Institution
Danube University Krems
Education•Krems, Niederösterreich, Austria•
About: Danube University Krems is a education organization based out in Krems, Niederösterreich, Austria. It is known for research contribution in the topics: Stroke & Population. The organization has 498 authors who have published 1572 publications receiving 68797 citations.
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7 citations
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09 Jan 2020TL;DR: People who played the serious game showed better performance in the comprehension of process models when comparing both studies, indicating that complex process models are more difficult to comprehend.
Abstract: Background: The management and comprehension of business process models are of utmost importance for almost any enterprise. To foster the comprehension of such models, this paper has incorporated the idea of a serious game called Tales of Knightly Process.
Objective: This study aimed to investigate whether the serious game has a positive, immediate, and follow-up impact on process model comprehension.
Methods: A total of two studies with 81 and 64 participants each were conducted. Within the two studies, participants were assigned to a game group and a control group (ie, study 1), and a follow-up game group and a follow-up control group (ie, study 2). A total of four weeks separated study 1 and study 2. In both studies, participants had to answer ten comprehension questions on five different process models. Note that, in study 1, participants in the game group played the serious game before they answered the comprehension questions to evaluate the impact of the game on process model comprehension.
Results: In study 1, inferential statistics (analysis of variance) revealed that participants in the game group showed a better immediate performance compared to control group participants (P<.001). A Hedges g of 0.77 also indicated a medium to large effect size. In study 2, follow-up game group participants showed a better performance compared to participants from the follow-up control group (P=.01); here, a Hedges g of 0.82 implied a large effect size. Finally, in both studies, analyses indicated that complex process models are more difficult to comprehend (study 1: P<.001; study 2: P<.001).
Conclusions: Participants who played the serious game showed better performance in the comprehension of process models when comparing both studies.
7 citations
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TL;DR: In this article, the performance of a recently introduced method to estimate the resonance parameters from complex spectral data and the error propagation for viscosity and density parameters of liquids is examined and compared with measurement results obtained with a piezoelectric tuning fork and a Lorentz force actuated and inductively read out platelet sensor.
7 citations
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University of Reims Champagne-Ardenne1, Brown University2, Harvard University3, Aichi Medical University4, Hospital Kuala Lumpur5, Monash University, Clayton campus6, University of Melbourne7, Royal Brisbane and Women's Hospital8, University of Wisconsin-Madison9, Queen's University10, Karolinska University Hospital11, University of Hamburg12, Istanbul University13, University of Bern14, University of Perugia15, Utrecht University16, University of Tsukuba17, Hyogo College of Medicine18, Central University, India19, Houston Methodist Hospital20, University of Kentucky21, FIU Herbert Wertheim College of Medicine22, University of California, Los Angeles23, Emory University24, Heidelberg University25, Danube University Krems26, Royal Melbourne Hospital27, University of Cape Town28, Mahidol University29, Toronto Western Hospital30
TL;DR: Standards of practice in acute ischemic stroke intervention: international recommendations according to international recommendations is published in Journal of NeuroInterventional Surgery.
Abstract: This article was first published in JNIS. Cite this article as: Pierot L, Jayaraman MV, Szikora I, et al. Standards of practice in acute ischemic stroke intervention: international recommendations. Journal of NeuroInterventional Surgery. Published Online First: 28 August 2018. doi: 10.1136/neurintsurg-2018-014287.
7 citations
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TL;DR: In this article, the authors used factor analysis and a machine learning algorithm (LASSO with 10-fold cross-validation) to detect potential reasons for not-on-track trajectories.
Abstract: Within the Routine Outcome Monitoring system "OQ-Analyst," the questionnaire "Assessment for Signal Cases" (ASC) supports therapists in detecting potential reasons for not-on-track trajectories. Factor analysis and a machine learning algorithm (LASSO with 10-fold cross-validation) were applied, and potential predictors of not-on-track classifications were tested using logistic multilevel modeling methods. The factor analysis revealed a shortened (30 items) version of the ASC with good internal consistency (α = 0.72-0.89) and excellent predictive value (area under the curve = 0.98; positive predictive value = 0.95; negative predictive value = 0.94). Item-level analyses showed that interpersonal problems captured by specific ASC items (not feeling able to speak about problems with family members; feeling rejected or betrayed) are the most important predictors of not-on-track trajectories. It should be considered that our results are based on analyses of ASC items only. Our findings need to be replicated in future studies including other potential predictors of not-on-track trajectories (e.g., changes in medication, specific therapeutic techniques, or treatment adherence), which were not measured this study.
7 citations
Authors
Showing all 514 results
Name | H-index | Papers | Citations |
---|---|---|---|
Jaakko Tuomilehto | 115 | 1285 | 210682 |
Massimo Zeviani | 104 | 478 | 39743 |
J. Tuomilehto | 69 | 197 | 19801 |
Manfred Reichert | 67 | 695 | 19569 |
Roland W. Scholz | 64 | 289 | 15387 |
Michael Brainin | 55 | 215 | 44194 |
Gerald Gartlehner | 54 | 295 | 15320 |
Thomas Schrefl | 50 | 403 | 10867 |
Charity G. Moore | 50 | 179 | 11040 |
Josef Finsterer | 48 | 1479 | 13836 |
Silvia Miksch | 44 | 264 | 7790 |
J. Tuomilehto | 44 | 107 | 11425 |
Heinrich Schima | 43 | 249 | 5973 |
Reinhard Bauer | 40 | 228 | 5435 |
Thomas Groth | 38 | 186 | 5191 |