ABSTRACT
【Objective】 To explore the dynamic change of depression in diabetic patients so as to provide evidence for early detection and warning of psychological problems in diabetic patients. 【Methods】 Based on the data from the China Health and Retirement Longitudinal Study （CHARLS）， the propensity score matching method was used to eliminate confounding factors in the study. The linear growth model， the nonlinear quadratic growth model， and the growth model without defined curve type were fitted respectively. According to the fitting indices of the models， the optimal solution of the growth function was determined to explore the changes of depression development in the diabetic patients. 【Results】 A total of 5 711 cases （5 380 cases in the non-diabetic group and 331 cases in the diabetic group） were included in the study. After propensity score matching， 1 621 cases （1 291 cases in the non-diabetic group and 330 cases in the diabetic group） were included and all confounding factors were balanced between the two groups. By fitting three growth curve models with latent variables， the results showed that the model without defined curve type was better than the other two models. The mean depression score for initial status in the non-diabetic and diabetic groups was 9.640 and 10.097， respectively， with significant inter-individual differences. During the follow-up period， the depression status of both groups showed a trend of decrease first and then increase， but the depression score was always lower in the non-diabetic group than in the diabetic group. At the same time， there was no individual difference in the rate of change between the two groups， and there was no statistical difference between the initial depression score and the subsequent slope of change. 【Conclusion】 Exploring the change track of depression status over time in diabetic patients， understanding the individual psychological change trend and further explaining the differences between individuals are of great significance for intervention on psychological status at different stages.
ABSTRACT
Objective@#To explore the development trajectories of quality of life and acceptance of disability of burn patients in the rehabilitation treatment stage and the influencing factors.@*Methods@#Totally 207 burn patients, including 157 males and 50 females, aged (40±13) years, who were in the rehabilitation treatment stage were selected by convenient sampling method from October 2016 to July 2017 in the Department of Burns of Fujian Medical University Union Hospital for this longitudinal study. At discharge and 1, 3, and 6 months after discharge, the patient′s quality of life and acceptance of disability were scored using the Burn Specific Health Scale-Brief and Chinese Version of Acceptance of Disability Scale-Revised respectively. Taking the intercept, the slope, and the curve slope as latent variables, the latent second growth curve model was constructed for the quality of life and the acceptance of disability. The robust maximum likelihood estimation (MLR) method was used to estimate the mean, the variance, and the covariance, so as to analyze the discharge level, the growth rate, the acceleration, and the correlation among them. Taking the acceptance of disability, the gender, the cause of burn, the severity of burn, the existence of complications, the payment way, and the education level as covariates, the latent second growth curve model was constructed for the quality of life. The MLR method was used to estimate the influence of covariates on the discharge level, the growth rate, and the acceleration of the quality of life.@*Results@#At discharge and 1, 3, and 6 months after discharge, the quality of life scores of patients were (102±36), (111±36), (118±37), and (122±37) points respectively, and the acceptance of disability scores were (73±17), (75±17), (77±17), and (78±18) points respectively. The estimated mean intercept of the quality of life and the acceptance of disability were 101.680 and 72.993 respectively at discharge, both of which showed a curve increasing trend in 1, 3, and 6 months after discharge (estimated mean slope=11.024, 3.086, t=15.376, 7.476, P<0.01), and the increasing rate (acceleration) gradually slowed down (estimated mean curve slope=-1.393, -0.426, t=-13.339, -4.776, P<0.01). There were significant individual differences in the discharge level and the acceleration of quality of life of patients (estimated intercept variance=1 174.527, t=9.332; estimated curve slope variance=2.379, t=6.402; P<0.01). There were significant individual differences in the discharge level, the growth rate, and the acceleration of patients′ acceptance of disability (estimated intercept variance=267.017, t=9.262; estimated slope variance=32.264, t=2.356; estimated curve slope variance=0.882, t=2.939; P<0.05 or P<0.01). There was no significant correlation among the discharge level, the growth rate, and the acceleration of the quality of life and those of the acceptance of disability of patients (estimated intercept and slope=37.273, -1.457, t=0.859, -0.131; estimated intercept and curve slope=-6.712, -0.573, t=-1.089, -0.248; estimated slope and curve slope=-5.494, -5.988, t=-0.930, -2.512; P>0.05). Among the time-constant covariates, only the severity of burn and the presence of complications had a significant impact on the quality of life of patients at discharge (estimated intercept=-10.721, 5.522, t=-6.229, 1.977, P<0.05 or P<0.01). At discharge and 1, 3, and 6 months after discharge, the level of acceptance of disability had a positive impact on the quality of life of patients (standardized regression coefficient=0.616, 0.669, 0.681, 0.678, t=18.874, 21.660, 22.824, 22.123, P<0.01).@*Conclusions@#The initial levels of quality of life and acceptance of disability of burn patients in the rehabilitation treatment stage are relatively low, both with a curve increasing trend over time, and the increasing rate gradually slows down. Patients with complications and serious burns have poor quality of life at discharge, while the acceptance of disability has a positive impact on the quality of life.
ABSTRACT
To compare two commonly used statistical approaches:the multilevel model and the latent growth curve model in analyzing longitudinal data. A longitudinal data set,obtained from the quality of life in patients with colorectal cancer after operation,was used to illustrate the similarities and differences between the two methods. Results from the study indicated that the latent growth curve modeling was equivalent to multilevel modeling with regards to longitudinal data which could yield identical results for the estimates of parameters. Multilevel model approach seemed easier for model specification. However,latent growth curve model had the advantage of providing model evaluation and was more flexible in statistical modeling by allowing the incorporation of latent variables. Both multilevel and latent growth curve models were suitable for analyzing longitudinal data with advantages on their own,they conld be chosen by researchers under different situation to be chosen accordingly by researchers under different situation.
ABSTRACT
To compare two commonly used statistical approaches:the multilevel model and the latent growth curve model in analyzing longitudinal data. A longitudinal data set,obtained from the quality of life in patients with colorectal cancer after operation,was used to illustrate the similarities and differences between the two methods. Results from the study indicated that the latent growth curve modeling was equivalent to multilevel modeling with regards to longitudinal data which could yield identical results for the estimates of parameters. Multilevel model approach seemed easier for model specification. However,latent growth curve model had the advantage of providing model evaluation and was more flexible in statistical modeling by allowing the incorporation of latent variables. Both multilevel and latent growth curve models were suitable for analyzing longitudinal data with advantages on their own,they conld be chosen by researchers under different situation to be chosen accordingly by researchers under different situation.
ABSTRACT
Objective To test the diathesis-stress component in the hopelessness theory and demonstrate the mediator effect of hopelessness in depression-generating process. Methods In the 6-month longitudinal study,latent growth curve model(LGM) was used in a sample of 269 Chinese undergraduates on the base of questionnaire investigation. Results The intercept for hopelessness depression had a significant association with the intercept for negative life events (path coefficient =0.48) and depressogenic attributional style (path coefficient=0.26).The slope for hopelessness depression had a significant association with the slope for negative life events (path coefficient=0.73). The complete mediator effect of hopelessness between depressogenic attributional style and the intercept for hopelessness depression was 0.143. The complete mediator effect of hopelessness between the slope for negative life events and the intercept for hopelessness depression was 0.131. The partial mediator effect of hopelessness between the intercept for negative life events and the intercept for hopelessness depression was 0.151.Conclusion Depressogenic attributional style interacted with the occurrence of negative events to predict the occurrence of hopelessness depression. Hopelessness made partial mediator effect on the hopelessness depression-generating process.