Evidence map›Paper›PMID 36804352›Full record

SynthesisJournal of substance use and addiction treatment2023

A systematic review of remotely delivered contingency management treatment for substance use.

Lara N Coughlin, Sarah Salino, Claudia Jennings, Madelyn Lacek, Whitney Townsend, Mikhail N Koffarnus, Erin E Bonar

Open access · greenAbstract readSystematic Review
In one paragraph

Synthesis 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 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
5.9field-weighted citation impact, top 3% 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

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

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  6. Interpol review of forensic drug chemistry, 2022-2025.Forensic science international. Synergy · 2026
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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.

Lara N CoughlinAddiction Center, Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA; Injury Prevention Center, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: laraco@med.umich.edu.
Sarah SalinoAddiction Center, Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA.
Claudia JenningsAddiction Center, Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA.
Madelyn LacekAddiction Center, Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA.
Whitney TownsendTaubman Health Sciences Library, University of Michigan, Ann Arbor, MI 48109, USA.
Mikhail N KoffarnusDepartment of Family and Community Medicine, University of Kentucky, Lexington, KY 40506, USA.
Erin E BonarAddiction Center, Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA; Injury Prevention Center, University of Michigan, Ann Arbor, MI 48109, USA.
University of Michigan–Ann Arbor · USUniversity of Kentucky · US

Funding

Optimizing mobile behavioral economic interventions for rural risky drinkersK23AA028232 · NIAAA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI COUGHLIN, LARA NICOLE · 2020 to 2024
$983k
NIAAA NIH HHS K23 AA028232
6 · The paper itself

Abstract

backgroundSubstance use and related consequences (e.g., impaired driving, injuries, disease transmission) continue to be major public health concerns. Contingency management (CM) is a highly effective treatment for substance use disorders. Yet CM remains vastly underutilized, in large part due to implementation barriers to in-person delivery. If feasible and effective, remote delivery of CM may reduce barriers at both the clinic- and patient-level, thus increasing reach and access to effective care. Here, we summarize data from a systematic review of studies reporting remote delivery of CM for substance use treatment.

methodsWe conducted a systematic review, reported according to PRISMA guidelines. The study team identified a total of 4358 articles after deduplication. Following title and abstract screening, full-text screening, and reference tracking, 39 studies met the eligibility criteria. We evaluated the methodological quality of the included studies using the Effective Public Health Practice Project Quality tool.

resultsOf 39 articles included in the review, most (n = 26) targeted cigarette smoking, with others focusing on alcohol (n = 9) or other substance use or targeting multiple substances (n = 4). Most remotely delivered CM studies focused on abstinence (n = 29), with others targeting substance use reduction (n = 2), intervention engagement (n = 5), and both abstinence and intervention engagement (n = 3). CM was associated with better outcomes (either abstinence, use reduction, or engagement), with increasingly more remotely delivered CM studies published in more recent years. Studies ranged from moderate to strong quality, with the majority (57.5 %) of studies being strong quality.

conclusionsConsistent with in-person CM, remotely delivered CM focusing on abstinence or use reduction from substances or engagement in substance use treatment services improves outcomes at the end of treatment compared to control conditions. Moreover, remotely delivered CM is feasible across a variety of digital delivery platforms (e.g., web, mobile, and wearable), with acceptability and reduced clinic and patient burden as technological advancements streamline monitoring and reinforcer delivery.

Indexed as

Substance-Related DisordersText MessagingAmbulatory Care FacilitiesBehavior TherapyHumansTreatment OutcomeAlcoholContingency managementDigital healthMotivational incentivesSmoking cessationSubstance useSystematic review

Identifiers

PMID36804352
PMCPMC10936237
OpenAlexW4320494267

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.