Evidence map›Paper›PMID 40191117›Full record

ArticleFrontiers in psychiatry2025

What does a dollar mean to you? utilizing intrinsic rewards within contingency management.

Anaheed Shirazi, Joseph A Carley, Dara G Ghahremani, Arthur L Brody, Ariel J Lang

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Anaheed ShiraziDepartment of Psychiatry, University of California, San Diego, San Diego, CA, United States.
Joseph A CarleyDepartment of Psychiatry, University of California, San Diego, San Diego, CA, United States.
Dara G GhahremaniDepartment of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States.
Arthur L BrodyDepartment of Psychiatry, University of California, San Diego, San Diego, CA, United States.
Ariel J LangDepartment of Psychiatry, University of California, San Diego, San Diego, CA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Substance Use Disorders (SUDs) pose a significant public health challenge. Medications used for treatment of SUDs are limited in their efficacy, particularly in cannabis and stimulant use disorders, and non-pharmacological interventions have shown, at most, moderate effectiveness, leaving a continuing need for improved treatments. Contingency management (CM) is an evidence-based treatment with promising results, operationalized in SUD treatment programs by using monetary rewards to help patients achieve target behaviors such as abstinence. Several factors limit the viability of CM as a sustainable, effective treatment, suggesting insufficiency of monetary reinforcement alone. Implementation can be costly, requiring increased monetary reinforcers over time to reach target behaviors, and effects do not endure. We propose an integrative model of CM that explicitly incorporates intrinsic rewards into CM to enhance its effectiveness. This model involves redirecting salience attribution of monetary rewards towards goals and activities that are personally relevant and motivating for the individual that do not involve substance use. This integrative model of CM may address current challenges of and some of the barriers to implementation of CM in clinical practice.

Indexed as

addictioncontingency management (CM)Integrative Contingency Managementintegrative treatment approachesintrinsic rewardsubstance use disorder

Identifiers

PMID40191117
PMCPMC11969068

What OpenQuestion holds

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Registered trials

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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.