Evidence map›Paper›PMID 40434969›Full record

ArticlePloS one2025

Mobile telephone-delivered Contingency Management (mCM) to reduce heroin use in individuals with opioid use disorder (CM4OUD): A feasibility study protocol.

Carol-Ann Getty, John Strang, Ewan Carr, Jesse Dallery, Nicola Metrebian

Abstract read
In one paragraph

Article in PloS one, 2025. 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
–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

1 citing paper in PubMed.

  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

5 authors.

Carol-Ann GettyNational Addiction Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0003-4151-7797
John StrangNational Addiction Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-5413-2725
Ewan CarrBiostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
Jesse DalleryDepartment of Psychology, University of Florida, Gainesville, Florida, United States of America.
Nicola MetrebianNational Addiction Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOpioid use disorder (OUD) is a major public health issue and recovery is a long-term and complex process. Opioid Agonist Treatment (OAT) including medications such as methadone and buprenorphine, is the first-line medical intervention for OUD, however clinical responses among sub-populations differ and concurrent heroin use among individuals in OAT is reported. Contingency management (CM) is a behavioural intervention involving the application of positive reinforcement (e.g., monetary incentives) contingent upon evidence of positive behaviour change. CM is based on the theoretical principles of operant conditioning and is among the most efficacious psychosocial intervention in promoting substance use-related behaviours, including abstinence from smoking, alcohol and illicit drugs, medication adherence, vaccination uptake and attendance. Technology can be leveraged to expand the reach and accessibility of these interventions, automating key components of intervention delivery, including objective behaviour monitoring and immediate reward delivery. Currently, there are no fully remote CM interventions specifically targeting heroin use among individuals undergoing treatment for OUD, highlighting a critical need for innovation in addressing this complex aspect of substance use. Developing and delivering a fully digitalised app-based CM intervention for reducing heroin use among individuals in treatment for OUD holds considerable potential. This paper provides a protocol for a feasibility study that aims to determine the acceptability and feasibility of conducting a future randomised controlled trial of the clinical effectiveness of app-based CM to encourage heroin abstinence among clients receiving OAT in UK drug treatment services.

methodsForty OAT service users in UK drug treatment services who continue to use heroin will be randomly assigned to either (1) OAT plus a smartphone app providing abstinence incentives or (2) standard OAT alone. Participants in the intervention arm will receive financial incentives contingent on heroin-negative toxicology results. Over a 12-week period, participants will receive thrice-weekly push notifications via the smartphone app when an oral saliva test is due. Participants will receive feedback upon submission and verified heroin-negative tests will result in notification of earnings. The primary outcome of this feasibility trial is the number of eligible service users recruited over the 6-month recruitment period. Other feasibility outcomes include intervention adherence, drug screening completion and follow-up rates. Acceptability will be explored among both clinicians and service users. Progression to a larger confirmatory trial will be evaluated based on the pre-specified progression criteria. DISCUSSION: Research on CM has grown exponentially over the last decade, with remote technologies being leveraged more than ever to expand the reach and scope of these interventions. This study will evaluate the feasibility of a mCM app to support heroin abstinence among OAT recipients. By integrating CM with mobile technology, this approach could enhance treatment accessibility and effectiveness, potentially improving outcomes for a high-risk population.

Indexed as

Behavior TherapyCell PhoneHeroin DependenceOpioid-Related DisordersAdultFeasibility StudiesFemaleHeroinHumansMaleOpiate Substitution TreatmentHeroin

Identifiers

PMID40434969
PMCPMC12118896

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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.