ASMR-Experience questionnaire (AEQ): a data-driven step towards accurately classifying ASMR responders
Swart, Thomas, Bowling, Natalie ORCID: https://orcid.org/0000-0001-5784-3664 and Banissy, Michael (2021) ASMR-Experience questionnaire (AEQ): a data-driven step towards accurately classifying ASMR responders. British Journal of Psychology. ISSN 0007-1269 (Print), 2044-8295 (Online) (doi:10.1111/bjop.12516)
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Abstract
Autonomous sensory meridian response (ASMR) describes an atypical multisensory experience of calming, tingling sensations that originate in the crown of the head in response to a specific subset of audio-visual triggers. There is currently no tool that can accurately classify both ASMR-Responders and non-responders, while simultaneously identifying False-Positive cases that are similar sensory-emotional experiences. This study sought to fill this gap by developing a new online psychometric tool – the ASMR-Experiences Questionnaire (AEQ). Participants watched a series of short ASMR videos and answered sensory-affective questions immediately afterwards. Using a k-means clustering approach, we identified five data-driven groupings, based on tingle- and affect-related scores. ASMR-Responders differentiate based on ASMR propensity and intensity (ASMR-Strong; ASMR-Weak); non-responders differentiate based on response valence (Control+; Control−; False-Positive). Recommendations for how the AEQ and the respective output groups can be best utilized to enhance ASMR research are discussed.
Item Type: | Article |
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Additional Information: | © 2021 The Authors. British Journal of Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
Uncontrolled Keywords: | N/a |
Subjects: | B Philosophy. Psychology. Religion > BF Psychology Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Faculty / School / Research Centre / Research Group: | Faculty of Education, Health & Human Sciences Faculty of Education, Health & Human Sciences > School of Human Sciences (HUM) |
Related URLs: | |
Last Modified: | 09 Sep 2021 14:07 |
URI: | http://gala.gre.ac.uk/id/eprint/33486 |
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