Solutions to Faking on Personality Tests

Solutions to Faking on Personality Tests

Any non-ability test used in a selection context runs the risk of individuals trying to ‘cheat’ or present themselves in a more favorable light. This is true for interviews, resumes, biodata tests, personality tests, values tests, and so forth. Early attempts to prevent this resulted in the use of forced choice measures in an attempt to get people to choose between two equally desirable attributes to reduce impression management. Unfortunately it doesn’t work for several reasons: a) the forced choice nature of this approach creates more inaccuracy than the initial problems over faking do b) controlled studies show that applicants ‘can’ fake if told they should present themselves in a better light, however, these studies show that most do not fake without being prompted to do so c) if we fear that faking is an issue, then we would expect that the test would not be very predictive of outcomes(i.e.valid) because of the distortion of the truth- there is no evidence that this is the case. In fact, the opposite is true. d) many tests incorporate indices and algorithms that catch people actively trying to cheat the system and look good. CounterpartMatch finds about 4-10% of applicants actively try to look better. These are normally screened out but it is up to the client to decide what to do with these cases e) some argue that the ability to identify what is needed in the company (i.e., saying what they want to hear) is actually a skill set. This is widely debated but it is one position f) we know that including warnings in the applicant instructions that cheating can be detected and that they will be removed from the competition if they exaggerate their responses has been demonstrated to eliminate cheating g) a combination of F and D is the best solution h) in their zeal to eliminate socially desirable responding, ipsative tests throw out important information and create false choices that corrupt the data they are trying to measure. It creates a worse problem than it is meant to solve. We figured that out in the 1950’s and 60’s but the testing methods being used by some tests pre-date even this very old news.

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