Evidence map›Paper›PMID 34487979›Full record

ArticleAddictive behaviors2022

Comprehensive measurement invariance of alcohol outcome expectancies among adolescents using regularized moderated nonlinear factor analysis.

Angela K Stevens, Tim Janssen, William C M Belzak, Hayley Treloar Padovano, Kristina M Jackson

Open access · greenAbstract read
In one paragraph

Article in Addictive behaviors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 35% 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, 5 citations in OpenAlex.

  1. Article
  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

5 authors at 2 institutions in 1 country.

Angela K StevensCenter for Alcohol and Addiction Studies, Brown University School of Public Health, Providence, RI 02903, USA. Electronic address: Angela_Stevens@brown.edu.
Tim JanssenCenter for Alcohol and Addiction Studies, Brown University School of Public Health, Providence, RI 02903, USA.
William C M BelzakDepartment of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Hayley Treloar PadovanoCenter for Alcohol and Addiction Studies, Brown University School of Public Health, Providence, RI 02903, USA.
Kristina M JacksonCenter for Alcohol and Addiction Studies, Brown University School of Public Health, Providence, RI 02903, USA.
Brown University · USUniversity of North Carolina at Chapel Hill · US

Funding

Using wearables and EMA to examine the links between cannabis and depressionP20GM130414 · NIGMS · BROWN UNIVERSITY · PI Lauren Gioia Micalizzi · 2019 to 2026
$22.0M
ALCOHOL INTERVENTION/TREATMENT OUTCOME RESEARCH TRAININGT32AA007459 · NIAAA · BROWN UNIVERSITY · PI ROBERT MIRANDA, PETER M. MONTI · 1986 to 2026
$13.3M
Initiation and Progression through Early Drinking Milestones in Underage DrinkersR01AA016838 · NIAAA · BROWN UNIVERSITY · PI JACKSON, KRISTINA MELIA · 2008 to 2018
$6.8M
Substance Abuse Intervention/Outcome Research TrainingT32DA016184 · NIDA · BROWN UNIVERSITY · PI Damaris J. Rohsenow, JENNIFER W. TIDEY · 2003 to 2026
$6.1M
Novel Approaches to Understanding How Alcohol Pathology Develops in AdolescentsK23AA024808 · NIAAA · BROWN UNIVERSITY · PI TRELOAR PADOVANO, HAYLEY · 2017 to 2021
$973k
Informing treatment adaptation based on the interplay between behavioral undercontrol and context: an event-level studyK01AA026335 · NIAAA · BROWN UNIVERSITY · PI JANSSEN, TIM · 2018 to 2022
$904k
NIAAA NIH HHS K01 AA026335NIAAA NIH HHS K23 AA024808NIAAA NIH HHS R01 AA016838NIAAA NIH HHS T32 AA007459NIDA NIH HHS T32 DA016184NIGMS NIH HHS P20 GM130414
6 · The paper itself

Abstract

Alcohol outcomes expectancies (AOEs) are robust predictors of alcohol initiation and escalation of drinking behavior among adolescents. Although measurement invariance is a prerequisite for inferring valid comparisons of AOEs across groups (e.g., age), empirical evidence is lacking. In a secondary data analysis study, we employed regularized moderated nonlinear factor analysis (MNLFA) to simultaneously test differential item functioning (DIF) across age, sex, race, ethnicity, socioeconomic status (SES), and alcohol initiation for a 22-item, two-factor measure of positive and negative AOEs among adolescents (analytic n = 936 drawn from a parent study of 1023 adolescents). Evidence of DIF was minimal, with no DIF for the negative AOE factor and DIF for only two items of the positive AOE factor. The item "feel grown up" exhibited DIF by age, and the item "feel romantic" exhibited DIF by SES. After accounting for DIF, the positive AOE latent factor mean differed by SES, age, and alcohol initiation, and exhibited lower variability by alcohol initiation. The negative AOE latent factor mean differed by sex and SES, with greater variability by SES and age and lower variability by alcohol initiation. Group-differences findings for age and alcohol initiation are consistent with prior work, and differences by sex and SES are a new contribution to the literature that should prompt additional research to ensure replicability. The present study demonstrates the utility of the MNLFA technique for examining comprehensive measurement invariance, particularly for applied researchers who seek to examine substantive research questions while accounting for any DIF present in the scales used.

Indexed as

Adolescent BehaviorAdolescentEthnicityFactor Analysis, StatisticalHumansParentsPsychometricsAdolescentsAlcohol initiationAlcohol outcome expectanciesMeasurement invarianceModerated nonlinear factor analysis

Identifiers

PMID34487979
PMCPMC8805203
OpenAlexW3195622195

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.