Tabea Schoeler, Jessie R. Baldwin, Ellen Martin, Wikus Barkhuizen, Jean-Baptiste Pingault
{"title":"Assessing rates and predictors of cannabis-associated psychotic symptoms across observational, experimental and medical research","authors":"Tabea Schoeler, Jessie R. Baldwin, Ellen Martin, Wikus Barkhuizen, Jean-Baptiste Pingault","doi":"10.1038/s44220-024-00261-x","DOIUrl":null,"url":null,"abstract":"Cannabis, one of the most widely used psychoactive substances worldwide, can give rise to acute cannabis-associated psychotic symptoms (CAPS). While distinct study designs have been used to examine CAPS, an overarching synthesis of the existing findings has not yet been carried forward. To that end, we quantitatively pooled the evidence on rates and predictors of CAPS (k = 162 studies, n = 210,283 cannabis-exposed individuals) as studied in (1) observational research, (2) experimental tetrahydrocannabinol (THC) studies, and (3) medicinal cannabis research. We found that rates of CAPS varied substantially across the study designs, given the high rates reported by observational and experimental research (19% and 21%, respectively) but not medicinal cannabis studies (2%). CAPS was predicted by THC administration (for example, single dose, Cohen’s d = 0.7), mental health liabilities (for example, bipolar disorder, d = 0.8), dopamine activity (d = 0.4), younger age (d = −0.2), and female gender (d = −0.09). Neither candidate genes (for example, COMT, AKT1) nor other demographic variables (for example, education) predicted CAPS in meta-analytical models. The results reinforce the need to more closely monitor adverse cannabis-related outcomes in vulnerable individuals as these individuals may benefit most from harm-reduction efforts. The authors synthesize data from previous literature on observational, experimental and medicinal cannabis research to assess rates and predictors of cannabis-associated psychotic symptoms.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"2 7","pages":"865-876"},"PeriodicalIF":0.0000,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44220-024-00261-x.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature mental health","FirstCategoryId":"1085","ListUrlMain":"https://www.nature.com/articles/s44220-024-00261-x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Cannabis, one of the most widely used psychoactive substances worldwide, can give rise to acute cannabis-associated psychotic symptoms (CAPS). While distinct study designs have been used to examine CAPS, an overarching synthesis of the existing findings has not yet been carried forward. To that end, we quantitatively pooled the evidence on rates and predictors of CAPS (k = 162 studies, n = 210,283 cannabis-exposed individuals) as studied in (1) observational research, (2) experimental tetrahydrocannabinol (THC) studies, and (3) medicinal cannabis research. We found that rates of CAPS varied substantially across the study designs, given the high rates reported by observational and experimental research (19% and 21%, respectively) but not medicinal cannabis studies (2%). CAPS was predicted by THC administration (for example, single dose, Cohen’s d = 0.7), mental health liabilities (for example, bipolar disorder, d = 0.8), dopamine activity (d = 0.4), younger age (d = −0.2), and female gender (d = −0.09). Neither candidate genes (for example, COMT, AKT1) nor other demographic variables (for example, education) predicted CAPS in meta-analytical models. The results reinforce the need to more closely monitor adverse cannabis-related outcomes in vulnerable individuals as these individuals may benefit most from harm-reduction efforts. The authors synthesize data from previous literature on observational, experimental and medicinal cannabis research to assess rates and predictors of cannabis-associated psychotic symptoms.