Prodonation campaigns geared toward the public and hospital staff should focus on specific objectives to increase the likelihood of consent for organ donation.
This study uses hierarchical or multilevel modeling to identify variables that contribute to daily stressors in a population of schoolchildren. Four hierarchical levels with several predictive variables were considered: student (age, sex, social adaptation of the student, number of life events and chronic stressors experienced, and educational level of the father and mother), class (number of students per class), school (type of school), and province (number of inhabitants per province). Participants were 6,078 students from primary years 3-6 in the region of Andalusia (Spain). After conducting a multilevel regression analysis, the final fitted model was a random intercept and random slope model (at the school level) for the variable age, with the fixed factors being the variables social adaptation, life events and chronic stressors, and the educational level of the father and mother. This model yielded a specific profile of daily stressors in childhood: children with the highest levels of daily stressors are younger, present aggressive or inhibited behavior, have experienced more life events and chronic stressors, and have parents who did not complete their primary education. The results provide relevant information for the design of psychoeducational interventions in relation to children's daily stressors.
Abstract. In this paper we review different structural equation models for the analysis of longitudinal data: (a) univariate models of observable variables, (b) multivariate models of observable variables, (c) models with latent variables, (d) models that are unconditioned or conditioned to other variables (depending on the variability of the independent variables: time-varying or time-invariant, and depending on the type of independent variables: of latent variables or of observable variables), (e) models with interaction of variables, (f) models with nonlinear variables, (g) models with a constant, (h) with single level and multilevel measurement, and (i) other advances in SEM of longitudinal data (latent growth curve model, latent difference score, etc.). We pay more attention to the interaction of variables and to nonlinear transformations of variables because they are not frequently used in empirical investigation. They do, however, offer interesting possibilities to researchers who wish to verify relations between the variables they obtain. Potential applications are described, with their advantages and disadvantages.
This study examined the use of verbalisms by 62 children aged 7-14 who were totally blind from birth and 64 sighted children. It found that a child's degree of sight and gender did not affect the frequency with which verbalisms were used; only age had a significant positive effect. The study shows that language is a flexible structure that is used correctly by children who are congenitally blind as they adapt to the language used by those around them.
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