faking good
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Author(s):  
Jessica Röhner ◽  
Ronald R. Holden

AbstractFaking detection is an ongoing challenge in psychological assessment. A notable approach for detecting fakers involves the inspection of response latencies and is based on the congruence model of faking. According to this model, respondents who fake good will provide favorable responses (i.e., congruent answers) faster than they provide unfavorable (i.e., incongruent) responses. Although the model has been validated in various experimental faking studies, to date, research supporting the congruence model has focused on scales with large numbers of items. Furthermore, in this previous research, fakers have usually been warned that faking could be detected. In view of the trend to use increasingly shorter scales in assessment, it becomes important to investigate whether the congruence model also applies to self-report measures with small numbers of items. In addition, it is unclear whether warning participants about faking detection is necessary for a successful application of the congruence model. To address these issues, we reanalyzed data sets of two studies that investigated faking good and faking bad on extraversion (n = 255) and need for cognition (n = 146) scales. Reanalyses demonstrated that having only a few items per scale and not warning participants represent a challenge for the congruence model. The congruence model of faking was only partly confirmed under such conditions. Although faking good on extraversion was associated with the expected longer latencies for incongruent answers, all other conditions remained nonsignificant. Thus, properties of the measurement and properties of the procedure affect the successful application of the congruence model.


Author(s):  
Merylin Monaro ◽  
Cristina Mazza ◽  
Marco Colasanti ◽  
Stefano Ferracuti ◽  
Graziella Orrù ◽  
...  

AbstractDeliberate 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%).


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Cristina Mazza ◽  
Merylin Monaro ◽  
Franco Burla ◽  
Marco Colasanti ◽  
Graziella Orrù ◽  
...  

2020 ◽  
Vol 36 (2) ◽  
pp. 250-258 ◽  
Author(s):  
Paolo Roma ◽  
Cristina Mazza ◽  
Simona Mammarella ◽  
Beatrice Mantovani ◽  
Gabriele Mandarelli ◽  
...  

Abstract. Speeded answering to items on a personality test has long been considered a factor in the validity of the results obtained. In this study, to better understand the utility of time pressure in the evaluation of faking-good behavior, we assessed four groups of volunteers in “honest versus faking-good” and “without time pressure versus speeded” conditions. We compared respondents’ T-point scores in the three self-favorable scales of the MMPI-2 (L, K, and S), their response latencies in these scales, and the number of pathological items they endorsed. Data from 102 males ( M = 25.5, SD = 2.16 years) showed that the faking-good condition required more time and the speeded condition increased T-point scores. Comparisons with previous research are discussed, and ideas for further study are generated.


2019 ◽  
Vol 28 (2) ◽  
pp. 176-185
Author(s):  
Pierpaolo Calanna ◽  
Marco Lauriola ◽  
Aristide Saggino ◽  
Marco Tommasi ◽  
Sarah Furlan

2018 ◽  
Vol 2 ◽  
Author(s):  
Gerry Fahey

High stakes selection contexts often drive the provision of socially desirable responses from job applicants. This can take the form of ‘faking good’ and can lead to inaccurate personality assessments. This article reviews the extant research on the extent to which faking good occurs, the psychological factors that may lead to faking good by job applicants, and how faking good is measured. In particular, the review considers the role of moral hypocrisy in this regard and considers how it can be minimised.


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