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Cited by 391

The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.

Autonomous Sensory Meridian Response (ASMR): a flow-like mental state

Open access
Barratt, Emma L., Davis, Nick J.·2015·PeerJ
DOI 10.7717/peerj.851
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Abstract

Autonomous Sensory Meridian Response (ASMR) is a previously unstudied sensory phenomenon, in which individuals experience a tingling, static-like sensation across the scalp, back of the neck and at times further areas in response to specific triggering audio and visual stimuli. This sensation is widely reported to be accompanied by feelings of relaxation and well-being. The current study identifies several common triggers used to achieve ASMR, including whispering, personal attention, crisp sounds and slow movements. Data obtained also illustrates temporary improvements in symptoms of depression and chronic pain in those who engage in ASMR. A high prevalence of synaesthesia (5.9%) within the sample suggests a possible link between ASMR and synaesthesia, similar to that of misophonia. Links between number of effective triggers and heightened flow state suggest that flow may be necessary to achieve sensations associated with ASMR.

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Metadata

Authors
Barratt, E. L., & Davis, N. J.
Venue
PeerJ
Publisher
PeerJ
Published
2015-03-26
Volume
3
Pages
e851
ISSN
2167-8359 (ISSN-L)
DOI
10.7717/peerj.851
OpenAlex
W2036916183
Cited by
391
References
20
FWCI
30.36
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Autonomous Sensory Meridian Response (ASMR): a flow-like mental state. https://app.cochat.ai/papers/10.7717/peerj.851
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Barratt, E. L., & Davis, N. J. (2015). Autonomous Sensory Meridian Response (ASMR): a flow-like mental state. PeerJ. https://doi.org/10.7717/peerj.851

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.