A review investigating the relationship between cannabis use and adolescent cognitive functioning

Cyrus, Elena; Coudray, Makella; Kiplagat, Sandra; Mariano, Yandra; Noel, Ines; Galea, Jerome T; Hadley, Dexter; Dévieux, Jessy G.; Wagner, Eric F.

doi:10.1016/j.copsyc.2020.07.006

Cited by 36 publications

(15 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although one cannot interpret null effects, it is possible that lower EF is a risk factor specifically for more frequent cannabis use, rather than infrequent use or “experimentation.” Furthermore, this finding mirrors prior cross-sectional studies that have found lower EF to be related to greater cannabis use frequency in adolescents, young adults, and adults (Block et al, 2022; Castellanos-Ryan et al, 2017; Dahlgren et al, 2016; Gruber et al, 2012; Lahanas & Cservenka, 2019; Lisdahl & Price, 2012). It is worth noting that frequent cannabis use in adolescence and young adulthood have been associated with various negative outcomes, including poorer cognitive functioning (Cyrus et al, 2021; Scott et al, 2018), decreased academic performance (Cyrus et al, 2021), higher levels of other substance use and substance use-related problems (Chan et al, 2021; Foster et al, 2018), and alterations in brain function and development (Blest-Hopley, Colizzi, et al, 2020; Blest-Hopley, Giampietro, et al, 2020). As such, child EF may serve as an important target for interventions aimed at preventing, delaying, or decreasing frequent cannabis use.…”

Section: Discussionmentioning

confidence: 99%

Ratings of executive function as a risk factor for adolescents’ frequent cannabis use: A prospective longitudinal study.

Cavalli¹,

Cservenka²,

Kerr³

et al. 2023

Psychology of Addictive Behaviors

View full text Add to dashboard Cite

Objective: We examined the extent to which behavioral ratings of children's executive function (EF) in early adolescence predicted adolescents' cannabis use, and whether associations were independent of parents' cannabis and alcohol use and adolescents' alcohol use. Method: Participants were 198 offspring (44% boys) of 127 mothers and 106 fathers. Parents and teachers completed the Behavior Rating Inventory of Executive Function (BRIEF) at ages 11-14 years. Youth were interviewed repeatedly from ages 14 to 20 years regarding frequency of cannabis and alcohol use. Two-level models regressed dichotomous cannabis outcomes (annual, weekly, or daily use) on age at the within-person level and the random intercept of cannabis use on EF, parent substance use, and covariates (age 7 IQ indicators, child gender, parent education, and mean of ages assessed) at the between-person level. Results: Poorer child EF predicted significantly ( p < .05) higher likelihood of weekly (b[SE] = .64[.24]) and daily (b[SE] = .65[.25]), but not annual (b[SE] = .38[.22]), cannabis use. Parent cannabis use (b[SE] = .53[.25] to .81[.39], p < .05) independently predicted all three outcomes, and effects were distinct from those explained by parent alcohol use (b[SE] = .66[.29] to .81[.35], p < .05). EF remained a significant predictor of weekly and daily cannabis use after adjusting for parental alcohol and cannabis use, and adolescents' alcohol use. Conclusions: Children exhibiting poorer EF were more likely to use cannabis weekly and daily in later adolescence.Whereas literature suggests poorer EF may be a consequence of cannabis use, these findings suggest EF should be considered prior to cannabis use initiation. EF during childhood may be a fruitful prevention target. Public Health Significance StatementThis study shows that older children with poorer executive function (EF)-a subset of cognitive abilities that continue developing into early adulthood-are more likely to use cannabis during adolescence and to do so weekly or daily. This is important because prior research has suggested poorer EF is a consequence of cannabis use, whereas this study indicates poorer EF may occur before youth have even tried cannabis.

show abstract

Section: Discussionmentioning

confidence: 99%

Ratings of executive function as a risk factor for adolescents’ frequent cannabis use: A prospective longitudinal study.

Cavalli¹,

Cservenka²,

Kerr³

et al. 2023

Psychology of Addictive Behaviors

View full text Add to dashboard Cite

show abstract

“…Generally, due to more craving in the CUD group, reappraisal strategies may become more difficult. Another reason could be that drug use can interrupt cognitive and executive function ( Cyrus et al, 2021 , Dolcos et al, 2011 , Núñez et al, 2016 ). Therefore, due to these cognitive changes, the use of reappraisal strategies occurs less in the CUD group.…”

Section: Discussionmentioning

confidence: 99%

A discriminant analysis model of psychosocial predictors of problematic Internet use and cannabis use disorder in university students

Akbari¹,

Bahadori²,

Mohammadkhani³

et al. 2021

Addictive Behaviors Reports

View full text Add to dashboard Cite

Highlights A discriminant analysis model of psychosocial factors was devised to differentiate between PIU and CUD. Compared to the control group, the PIU group had higher scores on motor, attentional and non-planning impulsiveness; tolerance of frustration, emotional pain, and ambiguity; negative and positive metacognitions, need to control thoughts, and cognitive confidence; and RNT. Compared to the control group, the CUD group had lower scores on family and significant other support; and had higher scores on motor and non-planning impulsiveness; tolerance of frustration, emotional pain, and ambiguity; suppression; need to control thoughts; and RNT. Social support, tolerance of physical discomfort, reappraisal, and cognitive confidence play a significant role in discriminating PIU and CUD. The classification analysis results showed that 68.8% of the control group, 70.8% of the PIU group, and 81.3% of the CUD group were correctly classified in their respective groups based on the predictor variables.

show abstract

“…It is reported that cannabis (marijuana) accounts for more than half of all drug-related offences globally (UNODC, 2020a). Additionally, cannabis is reported as the most widely consumed psychoactive substance worldwide, especially in developed countries, for medical, recreational (Ajayi & Somefun, 2020; Alasmari, 2013; Cyrus et al, 2020), and other purposes. However, new psychotropic substances (NPS) are reported to be on the rise (UNODC, 2020a).…”

Section: Related Literaturementioning

confidence: 99%

A Model for Predicting the Class of Illicit Drug Suspects and Offenders

Atsa’am

Balogun

Agjei

et al. 2021

Journal of Drug Issues

View full text Add to dashboard Cite

In this study, the artificial neural network was deployed to develop a classification model for predicting the class of a drug-related suspect into either the drug peddler or non-drug peddler class. A dataset consisting of 262 observations on drug suspects and offenders in central Nigeria was used to train the model which uses parameters such as exhibit type, suspect’s age, exhibit weight, and suspect’s gender to predict the class of a suspect, with a predictive accuracy of 83%. The model sets the pace for the implementation of a full system for use at airports, seaports, police stations, and by security agents concerned with drug-related matters. The accurate classification of suspects and offenders will ensure a faster and correct reference to the sections of the drug law that correspond to a particular offence for appropriate actions such as prosecution or rehabilitation.

show abstract

A review investigating the relationship between cannabis use and adolescent cognitive functioning

Cited by 36 publications

References 38 publications

Ratings of executive function as a risk factor for adolescents’ frequent cannabis use: A prospective longitudinal study.

Ratings of executive function as a risk factor for adolescents’ frequent cannabis use: A prospective longitudinal study.

A discriminant analysis model of psychosocial predictors of problematic Internet use and cannabis use disorder in university students

A Model for Predicting the Class of Illicit Drug Suspects and Offenders

Contact Info

Product

Resources

About