Evidence map›Paper›PMID 33512731›Full record

ArticleAlcoholism, clinical and experimental research2021

Delineating Developmental Periods in Adulthood Suggests Age-Related Shifts in the Correlates of Alcohol Use and Problems.

Jarrod M Ellingson, Andrew K Littlefield, Phillip K Wood, Kenneth J Sher

Abstract read
In one paragraph

Article in Alcoholism, clinical and experimental research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. New Frontiers in Prevention Research Models: Commentary on the Special Issue.Prevention science : the official journal of the Society for Prevention Research · 2023
    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

4 authors.

Jarrod M EllingsonDepartment of Psychiatry, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.ORCID 0000-0001-9932-2656
Andrew K LittlefieldDepartment of Psychological Sciences, Texas Tech University, Lubbock, TX, USA.ORCID 0000-0002-4725-1152
Phillip K WoodDepartment of Psychological Sciences, University of Missouri-Columbia, Columbia, MO, USA.
Kenneth J SherDepartment of Psychological Sciences, University of Missouri-Columbia, Columbia, MO, USA.ORCID 0000-0002-4420-8546

Funding

PROPSPECTIVE STUDY OF OFFSPRING OF ALCOHOLICSR37AA007231 · NIAAA · UNIVERSITY OF MISSOURI-COLUMBIA · PI SHER, KENNETH JAMES · 1998 to 2006
$2.9M
Long Term Consequences of Collegiate Alcohol InvolvementR01AA013987 · NIAAA · UNIVERSITY OF MISSOURI-COLUMBIA · PI SHER, KENNETH JAMES · 2002 to 2005
$2.3M
Alcohol and Adult Development: Understanding Etiology and ConsequencesK05AA017242 · NIAAA · UNIVERSITY OF MISSOURI-COLUMBIA · PI SHER, KENNETH JAMES · 2007 to 2016
$2.1M
Common mechanisms of the microbiota-gut-brain axis in alcohol use disorder and depression: A genetically informed investigationK23AA026635 · NIAAA · UNIVERSITY OF COLORADO DENVER · PI ELLINGSON, JARROD MARTIN · 2018 to 2022
$907k
Investigating how bottom-up and top-down processes relate to alcohol use disorderF31AA022294 · NIAAA · UNIVERSITY OF MISSOURI-COLUMBIA · PI ELLINGSON, JARROD MARTIN · 2013 to 2014
$68k
NIAAA NIH HHS F31 AA022294NIAAA NIH HHS K05 AA017242NIAAA NIH HHS K23 AA026635NIAAA NIH HHS R01 AA013987NIAAA NIH HHS R37 AA007231
6 · The paper itself

Abstract

backgroundDevelopmental context is related to the propensity to engage in alcohol use, the rate at which alcohol use changes, and the relevance of different risk factors to alcohol use disorder (AUD). Therefore, studies of change should consider developmental nuances, but change is often modeled to follow a uniform pattern, even across distinct developmental periods.

methodsThis study implemented a novel analytic approach to delineate developmental periods of alcohol behavior (n = 478, ages 18 to 35). This approach was further leveraged to examine age-related shifts in the association of impulsivity risk factors (lack of planning, general sensation seeking, alcohol enhancement expectancies) with alcohol behavior (alcohol quantity*frequency, heavy drinking, AUD).

resultsA sequence of exploratory and confirmatory latent growth models (LGMs) suggested modeling separate linear change factors for alcohol behavior during the primary college (ages 18 to 21) and postcollege years (21 to 35). Bivariate LGMs estimated correlations for alcohol behavior changes with lack of planning, sensation seeking, and enhancement expectancies during these periods. The rate at which heavy drinking changed during the college years was positively correlated with general sensation seeking and lack of planning during this period (rs = 0.61 to 0.63). These correlations were significantly weaker during the postcollege years (rs = 0.29 to 0.34). Notably, the rate of change in alcohol behavior was strongly correlated with enhancement expectancies during the college (r = 0.45 to 0.70) and postcollege years (r = 0.45 to 0.61).

conclusionsThese findings highlight the importance of sensation seeking and lack of planning with regard to adult alcohol use, particularly in a college environment. There was also a strong link between the rates of change in alcohol behavior and enhancement expectancies across all waves. This study supports the utility of exploratory LGMs for delineating developmental periods of alcohol behavior, which are characterized by different processes.

Indexed as

Risk-TakingAdolescentAdultAlcohol DrinkingAlcoholismFemaleHumansImpulsive BehaviorMaleUniversitiesYoung AdultAlcoholChangeExploratoryImpulsivityLatent Growth ModelsSensation Seeking

Identifiers

PMID33512731
PMCPMC7887060

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.