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.
Original language | English |
---|---|
Title of host publication | Pervasive Computing Paradigms for Mental Health |
Pages | 19-27 |
Number of pages | 9 |
Volume | 2018 |
DOIs | |
Publication status | Published - 2018 |
Keywords
- Awe
- Bayesian
- Emotions
- Mood-induction
- Wellbeing