Objective To identify and describe health literacy profiles of patients with rheumatic diseases and explore whether the identified health literacy profiles can be generalized to a broader... Show moreObjective To identify and describe health literacy profiles of patients with rheumatic diseases and explore whether the identified health literacy profiles can be generalized to a broader rheumatology context.Methods Patients with rheumatoid arthritis, spondyloarthritis, and gout from 3 hospitals in different regions in The Netherlands completed the Health Literacy Questionnaire (HLQ). Hierarchical cluster analysis was used to identify patients' health literacy profiles based on 9 HLQ domains. A multinomial regression model with the identified health literacy profiles as the dependent variable was fitted to assess whether patients with a given disease type or attending a given hospital were more likely to belong to a specific profile.Results Among 895 participating patients, the lowest mean HLQ domain scores (indicating most difficulty) were found for "critical appraisal," "navigating the health system," and "finding good health information." The 10 identified profiles revealed substantial diversity in combinations of strengths and weaknesses. While 42% of patients scored moderate to high on all 9 domains (profiles 1 and 3), another 42% of patients (profiles 2, 4, 5, and 6) clearly struggled with 1 or several aspects of health literacy. Notably, 16% (profiles 7-10) exhibited difficulty across a majority of health literacy domains. The probability of belonging to one of the profiles was independent of the hospital where the patient was treated or the type of rheumatic disease.Conclusion Ten distinct health literacy profiles were identified among patients with rheumatic diseases, independent of disease type and treating hospital. These profiles can be used to facilitate the development of health literacy interventions in rheumatology. Show less
Knaap, Y.A.M. van der; Bakker, M.M.; Jamal Alam, S.; Witte, J.P.M.; Aerts, R.; Eck, R. van; Bodegom, P.M. van 2018
Climate change is projected to strongly affect the hydrological cycle, altering water availability and causing successive shifts in vegetation composition and distribution. To reduce potential... Show moreClimate change is projected to strongly affect the hydrological cycle, altering water availability and causing successive shifts in vegetation composition and distribution. To reduce potential negative effects on vegetation, policymakers may implement hydrological climate adaptation measures, which may -in turn- require land use changes to be successful. Policy driven land use changes should therefore be taken into account when evaluating climate change and adaptation effects on the water-vegetation system, but this is rarely done. To support such policy interventions, we applied a coupled land use – hydrology – vegetation model to simulate effects of (i) climate change, (ii) socio-economic change, (iii) hydrological measures and (iv) policy driven land use change, alone and in interaction, on vegetation communities in the Netherlands. We simulated two climate scenarios for 2050 that differed in predicted temperature (+0.9 °C and +2.8 °C) and precipitation changes (groundwater recharge +4% or −14%). The associated socio-economic scenarios differed in the increase of gross margins per agricultural class. The land use changes concerned agricultural changes and development of new nature areas from agricultural land. Individually, land use changes had the biggest effect on vegetation distribution and composition, followed by the hydrological measures and climate change itself. Our results also indicate that the combination of all four factors triggered the biggest response in the extent of newly created nature areas (+6.5%) and the highest diversity in vegetation types, compared to other combinations (max. +5.4%) and separate factors. This study shows that an interdisciplinary, coupled modelling approach is essential when evaluating climate adaptation measures. Show less
