In this section
Several of our current PhD candidates and fellow researchers at the Data Science Institute have published, or in the proccess of publishing, papers to present their research.
@article{Timmermann:2021:10.1038/s41598-021-01209-2,
author = {Timmermann, Slater CB and Kettner, H and Letheby, C and Roseman, L and Rosas, F and Carhart-Harris, R},
doi = {10.1038/s41598-021-01209-2},
journal = {Scientific Reports},
pages = {1--12},
title = {Psychedelics alter metaphysical beliefs},
url = {http://dx.doi.org/10.1038/s41598-021-01209-2},
volume = {11},
year = {2021}
}
TY - JOUR
AB - Can the use of psychedelic drugs induce lasting changes in metaphysical beliefs? While it is popularly believed that they can, this question has never been formally tested. Here we exploited a large sample derived from prospective online surveying to determine whether and how beliefs concerning the nature of reality, consciousness, and free-will, change after psychedelic use. Results revealed significant shifts away from ‘physicalist’ or ‘materialist’ views, and towards panpsychism and fatalism, post use. With the exception of fatalism, these changes endured for at least 6 months, and were positively correlated with the extent of past psychedelic-use and improved mental-health outcomes. Path modelling suggested that the belief-shifts were moderated by impressionability at baseline and mediated by perceived emotional synchrony with others during the psychedelic experience. The observed belief-shifts post-psychedelic-use were consolidated by data from an independent controlled clinical trial. Together, these findings imply that psychedelic-use may causally influence metaphysical beliefs—shifting them away from ‘hard materialism’. We discuss whether these apparent effects are contextually independent.
AU - Timmermann,Slater CB
AU - Kettner,H
AU - Letheby,C
AU - Roseman,L
AU - Rosas,F
AU - Carhart-Harris,R
DO - 10.1038/s41598-021-01209-2
EP - 12
PY - 2021///
SN - 2045-2322
SP - 1
TI - Psychedelics alter metaphysical beliefs
T2 - Scientific Reports
UR - http://dx.doi.org/10.1038/s41598-021-01209-2
UR - https://www.nature.com/articles/s41598-021-01209-2
UR - http://hdl.handle.net/10044/1/92735
VL - 11
ER -
Data Science Institute
William Penney Laboratory
Imperial College London
South Kensington Campus
London SW7 2AZ
United Kingdom
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