In recent studies on the association between education and fertility, increased attention has been paid to the field of study. Women who studied in traditionally more “feminine” fields, like care, teaching, and health, were found to have their children earlier and to have more children than other women. A point of debate in this literature is on the causal direction of this relationship. Does the field of study change the attitudes towards family formation, or do young adults with stronger family-life attitudes self-select into educational fields that emphasize care, teaching, and health? Or do both field of study preferences and family-life attitudes arise before actual choices in these domains are made?We contribute to this debate by examining the relationship between fertility expectations and expected fields of study and occupation among 14-17 year-old adolescents. We use data collected in 2005 from 1500 Dutch adolescents and Structural Equation Modelling (SEM) to examine the associations between expected field of study and occupation and fertility expectations. Our results show that expectations concerning fertility and field of study are already interrelated during secondary education. Both female and male adolescents who expect to pursue studies in fields that focus on care and social interaction (like health care, teaching etc.) are less likely to expect to remain childless. This holds equally for girls and boys. In addition, girls who more strongly aspire to an occupation in which communication skills are important also expect to have more children. We did not find any relationship between expectations of pursuing a communicative field of study and occupation and expectations of earlier parenthood.In addition, among boys, we find that the greater their expectation of opting for an economics, a technical, or a communicative field of study, the less likely they were to expect to remain childless. Boys who expected to study in the economic field also expect to have their first child earlier, but boys expecting to pursue a technical course of studies expect to enter parenthood later. We also found that those who expect to pursue cultural studies are more likely to have a preference for no children, or if they do want children, to have them later in life.Overall, our findings suggest that the processes of elective affinity between the communicative fields of study and work on the one hand and fertility on the other hand are more or less comparable for boys and girls. With respect to the other domains, we find, apart from the gender differences in the relation between fields of study and childlessness, hardly or no gender differences in the expected timing of parenthood and the number of children. The genders do differ in their level of preference for communicative and economics-related fields of study and occupation, but if they do have the same preference, the association with fertility expectations is more or less similar.
MULTIFILE
Background: Modern modeling techniques may potentially provide more accurate predictions of dichotomous outcomes than classical techniques. Objective: In this study, we aimed to examine the predictive performance of eight modeling techniques to predict mortality by frailty. Methods: We performed a longitudinal study with a 7-year follow-up. The sample consisted of 479 Dutch community-dwelling people, aged 75 years and older. Frailty was assessed with the Tilburg Frailty Indicator (TFI), a self-report questionnaire. This questionnaire consists of eight physical, four psychological, and three social frailty components. The municipality of Roosendaal, a city in the Netherlands, provided the mortality dates. We compared modeling techniques, such as support vector machine (SVM), neural network (NN), random forest, and least absolute shrinkage and selection operator, as well as classical techniques, such as logistic regression, two Bayesian networks, and recursive partitioning (RP). The area under the receiver operating characteristic curve (AUROC) indicated the performance of the models. The models were validated using bootstrapping. Results: We found that the NN model had the best validated performance (AUROC=0.812), followed by the SVM model (AUROC=0.705). The other models had validated AUROC values below 0.700. The RP model had the lowest validated AUROC (0.605). The NN model had the highest optimism (0.156). The predictor variable “difficulty in walking” was important for all models. Conclusions: Because of the high optimism of the NN model, we prefer the SVM model for predicting mortality among community-dwelling older people using the TFI, with the addition of “gender” and “age” variables. External validation is a necessary step before applying the prediction models in a new setting.
The Procurement and Supply of hospital isolation gowns (IGs) pose significant challenges, including the potential for sudden increases in demand, the necessity of maintaining high-quality gowns, and the complexity of the supply process. One potential solution to these challenges is the investment in reusable IGs, which may seem financially infeasible due to their initial purchasing price. However, it can provide long-term financial and environmental benefits. In this research, a Simulation Optimization (SO) framework is utilized to model and analyze various product portfolio selection strategies, considering both financial and environmental perspectives, and to determine the optimal strategy for meeting both financial and environmental objectives. The proposed strategy is implemented to the problem based on obtained Life Cycle Assessment and market data.
