Abstract Background Attention-deficit/hyperactivity disorder (ADHD) is associated with substance use and substance use disorders (SUD). However, relatively little is known about the relationship ...between DSM-IV ADHD subtypes and substance use or DSM-IV abuse/dependence in epidemiological samples. Methods Data were obtained from the National Epidemiologic Survey of Alcohol and Related Conditions (NESARC, N = 33,588). Respondents reported on ADHD symptoms (DSM-IV) for the period of time when they were 17 years or younger. Lifetime use and DSM-IV abuse/dependence of alcohol, nicotine, cannabis, cocaine, sedatives, stimulants and heroin/opiates were compared across those with ADHD symptoms but no diagnosis (ADHDsx; N = 17,009), the Combined (ADHD-C; N = 361), Predominantly Inattentive (ADHD-I; N = 325), and the Predominantly Hyperactive-Impulsive (ADHD-HI; N = 279) ADHD subtypes. Taking a more dimensional approach, inattentive and hyperactive-impulsive symptom counts and their associations with substance use and misuse were also examined. Results After adjustments for conduct disorder, major depressive disorder, any anxiety disorder and other socio-demographic covariates, substance use and SUD were associated with ADHDsx, ADHD-C, ADHD-I and ADHD-HI. Overall, substance use and SUD were more weakly associated with the ADHDsx group compared to the three ADHD diagnostic groups. Statistically significant differences were not evident across the three diagnostic groups. Hyperactive–impulsive symptoms were more consistently associated with substance use and SUD compared to inattentive symptoms. Conclusions ADHD subtypes are consistently associated with substance use and SUD. The relatively stronger association of hyperactive/impulsive symptoms with substance use and abuse/dependence is consistent with the extant literature noting impulsivity as a precursor of substance use and SUD.
Cannabis and tobacco are common drugs of abuse worldwide and are often used in combination through various routes of administration (ROAs). Here, we aimed to provide an overview of how cannabis and ...tobacco routes varied across countries and assess the impact of tobacco-based ROAs on motivation to use less cannabis, and less tobacco, in different models. A cross-sectional online survey (Global Drugs Survey 2014) was completed by 33,687 respondents (mean age = 27.9; % female = 25.9) who smoked cannabis at least once in the last 12 months. Most common ROA, frequency of cannabis/tobacco use, and questions about motivation to use less cannabis/tobacco were recorded. Tobacco-based ROA were used by 65.6% of respondents. These were most common in Europe (77.2-90.9%) and Australasia (20.7-51.6%) and uncommon in the Americas (4.4-16.0%). Vaporizer use was most common in Canada (13.2%) and the United States (11.2%). Using a non-tobacco ROA was associated with a 10.7% increase in odds for "desire to use less" tobacco (OR: 1.107, 95% CI: 1.003, 1.221), 80.6% increase in odds for "like help to use less tobacco" (OR: 1.806, 95% CI: 1.556, 2.095), and a 103.9% increase in the odds for "planning to seek help to use less tobacco" (OR: 2.039, 95% CI: 1.638, 2.539), in comparison to using a tobacco-based ROA. Associations between ROA and intentions to use less cannabis were inconsistent. Results support considerable global variation in cannabis and tobacco ROA. Tobacco routes are common, especially "joints with tobacco," especially in Europe, but not in the Americas. Non-tobacco-based routes are associated with increased motivation to change tobacco use. Interventions addressing tobacco and cannabis need to accommodate this finding and encourage non-tobacco routes.
The sale of cannabis for adult recreational use has been made legal in nine US states since 2012, and nationally in Uruguay in 2013 and Canada in 2018. We review US research on the effects of ...legalization on cannabis use among adults and adolescents and on cannabis‐related harms; the impact of legalizing adult recreational use on cannabis price, availability, potency and use; and regulatory policies that may increase or limit adverse effects of legalization. The legalization of recreational cannabis use in the US has substantially reduced the price of cannabis, increased its potency, and made cannabis more available to adult users. It appears to have increased the frequency of cannabis use among adults, but not so far among youth. It has also increased emergency department attendances and hospitalizations for some cannabis‐related harms. The relatively modest effects on cannabis use to date probably reflect restrictions on the number and locations of retail cannabis outlets and the constraints on commercialization under a continued federal prohibition of cannabis. Future evaluations of legalization should monitor: cannabis sales volumes, prices and content of tetrahydrocannabinol; prevalence and frequency of cannabis use among adolescents and adults in household and high school surveys; car crash fatalities and injuries involving drivers who are cannabis‐impaired; emergency department presentations related to cannabis; the demand for treatment of cannabis use disorders; and the prevalence of regular cannabis use among vulnerable young people in mental health services, schools and the criminal justice system. Governments that propose to legalize and regulate cannabis use need to fund research to monitor the impacts of these policy changes on public health, and take advantage of this research to develop ways of regulating cannabis use that minimize adverse effects on public health.
Background and aims
Since 2012 four US states have legalized the retail sale of cannabis for recreational use by adults, and more are likely to follow. This report aimed to (1) briefly describe the ...regulatory regimes so far implemented; (2) outline their plausible effects on cannabis use and cannabis‐related harm; and (3) suggest what research is needed to evaluate the public health impact of these policy changes.
Method
We reviewed the drug policy literature to identify: (1) plausible effects of legalizing adult recreational use on cannabis price and availability; (2) factors that may increase or limit these effects; (3) pointers from studies of the effects of legalizing medical cannabis use; and (4) indicators of cannabis use and cannabis‐related harm that can be monitored to assess the effects of these policy changes.
Results
Legalization of recreational use will probably increase use in the long term, but the magnitude and timing of any increase is uncertain. It will be critical to monitor: cannabis use in household and high school surveys; cannabis sales; the number of cannabis plants legally produced; and the tetrahydrocannabinol (THC) content of cannabis. Indicators of cannabis‐related harms that should be monitored include: car crash fatalities and injuries; emergency department presentations; presentations to addiction treatment services; and the prevalence of regular cannabis use among young people in mental health services and the criminal justice system.
Conclusions
Plausible effects of legalizing recreational cannabis use in the United States include substantially reducing the price of cannabis and increasing heavy use and some types of cannabis‐related harm among existing users. In the longer term it may also increase the number of new users.
Drug classes are grouped based on their chemical and pharmacological properties, but prescription and illicit drugs differ in other important ways. Potential differences in genetic and environmental ...influences on the (mis)use of prescription and illicit drugs that are subsumed under the same class should be examined. Opioid and stimulant classes contain prescription and illicit forms differentially associated with salient risk factors (common route of administration, legality), making them useful comparators for addressing this etiological issue.
A total of 2410 individual Australian twins M
= 31.77 (s.d. = 2.48); 67% women were interviewed about prescription misuse and illicit use of opioids and stimulants. Univariate and bivariate biometric models partitioned variances and covariances into additive genetic, shared environmental, and unique environmental influences across drug types.
Variation in the propensity to misuse prescription opioids was attributable to genes (41%) and unique environment (59%). Illicit opioid use was attributable to shared (71%) and unique (29%) environment. Prescription stimulant misuse was attributable to genes (79%) and unique environment (21%). Illicit stimulant use was attributable to genes (48%), shared environment (29%), and unique environment (23%). There was evidence for genetic influence common to both stimulant types, but limited evidence for genetic influence common to both opioid types. Bivariate correlations suggested that prescription opioid use may be more genetically similar to prescription stimulant use than to illicit opioid use.
Prescription opioid misuse may share little genetic influence with illicit opioid use. Future research may consider avoiding unitary drug classifications, particularly when examining genetic influences.
We did a systematic review of reviews with evidence on the effectiveness of prevention, early intervention, harm reduction, and treatment of problem use in young people for tobacco, alcohol, and ...illicit drugs (eg, cannabis, opioids, amphetamines, or cocaine). Taxation, public consumption bans, advertising restrictions, and minimum legal age are effective measures to reduce alcohol and tobacco use, but are not available to target illicit drugs. Interpretation of the available evidence for school-based prevention is affected by methodological issues; interventions that incorporate skills training are more likely to be effective than information provision-which is ineffective. Social norms and brief interventions to reduce substance use in young people do not have strong evidence of effectiveness. Roadside drug testing and interventions to reduce injection-related harms have a moderate-to-large effect, but additional research with young people is needed. Scarce availability of research on interventions for problematic substance use in young people indicates the need to test interventions that are effective with adults in young people. Existing evidence is from high-income countries, with uncertain applicability in other countries and cultures and in subpopulations differing in sex, age, and risk status. Concerted efforts are needed to increase the evidence base on interventions that aim to reduce the high burden of substance use in young people.
Alcohol dependence and humor styles Schermer, Julie Aitken; Kfrerer, Marisa L.; Lynskey, Michael T.
Current psychology (New Brunswick, N.J.),
07/2023, Letnik:
42, Številka:
19
Journal Article
Recenzirano
This study explores the relationship between alcohol dependence and humor styles based on a large data set of 2752 adults. Participants completed a humor styles questionnaire, assessing four ...dimensions: affiliative, self-enhancing, aggressive, and self-defeating. Participants also completed a telephone survey assessing their lifetime use and problems with alcohol. The survey classified individuals as meeting or failing to meet the DSM-IV definition of alcohol dependence. Logistic regression analyses in predicting alcohol dependence categorization resulted in a 95.6% correct classification and two significant predictors: being a man and aggressive humor style scores. These results show that those who characteristically engage in an aggressive humor style, are more likely to meet the criteria for alcohol dependence.
•Four subtypes of cannabis users were identified at varying degrees of risk.•Compared to co-users, simultaneous alcohol users had more alcohol-related problems.•Simultaneous use of tobacco and ...cannabis was linked to the most negative outcomes.•Familial factors (both genes and shared environment) contributed to use patterns.
Cannabis use patterns vary considerably, with many users reporting simultaneous and non-simultaneous use (co-use) of other substances. Despite this, little research has examined the extent to which subtypes of cannabis users may be identified based on their simultaneous and co-use behaviors.
The sample consisted of adult Australian twins and siblings who reported lifetime cannabis use (n = 2590). A latent class analysis was conducted to determine subtypes of cannabis users based on five indicators of substance co-use and simultaneous use. Adolescent correlates (age of substance initiation and conduct disorder) and adult correlates (substance use/disorder and depression) of class membership were assessed. Twin similarity for class membership was also examined.
Four subtypes of users were identified: 1) alcohol co-users, 2) simultaneous alcohol users, 3) simultaneous tobacco users, and 4) simultaneous alcohol, tobacco, and drug users. Compared to co-users of alcohol, simultaneous alcohol users were at increased risk for alcohol problems. Patterns of use that involved simultaneous tobacco and cannabis use (i.e., simultaneous tobacco users and simultaneous alcohol, tobacco, and drug users) were associated with the most problematic outcomes, including substance use and disorder. There was evidence for genetic influences (12–58%) on cannabis use patterns, with higher concordance for latent class membership among monozygotic compared to dizygotic twins (χ2 (1) = 7.19, p = 0.007).
The current study identified four classes of cannabis users at varying degrees of risk. Results suggest that simultaneous tobacco and cannabis use may be especially associated with deleterious outcomes.
Introduction and Aims
Polysubstance use is associated with adverse health and social outcomes, but few studies have investigated whether these associations differ between individuals engaged in ...different patterns of illicit drug and non‐prescription medication use.
Design and Methods
Latent class analysis (LCA) was used to identify patterns of drug use in the Global Drug Survey, a purposive sample collected in late 2012 and surveyed using an online questionnaire including past‐year drug use, sociodemographics, mental illness, involvement in violence and sexual behaviour. The sample analysed (n = 14 869; median age 27 years; 68.5% male) included those residing in the UK (n = 5869), Australia (n = 6313) and the USA (n = 2687).
Results
LCA of cannabis, ecstasy, cocaine, stimulants, nitrous, ketamine, benzodiazepines and opioid painkiller use identified six classes: no polysubstance use (Class 1, 49.1%); cannabis and ecstasy (Class 2, 23.6%); all illicit drugs (Class 3, 9.4%); ecstasy and cocaine (Class 4, 8.3%); cannabis and medication (Class 5, 5.9%); and all drugs (Class 6, 3.8%). Participants diagnosed with anxiety were most likely to belong to Class 5 odds ratio (OR) 2.66, 95% confidence interval (CI) 2.10–3.38. Violent behaviour was most strongly associated with Class 6 membership (OR 1.9, 95% CI 1.36–2.64). Sexual risk‐taking also predicted membership of this class (OR 5.79, 95% CI 4.66–7.18) and Class 4 (OR 4.41, 95% CI 3.57–5.43).
Discussion and Conclusions
Five heterogeneous groups of polysubstance users were identified in this international sample covering the UK, Australia and USA. Anxiety disorders were associated with medication and cannabis use, while high‐risk behaviours predicted use of cocaine and ecstasy, or wide‐ranging polysubstance use including ketamine and medications. Morley KI, Lynskey MT, Moran P, Borschmann R, Winstock AR. Polysubstance use, mental health and high‐risk behaviours: Results from the 2012 Global Drug Survey. Drug Alcohol Rev 2015;34:427–37
Despite evidence of substantial comorbidity between psychiatric disorders and substance involvement, the extent to which common genetic factors contribute to their co-occurrence remains understudied. ...In the current study, we tested for associations between polygenic risk for psychiatric disorders and substance involvement (i.e., ranging from ever-use to severe dependence) among 2573 non-Hispanic European-American participants from the Study of Addiction: Genetics and Environment. Polygenic risk scores (PRS) for cross-disorder psychopathology (CROSS) were generated based on the Psychiatric Genomics Consortium's Cross-Disorder meta-analysis and then tested for associations with a factor representing general liability to alcohol, cannabis, cocaine, nicotine, and opioid involvement (GENSUB). Follow-up analyses evaluated specific associations between each of the five psychiatric disorders which comprised CROSS-attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (AUT), bipolar disorder (BIP), major depressive disorder (MDD), and schizophrenia (SCZ)-and involvement with each component substance included in GENSUB. CROSS PRS explained 1.10% of variance in GENSUB in our sample (p < 0.001). After correction for multiple testing in our follow-up analyses of polygenic risk for each individual disorder predicting involvement with each component substance, associations remained between: (A) MDD PRS and non-problem cannabis use, (B) MDD PRS and severe cocaine dependence, (C) SCZ PRS and non-problem cannabis use and severe cannabis dependence, and (D) SCZ PRS and severe cocaine dependence. These results suggest that shared covariance from common genetic variation contributes to psychiatric and substance involvement comorbidity.
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