Evidence map›Paper›PMID 36801204›Full record

Trial reportJournal of substance use and addiction treatment2023

Exploring the mediating role of baseline urinalysis results on demographic characteristics and stimulant use disorder treatment outcomes.

Crystal L Smith, André Q Miguel, Abigail Keever, Theresa Bowden, Ekaterina Burduli, John Roll, Sterling M McPherson

Open access · greenAbstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Journal of substance use and addiction treatment, 2023. 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
0.3field-weighted citation impact, top 43% 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, 1 citations in OpenAlex.

  1. 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

7 authors at 2 institutions in 1 country.

Crystal L SmithWashington State University, Program of Excellence in Addictions Research (PEAR), USA; Washington State University, Elson S. Floyd College of Medicine Department of Community and Behavioral Health, USA; Washington State University, Analytics and PsychoPharmacology Laboratory (APPL), USA.
André Q MiguelWashington State University, Program of Excellence in Addictions Research (PEAR), USA; Washington State University, Elson S. Floyd College of Medicine Department of Community and Behavioral Health, USA; Washington State University, Analytics and PsychoPharmacology Laboratory (APPL), USA. Electronic address: andre.miguel@wsu.edu.
Abigail KeeverWashington State University, Program of Excellence in Addictions Research (PEAR), USA; Washington State University, Elson S. Floyd College of Medicine Department of Community and Behavioral Health, USA; Washington State University, Analytics and PsychoPharmacology Laboratory (APPL), USA.
Theresa BowdenWashington State University, Program of Excellence in Addictions Research (PEAR), USA; Washington State University, Analytics and PsychoPharmacology Laboratory (APPL), USA; Washington State University, College of Nursing, USA.
Ekaterina BurduliWashington State University, Program of Excellence in Addictions Research (PEAR), USA; Washington State University, Analytics and PsychoPharmacology Laboratory (APPL), USA; Washington State University, College of Nursing, USA.
John RollWashington State University, Program of Excellence in Addictions Research (PEAR), USA; Washington State University, Elson S. Floyd College of Medicine Department of Community and Behavioral Health, USA; Washington State University, Analytics and PsychoPharmacology Laboratory (APPL), USA; Washington State University, College of Nursing, USA.
Sterling M McPhersonWashington State University, Program of Excellence in Addictions Research (PEAR), USA; Washington State University, Elson S. Floyd College of Medicine Department of Community and Behavioral Health, USA; Washington State University, Analytics and PsychoPharmacology Laboratory (APPL), USA.
Georgia Highlands College · USWashington State University · US

Funding

CLINICAL TRIALS NETWORK: PACIFIC NORTHWEST NODEU10DA013714 · NIDA · UNIVERSITY OF WASHINGTON · PI DONOVAN, DENNIS MICHAEL, ROLL, JOHN M. · 2001 to 2015
$25.5M
Clinical Trials Network: Pacific Northwest Node (CTN-0082, -0131, -0139 and dissemination library)UG1DA013714 · NIDA · UNIVERSITY OF WASHINGTON · PI Mary Akiko Hatch, John M. Roll · 2015 to 2026
$19.8M
NIDA NIH HHS U10 DA013714NIDA NIH HHS UG1 DA013714
6 · The paper itself

Abstract

introductionBaseline stimulant urinalysis (UA) is one of the most reliable predictors of stimulant use disorder treatment outcomes. Yet we know little about the role of baseline stimulant UA mediating the effects of different baseline characteristics on treatment outcomes.

objectivesThis study aimed to explore the potential mediating role of baseline stimulant UA results on the relationship between baseline characteristics and total number of stimulant negative UAs submitted during treatment.

methodsThe study team conducted analyses on data from a multisite randomized clinical trial of contingency management (CM) targeting stimulant use among individuals enrolled in methadone maintenance treatment programs (n = 394). Baseline characteristics included trial arm, education, race, sex, age, and Addiction Severity Index (ASI) composite measures. Baseline stimulant UA was the mediator and total number of stimulant negative UAs provided during treatment was the primary outcome variable.

resultsThe baseline characteristics of sex (OR = 1.85), ASI drug (OR = 0.01) and psychiatric (OR = 6.20) composites were directly associated with the baseline stimulant UA result (p < 0.05 for all). Baseline stimulant UA result (B = -8.24), trial arm (B = -2.55), ASI drug composite (B = -8.38) and education (B = -1.95) were directly associated with the total number of negative UAs submitted (p < 0.05 for all). The evaluation of indirect effects of baseline characteristics on the primary outcome through baseline stimulant UA revealed significant mediated effects for the ASI drug composite (B = -5.50) and age (B = -0.05; p < 0.05 for both).

conclusionsBaseline stimulant UA is a strong predictor of stimulant use treatment outcomes and mediates the association of some baseline characteristics and a stimulant use treatment outcome.

Indexed as

Behavior TherapyCentral Nervous System StimulantsDemographyHumansTreatment OutcomeUrinalysisCentral Nervous System StimulantsBaseline urinalysisClinical trialsContingency managementMediationStimulant use

Identifiers

PMID36801204
PMCPMC10313760
OpenAlexW4319993056

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.