Abstract
Awe is a complex emotion that influences positively individuals’ wellbeing both at a physical and at a psychological level. Eliciting awe in a lab setting is a delicate task, and several effective techniques have been developed to pursue this goal, such as audio-video stimuli. Nevertheless, a standardized procedure to select these audio-video awe-inducing stimuli is still needed. Therefore, we validated a methodology to select and discriminate among awe- inducing stimuli. The novelty of the methodology is two-fold: (i) it allows testing whether each content elicited the target emotion, and (ii) it allows to identify the most awe-conductive videos, using both classical statistics and Bayesian analyses. Four videos displaying awe, amusement and neutral contents were shown to participants in a counterbalanced order. This procedure allowed for identifying and validating awe-inducing stimuli that can be pliably used to improve individual’s wellbeing and mental health in different contexts.
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Notes
- 1.
Evidence in favor of the model of interest (similarity of measures) is considered anecdotal (1 < BF < 2.5) or substantial (2.5 < BF < 10). Comparing the relative predictive success of one model on another, if the BF was substantial the two measures were statistically similar relative to the hypothesis that are different. If BF < 1, it can be considered as an evidence supporting the differences instead of similarities.
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Chirico, A., Cipresso, P., Riva, G., Gaggioli, A. (2018). A Process for Selecting and Validating Awe-Inducing Audio-Visual Stimuli. In: Oliver, N., Serino, S., Matic, A., Cipresso, P., Filipovic, N., Gavrilovska, L. (eds) Pervasive Computing Paradigms for Mental Health. FABULOUS MindCare IIOT 2016 2016 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 207. Springer, Cham. https://doi.org/10.1007/978-3-319-74935-8_3
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