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Institution

Danube University Krems

EducationKrems, 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.


Papers
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Journal ArticleDOI
09 Jan 2020
TL;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

Journal ArticleDOI
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

Journal ArticleDOI
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

Journal ArticleDOI
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

NameH-indexPapersCitations
Jaakko Tuomilehto1151285210682
Massimo Zeviani10447839743
J. Tuomilehto6919719801
Manfred Reichert6769519569
Roland W. Scholz6428915387
Michael Brainin5521544194
Gerald Gartlehner5429515320
Thomas Schrefl5040310867
Charity G. Moore5017911040
Josef Finsterer48147913836
Silvia Miksch442647790
J. Tuomilehto4410711425
Heinrich Schima432495973
Reinhard Bauer402285435
Thomas Groth381865191
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20237
202221
2021176
2020165
2019157
2018144