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An Improved Diagnostic Evaluation Instrument for Substance Abuse Patients: The Addiction Severity Index
Abstract
The Addiction Severity Index (ASI) is a structured clinical interview developed to fill the need for a reliable, valid, and standardized diagnostic and evaluative instrument in the field of alcohol and drug abuse. The ASI may be administered by a technician in 20 to 30 minutes producing 10-point problem severity ratings in each of six areas commonly affected by addiction. Analyses of these problem severity ratings on 524 male veteran alcoholics and drug addicts showed them to be highly reliable and valid. Correlational analyses using the severity ratings indicated considerable independence between the problem areas, suggesting that the treatment problems of patients are not necessarily related to the severity of their chemical abuse. Cluster analyses using these ratings revealed the presence of six subgroups having distinctly different patterns of treatment problems. The authors suggest the use of the ASI to match patients with treatments and to promote greater comparability of research findings.
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Metadata
- Authors
- McLELLAN, A. T., LUBORSKY, L., WOODY, G. E., & O??BRIEN, C. P.
- Venue
- The Journal of Nervous and Mental Disease
- Published
- 1980-01
- Volume
- 168
- Issue
- 1
- Pages
- 26-33
- ISSN
- 0022-3018 (ISSN-L)
- OpenAlex
- W2024374498
- Cited by
- 3,188
- References
- 0
- FWCI
- 8.61
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.