Danielle Amiet1, George J Youssef2,3, Lauryn J Hagg2, Valentina Lorenzetti4, Linden Parkes5, Nadia Solowij6,7, Murat Yücel1. 1. BrainPark, School of Psychological Sciences and Monash Biomedical Imaging Facility, Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia. 2. Centre for Social and Early Emotional Development, School of Psychology, Deakin University, Geelong, VIC, Australia. 3. Centre for Adolescent Health, Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, VIC, Australia. 4. Neuroscience of Addiction & Mental Health Program, Healthy Brain and Mind Research Centre, Faculty of Health Sciences, School of Behavioural & Health Sciences, Australian Catholic University, Melbourne, VIC, Australia. 5. Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA, United States. 6. School of Psychology and Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, NSW, Australia. 7. The Australian Centre for Cannabinoid Clinical and Research Excellence, New Lambton Heights, NSW, Australia.
Abstract
Background: Young adults regularly using cannabis represent a uniquely vulnerable yet heterogeneous cohort. Few studies have examined user profiles using cannabis use motives and expectations. The association between user profiles and psychosocial functioning among only regular users remains unexplored. This exploration is important to improve public education efforts and design tailor treatment approaches. Methods: Regular cannabis users (at least weekly; n = 329) completed an online survey via Amazon Mechanical Turk. The survey measured levels of cannabis use, other substance use, motives and expectations of cannabis use, symptoms of psychosis, depression, anxiety and stress, and reckless behavior such as getting high before work or driving under the influence of cannabis. Latent class analysis was performed using motives and expectations to identify data driven patterns of regular cannabis use. Classes were then used to investigate mental health and behavioral correlates of differences in motives and expectations. Results: A 2-class solution provided the best fit to the data; Class 1: Low Motives and Expectancies (n = 158) characterized by lower endorsement across all motivation and expectation variables, and Class 2: High Motives and Expectancies (n = 171) characterized by endorsing multiple motivations, and higher positive and negative expectations of cannabis use. Classes differed in a range of cannabis use variables; e.g., greater proportion of peer use in Class 2. The High Motives and Expectancies users reported higher symptoms of psychosis (positive and negative symptoms), depression, anxiety, and stress. A higher proportion met the criteria for a cannabis use disorder compared with Low Motives and Expectancies users. High Motives and Expectancies users reported higher mean problems with nicotine dependence and illicit drug use other than cannabis and were more likely to get high before work and drive under the influence of cannabis. Conclusions: There is heterogeneity among young regular cannabis users in their motivations and expectancies of use and associated psychosocial functioning. Understanding motives and expectancies can help segregate which users are at higher risk of worse functioning. These findings are timely when designing targeted assessment and treatment strategies, particularly as cannabis is further decriminalized and accessibility increases.
Background: Young adults regularly using cannabis represent a uniquely vulnerable yet heterogeneous cohort. Few studies have examined user profiles using cannabis use motives and expectations. The association between user profiles and psychosocial functioning among only regular users remains unexplored. This exploration is important to improve public education efforts and design tailor treatment approaches. Methods: Regular cannabis users (at least weekly; n = 329) completed an online survey via Amazon Mechanical Turk. The survey measured levels of cannabis use, other substance use, motives and expectations of cannabis use, symptoms of psychosis, depression, anxiety and stress, and reckless behavior such as getting high before work or driving under the influence of cannabis. Latent class analysis was performed using motives and expectations to identify data driven patterns of regular cannabis use. Classes were then used to investigate mental health and behavioral correlates of differences in motives and expectations. Results: A 2-class solution provided the best fit to the data; Class 1: Low Motives and Expectancies (n = 158) characterized by lower endorsement across all motivation and expectation variables, and Class 2: High Motives and Expectancies (n = 171) characterized by endorsing multiple motivations, and higher positive and negative expectations of cannabis use. Classes differed in a range of cannabis use variables; e.g., greater proportion of peer use in Class 2. The High Motives and Expectancies users reported higher symptoms of psychosis (positive and negative symptoms), depression, anxiety, and stress. A higher proportion met the criteria for a cannabis use disorder compared with Low Motives and Expectancies users. High Motives and Expectancies users reported higher mean problems with nicotine dependence and illicit drug use other than cannabis and were more likely to get high before work and drive under the influence of cannabis. Conclusions: There is heterogeneity among young regular cannabis users in their motivations and expectancies of use and associated psychosocial functioning. Understanding motives and expectancies can help segregate which users are at higher risk of worse functioning. These findings are timely when designing targeted assessment and treatment strategies, particularly as cannabis is further decriminalized and accessibility increases.
Authors: Kara Manning; Lorra Garey; Daniel J Paulus; Julia D Buckner; Julianna B D Hogan; Norman B Schmidt; Michael J Zvolensky Journal: Addict Behav Date: 2018-12-10 Impact factor: 3.913
Authors: Todd C Buckley; Susannah L Mozley; Dana R Holohan; Kate Walsh; Jean C Beckham; Jon D Kassel Journal: Addict Behav Date: 2005-06 Impact factor: 3.913
Authors: Lindsey A Hines; Tom P Freeman; Suzanne H Gage; Stanley Zammit; Matthew Hickman; Mary Cannon; Marcus Munafo; John MacLeod; Jon Heron Journal: JAMA Psychiatry Date: 2020-10-01 Impact factor: 21.596
Authors: Angela K Stevens; Megan M Drohan; Holly K Boyle; Helene R White; Kristina M Jackson Journal: J Stud Alcohol Drugs Date: 2021-11 Impact factor: 2.582