Toward a Predictive Model of Success in Contingency Management: A Proof of Concept Study Utilizing Behavioral Economic, Clinical Severity, and Alcohol Use Severity Measures.
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| Title: | Toward a Predictive Model of Success in Contingency Management: A Proof of Concept Study Utilizing Behavioral Economic, Clinical Severity, and Alcohol Use Severity Measures. |
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| Authors: | Traxler, Haily K. (AUTHOR), Franck, Christopher T. (AUTHOR), Koffarnus, Mikhail N. (AUTHOR) |
| Source: | Psychological Record. Mar2026, Vol. 76 Issue 1, p121-130. 10p. |
| Subjects: | Prediction models, Treatment effectiveness, Delay discounting (Psychology), Logistic regression analysis, Anxiety, Behavioral economics, Alcoholism, Contingency management |
| Abstract: | As contingency management (CM) moves from research to practice, researchers have a responsibility to outline the minimum procedural necessities that lead to an effective, sustainable treatment that can be implemented as a mainstream therapy for substance use disorders. To begin identifying the minimum requirements, the purpose of the current study was to provide framework and a first step toward building a risk calculator that predicts treatment outcomes in CM, and can predict the optimal incentive size to prescribe by evaluating behavioral economic factors, demographic variables, and use severity measures in individuals who completed CM treatment for alcohol use. Participants were 38 individuals enrolled in the active treatment arms of two parent CM studies for reducing alcohol use (Koffarnus et al., 2018; Koffarnus et al., 2021). Participants were 42 years old on average, 55% male, and a majority were white, non-Hispanic. Fifteen candidate predictor variables were assessed for inclusion in the predictive model including demographic variables, use severity scores, and behavioral economic parameters. A logistic regression framework was used to identify top predictive models. Accuracy was assessed by computing receiver operating characteristic (ROC) curves and area under the curves. A model including the delay discounting parameter, log10(ED50) of alcohol, participant age, and Beck's Anxiety Inventory score was predictive of treatment outcomes in the current sample. The results demonstrate the utility of the ROC analysis as a method for identifying a predictive model. Further research is needed to replicate and verify the findings of the current analysis. [ABSTRACT FROM AUTHOR] |
| Copyright of Psychological Record is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
| FullText | Text: Availability: 0 |
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| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 193564496 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Toward a Predictive Model of Success in Contingency Management: A Proof of Concept Study Utilizing Behavioral Economic, Clinical Severity, and Alcohol Use Severity Measures. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Traxler%2C+Haily+K%2E%22">Traxler, Haily K.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Franck%2C+Christopher+T%2E%22">Franck, Christopher T.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Koffarnus%2C+Mikhail+N%2E%22">Koffarnus, Mikhail N.</searchLink> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Psychological+Record%22">Psychological Record</searchLink>. Mar2026, Vol. 76 Issue 1, p121-130. 10p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Prediction+models%22">Prediction models</searchLink><br /><searchLink fieldCode="DE" term="%22Treatment+effectiveness%22">Treatment effectiveness</searchLink><br /><searchLink fieldCode="DE" term="%22Delay+discounting+%28Psychology%29%22">Delay discounting (Psychology)</searchLink><br /><searchLink fieldCode="DE" term="%22Logistic+regression+analysis%22">Logistic regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Anxiety%22">Anxiety</searchLink><br /><searchLink fieldCode="DE" term="%22Behavioral+economics%22">Behavioral economics</searchLink><br /><searchLink fieldCode="DE" term="%22Alcoholism%22">Alcoholism</searchLink><br /><searchLink fieldCode="DE" term="%22Contingency+management%22">Contingency management</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: As contingency management (CM) moves from research to practice, researchers have a responsibility to outline the minimum procedural necessities that lead to an effective, sustainable treatment that can be implemented as a mainstream therapy for substance use disorders. To begin identifying the minimum requirements, the purpose of the current study was to provide framework and a first step toward building a risk calculator that predicts treatment outcomes in CM, and can predict the optimal incentive size to prescribe by evaluating behavioral economic factors, demographic variables, and use severity measures in individuals who completed CM treatment for alcohol use. Participants were 38 individuals enrolled in the active treatment arms of two parent CM studies for reducing alcohol use (Koffarnus et al., 2018; Koffarnus et al., 2021). Participants were 42 years old on average, 55% male, and a majority were white, non-Hispanic. Fifteen candidate predictor variables were assessed for inclusion in the predictive model including demographic variables, use severity scores, and behavioral economic parameters. A logistic regression framework was used to identify top predictive models. Accuracy was assessed by computing receiver operating characteristic (ROC) curves and area under the curves. A model including the delay discounting parameter, log10(ED50) of alcohol, participant age, and Beck's Anxiety Inventory score was predictive of treatment outcomes in the current sample. The results demonstrate the utility of the ROC analysis as a method for identifying a predictive model. Further research is needed to replicate and verify the findings of the current analysis. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Psychological Record is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=193564496 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s40732-025-00671-y Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 121 Subjects: – SubjectFull: Prediction models Type: general – SubjectFull: Treatment effectiveness Type: general – SubjectFull: Delay discounting (Psychology) Type: general – SubjectFull: Logistic regression analysis Type: general – SubjectFull: Anxiety Type: general – SubjectFull: Behavioral economics Type: general – SubjectFull: Alcoholism Type: general – SubjectFull: Contingency management Type: general Titles: – TitleFull: Toward a Predictive Model of Success in Contingency Management: A Proof of Concept Study Utilizing Behavioral Economic, Clinical Severity, and Alcohol Use Severity Measures. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Traxler, Haily K. – PersonEntity: Name: NameFull: Franck, Christopher T. – PersonEntity: Name: NameFull: Koffarnus, Mikhail N. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 00332933 Numbering: – Type: volume Value: 76 – Type: issue Value: 1 Titles: – TitleFull: Psychological Record Type: main |
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