The Facial Affective Scale (FAS) as a predictor for pain unpleasantness when children undergo immunizations

Needle fear is a common problem in children undergoing immunization. To ensure that the individual child’s needs are met during a painful procedure it would be beneficial to be able to predict whether there is a need for extra support. The self-reporting instrument facial affective scale (FAS) could have potential for this purpose. The aim of this study was to evaluate whether the FAS can predict pain unpleasantness in girls undergoing immunization. Girls, aged 11-12 years, reported their expected pain unpleasantness on the FAS at least two weeks before and then experienced pain unpleasantness immediately before each vaccination. The experienced pain unpleasantness during the vaccination was also reported immediately after each immunization. The level of anxiety was similarly assessed during each vaccination and supplemented with stress measures in relation to the procedure in order to assess and evaluate concurrent validity. The results show that the FAS is valid to predict pain unpleasantness in 11-12-year-old girls who undergo immunizations and that it has the potential to be a feasible instrument to identify children who are in need of extra support to cope with immunization. In conclusion, the FAS measurement can facilitate caring interventions.

Compositional Model Repositories via Dynamic Constraint Satisfaction with Order-of-Magnitude Preferences

The predominant knowledge-based approach to automated model construction, compositional modelling, employs a set of models of particular functional components. Its inference mechanism takes a scenario describing the constituent interacting components of a system and translates it into a useful mathematical model. This paper presents a novel compositional modelling approach aimed at building model repositories. It furthers the field in two respects. Firstly, it expands the application domain of compositional modelling to systems that can not be easily described in terms of interacting functional components, such as ecological systems. Secondly, it enables the incorporation of user preferences into the model selection process. These features are achieved by casting the compositional modelling problem as an activity-based dynamic preference constraint satisfaction problem, where the dynamic constraints describe the restrictions imposed over the composition of partial models and the preferences correspond to those of the user of the automated modeller. In addition, the preference levels are represented through the use of symbolic values that differ in orders of magnitude.