中文摘要：

在应聘情境中,被试容易对人格测验作假。应对作假的常用方法是采用社会称许性量表对作假直接测量,再去校正和识别作假效应。但是采用社会称许性量表测量作假存在很多问题,因而基于作假的特殊性质开发了《作假识别量表》。采用探索性因素分析证实了量表的单维性,解释率为54.650%。概化理论检验表明测验信度较好,G系数为0.906,？系数为0.902。采用一个真实的应聘情境检验效度,发现《作假识别量表》对作假更加敏感,能够比较充分地测量作假。

英文摘要：

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