on patients with depression under the latent growth curve modeling.514 patients were studied with Hamilton Depression Rating Scale for depression and nonlinear conditional.Latent growth curve modeling was constructed to assess the features of outcome growth trajectory and possible related influencing factors.Results indicated that the outcome measure showing nonlinear growth trajectory and rapid drop during the first follow-up period and then declining or leveling off for the rest of the observation period on symptoms of anxiety,cognitive disturbance,retardation,sleeping disorder and HAMD scores.The variances of both latent intercept and the slope growth factor were statistically significant,indicating they varied across individuals.Gender did not show significant effect on both the intercept and the slope growth factor for the six outcomes,while age had a significant positive effect on initial weight loss,sleep disorder and HAMD scores at the baseline (0.015,0.048 and 0.068,P＜0.05) survey.Marriage showed significant positive effect on intercept factor of anxiety symptoms (0.563,P＜0.05) but negative effect on slope growth factor (-0.244,P＜0.05) while family history had significant positive effect on intercept factor regarding retardation (0.471,P＜0.05).The level of received education had a significant negative effect on intercept factor of anxiety symptoms and HAMD scores (-0.424 and-0.914,P＜0.05).Latent growth curve models allowed the researchers to study the overall growth trajectory as well as the captured individual differences on these trajectories over time,that also provided a powerful tool for the analysis on longitudinal data.