Detecting faking-good response style in personality questionnaires with four choice alternatives.
Saved in:
| Title: | Detecting faking-good response style in personality questionnaires with four choice alternatives. |
|---|---|
| Authors: | Monaro, Merylin (AUTHOR), Mazza, Cristina (AUTHOR), Colasanti, Marco (AUTHOR), Ferracuti, Stefano (AUTHOR), Orrù, Graziella (AUTHOR), di Domenico, Alberto (AUTHOR), Sartori, Giuseppe (AUTHOR), Roma, Paolo (AUTHOR) |
| Source: | Psychological Research. Nov2021, Vol. 85 Issue 8, p3094-3107. 14p. 1 Diagram, 6 Charts. |
| Subjects: | Personality questionnaires, Impression management, Mice (Computers), Time pressure, Machine learning, Response styles (Examinations) |
| Abstract: | Deliberate attempts to portray oneself in an unrealistic manner are commonly encountered in the administration of personality questionnaires. The main aim of the present study was to explore whether mouse tracking temporal indicators and machine learning models could improve the detection of subjects implementing a faking-good response style when answering personality inventories with four choice alternatives, with and without time pressure. A total of 120 volunteers were randomly assigned to one of four experimental groups and asked to respond to the Virtuous Responding (VR) validity scale of the PPI-R and the Positive Impression Management (PIM) validity scale of the PAI via a computer mouse. A mixed design was implemented, and predictive models were calculated. The results showed that, on the PIM scale, faking-good participants were significantly slower in responding than honest respondents. Relative to VR items, PIM items are shorter in length and feature no negations. Accordingly, the PIM scale was found to be more sensitive in distinguishing between honest and faking-good respondents, demonstrating high classification accuracy (80–83%). [ABSTRACT FROM AUTHOR] |
| Copyright of Psychological Research 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 |
|
Full text is not displayed to guests.
Login for full access.
|
|
| FullText | Links: – Type: pdflink Text: Availability: 1 |
|---|---|
| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 152654990 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Detecting faking-good response style in personality questionnaires with four choice alternatives. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Monaro%2C+Merylin%22">Monaro, Merylin</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mazza%2C+Cristina%22">Mazza, Cristina</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Colasanti%2C+Marco%22">Colasanti, Marco</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ferracuti%2C+Stefano%22">Ferracuti, Stefano</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Orrù%2C+Graziella%22">Orrù, Graziella</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22di+Domenico%2C+Alberto%22">di Domenico, Alberto</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sartori%2C+Giuseppe%22">Sartori, Giuseppe</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Roma%2C+Paolo%22">Roma, Paolo</searchLink> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Psychological+Research%22">Psychological Research</searchLink>. Nov2021, Vol. 85 Issue 8, p3094-3107. 14p. 1 Diagram, 6 Charts. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Personality+questionnaires%22">Personality questionnaires</searchLink><br /><searchLink fieldCode="DE" term="%22Impression+management%22">Impression management</searchLink><br /><searchLink fieldCode="DE" term="%22Mice+%28Computers%29%22">Mice (Computers)</searchLink><br /><searchLink fieldCode="DE" term="%22Time+pressure%22">Time pressure</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Response+styles+%28Examinations%29%22">Response styles (Examinations)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Deliberate attempts to portray oneself in an unrealistic manner are commonly encountered in the administration of personality questionnaires. The main aim of the present study was to explore whether mouse tracking temporal indicators and machine learning models could improve the detection of subjects implementing a faking-good response style when answering personality inventories with four choice alternatives, with and without time pressure. A total of 120 volunteers were randomly assigned to one of four experimental groups and asked to respond to the Virtuous Responding (VR) validity scale of the PPI-R and the Positive Impression Management (PIM) validity scale of the PAI via a computer mouse. A mixed design was implemented, and predictive models were calculated. The results showed that, on the PIM scale, faking-good participants were significantly slower in responding than honest respondents. Relative to VR items, PIM items are shorter in length and feature no negations. Accordingly, the PIM scale was found to be more sensitive in distinguishing between honest and faking-good respondents, demonstrating high classification accuracy (80–83%). [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Psychological Research 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=152654990 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s00426-020-01473-3 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 3094 Subjects: – SubjectFull: Personality questionnaires Type: general – SubjectFull: Impression management Type: general – SubjectFull: Mice (Computers) Type: general – SubjectFull: Time pressure Type: general – SubjectFull: Machine learning Type: general – SubjectFull: Response styles (Examinations) Type: general Titles: – TitleFull: Detecting faking-good response style in personality questionnaires with four choice alternatives. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Monaro, Merylin – PersonEntity: Name: NameFull: Mazza, Cristina – PersonEntity: Name: NameFull: Colasanti, Marco – PersonEntity: Name: NameFull: Ferracuti, Stefano – PersonEntity: Name: NameFull: Orrù, Graziella – PersonEntity: Name: NameFull: di Domenico, Alberto – PersonEntity: Name: NameFull: Sartori, Giuseppe – PersonEntity: Name: NameFull: Roma, Paolo IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: Nov2021 Type: published Y: 2021 Identifiers: – Type: issn-print Value: 03400727 Numbering: – Type: volume Value: 85 – Type: issue Value: 8 Titles: – TitleFull: Psychological Research Type: main |
| ResultId | 1 |
