The prediction of emotional decision making from working memory and inhibitory control in preschool children: using decision tree model.
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| Title: | The prediction of emotional decision making from working memory and inhibitory control in preschool children: using decision tree model. |
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| Authors: | Abbaasi, Marzihe (AUTHOR), Mashhadi, Ali (AUTHOR), Bigdeli, Imanollah (AUTHOR), Shahaeian, Ameneh (AUTHOR) |
| Source: | Child Neuropsychology. Feb2025, Vol. 31 Issue 2, p312-330. 19p. |
| Subjects: | Statistical decision making, Executive function, Response inhibition, Decision trees, Memory span |
| Abstract: | While there is a theoretical distinction between cool (cognitive) and hot (emotional) executive functions, potential relationships can be identified between tasks associated with these two aspects. A decision tree serves as a model for training and analyzing data, predicting the target variable based on independent variables in a hierarchical fashion. In contrast to other predictive methods, this model doesn't necessitate statistical expertise and makes decisions akin to human decision-making through hierarchical "if" and "then" rules, providing an easily interpretable framework. To date, no studies have explored the relationship between cool and hot executive functions using decision tree models. In this study, preschool children specifically Persian-speaking Iranian children aged 4 to 5 years (N = 71, M age = 59.07; SD = 6.03), participated in cool (Forward Digit Span, Backward Digit Span, Day-Night inhibitory control, and Happy-Sad Inhibitory control) and hot (Children Gambling Task) executive function tasks. Analyses were performed using MATLAB programming software. The C4.5 version of the decision tree was employed to predict the final CGT blocks' scores using scores from cool executive function tasks as inputs. By employing this method, a minimal prediction error (approaching zero) was achieved, significantly showing the robust predictive capability of cool executive function in anticipating hot executive function. This outcome suggests potential relationships between the cognitive and emotional aspects of executive function. [ABSTRACT FROM AUTHOR] |
| Copyright of Child Neuropsychology is the property of Taylor & Francis Ltd 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 | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 183112455 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: The prediction of emotional decision making from working memory and inhibitory control in preschool children: using decision tree model. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Abbaasi%2C+Marzihe%22">Abbaasi, Marzihe</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mashhadi%2C+Ali%22">Mashhadi, Ali</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bigdeli%2C+Imanollah%22">Bigdeli, Imanollah</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shahaeian%2C+Ameneh%22">Shahaeian, Ameneh</searchLink> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Child+Neuropsychology%22">Child Neuropsychology</searchLink>. Feb2025, Vol. 31 Issue 2, p312-330. 19p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Statistical+decision+making%22">Statistical decision making</searchLink><br /><searchLink fieldCode="DE" term="%22Executive+function%22">Executive function</searchLink><br /><searchLink fieldCode="DE" term="%22Response+inhibition%22">Response inhibition</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+trees%22">Decision trees</searchLink><br /><searchLink fieldCode="DE" term="%22Memory+span%22">Memory span</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: While there is a theoretical distinction between cool (cognitive) and hot (emotional) executive functions, potential relationships can be identified between tasks associated with these two aspects. A decision tree serves as a model for training and analyzing data, predicting the target variable based on independent variables in a hierarchical fashion. In contrast to other predictive methods, this model doesn't necessitate statistical expertise and makes decisions akin to human decision-making through hierarchical "if" and "then" rules, providing an easily interpretable framework. To date, no studies have explored the relationship between cool and hot executive functions using decision tree models. In this study, preschool children specifically Persian-speaking Iranian children aged 4 to 5 years (N = 71, M age = 59.07; SD = 6.03), participated in cool (Forward Digit Span, Backward Digit Span, Day-Night inhibitory control, and Happy-Sad Inhibitory control) and hot (Children Gambling Task) executive function tasks. Analyses were performed using MATLAB programming software. The C4.5 version of the decision tree was employed to predict the final CGT blocks' scores using scores from cool executive function tasks as inputs. By employing this method, a minimal prediction error (approaching zero) was achieved, significantly showing the robust predictive capability of cool executive function in anticipating hot executive function. This outcome suggests potential relationships between the cognitive and emotional aspects of executive function. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Child Neuropsychology is the property of Taylor & Francis Ltd 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=183112455 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/09297049.2024.2368222 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 19 StartPage: 312 Subjects: – SubjectFull: Statistical decision making Type: general – SubjectFull: Executive function Type: general – SubjectFull: Response inhibition Type: general – SubjectFull: Decision trees Type: general – SubjectFull: Memory span Type: general Titles: – TitleFull: The prediction of emotional decision making from working memory and inhibitory control in preschool children: using decision tree model. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Abbaasi, Marzihe – PersonEntity: Name: NameFull: Mashhadi, Ali – PersonEntity: Name: NameFull: Bigdeli, Imanollah – PersonEntity: Name: NameFull: Shahaeian, Ameneh IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 09297049 Numbering: – Type: volume Value: 31 – Type: issue Value: 2 Titles: – TitleFull: Child Neuropsychology Type: main |
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