Are cannabis use problems comparable across individuals using for recreational and medical purposes? An international cross-sectional study of individuals who use self-grown cannabis

The aim of the current study was to investigate the concurrent validity of cannabis misuse diagnoses (abuse and/or dependence) on the Composite International Diagnostic Interview (CIDI-Auto 2.1) in 50 relatively low-level cannabis users from the general population. Cannabis misuse diagnoses on the CIDI were compared with Severity of Dependence Scale (SDS) scores indicating the level of cannabis dependence. Participants with cannabis misuse diagnoses had significantly higher SDS scores, and significantly more of them (82%) self-reported daily or weekly cannabis use than participants without such diagnoses. The overall agreement between CIDI-Auto diagnoses and SDS scores was 86%. SDS scores were 3.5 times more likely than chance to predict presence of cannabis misuse diagnoses on the CIDI. Therefore it appears that CIDI-Auto 2.1 assigns cannabis misuse diagnoses to relatively low-level cannabis users from the general population in fair agreement with SDS scores and self-reports of cannabis use.

Dependence scores predict prognosis of medication overuse headache: A prospective cohort from the Akershus study of chronic headache

The severity of dependence score correlates with medication overuse in persons with secondary chronic headaches. The Akershus study of chronic headache

Background: Many studies have employed both direct and indirect methods of measuring the brain dopaminergic activity in relation to drug dependence, internet addiction and other disorders in which dopamine signalling has been implicated. However, only a few scientific reports have found a relationship between plasma dopamine and/or norepinephrine levels and addiction. Objective: The present work was aimed at determining the association between plasma dopamine level and consumption of cannabis as the most widely used illicit drug in the world. Methods: One hundred and six participants with cannabis use disorder based on International Classification of Diseases version 10 (ICD-10) were recruited for the study. Screening for current cannabis use disorder was done using Cannabis Use Disorder Identification Test (CUDIT). Cannabis dependence was assessed using the Severity of Dependence Scale (SDS). Venous blood samples were taken from the subjects to assay for the plasma dopamine by enzyme-linked immunosorbent assay (ELISA) method. Results: There was a high correlation between plasma dopamine and SDS scores with plasma dopamine accounting for more than 31% of the variance in SDS scores. However, the relationship between plasma dopamine and current cannabis use disorder was not strong as it accounts for just more than 9% of the variance in CUDIT scores. There was a relationship found between plasma norepinephrine and SDS scores. Plasma norepinephrine only accounts for about 5% of the variance in SDS score while there was virtually no association between plasma norepinephrine and CUDIT scores. Conclusion: Higher plasma dopamine level was found to be significantly associated with cannabis use and dependence as measured by SDS but less associated with current cannabis use disorder as measured by CUDIT.

Dependence-like behaviour may complicate withdrawal and increase risk of relapse of medication overuse headache (MOH). The most effective treatment for reducing dependence-like behaviour is unknown. To compare patient-reported outcomes among three treatment strategies for MOH. The primary outcome was change in Severity of Dependence Scale (SDS) score from baseline to 6months. Patients with MOH were randomized to (1) withdrawal combined with preventive medication from start (W+P), (2) preventive medication without withdrawal (P), or (3) withdrawal with optional preventive medication 2months after withdrawal (W). At baseline, 2, and 6months, patients filled out SDS (used for measurements of dependence-like behaviour and treatment feasibility), Headache Under-Response of Treatment (HURT) and WHO Quality of Life BREF questionnaires. Out of 120 patients with MOH, 100 completed the 6-month follow-up and filled out questionnaires. The W+P arm was the most effective in treating MOH. After 6months, the SDS score was reduced by 3.69 (95% CI 3.23-4.49) in the W+P arm, by 3.19 (95% CI 2.43-3.96) in the W arm, and by 1.65 (95% CI 0.96-2.33) in the P arm (p=0.04). At baseline and after 2months, the P arm was considered the most feasible treatment, but at 6-month follow-up, there was no difference in feasibility score, change in HURT score, or quality of life. Dependence-like behaviour was reduced most in the two withdrawal arms. Withdrawal combined with preventive medication is recommended for the treatment of MOH. Withdrawal combined with preventive medication from start is the treatment strategy that reduces dependence-like behaviour the most in MOH patients. Patients initially considered preventive treatment without withdrawal as the most feasible treatment. However, no difference in feasibility between the three arms was found at 6-month follow-up. Withdrawal combined with preventive medication is recommended for treatment of MOH.

Effective interventions for cannabis use disorders are fairly limited. The present randomized controlled trial (RCT) aimed to compare the reduction in cannabis use (number of days cannabis used) with brief intervention and simple advice in patients with cannabis use disorder. This non-blinded and parallel two-group RCT included 100 male patients with cannabis use disorder. A semi-structured pro forma and severity of dependence scale (SDS) were used. Participants were then randomized to either of the two arms (brief intervention and simple advice) in a 1:1 ratio. Cannabis use patterns and SDS scores were assessed over the phone at week 4, week 8, and week 12. The two groups were comparable in sociodemographics and cannabis use characteristics. Participants in both groups were using cannabis for 30 days in the past month before enrolment. The brief intervention group had a lesser number of days of cannabis use vis-a-vis the simple advice group at 4, 8, and 12 weeks. There was a significant time effect for change in SDS scores (F = 30.629, P < 0.001), but the group effect was not significant (F = 0.379, P = 0.541). In this population of regular cannabis users, brief intervention may be useful in reducing cannabis usage. It can be integrated into routine assessments and management of those with regular use of cannabis.

Drug dependence, which can exist concurrently with chronic pain, is seen as one of the major causes of rapidly increasing medical expenses. However, drug dependence in patients with chronic pain has not been evaluated. The aim of this study was to identify the risk factors for drug dependence in patients with chronic noncancer pain.This retrospective study included 151 patients with chronic noncancer pain (43 males, 108 females; mean age, 72 years). Low back pain (LBP) occurred in 96 patients, whereas 22 had shoulder pain, 8 had hip pain, and 77 had knee pain. Patients were divided into drug dependence and nondrug dependence groups based on the Severity of Dependence Scale (SDS) scores. Patients with SDS scores ≥5 and <5 were classified into drug dependence and nondrug dependence groups, respectively. All patients completed self-report questionnaires. Factors that predict drug dependence were identified by performing univariate and multivariate analyses.Sixty (40%) of the 151 patients met the SDS criteria for drug dependence. Significant differences were found between patients with and without drug dependence for the LBP, hip pain, number of medications, and for the Numerical Rating Scale, Pain Disability Assessment Scale (PDAS), Hospital Anxiety and Depression Scale, and Pain Catastrophizing Scale (PCS) scores. Multiple regression analysis identified LBP, hip pain, PCS, and PDAS scores as factors related to drug dependence in patients with chronic noncancer pain.Drug dependence tends to differ in patients based on the location of their chronic pain. Pain catastrophizing and disability indicated a greater tendency for drug dependence. Thus, PCS and PDAS scores are useful screening tools for predicting drug dependence in patients with chronic pain.

Background and Aims:Medication-overuse headache (MOH) is a common chronic headache caused by overuse of headache analgesics. It has similarities with substance dependence disorders. The treatment of choice for MOH is withdrawal of the offending analgesics. Behavioral brief intervention treatment using methods adapted from substance misuse settings is effective. Here we investigate the severity of analgesics dependence in MOH using the Severity of Dependence Scale (SDS), validate the SDS score against formal substance dependence diagnosis based on the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) and examine whether the SDS predicts successful withdrawal.Methods:Representative recruitment from the general population; 60 MOH patients, 15 chronic headache patients without medication overuse and 25 population controls. Headaches were diagnosed using the International Classification of Headache Disorders, medication use was assessed and substance dependence classified according to the DSM-IV. The SDS was scored by interviewers blinded to patient group. Descriptive statistics were used and validity of the SDS score assessed against a substance dependence diagnosis using ROC analysis.Results:Sixty-two percent of MOH patients overused simple analgesics, 38% centrally acting analgesics (codeine, opiates, triptans). Fifty percent of MOH patients were classified as DSM-IV substance dependent. Centrally active medication and high SDS scores were associated with higher proportions of dependence. ROC analysis showed SDS scores accurately identified dependence (area under curve 88%). Lower SDS scores were associated with successful withdrawal (P = 0.004).Conclusions:MOH has characteristics of substance dependence which should be taken into account when choosing treatment strategy.Trial registration:Based on data collected in previously reported randomized BIMOH trial (Kristoffersen et al., 2012; Kristoffersen et al., 2015 in the present manuscript, Clinical trials registration number: NCT01314768). The present part, however, represents observational data and is not a treatment trial.

The 2018 Cannabis Act legalizing the production, sale, and use of cannabis for non-medical purposes renewed interest in the importance of ongoing and more detailed monitoring of cannabis consumption and consequences. Some cannabis users will experience impaired control over their use of cannabis, putting them at risk for cannabis use disorder (CUD, sometimes called addiction) and other harms. Including the Severity of Dependence Scale (SDS) in the annual Canadian Community Health Survey (CCHS) would allow for monitoring of one of the more harmful consequences of cannabis use in the post-legalization period. Data from the nationally representative 2019-2020 CCHS were used to examine cannabis consumers with and without impaired control. Respondents who used cannabis in the past year were categorized according to their SDS scores: those with impaired control (SDS ≥ 4) versus those without impaired control (SDS < 4). Cross-tabulations were used to examine the sociodemographic, mental health, health behaviour and cannabis exposure characteristics of those with impaired control. Multivariable logistic regression models assessed associations between these characteristics and the risk of impaired control. The prevalence of self-reported cannabis-related problems experienced by consumers-with and without impaired control-is also presented. In 2019-2020, 4.7% of past-year cannabis consumers scored ≥ 4 on the SDS and were considered to have impaired control. Multivariable logistic regression suggested that the odds of having impaired control remained higher for people who were male, were aged 18 to 24 years, were single or never married, were from lower-income households, were diagnosed with an anxiety or a mood disorder, started consuming cannabis at age ≤ 15, and consumed at least monthly. A better understanding of the characteristics of cannabis consumers experiencing impaired control (a correlate of future CUD or addiction) could help with the development of more effective education, prevention and treatment strategies.

Objective:Prior literature has documented how motives for cannabis use predict frequency of use and cannabis use problems among adolescents. However, few studies have examined possible moderating variables that may influence the association between cannabis use motives and frequency of use. The current study examines how risky decision-making moderates this association to help better understand which individuals are at greater risk for cannabis use escalation. The current study will be the first to examine the interactive effects of motives for cannabis use (i.e., health or recreational reasons) and risky decision-making on cannabis use trajectories among a sample of adolescent cannabis users.Participants and Methods:Data from 194 adolescent cannabis users aged 14–17 at baseline were analyzed as part of a larger longitudinal study. Participants included those who self-reported use of cannabis within six months prior to the baseline assessment. The Marijuana Reasons for Use Questionnaire (MJRUQ) was used to assess motives for cannabis use from a list of 13 items. A confirmatory factor analysis identified “health” and “recreational” factors for motives for cannabis use. Lifetime frequency of cannabis use (number of days used) was assessed through the Drug Use History Questionnaire, while risky decision-making was assessed using the Game of Dice Task. We used latent growth curve modeling and linear regression analyses to examine the interactive effects of motives for cannabis use and risky decision-making on initial levels of lifetime cannabis use at baseline, and rate of cannabis use escalation over time.Results:No significant interactive effects were found for health motives for cannabis use; however, we found significant main effects of health motives on initial levels of lifetime cannabis use at baseline (b = 100.82, p &lt; .01) and rate of cannabis use escalation (b = 24.79, p &lt; .01). Those with a greater proclivity to use cannabis for health purposes showed higher initial levels of lifetime use at baseline and steeper increases in the rate of cannabis use escalation relative to those less likely to use for health purposes. Furthermore, we found a significant interactive effect of recreational motives for use and risky decision-making on the rate of cannabis use escalation (b = -2.53, p &lt; .01). Follow-up analyses revealed that among those less likely to use cannabis for recreational purposes, higher risky decision-making was associated with a steeper increase in the rate of cannabis use escalation relative to those who exhibited lower risky decision-making.Conclusions:The current study replicated findings suggesting that cannabis use motives influence cannabis use trajectories. We found that using cannabis primarily for health reasons was associated with higher initial levels and steeper increases in use regardless of decision-making. Furthermore, we found that both motives for use and risky decision-making interacted to influence associations with cannabis use trajectories. Specifically, among individuals reporting less cannabis use for recreational reasons, those with relatively riskier decision-making showed steeper increases in the rate of cannabis use escalation. These findings inform prevention and intervention practices that focus on decision-making by tailoring approaches based on an individual’s primary motives for cannabis use.

TaqI A polymorphism (rs1800497) has been linked to many substance use disorders but there is a shortage of data on cannabis use disorder. Nigeria has a huge burden of cannabis use disorder, prompting our investigation of the relation between cannabis use disorder and the TaqI A polymorphism among males in Lagos, Nigeria. We recruited 106 males with cannabis use disorder based on International Classification of Diseases, version 10 (ICD-10) and 98 cannabis-naive males for the study. Cannabis use disorder was assessed using the Severity of Dependence Scale (SDS) and Cannabis Use Disorder Identification Test (CUDIT). Genotyping was done using the Restriction Fragment Length Polymorphism (RFLP). The frequency of the A1 allele was higher among the cannabis users (57.8%) compared with the nonusers (42.2%). The genotype distribution was found to be in Hardy-Weinberg equilibrium in both populations. The homozygous A1 genotype alone contributed 11.8% to the variance in the SDS scores. However, both A1/A1 and A1/A2 genotypes contributed to the variance in the CUDIT scores (10.2% and 5.1%, respectively). In conclusion, the distribution of the A1 allele among the general population in this study correlates with the previously reported findings in a southwestern Nigerian population. We also found that carrying an A1 allele appears to be a significant predictor of cannabis use disorder. The result suggests that carrying just a single allele of the A1 is enough to predict cannabis abuse, as shown by the allele association with CUDIT scores. However, double A1 alleles seem to be necessary for the prediction of dependence.

BackgroundPrevalence rates for lifetime cannabis use and cannabis use disorder are much higher in people with attention deficit/hyperactivity disorder than in those without. CANreduce 2.0 is an intervention that is generally effective at reducing cannabis use in cannabis misusers. This self-guided web-based intervention (6-week duration) consists of modules grounded in motivational interviewing and cognitive behavioral therapy.ObjectiveWe aimed to evaluate whether the CANreduce 2.0 intervention affects cannabis use patterns and symptom severity in adults who screen positive for attention deficit/hyperactivity disorder more than in those who do not.MethodsWe performed a secondary analysis of data from a previous study with the inclusion criterion of cannabis use at least once weekly over the last 30 days. Adults with and without attention deficit/hyperactivity disorder (based on the Adult Attention deficit/hyperactivity disorder Self-Report screener) who were enrolled to the active intervention arms of CANreduce 2.0 were compared regarding the number of days cannabis was used in the preceding 30 days, the cannabis use disorder identification test score (CUDIT) and the severity of dependence scale score (SDS) at baseline and the 3-month follow-up. Secondary outcomes were Generalized Anxiety Disorder score, Center for Epidemiological Studies Depression scale score, retention, intervention adherence, and safety.ResultsBoth adults with (n=94) and without (n=273) positive attention-deficit/hyperactivity disorder screening reported significantly reduced frequency (reduction in consumption days: with: mean 11.53, SD 9.28, P<.001; without: mean 8.53, SD 9.4, P<.001) and severity of cannabis use (SDS: with: mean 3.57, SD 3.65, P<.001; without: mean 2.47, SD 3.39, P<.001; CUDIT: with: mean 6.38, SD 5.96, P<.001; without: mean 5.33, SD 6.05, P<.001), as well as anxiety (with: mean 4.31, SD 4.71, P<.001; without: mean 1.84, SD 4.22, P<.001) and depression (with: mean 10.25, SD 10.54; without: mean 4.39, SD 10.22, P<.001). Those who screened positive for attention deficit/hyperactivity disorder also reported significantly decreased attention deficit/hyperactivity disorder scores (mean 4.65, SD 4.44, P<.001). There were no significant differences in change in use (P=.08), dependence (P=.95), use disorder (P=.85), attention deficit/hyperactivity disorder status (P=.84), depression (P=.84), or anxiety (P=.26) between baseline and final follow-up, dependent on positive attention-deficit/hyperactivity disorder screening. Attention deficit/hyperactivity disorder symptom severity at baseline was not associated with reduced cannabis use frequency or severity but was linked to greater reductions in depression (Spearman ρ=.33) and anxiety (Spearman ρ=.28). Individuals with positive attention deficit/hyperactivity disorder screening were significantly less likely to fill out the consumption diary (P=.02), but the association between continuous attention deficit/hyperactivity disorder symptom severity and retention (Spearman ρ=−0.10, P=.13) was nonsignificant. There also was no significant intergroup difference in the number of completed modules (with: mean 2.10, SD 2.33; without: mean 2.36, SD 2.36, P=.34), and there was no association with attention deficit/hyperactivity disorder symptom severity (Spearman ρ=−0.09; P=.43). The same was true for the rate of adverse effects (P=.33).ConclusionsCannabis users screening positive for attention deficit/hyperactivity disorder may benefit from CANreduce 2.0 to decrease the frequency and severity of cannabis dependence and attenuate symptoms of depression and attention deficit/hyperactivity disorder-related symptoms. This web-based program’s advantages include its accessibility for remote users and a personalized counselling option that may contribute to increased adherence and motivation to change among program users.Trial RegistrationInternational Standard Randomized Controlled Trial Number (ISRCTN) 11086185; http://www.isrctn.com/ISRCTN11086185

The Severity of Dependence Scale (SDS) was devised to provide a short, easily administered scale which can be used to measure the degree of dependence experienced by users of different types of drugs. The SDS contains five items, all of which are explicitly concerned with psychological components of dependence. These items are specifically concerned with impaired control over drug taking and with preoccupation and anxieties about drug use. The SDS was given to five samples of drug users in London and Sydney. The samples comprised users of heroin and users of cocaine in London, and users of amphetamines and methadone maintenance patients in Sydney. The SDS satisfies a number of criteria which indicate its suitability as a measure of dependence. All SDS items load significantly with a single factor, and the total SDS score was extremely highly correlated with the single factor score. The SDS score is related to behavioural patterns of drug taking that are, in themselves, indicators of dependence, such as dose, frequency of use, duration of use, daily use and degree of contact with other drug users; it also shows criterion validity in that drug users who have sought treatment at specialist and non-specialist agencies for drug problems have higher SDS scores than non-treatment samples. The psychometric properties of the scale were good in all five samples, despite being applied to primary users of different classes of drug, using different recruitment procedures in different cities in different countries.

The Severity of Dependence Scale (SDS) in an adolescent population of cannabis users: Reliability, validity and diagnostic cut-off

Cannabis remains the most widely used illicit drug among Nigerians, often associated with psychiatric disorders. Since genetic predisposition has been implicated in substance use disorders, we, therefore, aimed at finding out the relationship between dopamine transporter gene (DAT1) polymorphism and cannabis use disorder. We recruited 104 patients from a tertiary psychiatric facility in Lagos, Nigeria, who were diagnosed with cannabis use disorder according to ICD-10 and 96 non-smokers as a comparative group. The smokers were screened with Cannabis Use Disorder Identification Test (CUDIT), and cannabis dependence was assessed with the Severity of Dependence Scale (SDS). Genotyping was carried out for the 40 bp 3' UTR VNTR of the DAT1 (rs28363170). The frequencies of 9R/9R, 9R/10R, 10R/10R among non-smokers and smokers were 14 (14.3%), 25 (26.2%), 57 (59.5%) and 17 (16.3%), 54 (51.9%), 33 (31.7%) respectively. The genotype distribution was in Hardy Weinberg equilibrium (HWE) only in the smokers' population (χ² = 1.896, P = .166). Individuals with the 10R allele were almost twice as likely as the 9R carriers to smoke cannabis (OR = 1.915, 95% CI: 1.225-2.995). However, this polymorphism was not associated with the quantity of cannabis smoked, age at onset of smoking, CUDIT, and SDS scores. The DAT VNTR polymorphism was associated with cannabis smoking but not cannabis use disorder.