Measurement invariance of DSM-IV alcohol, marijuana and cocaine dependence between community-sampled and clinically overselected studies.
- Authors
- Derringer, Jaime; Krueger, Robert F; Dick, Danielle M; Agrawal, Arpana; Bucholz, Kathleen K; Foroud, Tatiana; Grucza, Richard A; Hesselbrock, Michie N; Hesselbrock, Victor; Kramer, John; Nurnberger, John I; Schuckit, Marc; Bierut, Laura J; Iacono, William G; McGue, Matt
- Year
- 2013
- Journal
- Addiction (Abingdon, England)
- PMID
- 23651171
- DOI
- 10.1111/add.12187
- PMCID
- PMC3742679
AIMS: To examine whether DSM-IV symptoms of substance dependence are psychometrically equivalent between existing community-sampled and clinically overselected studies. PARTICIPANTS: A total of 2476 adult twins born in Minnesota and 4121 unrelated adult participants from a case-control study of alcohol dependence. MEASUREMENTS: Life-time DSM-IV alcohol, marijuana and cocaine dependence symptoms and ever use of each substance. DESIGN: We fitted a hierarchical model to the data, in which ever use and dependence symptoms for each substance were indicators of alcohol, marijuana or cocaine dependence which were, in turn, indicators of a multi-substance dependence factor. We then tested the model for measurement invariance across participant groups, defined by study source and participant sex. FINDINGS: The hierarchical model fitted well among males and females within each sample [comparative fit index (CFI) > 0.96, Tucker-Lewis index (TLI) > 0.95 and root mean square error of approximation (RMSEA) < 0.04 for all], and a multi-group model demonstrated that model parameters were equivalent across sample- and sex-defined groups (ΔCFI = 0.002 between constrained and unconstrained models). Differences between groups in symptom endorsement rates could be expressed solely as mean differences in the multi-substance dependence factor. CONCLUSIONS: Life-time substance dependence symptoms fitted a dimensional model well. Although clinically overselected participants endorsed more dependence symptoms, on average, than community-sampled participants, the pattern of symptom endorsement was similar across groups. From a measurement perspective, DSM-IV criteria are equally appropriate for describing substance dependence across different sampling methods.
Hierarchical model, in which ever use (Use) and dependence symptoms (denoted Sx1–Sx7) are indicators of dependence on each substance, which are in turn indicators of the higher-order multi-substance dependence latent trait.
LLM interpretation
This is a hierarchical structural diagram illustrating a latent trait model for multi-substance dependence. The top-level latent trait, "Multi-substance dependence," branches down to three substance-specific latent variables: Alcohol, Marijuana, and Cocaine. Each substance variable is further indicated by a set of observed measures, including "Use" and seven dependence symptoms (Sx1–Sx7).
Criterion information curves for each substance (derived from parameters shown in Table 3*). The peak height of each criterion’s curve represents the relative loading of that criterion. The horizontal location of the peak is the threshold, or the Z-score latent trait level at which the likelihood of an individual endorsing that criterion is 50%.* Information was calculated as I(θ)=(1.7*αi)2Pi(θ) (1-Pi(θ)) where αi is the normal-metric criterion discrimination (as given in Table 3) and Pi(θ) is the probability of an individual with latent trait level θ endorsing that criterion. [39]
LLM interpretation
This figure consists of three line graphs showing criterion information curves for Alcohol, Marijuana, and Cocaine. The x-axis represents the standardized latent trait level, and the y-axis represents Information. Each graph contains multiple colored curves corresponding to different diagnostic criteria, with the peaks indicating the relative loading and threshold for each criterion across the three substances.
| # | Section | Preview |
|---|---|---|
| 20 | Results | Figure 2 demonstrates visually that, as expected based on endorsement rates, ever use or endorsement… |
| 21 | Results | Within the preferred constrained model, mean differences in the multi-substance factor entirely… |
| 22 | Discussion | Based on evidence from the existing substance dependence literature, we identified a hierarchical… |
| 23 | Discussion — Limitations | These findings should be considered in light of several limitations, which may impact the… |
| 24 | Discussion — Limitations | We also note that the current findings refer to lifetime history of substance use and dependence… |
| 25 | Discussion — Conclusions | The current study provides strong support for the conceptualization of substance dependence as a… |
| 26 | Discussion — Conclusions | The current data are unable to address the important question of predictive validity or utility of… |
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| Do DSM-5 substance use disorder criteria differ by user care settings? An item response theory analysis approach. | Kervran C et al. | — | 2021 | → |
| Symptoms of anxiety, depression, and borderline personality in alcohol use disorder with and without comorbid substance use disorder. | Howe LK et al. | — | 2021 | → |
| Examining the Utility of a General Substance Use Spectrum Using Latent Trait Modeling. | Bailey AJ et al. | — | 2020 | → |
| A Decline in Propensity Toward Risk Behaviors Among U.S. Adolescents. | Borodovsky JT et al. | — | 2019 | → |
| Quantifying the impact of partial measurement invariance in diagnostic research: An application to addiction research. | Lai MHC et al. | — | 2019 | → |
| Alcohol use from adolescence through early adulthood: an assessment of measurement invariance by age and gender. | Fish JN et al. | — | 2017 | → |
| Meta-analysis of DSM alcohol use disorder criteria severities: structural consistency is only 'skin deep'. | Lane SP et al. | — | 2016 | → |
| Commonalities and Differences Across Substance Use Disorders: Phenomenological and Epidemiological Aspects. | Shmulewitz D et al. | — | 2015 | → |
| Examining the role of common genetic variants on alcohol, tobacco, cannabis and illicit drug dependence: genetics of vulnerability to drug dependence. | Palmer RH et al. | — | 2015 | → |
| Examining the shared and unique relationships among substance use and mental disorders. | Sunderland M et al. | — | 2015 | → |
| Measurement invariance of alcohol instruments with Hispanic youth. | Feldstein Ewing SW et al. | — | 2015 | → |
| Distress intolerance in substance dependent patients. | Özdel K et al. | — | 2014 | → |
| Commentary on Derringer et al. (2013): more evidence for a unidimensional framework for substance use disorders. | Willenbring ML | — | 2013 | → |