Evidence map›Paper›PMID 38258850›Full record

Trial reportSubstance use & addiction journal2024

Prediction Rules Identify Which Young Adults Have Higher Rates of Heavy Episodic Drinking After Exposure to 12-Week Text Message Interventions.

Tammy Chung, Brian Suffoletto, Sarah W Feldstein Ewing, Trishnee Bhurosy, Yanping Jiang, Pamela Valera

Open access · greenAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Substance use & addiction journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.9field-weighted citation impact, top 23% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Review
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 4 institutions in 1 country.

Tammy ChungDepartment of Psychiatry, Rutgers, The State University of New Jersey, New Brunswick, NJ, USA.ORCID 0000-0002-1527-2792
Brian SuffolettoDepartment of Emergency Medicine, Stanford University, Stanford, CA, USA.
Sarah W Feldstein EwingDepartment of Psychology, University of Rhode Island, Kingston, RI, USA.
Trishnee BhurosyDepartment of Population Health, School of Health Professions and Human Services, Hofstra University, Hempstead, NY, USA.
Yanping JiangInstitute for Health, Health Care Policy and Aging Research, Rutgers, The State University of New Jersey, New Brunswick, NJ, USA.
Pamela ValeraDepartment of Urban-Global Public Health, School of Public Health, Rutgers, The State University of New Jersey, New Brunswick, NJ, USA.
Rutgers, The State University of New Jersey · USHofstra University · USStanford University · USUniversity of Rhode Island · US

Funding

MECHANISMS OF CHANGE FOR AN EFFECTIVE ALCOHOL TEXT MESSAGE INTERVENTIONR01AA023650 · NIAAA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CHUNG, TAMMY, SUFFOLETTO, BRIAN P · 2016 to 2020
$1.8M
Smartphone sensors to detect shifts toward healthy behavior during alcohol treatmentR21AA030153 · NIAAA · RUTGERS BIOMEDICAL AND HEALTH SCIENCES · PI CHUNG, TAMMY · 2022 to 2023
$456k
NIAAA NIH HHS R01 AA023650NIAAA NIH HHS R21 AA030153
6 · The paper itself

Abstract

backgroundAn alcohol text message intervention recently demonstrated effects in reducing heavy episodic drinking (HED) days at the three month follow-up in young adults with a history of hazardous drinking. An important next step in understanding intervention effects involves identifying baseline participant characteristics that predict who will benefit from intervention exposure to support clinical decision-making and guide further intervention development. To identify baseline characteristics that predict HED, this exploratory study used a prediction rule ensemble (PRE). Compared to more complex decision-tree methods (e.g., random forest), PREs have comparable performance, while generating simpler rules that can directly identify subgroups that do or do not respond to intervention.

methodsThis secondary analysis examined data from 916 young adults who reported HED (68.5% female, mean age = 22.1, SD = 2.1), were enrolled in an alcohol text message randomized clinical trial and who completed baseline assessment and the three month follow-up. A PRE with ten fold cross-validation, which included 21 baseline variables representing sociodemographic characteristics (e.g., sex, age, race, ethnicity, college enrollment), alcohol consumption (frequency of alcohol consumption, quantity consumed on a typical drinking day, frequency of HED), impulsivity subscales (i.e., negative urgency, positive urgency, lack of premeditation, lack of perseverance, sensation seeking), readiness to change, perceived peer drinking and HED-related consequences, and intervention status were used to predict HED at the three month follow-up.

resultsThe PRE identified 12 rules that predicted HED at three months (

conclusionsThe rules provide interpretable decision-making tools that predict who has higher alcohol consumption following exposure to alcohol text message interventions using baseline participant characteristics (prior to intervention), which highlight the importance of interventions related to negative urgency and peer alcohol use.

Indexed as

Text MessagingAdultClinical Decision-MakingEthanolEthnicityHumansImpulsive BehaviorYoung AdultEthanolbinge drinkingheavy episodic drinkinginterventionprediction ruletext message

Identifiers

PMID38258850
PMCPMC10924270
OpenAlexW4390395478

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.