Contributions of Ethnicity to Differential Item Functioning of Cannabis Abuse and Dependence Symptoms

Gizer, Ian R.; Gilder, David A.; Lau, Philip; Wang, Ting; Wilhelmsen, Kirk C.; Ehlers, Cindy L.

doi:10.15288/jsad.2013.74.320

Cited by 8 publications

(9 citation statements)

References 42 publications

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“…The prevalence of withdrawal (40.0%) and average number of withdrawal symptoms (2.03±1.25) is similar to a previous study of adolescents with cannabis use problems in outpatient treatment (Chung et al, 2008), but lower than samples of adolescents with cannabis dependence in inpatient treatment or comorbid psychopathology (Cornelius et al, 2008; Crowley et al, 1998; Preuss et al, 2010). Contrary to previous literature, the presence of self-reported withdrawal did not differ by demographic variables or substance use at baseline (Agrawal et al, 2008; Gizer et al, 2013). …”

Section: Discussioncontrasting

confidence: 99%

“…Previous research suggests the prevalence of withdrawal does not differ by gender, lifetime history of drug and tobacco use, or psychopathology (Agrawal, Pergadia, & Lynskey, 2008; Allsop et al, 2012; Piontek, Kraus, Legleye, & Buhringer, 2011). Conversely, ethnicity, polysubstance use, concurrent tobacco cessation, family history of substance use, and certain genetic polymorphisms were shown to moderate cannabis withdrawal (Agrawal et al, 2008; Ehlers et al, 2010; Gizer et al, 2013; Haughey, Marshall, Schacht, Louis, & Hutchison, 2008; Preuss et al, 2010; Vandrey et al, 2008). The most common symptoms of withdrawal can be clustered into symptoms of weakness or symptoms of anxiety and depression (Hasin et al, 2008), with restlessness, appetite change, irritability, sleep problems and craving being most severe (Milin, Manion, Dare, & Walker, 2008; Vandrey et al, 2008; Allsop, Norberg, Copeland, Fu & Budney, 2011).…”

Section: Introductionmentioning

confidence: 99%

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The Prevalence of Cannabis Withdrawal and Its Influence on Adolescents' Treatment Response and Outcomes

Greene

Kelly

2014

Journal of Addiction Medicine

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Background Withdrawal, a diagnostic indicator of cannabis use disorder, is often minimized or ignored as a consequence of cannabis use, particularly among adolescents. This study aims to characterize cannabis withdrawal among adolescents in outpatient treatment for substance use disorder and evaluate the clinical significance of withdrawal as a predictor of substance-related outcomes. Methods Adolescent outpatients (N=127) reporting cannabis as their drug of choice (n=90) were stratified by presence of withdrawal and compared on demographic and clinical variables at treatment intake. Hierarchical linear models compared the effect of withdrawal on percent days abstinent (PDA) and related outcomes over a 1-year follow-up period. Results Adolescents reporting withdrawal (40%) were more likely to meet criteria for cannabis dependence, have higher levels of substance use severity, report more substance-related consequences, and have a mood disorder. Withdrawal was not associated with PDA over the follow-up period; however, this relationship was moderated by problem recognition such that adolescents reporting withdrawal and a drug problem improved at a greater rate with respect to PDA than those that didn’t recognize a problem with drugs and didn’t report withdrawal. Discussion Withdrawal is common among adolescent outpatients and is associated with a more clinically severe profile. In this sample, all adolescents reporting withdrawal met criteria for cannabis dependence, suggesting that withdrawal is a highly specific indicator of cannabis use disorder. While withdrawal doesn’t appear to be independently associated with substance use outcomes post-treatment, moderating factors such as drug problem recognition should be taken into account when formulating treatment and continuing care plans.

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Section: Discussioncontrasting

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Prevalence of Cannabis Withdrawal and Its Influence on Adolescents' Treatment Response and Outcomes

Greene

Kelly

2014

Journal of Addiction Medicine

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“…It is prevalent in both general and clinical samples, and has clinical significance, since withdrawal was associated with difficulty quitting and worse treatment outcomes. Additionally, cannabis withdrawal fit the unidimensional model of cannabis use disorder criteria (Derringer et al, 2013, Gillespie et al, 2007, Gizer et al, 2013, Hartman et al, 2008, Langenbucher et al, 2004, Lynskey and Agrawal, 2007, Mewton et al, 2010, Piontek et al, 2011, Wu et al, 2009b, Wu et al, 2013). …”

Section: Physiological/pharmacological Criteriamentioning

confidence: 97%

“…This supported replacing the two DSM-IV disorders (dependence, abuse) with a single combined disorder in DSM-5. More recent IRT studies continue to consistently indicate unidimensionality for alcohol (Castaldelli-Maia et al, 2015; Preuss et al, 2014, Hagman and Cohn, 2013, Kuerbis et al, 2013b, Ehlke et al, 2012, Rose et al, 2012, Edwards et al, 2013, Wu et al, 2013, Derringer et al, 2013), cannabis (Wu et al, 2013, Gizer et al, 2013, Derringer et al, 2013), cocaine and stimulants (Wu et al, 2013, Derringer et al, 2013, Gilder et al, 2014), opioids (Wu et al, 2013), and inhalants (Ridenour et al, 2014). The unidimensionality evidence also supports dimensional SUD severity scales across all substances; such scales are important in both research and clinical work as they provide information beyond a binary diagnosis (Grant et al, 2015, Hasin et al, 2015).…”

Section: Psychometric Evidencementioning

confidence: 99%

Commonalities and Differences Across Substance Use Disorders: Phenomenological and Epidemiological Aspects

Shmulewitz

Greene

Hasin

2015

Alcohol Clin Exp Res

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Background Although psychoactive substances vary in many ways, they have important commonalties, particularly in their ability to lead to an addiction syndrome. The field lacks an updated review of the commonalities and differences in the phenomenology of alcohol, cannabis, tobacco, stimulants, opioids, hallucinogens, sedatives/tranquilizers and inhalants and their related substance use disorders (SUD). Methods DSM-IV and DSM-5 SUD diagnostic criteria were reviewed, as was evidence from recent epidemiological and clinical research: psychometric studies (test-retest reliability, latent trait analysis); physiological indicators (tolerance, withdrawal); prevalence and age of onset. Information was incorporated from previous reviews, PubMed and Scopus literature searches, and data from large U.S. national surveys. Results Empirical evidence in the form of test-retest reliability and unidimensionality supports use of the same DSM-IV dependence or DSM-5 SUD diagnostic criteria across substances. For most substances, the criteria sets were generally most informative in general population samples at moderate-to-severe levels of SUD. Across substances, two criteria (tolerance and use in hazardous situations) were identified as functioning differently in population subgroups. Since substances have different pharmacological effects, withdrawal is assessed using substance-specific symptoms, while tolerance is not; issues remain with the assessment of tolerance. Alcohol, tobacco, and cannabis were consistently identified as the substances with earliest onset of use, highest prevalence of lifetime use, and highest prevalence of lifetime disorder. Conclusions Despite differences between psychoactive substances, the generic DSM criteria set appear equally applicable across substances. Additional studies of tolerance and hazardous use will be useful for future nosologies. Alcohol, cannabis, and tobacco are the substances with the greatest public health impact due to the high prevalence and early onset of their use, and the potential all three substances have to lead to addiction.

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“…Regarding the legal problems criterion, it was removed from AUD because of its: (a) low prevalence in the general population and high severity, which was inconsistent with its classification as a milder abuse criterion (Compton et al, 2009; Gelhorn et al, 2008; Harford et al, 2009; Hartman et al, 2008); (b) poor ability to discriminate between people with high and low AUD severity (Hasin et al, 2012; Martin et al, 2006; Piontek et al, 2011; Saha et al, 2006); (c) poor associations with other SUD criteria (including AUD), which increases construct multidimensionality (Langenbucher et al, 2004; Martin et al, 2006); (d) failure to measure the same construct across different genders (Martin et al, 2006) and racial/ethnic groups (Gizer et al, 2013; Harford et al, 2009); (e) and failure to increment other SUD criteria in terms of the information it provided to the latent trait (Lynskey & Agrawal, 2007; Martin et al, 2006; Saha et al, 2012; Shmulewitz et al, 2010). Finally, DSM–5 also added craving as a criterion given that it increases consistency of AUD diagnosis between diagnostic systems (i.e., International Classification of Diseases , tenth edition [ ICD-10 ] and eleventh edition [ ICD-11 ]) and may have utility as a pharmacological treatment target (Hasin et al, 2013).…”

Section: Problems With the Classification Of Dsm–5 Alcohol Use Disordermentioning

confidence: 99%

The etiologic, theory-based, ontogenetic hierarchical framework of alcohol use disorder: A translational systematic review of reviews.

Boness¹,

Watts²,

Moeller³

et al. 2021

Psychological Bulletin

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Modern nosologies (e.g., International Classification of Diseases, 11th edition [ICD-11], Diagnostic and Statistical Manual of Mental Disorders, 5th edition [DSM–5]) for alcohol use disorder (AUD) and dependence prioritize reliability and clinical presentation over etiology, resulting in a diagnosis that is not always strongly grounded in basic theory and research. Within these nosologies, DSM–5 AUD is treated as a discrete, largely categorical, but graded, phenomenon, which results in additional challenges (e.g., significant phenotypic heterogeneity). Efforts to increase the compatibility between AUD diagnosis and modern conceptualizations of alcohol dependence, which describe it as dimensional and partially overlapping with other psychopathology (e.g., other substance use disorders), will inspire a stronger scientific framework and strengthen AUD’s validity. We conducted a systematic review of 144 reviews to integrate addiction constructs and theories into a comprehensive framework to identify fundamental mechanisms implicated in AUD. The product of this effort was the Etiologic, Theory-based, Ontogenetic Hierarchical Framework (ETOH Framework) of AUD mechanisms, which outlines superdomains of cognitive control, reward, and negative valence and emotionality, each of which subsume narrower, hierarchically organized components. We also outline opponent processes and self-awareness as key moderators of AUD mechanisms. In contrast with other frameworks, we recommend an increased conceptual role for negative valence and compulsion in AUD. The ETOH framework serves as a critical step toward conceptualizations of AUD as dimensional and heterogeneous. It has the potential to improve AUD assessment and aid in the development of evidence-based diagnostic measures that focus on key mechanisms in AUD, consequently facilitating precision medicine.

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Contributions of Ethnicity to Differential Item Functioning of Cannabis Abuse and Dependence Symptoms

Cited by 8 publications

References 42 publications

The Prevalence of Cannabis Withdrawal and Its Influence on Adolescents' Treatment Response and Outcomes

The Prevalence of Cannabis Withdrawal and Its Influence on Adolescents' Treatment Response and Outcomes

Commonalities and Differences Across Substance Use Disorders: Phenomenological and Epidemiological Aspects

The etiologic, theory-based, ontogenetic hierarchical framework of alcohol use disorder: A translational systematic review of reviews.

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