Organisatorische Spannungen

Organisatorische Spannungen („Tensions“) bezeichnen Konflikte, die aus gegensätzlichen, mitunter widersprüchlichen Ansichten und Anforderungen in einer Organisation hervorgehen (Smith/Lewis 2011, 2022; Putnam et al. 2016; Farjoun 2017). In Situationen, in denen unterschiedliche Entwicklungsrichtungen und Perspektiven aufeinandertreffen, werden diese Spannungen wahrnehmbar. Die den Spannungen zugrundeliegenden Gegensätzlichkeiten in einer Organisation können dabei unterschiedlich stark sein und von einfachen Diskrepanzen und differierenden Ansichten, über Dilemmata, also gegensätzlichen Handlungsoptionen, bis hin zu unauflösbaren Widersprüchen bzw. Paradoxien reichen

ATHENA Research Book

The ATHENA European University is an alliance of nine Higher Education Institutions with the mission of fostering excellence in research and innovation by facilitating international cooperation. The ATHENA acronym stands for Advanced Technologies in Higher Education Alliance. The partner institutions are from France, Germany, Greece, Italy, Lithuania, Portugal, and Slovenia: the University of Orléans, the University of Siegen, the Hellenic Mediterranean University, the Niccolò Cusano University, the Vilnius Gediminas Technical University, the Polytechnic Institute of Porto, and the University of Maribor. In 2022 institutions from Poland and Spain joined the alliance: the Maria Curie-Skłodowska University and the University of Vigo. This research book presents a selection of the ATHENA university partners' research activities. It incorporates peer-reviewed original articles, reprints and student contributions. The ATHENA Research Book provides a platform that promotes joint and interdisciplinary research projects of both advanced and early-career researchers

Fasting blood glucose, glycaemic control and prostate cancer risk in the Finnish Randomized Study of Screening for Prostate Cancer

BACKGROUND: Diabetic men have lowered overall risk of prostate cancer (PCa), but the role of hyperglycaemia is unclear. In this cohort study, we estimated PCa risk among men with diabetic fasting blood glucose level. METHODS: Participants of the Finnish Randomized Study of Screening for Prostate Cancer (FinRSPC) were linked to laboratory database for information on glucose measurements since 1978. The data were available for 17,860 men. Based on the average yearly level, the men were categorised as normoglycaemic, prediabetic, or diabetic. Median follow-up was 14.7 years. Multivariable-adjusted Cox regression was used to calculate hazard ratios (HRs) and 95% confidence intervals (95% CIs) for prostate cancer overall and separately by Gleason grade and metastatic stage. RESULTS: In total 1,663 PCa cases were diagnosed. Compared to normoglycaemic men, those men with diabetic blood glucose level had increased risk of PCa (HR 1.52; 95% CI 1.31-1.75). The risk increase was observed for all tumour grades, and persisted for a decade afterwards. Antidiabetic drug use removed the risk association. Limitations include absence of information on lifestyle factors and limited information on BMI. CONCLUSIONS: Untreated diabetic fasting blood glucose level may be a prostate cancer risk factor.Peer reviewe

The Saving and Empowering Young Lives in Europe (SEYLE) Randomized Controlled Trial (RCT): methodological issues and participant characteristics

Background: Mental health problems and risk behaviours among young people are of great public health concern. Consequently, within the VII Framework Programme, the European Commission funded the Saving and Empowering Young Lives in Europe (SEYLE) project. This Randomized Controlled Trial (RCT) was conducted in eleven European countries, with Sweden as the coordinating centre, and was designed to identify an effective way to promote mental health and reduce suicidality and risk taking behaviours among adolescents. Objective: To describe the methodological and field procedures in the SEYLE RCT among adolescents, as well as to present the main characteristics of the recruited sample. Methods: Analyses were conducted to determine: 1) representativeness of study sites compared to respective national data; 2) response rate of schools and pupils, drop-out rates from baseline to 3 and 12 month follow-up, 3) comparability of samples among the four Intervention Arms; 4) properties of the standard scales employed: Beck Depression Inventory, Second Edition (BDI-II), Zung Self-Rating Anxiety Scale (Z-SAS), Strengths and Difficulties Questionnaire (SDQ), World Health Organization Well-Being Scale (WHO-5). Results: Participants at baseline comprised 12,395 adolescents (M/F: 5,529/6,799; mean age=14.9±0.9) from Austria, Estonia, France, Germany, Hungary, Ireland, Israel, Italy, Romania, Slovenia and Spain. At the 3 and 12 months follow up, participation rates were 87.3% and 79.4%, respectively. Demographic characteristics of participating sites were found to be reasonably representative of their respective national population. Overall response rate of schools was 67.8%. All scales utilised in the study had good to very good internal reliability, as measured by Cronbach’s alpha (BDI-II: 0.864; Z-SAS: 0.805; SDQ: 0.740; WHO-5: 0.799). Conclusions: SEYLE achieved its objective of recruiting a large representative sample of adolescents within participating European countries. Analysis of SEYLE data will shed light on the effectiveness of important interventions aimed at improving adolescent mental health and well-being, reducing risk-taking and self-destructive behaviour and preventing suicidality. Trial registration: US National Institute of Health (NIH) clinical trial registry (NCT00906620) and the German Clinical Trials Register (DRKS00000214)

Utilizing the Topology Preserving Property of Self-Organizing Maps for Classification

The Kohonen Self-Organizing Map (SOM) is a popular algorithm for constructing a nearest neighbor codebook in pattern space. The algorithm utilizes a predefined ordering on the codebook to distribute the codes proportionally on the input manifold. In the end this ordering should reflect the structure of the input. Prototypical application of the SOM uses the codebook but neglects the ordering. We explore the practical possibilities for taking advantage of the ordering, concentrating mainly on classification tasks. We present three approaches: coding class boundaries with a duo of SOMs, construction of radial basis function networks with ordering information and using a SOM as a preprocessor for backpropagation networks. We obtain positive results on a number of real world data sets from the field of medical diagnosis, speech-- and image processing. From this we conclude the ordering property of SOMs contains useful information. However, it is still unclear how to profit from it in the b..