Medical decision-making capacity (MDC) is known to decline in individuals with Alzheimer's disease (AD). The vignette method uses hypothetical information as a prerequisite for measuring the capacity to make well-informed decisions to clinical trials. Our aim was to investigate if adapted vignettes can help individuals with mild AD to assimilate information, make decisions and express them in an understandable way, compared to corresponding decisions based on linguistically more demanding vignettes, as measured by the Swedish Linguistic Instrument for Medical Decision-making (LIMD). Two vignettes from LIMD were altered linguistically with the aim to facilitate understanding for individuals with AD. An experimental within-subject design was used to study the influence on MDC of readability (original/adapted vignettes) and content (two different clinical trials). We included 24 patients with mild AD in this prospective study, which read all four vignettes along with a few other tests. This allowed us to investigate the association between MDC and cognitive function. Adapted vignettes did not yield significant differences regarding MDC as compared with original vignettes using a two-way repeated measures analysis of variance. A difference was found between the two clinical trials where LIMD score was significantly higher for Kidney disease than hypertension vignettes. Our results indicate that adapted vignettes may not improve MDC for individuals with mild AD. MDC was affected by which clinical trial the vignettes regarded, which implies that other factors affecting MDC need to be investigated, like length of text and vocabulary used.

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We present T-MASTER, a tool for assessing students' reading skills on a variety of dimensions. T-MASTER uses sophisticated measures for assessing a student's reading comprehension and vocabulary understanding. Texts are selected based on their difficulty using novel readability measures and tests are created based on the texts. The results are analyzed in T-MASTER, and the numerical results are mapped to textual descriptions that describe the student's reading abilities on the dimensions being analysed. These results are presented to the teacher in a form that is easily comprehensible, and lends itself to inspection of each individual student's results.

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The Concept Coding Framework (CCF) technology represents a long term commitment to develop and deliver an open infrastructure for multi-modal and multilingual language support for a wide area of applications. In this way the varying needs among several smaller groups of users of AAC (Augmentative and Alternative Communication) may be met as part of a more inclusively designed [1] mainstream environment of much broader interest. With support from the EU via the AEGIS project, a "CCF-SymbolServer" has been developed. It can be installed locally on any of the major desktop platforms (GNU/Linux, MacOS X and Windows), or online, to support many kinds of local or web based services and networked mobile systems. In any of these environments the CCF-SymbolServer can provide its multilingual and multi-modal representation services to other applications. Three such applications, developed and tested with users within AEGIS, are presented: 1) CCF-SymbolWriter, an extension for symbol support in LibreOffice/OpenOffice Writer; 2) CCF-SymbolDroid, an AAC app for Android mobile devices; 3) the new CCF supported version of Special Access to Windows (SAW6). Three current follow-up projects are briefly presented in the outline of perspectives for further research and development.