Evidence map›Paper›PMID 27191732›Full record

ArticleSubstance use & misuse2016

Substance Use Profiles of Urban American Indian Adolescents: A Latent Class Analysis.

Stephen S Kulis, Justin Jager, Stephanie L Ayers, Husain Lateef, Elizabeth Kiehne

Open access · greenAbstract read
In one paragraph

Article in Substance use & misuse, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 16% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Polysubstance Use among Maryland High School Students: Variations across County-Level School Districts.International journal of environmental research and public health · 2024
    Article
  5. Article
  6. Review
  7. Article
  8. Belief patterns and drug use in a sample of Brazilian youth: an exploratory latent class analysis.Revista brasileira de psiquiatria (Sao Paulo, Brazil : 1999) · 2020
    Article
  9. Article
  10. Article
  11. 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

5 authors at 1 institution in 1 country.

Stephen S Kulisa T. Denny Sanford School of Social and Family Dynamics , Arizona State University , Tempe , Arizona , USA.
Justin Jagera T. Denny Sanford School of Social and Family Dynamics , Arizona State University , Tempe , Arizona , USA.
Stephanie L Ayersb Southwest Interdisciplinary Research Center , Arizona State University , Phoenix , Arizona , USA.
Husain Lateefb Southwest Interdisciplinary Research Center , Arizona State University , Phoenix , Arizona , USA.
Elizabeth Kiehneb Southwest Interdisciplinary Research Center , Arizona State University , Phoenix , Arizona , USA.
Arizona State University · US

Funding

Urban American Indian Youth Substance Use: Ecodevelopmental Influences P20MD002316 · NIMHD · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI MARSIGLIA, FLAVIO FRANCISCO · 2007 to 2016
$13.3M
'keepin' It REAL in Mexico: An Adaptation and Multisite RCTR01DA038657 · NIDA · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI MARSIGLIA, FLAVIO FRANCISCO · 2015 to 2019
$3.0M
Using CBPR to Adapt a Culturally-grounded Prevention Curriculum for Urban AmericaR01MD006110 · NIMHD · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI KULIS, STEPHEN S. · 2010 to 2014
$1.9M
Drug Resistance Strategies: The Next GenerationR01DA014825 · NIDA · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI MARSIGLIA, FLAVIO FRANCISCO · 2001 to 2001
$301k
NIDA NIH HHS R01 DA014825NIDA NIH HHS R01 DA038657NIMHD NIH HHS P20 MD002316NIMHD NIH HHS R01 MD006110
6 · The paper itself

Abstract

unlabelledA growing majority of American Indian adolescents now live in cities and are at high risk of early and problematic substance use and its negative health effects.

objectiveThis study used latent class analysis to empirically derive heterogeneous patterns of substance use among urban American Indian adolescents, examined demographic correlates of the resulting latent classes, and tested for differences among the latent classes in other risk behavior and prosocial outcomes.

methodThe study employed a representative sample of 8th, 10th, and 12th grade American Indian adolescents (n = 2,407) in public or charter schools in metropolitan areas of Arizona in 2012. Latent class analysis examined eight types of last 30 day substance use.

resultsFour latent classes emerged: a large group of "nonusers" (69%); a substantial minority using alcohol, tobacco, and/or marijuana [ATM] (17%); a smaller group of polysubstance users consuming, alcohol, tobacco, marijuana, other illicit drugs, and prescription or OTC drugs in combination (6%); and a "not alcohol" group reporting combinations of tobacco, marijuana, and prescription drug use, but rarely alcohol use (4%). The latent classes varied by age and grade level, but not by other demographic characteristics, and aligned in highly consistent patterns on other non-substance use outcomes. Polysubstance users reported the most problematic and nonusers the least problematic outcomes, with ATM and "not alcohol" users in the middle.

conclusionsUrban AI adolescent substance use occurs in three somewhat distinctive patterns of combinations of recent alcohol and drug consumption, covarying in systematic ways with other problematic risk behaviors and attitudes.

Indexed as

Substance-Related DisordersAdolescentAlcohol DrinkingHumansIllicit DrugsIndians, North AmericanPrescription DrugsIllicit DrugsPrescription DrugsadolescentsAmerican Indianlatent classSubstance useurban

Identifiers

PMID27191732
PMCPMC4964876
OpenAlexW2402260250

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.