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Little is known about the factors influencing inter- and intra-individual differences in the acute response to MDMA. Effects of other psychoactive substances have been shown to be critically influenced by personality traits and mood state before intake.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>We pooled data from 10 randomized, double-blind, placebo-controlled, cross-over studies performed in the same laboratory in 194 healthy subjects receiving doses of 75 or 125mg of MDMA. We investigated the influence of drug dose, body weight, sex, age, drug pre-experience, genetics, personality and mental state before drug intake on the acute physiological and psychological response to MDMA.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>In univariable analyses, the MDMA plasma concentration was the strongest predictor for most outcome variables. When adjusting for dose per body weight, we found that (a) a higher activity of the enzyme CYP2D6 predicted lower MDMA plasma concentration, (b) a higher score in the personality trait \u201copenness to experience\u201d predicted more perceived \u201ccloseness\u201d, a stronger decrease in \u201cgeneral inactivation\u201d, and higher scores in the 5D-ASC (5 Dimensions of Altered States of Consciousness Questionnaire) scales \u201coceanic boundlessness\u201d and \u201cvisionary restructuralization\u201d, and (c) subjects with high \u201cneuroticism\u201d or trait anxiety were more likely to have unpleasant and\/or anxious reactions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>Although MDMA plasma concentration was the strongest predictor, several personality traits and mood state variables additionally explained variance in the response to MDMA. The results confirm that both pharmacological and non-pharmacological variables influence the response to MDMA. These findings may be relevant for the therapeutic use of MDMA.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/0269881121998322","type":"journal-article","created":{"date-parts":[[2021,3,30]],"date-time":"2021-03-30T03:06:01Z","timestamp":1617073561000},"page":"556-565","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":49,"title":["Prediction of MDMA response in healthy humans: a pooled analysis of placebo-controlled studies"],"prefix":"10.1177","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4233-0182","authenticated-orcid":false,"given":"Erich","family":"Studerus","sequence":"first","affiliation":[{"name":"Division of Personality and Developmental Psychology, University of Basel, Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Patrick","family":"Vizeli","sequence":"additional","affiliation":[{"name":"Division of Clinical Pharmacology and Toxicology, University Hospital Basel, Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samuel","family":"Harder","sequence":"additional","affiliation":[{"name":"Division of Clinical Pharmacology and Toxicology, University Hospital Basel, Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laura","family":"Ley","sequence":"additional","affiliation":[{"name":"Division of Clinical Pharmacology and Toxicology, University Hospital Basel, Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1765-9659","authenticated-orcid":false,"given":"Matthias E","family":"Liechti","sequence":"additional","affiliation":[{"name":"Division of Clinical Pharmacology and Toxicology, University Hospital Basel, Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2021,3,30]]},"reference":[{"key":"e_1_3_2_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neubiorev.2006.09.009"},{"key":"e_1_3_2_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.paid.2017.06.004"},{"key":"e_1_3_2_4_1","doi-asserted-by":"publisher","DOI":"10.2174\/1874941001104010006"},{"key":"e_1_3_2_5_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1995.tb02031.x"},{"key":"e_1_3_2_6_1","doi-asserted-by":"publisher","DOI":"10.1177\/0269881116663120"},{"key":"e_1_3_2_7_1","doi-asserted-by":"publisher","DOI":"10.1080\/17470919.2016.1143026"},{"key":"e_1_3_2_8_1","first-page":"5938","article-title":"mlr: Machine Learning in R","volume":"17","author":"Bischl B","year":"2016","unstructured":"Bischl B, Lang M, Kotthoff L, et al. 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