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Evaluation of a concurrent‐operant demand assessment to determine task preference.

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Title: Evaluation of a concurrent‐operant demand assessment to determine task preference.
Authors: Lloveras, Lindsay A., Call, Nathan A., Bourret, Jason C., Slocum, Sarah K.
Source: Behavioral Interventions. Nov2020, Vol. 35 Issue 4, p508-523. 16p. 6 Graphs.
Subjects: Behavior disorders in children, Decision making, Medical needs assessment, Technology
Abstract: We conducted a concurrent‐operant demand assessment (CODA) to identify a hierarchy of preference for demands in 17 individuals who exhibited problem behavior. We presented demands in pairs, with selection between demands serving as the dependent variable. The reinforcing efficacy of escape from the most‐ and least‐selected demands from the CODA was evaluated for 7 participants using progressive‐ratio (PR) schedules. Outcomes from the PR analysis corresponded with the rank order of demands from the CODA. Four of these seven participants were subsequently exposed to a brief CODA with only two items, which consisted of successive presentations of the most‐ and least‐selected demands from the CODA. Outcomes of the brief CODA corresponded with the PR and CODA for 3 out of 4 participants. These results suggest that the CODA might be an effective technology to determine a hierarchy of preference for demands for assessment and treatment purposes. [ABSTRACT FROM AUTHOR]
Copyright of Behavioral Interventions is the property of Wiley-Blackwell 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
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  Data: Evaluation of a concurrent‐operant demand assessment to determine task preference.
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  Data: <searchLink fieldCode="AR" term="%22Lloveras%2C+Lindsay+A%2E%22">Lloveras, Lindsay A.</searchLink><br /><searchLink fieldCode="AR" term="%22Call%2C+Nathan+A%2E%22">Call, Nathan A.</searchLink><br /><searchLink fieldCode="AR" term="%22Bourret%2C+Jason+C%2E%22">Bourret, Jason C.</searchLink><br /><searchLink fieldCode="AR" term="%22Slocum%2C+Sarah+K%2E%22">Slocum, Sarah K.</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22Behavioral+Interventions%22">Behavioral Interventions</searchLink>. Nov2020, Vol. 35 Issue 4, p508-523. 16p. 6 Graphs.
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  Data: We conducted a concurrent‐operant demand assessment (CODA) to identify a hierarchy of preference for demands in 17 individuals who exhibited problem behavior. We presented demands in pairs, with selection between demands serving as the dependent variable. The reinforcing efficacy of escape from the most‐ and least‐selected demands from the CODA was evaluated for 7 participants using progressive‐ratio (PR) schedules. Outcomes from the PR analysis corresponded with the rank order of demands from the CODA. Four of these seven participants were subsequently exposed to a brief CODA with only two items, which consisted of successive presentations of the most‐ and least‐selected demands from the CODA. Outcomes of the brief CODA corresponded with the PR and CODA for 3 out of 4 participants. These results suggest that the CODA might be an effective technology to determine a hierarchy of preference for demands for assessment and treatment purposes. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Behavioral Interventions is the property of Wiley-Blackwell 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.)
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              Text: Nov2020
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