Background: Accurate measurement of health literacy is essential to improve accessibility and effectiveness of health care and prevention. One measure frequently applied in international research is the Short Assessment of Health Literacy (SAHL). While the Dutch SAHL (SAHL-D) has proven to be valid and reliable, its administration is time consuming and burdensome for participants. Our aim was to further validate, strengthen and shorten the SAHL-D using Rasch analysis. Methods: Available cross-sectional SAHL-D data was used from adult samples (N = 1231) to assess unidimensionality, local independence, item fit, person fit, item hierarchy, scale targeting, precision (person reliability and person separation), and presence of differential item functioning (DIF) depending on age, gender, education and study sample. Results: Thirteen items for a short form were selected based on item fit and DIF, and scale properties were compared between the two forms. The long form had several items with DIF for age, gender, educational level and study sample. Both forms showed lower measurement precision at higher health literacy levels. Conclusions: The findings support the validity and reliability of the SAHL-D for the long form and the short form, which can be used for a rapid assessment of health literacy in research and clinical practice.
In the past 5 years Electric Car use has grown rapidly, almost doubling each year. To provide adequate charging infrastructure it is necessary to model the demand. In this paper we model the distribution of charging demand in the city of Amsterdam using a Cross-Nested Logit Model and sociodemographic statistics of neighborhoods.
Background and aim Self-management support is an integral part of current chronic care guidelines. The success of self-management interventions varies between individual patients, suggesting a need for tailored self-management support. Understanding the role of patient factors in the current decision making of health professionals can support future tailoring of self-management interventions. The aim of this study is to identify the relative importance of patient factors in health professionals’ decision making regarding self-management support. Method A factorial survey was presented to primary care physicians and nurses. The survey consisted of clinical vignettes (case descriptions), in which 11 patient factors were systematically varied. Each care provider received a set of 12 vignettes. For each vignette, they decided whether they would give this patient self-management support and whether they expected this support to be successful. The associations between respondent decisions and patient factors were explored using ordered logit regression. Results The survey was completed by 60 general practitioners and 80 nurses. Self-management support was unlikely to be provided in a third of the vignettes. The most important patient factor in the decision to provide self-management support as well as in the expectation that self-management support would be successful was motivation, followed by patient-provider relationship and illness perception. Other factors, such as depression or anxiety, education level, self-efficacy and social support, had a small impact on decisions. Disease, disease severity, knowledge of disease, and age were relatively unimportant factors. Conclusion This is the first study to explore the relative importance of patient factors in decision making and the expectations regarding the provision of self-management support to chronic disease patients. By far, the most important factor considered was patient’s motivation; unmotivated patients were less likely to receive self-management support. Future tailored interventions should incorporate strategies to enhance motivation in unmotivated patients. Furthermore, care providers should be better equipped to promote motivational change in their patients.
DOK4CT (in Dutch: Digitale Onderwijsmiddelen en Kennisontsluiting for Control Towers)In this project the practical applied knowledge, derived from innovative projects within the “Topsector logistiek”, is made accessible by Breda University and Deltago. This online Control Tower Course is specifically meant for logistic professionals and students in logistic orientated education. The project was made accesible and supported by the NWO, Netherlands Organisation for Scientific Research. The scope of this project is limited to the area of Cross Chain Control Centers (4C) / Control Towers. The educational valorisation will be executed by the development of digital materials. These are used for student education as well as dissemination towards professionals in the logistics sector. Hereby, the interaction between students and professionals is an important additional benefit under the name of “social learning”. For example the interviews that Marcel Wouterse (Deltago and lecturer at Breda University of Applied Sciences) has created with key partners in the logistics sector were recorded and edited by students. By the use of digital educational tools and serious games, the benefits of Control Towers are now visible for students and professionals. The next phase is to introduce the gained knowledge in future organisations in order to support the Netherlands in the top of the logistics sector.Project goalThe goal of this project is to improve the exploitation of fundamental- and applied knowledge in the expertise area of Cross Chain Control Centers (4C) and Control Towers (CT).The tasks are divided in five subprojects:1. Preparations to transfer existing materials in digital learning tools;2. Shape digital education material (Webinars, online platform, knowledge clips and e-learnings)3. Develop and/or use several serious games (Convoy game / Synchromania)4. Promotion of the course to specified target groups (professionals / international students)5. Project managementExcising knowledge regarding Cross Chain Control Centers and Control Towers is used in this project. New knowledge will not be generated. The project focus lies on the disclosure of acquired knowledge by digital learning tools.
