A Step Forward in Identifying Socially Desirable Respondents: An Integrated Machine Learning Model Considering T-Scores, Response Time, Kinematic Indicators, and Eye Movements
Implications: Combining self-report measures with implicit data can improve SDR detection, particularly in managerial, organizational, and forensic contexts where precise assessments are crucial.
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| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-01-01
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| Series: | Human Behavior and Emerging Technologies |
| Online Access: | http://dx.doi.org/10.1155/2024/7267030 |
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| author | Cristina Mazza Irene Ceccato Loreta Cannito Merylin Monaro Eleonora Ricci Emanuela Bartolini Alessandra Cardinale Adolfo Di Crosta Matteo Cardaioli Pasquale La Malva Marco Colasanti Renata Tambelli Luciano Giromini Rocco Palumbo Riccardo Palumbo Alberto Di Domenico Paolo Roma |
| author_facet | Cristina Mazza Irene Ceccato Loreta Cannito Merylin Monaro Eleonora Ricci Emanuela Bartolini Alessandra Cardinale Adolfo Di Crosta Matteo Cardaioli Pasquale La Malva Marco Colasanti Renata Tambelli Luciano Giromini Rocco Palumbo Riccardo Palumbo Alberto Di Domenico Paolo Roma |
| author_sort | Cristina Mazza |
| collection | DOAJ |
| description | Implications: Combining self-report measures with implicit data can improve SDR detection, particularly in managerial, organizational, and forensic contexts where precise assessments are crucial. |
| format | Article |
| id | doaj-art-4ba5285c8fc64aa192bd83eaa7e0b4ca |
| institution | Kabale University |
| issn | 2578-1863 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Human Behavior and Emerging Technologies |
| spelling | doaj-art-4ba5285c8fc64aa192bd83eaa7e0b4ca2025-02-03T05:15:52ZengWileyHuman Behavior and Emerging Technologies2578-18632024-01-01202410.1155/2024/7267030A Step Forward in Identifying Socially Desirable Respondents: An Integrated Machine Learning Model Considering T-Scores, Response Time, Kinematic Indicators, and Eye MovementsCristina Mazza0Irene Ceccato1Loreta Cannito2Merylin Monaro3Eleonora Ricci4Emanuela Bartolini5Alessandra Cardinale6Adolfo Di Crosta7Matteo Cardaioli8Pasquale La Malva9Marco Colasanti10Renata Tambelli11Luciano Giromini12Rocco Palumbo13Riccardo Palumbo14Alberto Di Domenico15Paolo Roma16Department of Dynamic and Clinical PsychologyDepartment of PsychologyDepartment of Social SciencesDepartment of General PsychologyDepartment of NeuroscienceDepartment of NeuroscienceNational Nuclear Physics InstituteDepartment of PsychologyDepartment of MathematicsDepartment of PsychologyDepartment of PsychologicalDepartment of Dynamic and Clinical PsychologyDepartment of PsychologyDepartment of PsychologyCenter for Advanced Studies and Technology (CAST)Department of PsychologyDepartment of Human NeuroscienceImplications: Combining self-report measures with implicit data can improve SDR detection, particularly in managerial, organizational, and forensic contexts where precise assessments are crucial.http://dx.doi.org/10.1155/2024/7267030 |
| spellingShingle | Cristina Mazza Irene Ceccato Loreta Cannito Merylin Monaro Eleonora Ricci Emanuela Bartolini Alessandra Cardinale Adolfo Di Crosta Matteo Cardaioli Pasquale La Malva Marco Colasanti Renata Tambelli Luciano Giromini Rocco Palumbo Riccardo Palumbo Alberto Di Domenico Paolo Roma A Step Forward in Identifying Socially Desirable Respondents: An Integrated Machine Learning Model Considering T-Scores, Response Time, Kinematic Indicators, and Eye Movements Human Behavior and Emerging Technologies |
| title | A Step Forward in Identifying Socially Desirable Respondents: An Integrated Machine Learning Model Considering T-Scores, Response Time, Kinematic Indicators, and Eye Movements |
| title_full | A Step Forward in Identifying Socially Desirable Respondents: An Integrated Machine Learning Model Considering T-Scores, Response Time, Kinematic Indicators, and Eye Movements |
| title_fullStr | A Step Forward in Identifying Socially Desirable Respondents: An Integrated Machine Learning Model Considering T-Scores, Response Time, Kinematic Indicators, and Eye Movements |
| title_full_unstemmed | A Step Forward in Identifying Socially Desirable Respondents: An Integrated Machine Learning Model Considering T-Scores, Response Time, Kinematic Indicators, and Eye Movements |
| title_short | A Step Forward in Identifying Socially Desirable Respondents: An Integrated Machine Learning Model Considering T-Scores, Response Time, Kinematic Indicators, and Eye Movements |
| title_sort | step forward in identifying socially desirable respondents an integrated machine learning model considering t scores response time kinematic indicators and eye movements |
| url | http://dx.doi.org/10.1155/2024/7267030 |
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