4,095 research outputs found

    Data and Results

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    These are the data and results files for the Maastricht University Lab (Karlijn Massar & Philippe Verduyn

    A primer on innovation and growth

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    Philippe Aghion emphasises that for Europe to stimulate innovation and growth, it is not enough to increase spending on research and development and the protection of intellectual property.

    RRR - Dijksterhuis - Massar & Verduyn

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    Our laboratory's Implementation of the Dijksterhuis RRR protoco

    RRR - Dijksterhuis - Massar & Verduyn

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    Our laboratory's Implementation of the Dijksterhuis RRR protoco

    When do smartphones displace face-to-face interactions and what to do about it?

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    There is a public concern that smartphone communication undermines well-being by displacing face-to-face interactions. However, research on this “social displacement hypothesis” has provided mixed results. We examined when this hypothesis holds true (within-persons vs. between-persons) and tested an intervention to decrease smartphone communication. Participants (N = 109) reported daily on smartphone communication, face-to-face communication, and emotional well-being for fifteen days. At day six, participants were assigned to a mindfulness-treatment intervention group or a no-treatment control group. The social displacement hypothesis was confirmed at the within-person but not between-person level. Specifically, when someone communicates a lot using her smartphone during a particular day, that person engages in less face-to-face interactions during that same day. However, people who tend to spend a lot of time communicating on their smartphone do not engage in less face-to-face conversations than people who largely refrain from smartphone communication. The mindfulness-intervention reduced daily smartphone communication, which decreased negative emotions

    KSC-N: Clustering of hierarchical time profile data

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    Quite a few studies in the behavioral sciences result in hierarchical time profile data, with a number of time profiles being measured for each person under study. Associated research questions often focus on individual differences in profile repertoire, that is, differences between persons in the number and the nature of profile shapes that show up for each person. In this paper, we introduce a new method, called KSC-N, that parsimoniously captures such differences while neatly disentangling variability in shape and amplitude. KSC-N induces a few person clusters from the data and derives for each person cluster the types of profile shape that occur most for the persons in that cluster. An algorithm for fitting KSC-N is proposed and evaluated in a simulation study. Finally, the new method is applied to emotional intensity profile data.sponsorship: This research was supported by Grant GOA/15/003 from the Research Fund of the University of Leuven. Philippe Verduyn is a Post-Doctoral Fellow of the Research Foundation-Flanders (FWO). The research leading to the results reported in this paper was supported in part by the Interuniversity Attraction Poles program financed by the Belgian government (IAP/P7/06). (University of Leuven|GOA/15/003, Interuniversity Attraction Poles program - Belgian government|IAP/P7/06)status: Publishe
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