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

Martin, Greg; Copeland, Jan; Gates, Peter; Gilmour, Stuart

doi:10.1016/j.drugalcdep.2005.10.014

Cited by 192 publications

(127 citation statements)

References 11 publications

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“…The recent publication of the CPQ-A-S which was based on a school sample (14- to 18-year-olds) did not provide information on sensitivity and specificity [9]. Finally, the SDS (5 items) used to screen for dependence in adolescents [2] exhibited high specificity (94.3%) but low sensitivity (65.1%).…”

Section: Discussionmentioning

confidence: 99%

“…A systematic review identified four instruments that had been validated [1]: the Severity of Dependence Scale (SDS [2]), the Cannabis Use Disorder Identification Test (CUDIT [3]), the Problematic Use of Marijuana (PUM [4]), and the Cannabis Abuse Screening Test (CAST [5]). However, with the exception of the SDS, research, especially with regard to adolescents, was scarce.…”

Section: Introductionmentioning

confidence: 99%

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Validation of the Cannabis Abuse Screening Test in a Sample of Cannabis Inpatients

Legleye

Kraus²,

Piontek³

et al. 2012

Eur Addict Res

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The present study aims at validating the Cannabis Abuse Screening Test (CAST) in a clinical sample of adolescent and young adult cannabis users seeking treatment. Applying a classical test theory approach using DSM-IV diagnoses as gold standard, two versions of the CAST questionnaire are compared. The sample consisted of 140 subjects aged 15–26 years (mean 18.9) recruited from two cannabis treatment centers. Gold standard diagnoses were assessed using the Adolescent Diagnostic Interview-Light. Internal structure and consistency of the CAST were assessed by principal component analysis and Cronbach’s α. Optimal thresholds were defined using receiver operating characteristic analysis. Both the binary and the full test version revealed unidimensional structures with moderate to satisfactory internal consistency (α = 0.66 and 0.73). Screening properties were unsatisfactory when the CAST was compared against cannabis dependence. With regard to cannabis use disorders, both test versions yielded comparable and good sensitivity and specificity at cut-off 3 (binary: 92.2%, 66.7%) and 6 (full: 93.0%, 66.7%). Overall, the full CAST may be used for screening cannabis use disorders in clinical settings. Further research may use validation methods that do without gold standard.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Validation of the Cannabis Abuse Screening Test in a Sample of Cannabis Inpatients

Legleye

Kraus²,

Piontek³

et al. 2012

Eur Addict Res

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“…A cutoff of "4" on this scale is commonly used to separate "non-dependent" from "dependent" substance users. 37,38 Only 12 respondents were dependent upon both caffeine and 175 nicotine. As an index of psychological distress, participants were also asked to complete the K10.…”

Section: Methodsmentioning

confidence: 99%

Consumption and foraging behaviors for common stimulants (nicotine, caffeine)

Phillips

Currie

Ogeil

2015

Journal of Addictive Diseases

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Q3 5Models are needed to understand the emerging capability to track consumers' movements. Therefore, we examined the use of legal and readily available stimulants that vary in their addictive potential (nicotine, caffeine). One hundred sixty-six participants answered the Kessler Psychological Distress Scale (K10), the Severity of Dependence Scale for nicotine and caffeine, and reported the number of times and locations stimulants were purchased and used. On average, nicotine 10 dependent individuals made their purchases from 2 locations, while caffeine dependent individuals consumed caffeine at 2 locations, but some people exhibited a greater range and intensity of use. Stimulant foraging behavior could be described by power laws, and is exacerbated by dependency. The finding has implications for attempts to control substance use. Q5

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“…Hence, harnessing a burgeoning variety of innovative technologydelivered interventions [59], public health SEI initiatives should target vulnerable adolescents at risk/on a trajectory to cannabis dependence to arrest transition to more serious harms. Specifically developed and/or validated for adolescent and adult general and clinical populations, appropriate screening tools include the Cannabis Use Problems Identification Test [37] and the SDS [45].…”

Section: Discussionmentioning

confidence: 99%

“…Twelve-month CUD diagnoses from the Diagnostic and Statistical Manual of Mental Disorders, fourth revision (DSM-IV) [42], and the International Classification of Diseases tenth revision (ICD10) [43] were obtained using the Drug Use module of the Composite International Diagnostic Interview (CIDI)-Auto, version 2.1 [44]. The Severity of Dependence Scale (SDS) [45] provided another measure of 6-month CUD.…”

Section: Assessmentmentioning

confidence: 99%

Cannabis Use and Disorder Transitions Among a Mixed Community Sample of At-Risk Adolescents and Adults: A Prospective New Zealand Study

Bashford¹,

Copeland²,

Flett³

2013

TOADDJ

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Introduction and Aims:The trajectories of cannabis use disorder (CUD) require more comprehensive delineation to expedite recognition of incubating dependence among high-risk users. This study examined baseline cannabis use and CUD over 12 months using DSM-IV/ICD10 diagnoses to distinguish transition groups. Design and Methods:In a prospective naturalistic design, 194 heterogeneous cannabis users (128 adolescents, 66 adults) aged 13-61 years were voluntarily recruited and assessed at baseline, and then re-assessed 12-months later.Results: Most participants met criteria for a baseline CUD (70% dependence, 20% abuse), 12 adolescents were 'diagnostic orphans', and 5 symptom-free. At follow-up, 25% adolescents reported using less, 6% the same level, and 69% using more cannabis. Significantly increased symptoms and dependence severity were reported, with no adolescent/adult differences evident. Three diagnostic transition groups were identified. While 84% adolescents (n=108) remained stable, 5% (n=7) had improved, 10% (n=13) had deteriorated. 'Deteriorators' scored significantly higher than 'improvers' on cannabis use, symptoms, and dependence severity measures. A subjective loss of control over cannabis use was among the earliest DSM-IV features among younger users on a trajectory towards dependence. Most participants (79%) anticipated difficulty trying to reduce/quit their use Discussion and Conclusions: Younger adolescents can rapidly develop cannabis dependence, reporting similar and equally severe symptoms as longer-term adult users. Impaired control over use occurs early in trajectories towards dependence. The seeming intractability of problematic cannabis use calls for concerted cannabis screening and early intervention (SEI) efforts at an earlier age to avert or reduce harmful consequences of cannabis use in the community.

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

Cited by 192 publications

References 11 publications

Validation of the Cannabis Abuse Screening Test in a Sample of Cannabis Inpatients

Validation of the Cannabis Abuse Screening Test in a Sample of Cannabis Inpatients

Consumption and foraging behaviors for common stimulants (nicotine, caffeine)

Cannabis Use and Disorder Transitions Among a Mixed Community Sample of At-Risk Adolescents and Adults: A Prospective New Zealand Study

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