Evidence map›Paper›PMID 38270342›Full record

ArticleSubstance use & misuse2024

Initial Validation of a Computerized Adaptive Test for Substance Use Disorder Identification in Adolescents.

Zachary W Adams, Leslie A Hulvershorn, Michael P Smoker, Brigid R Marriott, Matthew C Aalsma, Robert D Gibbons

Open access · greenAbstract read
In one paragraph

Article in Substance use & misuse, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Zachary W AdamsDepartment of Psychiatry, Indiana University, Indianapolis, IN, USA.ORCID 0000-0002-0044-4926
Leslie A HulvershornDepartment of Psychiatry, Indiana University, Indianapolis, IN, USA.ORCID 0000-0001-5827-4889
Michael P SmokerDepartment of Psychiatry, Indiana University, Indianapolis, IN, USA.ORCID 0000-0002-6515-7362
Brigid R MarriottDepartment of Psychiatry, Indiana University, Indianapolis, IN, USA.ORCID 0000-0001-5241-8159
Matthew C AalsmaDepartment of Pediatrics, Indiana University, Indianapolis, IN, USA.ORCID 0000-0001-5952-6785
Robert D GibbonsDepartments of Medicine and Public Health Sciences, The University of Chicago Biological Sciences, Chicago, IL, USA.
Indiana University – Purdue University Indianapolis · USChicago Department of Public Health · US

Funding

Survey CoreU2CDA050098 · NIDA · UNIVERSITY OF CHICAGO · PI POLLACK, HAROLD ALEXANDER, SCHNEIDER, JOHN · 2019 to 2019
$17.2M
Alliance to Disseminate Addiction Prevention and Treatment (ADAPT): A Statewide Learning Health System to Reduce Substance Use among Justice-Involved Youth in Rural Communities.UG1DA050070 · NIDA · INDIANA UNIVERSITY INDIANAPOLIS · PI AALSMA, MATTHEW · 2019 to 2023
$5.7M
NIDA NIH HHS U2C DA050098NIDA NIH HHS UG1 DA050070
6 · The paper itself

Abstract

purposeComputerized adaptive tests (CATs) are highly efficient assessment tools that couple low patient and clinician time burden with high diagnostic accuracy. A CAT for substance use disorders (CAT-SUD-E) has been validated in adult populations but has yet to be tested in adolescents. The purpose of this study was to perform initial evaluation of the K-CAT-SUD-E (i.e., Kiddy-CAT-SUD-E) in an adolescent sample compared to a gold-standard diagnostic interview.

methodsAdolescents (

resultsUsing the K-CAT-SUD-E continuous severity score and diagnoses to predict the presence of any K-SADS SUD diagnosis, the classification accuracy ranged from excellent for current SUD (AUC = 0.89, 95% CI = 0.81, 0.95) to outstanding (AUC = 0.93, 95% CI = 0.82, 0.97) for lifetime SUD. Regarding current substance-specific diagnoses, the classification accuracy was excellent for alcohol (AUC = 0.82), cannabis (AUC = 0.83) and nicotine/tobacco (AUC = 0.90). For lifetime substance-specific diagnoses, the classification accuracy ranged from excellent (e.g., opioids, AUC = 0.84) to outstanding (e.g., stimulants, AUC = 0.96). K-CAT-SUD-E median completion time was 4 min 22 s compared to 45 min for the K-SADS.

conclusionsThis study provides initial support for the K-CAT-SUD-E as a feasible accurate diagnostic tool for assessing SUDs in adolescents. Future studies should further validate the K-CAT-SUD-E in a larger sample of adolescents and examine its acceptability, feasibility, and scalability in youth-serving settings.

Indexed as

CannabisSubstance-Related DisordersAdolescentAdultEthanolHumansPsychiatric Status Rating ScalesEthanoladolescentcomputerized adaptive testingitem response theorymental healthSubstance use disorder

Identifiers

PMID38270342
PMCPMC11187757
OpenAlexW4391229988

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.