Abstract: Using personality tests in personnel selection becomes increasingly popular in industries in China. However, the validity of personality tests is challenged due to the possibility of getting faking answers (Morgeson et al, 2007). Methods dealing with faking in personality tests are available. The most commonly used one is to detect faking by using social desirability (SD) scale, and then calibrate the results to remove the faking effect.
However, authors of this study argue that faking is conceptually different from socially desirable responding (SDR), and using SD Scale to measure faking effect is inappropriate. The reasons include: (1) although both faking and SDR are the tendency to exaggerate, the former is influenced by job desirability, while the later is influenced by social desirability. (2) SD Scale can not measure Impression Management and Self-Deception independently and has poor construct validity (Paulhus, 2002).
This research developed a “Faking Detection Scale for General Positions” in seven steps based on the procedures used to develop the SD scale and the special tributes of faking.
First, behavior descriptions which are strong job-desirable and extremely infrequent or high frequency were collected and rewritten into 114 items. Second, trained raters rated the desirability and occur-probability of these items and selected 50 items for the draft scale. Third, an experimental study was conducted with 679 subjects to further select items. Subjects were paid for 20 RMB if they successfully faked in simulated selection situations. As a result, 20 items which sufficiently measure faking and are not contaminated by Self-Deception remained in the scale. Forth, principal component analysis was used to examine the construct validity of this scale. Results showed the first factor explained 55% of the total variance. Fifth, multivariate generalization theory was used to study the optimal number of items included in the scale. The results showed that when 10 items remained in the Faking Detection Scale, the scale has good reliability, with G=0.823 and φ=0.818. Sixth, the scale’s validity was further examined using logistic regression. The Cox&Snell R Square and Nagelkerke R Square were .386 and .468, repectively. These results showed that the scale was valid and can effectively detect faking candidates. However, there is a dilemma when setting the cut-off score, because it is impossible to decrease the false judgment and false selection rate at the same time. Results from this study showed that setting up higher cut-off score to detect serious faking candidates and exclude unqualified candidates using select-out mode can help organization make valid recruitment decisions and accomplish personnel selection goals. Finally, this scale’s validity was verified in real occupational selection situations with 234 subjects. Faking Detection Scale (effect size was 1.163) is far more sensitive than personality scale (the largest effect size was .767) and can more effectively measure faking effect. This scale has been validated and can effectively detect faking candidates in real occupational selection situations.
By exploring the quality of items, it is found that most faking detection items described common behaviors in daily life and repeatedly emphasized in work-settings. Subjects showed a high consciously inflation on these items when they were faking; when faking did not happen, they would unconsciously exaggerate the reaction to a less extent because of Self-Deception. So the scale could sufficiently measure faking effect with less contaminative by Self-Deception.
As a conclusion, this study differentiated faking from SDR and developed a scale to detect faking. This scale has 20 items which is very sensitive to faking. Its validity was verified in simulative and one real occupational selection situation. More studies are needed to further explore whether this scale can be applied to varied situations.

Key words: faking, socially desirable responding, social desirability scale, job desirability