Persistent increased severity of cannabis use disorder symptoms in adolescents compared to adults: a one-year longitudinal study

Cannabis is used by over 200 million individuals globally, with 4% of the global population reporting use in the past year [1]. This rate is higher in younger people, with 5.8% of 15–16-year-olds reporting past-year use. Regular use of cannabis can lead to a pattern of symptoms causing clinically significant impairment or distress, known as cannabis use disorder (CUD, [2]). DSM-5 criteria for CUD include unsuccessful reduction or quit attempts, cannabis use interfering with daily obligations, worsening mental or physical health, using cannabis in physically hazardous situations, as well as experience of craving, tolerance, and withdrawal symptoms. Early cannabis use is associated with negative outcomes such as poorer mental health and sociodemographic disadvantage in adulthood [3‐5]. Furthering our understanding of the consequences of early cannabis use is therefore crucial to trying to reduce the incidence of CUD in adolescence and improve wellbeing during and beyond the adolescent period.

Adolescence is a key developmental period characterised by an increased risk of CUD amongst those who use cannabis. Research has indicated that using cannabis in adolescence is associated with an approximately 3 times increased risk of having CUD compared to using cannabis during adulthood (typically considered as > 18 or > 21; [6‐8]), even in samples with the same frequency of use [7, 8]. Further, earlier age-of-onset of cannabis use is associated with an increased risk of having CUD in adulthood [9‐13]. However, previous studies comparing adolescent and adult CUD symptoms have had two main limitations. Firstly, evidence for increased risk of CUD in adolescents has typically not accounted for measures of cannabis use. This means that estimates for increased risk of CUD in previous studies may have been inflated due to increased levels of cannabis use in adolescents compared to adults.

The current investigation uses longitudinal data from the CannTeen study, a 12-month observational study developed to provide a direct comparison of adults and adolescents who use cannabis, matched for gender and baseline days per week of cannabis use. Previously published cross-sectional comparisons at baseline replicated previous findings, with a 3.5 times greater risk of severe CUD (measured using DSM-5 criteria) in adolescents, after adjustment for gender, socioeconomic status, risk taking, daily smoking, alcohol use disorder, and other drug use [7].

Adults and adolescents in CannTeen used cannabis at the same frequency at baseline (mean = 4 days per week), but recent research developments have suggested necessary improvements to the measurement of cannabis use [14, 15]. A ‘standard THC unit’ of 5mg THC, the primary psychoactive component of cannabis, has been proposed as a novel measure of cannabis quantity that can be applied to all cannabis products and methods of administration. The standard THC unit has been endorsed by the US National Institutes of Health, and all investigators funded by these institutes are currently required to report research using the standard THC unit in replicable research studies. The standard THC unit can provide rich data on THC dose by incorporating information on potency, frequency, and quantity, all of which are associated with CUD [16‐20]. Standard THC units can be assessed using an enhanced cannabis timeline follow-back method (EC-TLFB [21]). The EC-TLFB has been validated in the CannTeen study, with standard THC units showing the strongest validity of all cannabis use measures assessed [21]. It is unclear whether adolescents typically consume more cannabis than adults in an average day of use, which could have influenced their assumed increased vulnerability to CUD in previous studies. Therefore, the current study uses standard THC units as the measurement of cannabis quantity to detect more nuanced differences in profiles of cannabis use across age groups and to identify whether this affects the likelihood of experiencing problems with cannabis use.

Secondly, comparisons have been mostly based on cross-sectional data. Longitudinal analyses are needed to strengthen evidence for the association between age and risk of CUD and to determine the time course of age-related risk. Previous literature has indicated different patterns of CUD that can occur over time, including the adolescent period [21‐24]. Studies have reported subgroups who have CUD symptoms that eventually remiss, and subgroups with CUD that increase in severity [21‐23]. Younger people may be more likely to have patterns of increasing cannabis use and transition to dependence than older people who use cannabis [25]. To our knowledge, no previous investigations have compared CUD symptoms in adults and adolescents (matched on frequency of cannabis use) longitudinally. Furthermore, the CannTeen study assessed participants at 3-monthly intervals, allowing for a detailed investigation of CUD symptoms as well as cannabis use over a short period which might reduce recall bias and improve accuracy of measurement, and to potentially pick up on shorter-term variation in use.

Here, we present data from a one-year longitudinal study on CUD symptoms in adults and adolescents who use cannabis from the CannTeen dataset. Research questions and hypotheses were pre-registered on the Open Science Framework prior to analyses (https://​osf.​io/​v2afh). We hypothesised that adolescents would show a different pattern of CUD symptoms to adults, characterised by more severe CUD symptoms across the 12 months. We also hypothesised that statistical associations between age, time, and CUD symptoms would be partially attenuated but persist after adjustment for THC units.

In this one-year, longitudinal investigation of adolescents and adults who use cannabis, we found that adolescents (aged 16–17) scored on average 3.7 points higher on the CUDIT-R than adults (aged 26–29) across all 5 assessment waves (3.68, 95% CIs 1.81, 5.56). This effect was only partially attenuated after adjustment for gender, COVID-19, and mean weekly standard THC units (3.66 95% CIs 1.99, 5.34). CUD symptoms decreased linearly over the year in both age groups (−0.47, 95%CIs −0.67, −0.27). Through the use of a longitudinal study with five assessment waves, and a comprehensive standardised assessment of cannabis exposure, these findings show that the increased number of CUD symptoms that have been observed in adolescents persists over 12 months and is robust after adjustment for variation in THC dose.

Evidence of the persistence of increased levels of CUD symptoms in adolescents compared to adults across the 12-month period builds on previous cross-sectional comparisons of the likelihood of CUD by current age [6‐8, 29, 30]. To our knowledge, the current study is the first such longitudinal comparison of adult and adolescent symptoms. This study is important because longitudinal comparisons can provide higher quality of evidence than cross-sectional comparisons. Furthermore, they can provide insight into the time course of such associations. The findings indicate that this is a persistent effect over a year, highlighting the need for a comprehensive evaluation of the impact of cannabis use on adolescent health and wellbeing. Adolescents often endorsed items related to cannabis affecting their general functioning, including failing to meet obligations and dedicating a lot of time to cannabis use. This indicates that the use of cannabis at this age has the potential to disrupt adolescents’ personal or academic lives, which could result in difficulties with educational outcomes and transitions into adulthood [31]. Given these findings, it is crucial that appropriate healthcare resources are available for this age group; however, the transition from child (< 18) to adult (> 18) health services can be challenging, and there is a risk of young people falling through the cracks [32]. Our findings add weight to the idea of integrated young peoples’ services covering a wider age range (e.g., 12 to 25). Further avenues of support could include education and harm reduction advice tailored for young people, as well as public health/policy-related changes to reduce stigma and barriers related to treatment seeking for cannabis-related support and increasing accessibility of support for young people [33]. Additionally, there was a linear decrease in CUD symptoms over time in both groups. This could be an indication of ‘maturing out’ from CUD [34]. However, longer follow-up periods would be necessary to demonstrate robust changes in CUD symptoms such as long-term remission. Furthermore, group means on the CUDIT-R were still elevated in both groups at the 12-month follow-up. By including longer follow-ups, such studies could provide valuable insight into the course of adolescent risk of CUD.

Some previous investigations have used samples with matched or similar levels of cannabis frequency [7, 8]; however, most do not consider cannabis quantity. Cannabis use profile (including frequency, quantity, and potency of use) has been consistently linked to the risk of CUD [18‐20], and adolescents may use higher quantities of cannabis than adults. Therefore, not accounting for this could have led to overinflation of estimates of risk in adolescents. The current analysis used a novel measurement of cannabis quantity, the THC unit (5mg THC). Here, we found that adolescents did report greater cannabis use using this measure that incorporates quantity, frequency, and potency. However, adjusting for this in models did not substantially alter the main effect of a greater number of symptoms in adolescents, indicating that increased cannabis use in adolescents was not primarily responsible for the increased CUD symptoms.

The current analysis investigated two important factors related to CUD: current age, and profile of cannabis use. However, there are several other factors that might influence the relationship between cannabis use during adolescence and CUD symptoms that were not accounted for in the main analysis model. For example, CUD often co-occurs with other mental health disorders and other substance use disorders [31, 35]. We chose not to adjust for this in the primary analysis due to concerns over the direction of causality, given that other mental health disorders could either act as a mediator of the relationship between adolescent cannabis use and CUD symptoms or as a common cause of both [36]. However, in an exploratory sensitivity analysis, we added mental health and other drug use to the model, and adolescents still scored on average 3.1 points higher on the CUDIT-R than adults. This provides more support for the role of adolescent vulnerability to CUD, as this will account for more relevant confounders. However, other factors could still confound the relationship between adolescent frequent cannabis use and CUD [37]. For example, we were unable to account for genetic risk factors that may have differed between the adolescent and adult groups. Further studies with larger sample sizes will be needed to provide adequate power to adjust for a more comprehensive set of potential confounds, to increase precision when estimating the risk of CUD in adolescents compared to adults.

Strengths of this study include its longitudinal design with five assessment waves, the use of a validated outcome variable (CUDIT-R score), and a comprehensive standardised assessment of THC exposure validated in this sample [21]. The current findings should be considered in the light of several limitations. Firstly, the study was limited to only a 12-month follow-up duration, restricting the conclusions that can be drawn about longer-term CUD across adolescence and into adulthood. Furthermore, the measurement of CUD symptoms was the CUDIT-R, rather than the diagnostic DSM-5 clinical interview. However, at the baseline assessment, mean CUDIT-R scores increased across DSM-5 severity classifications (see Online Resource, Fig. 1). The CUDIT-R has not been validated for use over periods shorter than 6 months and, therefore, this may have induced unintended consequences. For example, it could be that assessment over a shorter period of time influences cannabis use in some way. However, there was no indication that this had a different effect on either age group given the lack of time by age interaction on CUDIT-R scores. Our finding of reduced CUDIT-R symptoms across groups could be in part due to the influence of being part of this longitudinal study. Repeated assessment of the CUDIT-R as well as administration of the TLFB to assess drug use may have in some way acted as an intervention (e.g., due to increased self-monitoring of drug use), bringing participants’ attention to their cannabis use and encouraging reduction of use. Another consideration is whether instruments assessing CUD symptoms are appropriate for comparison across age groups. The CUDIT-R has been implemented in adolescent samples previously; however, little research has investigated measurement invariance of CUD assessments, a key assumption underlying comparison of age groups, and therefore this should be considered a necessary avenue for future research into adolescent/adult comparisons.

Additionally, whilst standard THC units can estimate the dose for all cannabis products and methods of administration, they may be influenced by participant error in reporting (e.g., estimation of grams). However, estimated standard THC units using these methods were associated with objectively verified THC exposure (THC:COOH/creatinine) with a large effect size (r = 0.52), with a stronger correlation than any other measure of cannabis use from the CannTeen dataset [21]). Our estimates of cannabis potency were based on available UK seizure data [29]. Cannabinoid potency testing can potentially be biased due to degradation in sample quality prior to testing for cannabinoid testing, which could lead to underestimates of the recorded THC concentration [38]. However, in the investigation of UK seizure data researchers found that CBN concentrations were low in their samples and this was not related to the length of time the samples were in storage for, with the authors indicating that these samples were a fair representation of the original seized materials [29].

Additionally, the sample size was modest and not sampled to be representative of the general population of people who use cannabis due to inclusion criteria around use. This enabled purposeful sampling of matched groups of adolescents and adults who use cannabis at the same high, mean frequency to increase the meaningfulness of comparisons. This approach can be considered advantageous to population cohort studies, as the prevalence of regular adolescent cannabis use in the general population is rare resulting in small sample sizes. Additionally, greater levels of cannabis use in adolescence than in adulthood could lead to overestimates of adolescent risk. Therefore, purposively sampling matched adult and adolescent groups can overcome these limitations. However, because of this sampling approach, these findings may not be representative of CUD risk in people who use cannabis less than weekly.

Criteria for the adult group to have had minimal cannabis use under age 18 means that they are likely not representative of the average adult who uses cannabis and are likely to differ from the adolescent group on other variables related to CUD. This design was chosen to isolate the effects of adolescent cannabis use compared to those from adult use, to investigate whether cannabis is associated with more harm when used frequently in adolescence. Given our inclusion criteria for adult participants to have no regular use of cannabis before the age of 18, our adult and adolescent groups varied based on their reported age of first cannabis use. As a sensitivity analysis, we included the age of first use as a covariate in the models, which did not substantially alter the pattern of results (see Online Resource, Table 5). Furthermore, the CannTeen sample was limited to those in the London area, and those willing to take part in a study with relatively frequent assessments and therefore high levels of engagement. The findings from this study should be viewed in the light of this.

These findings add to a wider literature on adolescent vulnerability to CUD, predominantly comprised of large-scale surveys. These research designs tend to have good statistical power to adjust for important confounding factors, but they typically lack detailed data on participants’ cannabis use and are mostly cross sectional. The current study therefore adds to the literature by examining the one-year course of CUD symptoms, adjusting for a detailed assessment of cannabis use and other relevant covariates. However, the clinical meaning of the current observed difference in CUDIT-R scores is yet to be determined, as we are not aware of work that has assessed the clinical meaning of CUDIT-R scores. Lived experience feedback from people who use and support those who use cannabis, including from adolescents themselves, is needed to further establish the implications of these findings.

In conclusion, the current study provides the first evidence of longitudinal persistence of increased severity of CUD in adolescents compared to adults, with adolescents on average scoring 3.7 points higher on a measure of CUD symptoms, over one year. This pattern of results remained after adjustment for a comprehensive measure of cannabis quantity. This study indicates the increased risk of CUD symptoms in adolescents and provides evidence to support the importance of delaying or minimising the use of cannabis during this developmental period.