Evidence map›Paper›PMID 30690502›Full record

ArticleThe international journal of neuropsychopharmacology2019

Behavioral and Accumbal Responses During an Affective Go/No-Go Task Predict Adherence to Injectable Naltrexone Treatment in Opioid Use Disorder.

Zhenhao Shi, Kanchana Jagannathan, An-Li Wang, Victoria P Fairchild, Kevin G Lynch, Jesse J Suh, Anna Rose Childress, Daniel D Langleben

Open access · goldAbstract read
In one paragraph

Article in The international journal of neuropsychopharmacology, 2019. 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 41% 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, 8 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

8 authors at 2 institutions in 1 country.

Zhenhao ShiCenter for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Kanchana JagannathanCenter for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
An-Li WangCenter for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Victoria P FairchildCenter for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Kevin G LynchCenter for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Jesse J SuhCenter for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Anna Rose ChildressCenter for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Daniel D LanglebenAnnenberg Public Policy Center, University of Pennsylvania, Philadelphia, PA.
University of Pennsylvania · USPhiladelphia VA Medical Center · US

Funding

T32 Translational Addiction Research Fellowship ProgramT32DA028874 · NIDA · UNIVERSITY OF PENNSYLVANIA · PI Julie A Blendy, Anna Rose Childress · 2010 to 2026
$5.0M
Brain and behavioral effects of graphic cigarette warning labelsR01DA036028 · NIDA · UNIVERSITY OF PENNSYLVANIA · PI LANGLEBEN, DANIEL D · 2013 to 2017
$2.9M
Neurobehavioral Study of Warnings for Adolescents at Risk for Nicotine DependenceR00HD084746 · NICHD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI WANG, AN-LI · 2017 to 2019
$747k
Neurobiology of care giving in opioid dependent mothersR21DA043983 · NIDA · UNIVERSITY OF PENNSYLVANIA · PI LANGLEBEN, DANIEL D · 2017 to 2018
$409k
Neurobehavioral Study of Warnings for Adolescents at Risk for Nicotine DependenceK99HD084746 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI WANG, AN-LI · 2015 to 2016
$263k
NICHD NIH HHS K99 HD084746NICHD NIH HHS R00 HD084746NIDA NIH HHS R01 DA036028NIDA NIH HHS R21 DA043983NIDA NIH HHS T32 DA028874
6 · The paper itself

Abstract

Adherence is a major factor in the effectiveness of the injectable extended-release naltrexone as a relapse prevention treatment in opioid use disorder. We examined the value of a variant of the Go/No-go paradigm in predicting extended-release naltrexone adherence in 27 detoxified opioid use disorder patients who were offered up to 3 monthly extended-release naltrexone injections. Before extended-release naltrexone, participants performed a Go/No-go task that comprised positively valenced Go trials and negatively valenced No-go trials during a functional magnetic resonance imaging scan. Errors of commission and neural responses to the No-go vs Go trials were independent variables. Adherence, operationalized as the completion of all 3 extended-release naltrexone injections, was the outcome variable. Fewer errors of commission and greater left accumbal response during the No-go vs Go trials predicted better adherence. These findings support the clinical potential of the behavioral and neurophysiological correlates of response inhibition in the prediction of extended-release naltrexone treatment outcomes in opioid use disorder.

Indexed as

Medication AdherenceAdolescentAdultDelayed-Action PreparationsFemaleHumansInjections, IntramuscularMagnetic Resonance ImagingMaleNaltrexoneNarcotic AntagonistsNucleus AccumbensOpioid-Related DisordersPhotic StimulationPredictive Value of TestsPsychomotor PerformanceDelayed-Action PreparationsNaltrexoneNarcotic Antagonistsadherenceerrors of commissionextended-release naltrexonenucleus accumbensopioid use disorder

Identifiers

PMID30690502
PMCPMC6403086
OpenAlexW2912328565

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.