Detection strategies for feigned psychopathology: test development and effects of criminal charge simulation design on response styles

© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. Feigned psychopathology detection strategy is needed for forensic settings in Thailand. This initial Thai version of the symptoms validity test (SVT-Th) was developed based on two global detection strategies including unlike...

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Bibliographic Details
Main Authors: Natthawut Arin, Salika Khowboonngam
Format: Journal
Published: 2018
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Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85054417245&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/62835
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Institution: Chiang Mai University
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Summary:© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. Feigned psychopathology detection strategy is needed for forensic settings in Thailand. This initial Thai version of the symptoms validity test (SVT-Th) was developed based on two global detection strategies including unlikely and amplified detection strategies proposed by Rogers. The participants were collected from populations of nonclinical undergraduate students and clinical psychiatric patients. Results of Study 1, confirmatory factor analysis (CFA) were used to determine the factor structures of the SVT-Th. The results of CFA supported 2-factorial model as proposed by Rogers. The SVT-Th was found to possess a high degree of internal consistency. Using a simulation designed in Study 2, the experimental group was asked to feign psychopathology to avoid criminal prosecution of homicide charges (simulator undergraduate students). The findings were compared with two control groups who were asked to reply to the questions honestly (honest undergraduate students and honest psychiatric patients). The results indicated that the SVT-Th were significantly distinguishable in the experimental group (classified as feigned response style) from the control groups (classified as honest response style). The area under the ROC curve showed high accuracy classification. The ROC curve determined the optimal cutoff score, sensitivity and specificity for the SVT-Th.