ObjectiveGenetic counseling and testing can be offered to individuals who are at high risk of carrying a breast cancer (BRCA) gene mutation. However, the content of genetic counseling could be difficult to understand due to complex medical information. The aim of this study was to investigate if comprehension can be improved with a new genetic counseling tool (NGCT hereafter; a tool that combines complex medical information with pictures, diagrams and tables) as compared to conventional oral-only genetic counseling (CGC).Methods207 clients attended genetic counseling for hereditary breast and ovarian cancer at the Medical University of Vienna between February 2015 and February 2016. Seventy clients participated in this study and were allocated into two groups: the first 36 participants received conventional (oral only) genetic counseling (CGC) and the following 34 participants received genetic counseling using a new genetic counseling tool (NGCT), which combines complex information with pictures, diagrams and tables. After genetic counseling, all consenting participants were invited to complete a questionnaire with seven questions evaluating their comprehension of the medical information provided.ResultsSocio-demographic backgrounds were comparable in both groups. Correct responses were significantly higher in the NGCT group compared to the CGC group (p = 0.012). NGCT also statistically improves correct response of Q1 (p = 0.03) and Q7 (p = 0.004).ConclusionThe NGCT leads to an overall better understanding of the content of a genetic counseling session than CGC alone.
Abstract. Meteorological in situ observational data comes with a variety of errors and uncertainties. Any further usage of this data requires a sophisticated quality control to detect, quantify and possibly eliminate or at least to reduce errors and to increase the value of the information. It must be assumed, that each observational value Ψ obs is contaminated by errors Ψ err so that the true state Ψ true is not known. Different kinds of errors can be identified. Each of them has different characteristics and therefore has to be detected through appropriate methods. For years, various methods as a self consistency test, clustering and nearest 5 neighbour techniques have been implemented in the complex quality control scheme of the Vienna Enhanced Resolution Analysis (VERA). Thereby former elaborations adressed the elimination and treatment of gross errors. In successioon the present investigation adresses the determination of stochastic and deterministic perturbations. In a first step we implemented the method to split up the observational value to smooth out the stochastic errors to the best and retain deterministic perturbations thereafter. Through controlled experiments on two dimensions the performance and limitations of the complex quality control 10 scheme has been investigated. The treatment of errors and signals on different scales and the limit of the usability of this property is the main focus of the presented investigation. We highly recommend to use the method for data quality control within a high resolution model analysing spatially distributed data in highly complex terrain.
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