Publikation: Webpage reading : Psychophysiological correlates of emotional arousal and regulation predict multiple-text comprehension
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This study aimed to investigate psychophysiological responses while reading multiple webpages on a debated topic. We measured heart rate (HR) as an index of emotional arousal and heart rate variability (HRV) as an index of emotional regulation. Forty-seven lower secondary school students in grade 7 read four webpages varying for reliability and position on the topic of the potential health risks associated with the use of mobile phones, while their cardiac activity was registered. Post-reading performance of multiple-text comprehension at intertextual level was measured by an essay, which was coded for sourcing (reference to the source information and connection with its content) and argumentation on the topic. Results showed that the type of webpage did not differentiate HR and HRV while reading. However, HR and HRV predicted comprehension across texts as reflected in argumentation, after controlling for prior knowledge and reading comprehension. Specifically, HR was a negative predictor and HRV a positive predictor; the less the students were emotionally reactive to the content read and the more they were able to self-regulate while reading, the greater their multiple-text comprehension, such as the ability to argue about the debated topic. Theoretical and practical contributions of the study are discussed.
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MASON, Lucia, Sara SCRIMIN, Sonia ZACCOLETTI, Maria Caterina TORNATORA, Thomas GÖTZ, 2018. Webpage reading : Psychophysiological correlates of emotional arousal and regulation predict multiple-text comprehension. In: Computers in Human Behavior. 2018, 87, pp. 317-326. ISSN 0747-5632. eISSN 1873-7692. Available under: doi: 10.1016/j.chb.2018.05.020BibTex
@article{Mason2018-10Webpa-43207, year={2018}, doi={10.1016/j.chb.2018.05.020}, title={Webpage reading : Psychophysiological correlates of emotional arousal and regulation predict multiple-text comprehension}, volume={87}, issn={0747-5632}, journal={Computers in Human Behavior}, pages={317--326}, author={Mason, Lucia and Scrimin, Sara and Zaccoletti, Sonia and Tornatora, Maria Caterina and Götz, Thomas} }
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