School of Data Science and Analytics, Kennesaw State University, Kennesaw, GA 30144, USA.
Healthcare Management and Informatics, Kennesaw State University, Kennesaw, GA 30144, USA.
Int J Environ Res Public Health. 2023 Feb 25;20(5):4115. doi: 10.3390/ijerph20054115.
Impostor Phenomenon (IP), also called impostor syndrome, involves feelings of perceived fraudulence, self-doubt, and personal incompetence that persist despite one's education, experience, and accomplishments. This study is the first to evaluate the presence of IP among data science students and to evaluate several variables linked to IP simultaneously in a single study evaluating data science. In addition, it is the first study to evaluate the extent to which gender identification is linked to IP. We examined: (1) the degree to which IP exists in our sample; (2) how gender identification is linked to IP; (3) whether there are differences in goal orientation, domain identification, perfectionism, self-efficacy, anxiety, personal relevance, expectancy, and value for different levels of IP; and (4) the extent to which goal orientation, domain identification, perfectionism, self-efficacy, anxiety, personal relevance, expectancy, and value predict IP. We found that most students in the sample showed moderate and frequent levels of IP. Moreover, gender identification was positively related to IP for both males and females. Finally, results indicated significant differences in perfectionism, value, self-efficacy, anxiety, and avoidance goals by IP level and that perfectionism, self-efficacy, and anxiety were particularly noteworthy in predicting IP. Implications of our findings for improving IP among data science students are discussed.
冒名顶替现象（IP），也称为冒名顶替综合征，涉及到一种持续存在的感觉，即感觉自己是骗子、自我怀疑和个人无能，尽管一个人已经接受了教育、拥有了经验和成就。这项研究是首次评估数据科学学生中存在的 IP，并在一项评估数据科学的单一研究中同时评估与 IP 相关的几个变量。此外，这也是首次评估性别认同与 IP 之间的关联程度的研究。我们检查了：（1）我们的样本中存在 IP 的程度；（2）性别认同与 IP 的关系；（3）在不同水平的 IP 下，目标导向、领域认同、完美主义、自我效能、焦虑、个人相关性、期望和价值观是否存在差异；（4）目标导向、领域认同、完美主义、自我效能、焦虑、个人相关性、期望和价值观对 IP 的预测程度。我们发现，样本中的大多数学生表现出中度和频繁的 IP 水平。此外，性别认同与男性和女性的 IP 呈正相关。最后，结果表明，在完美主义、价值观、自我效能、焦虑和回避目标方面，IP 水平存在显著差异，而且完美主义、自我效能和焦虑在预测 IP 方面特别值得关注。我们的研究结果对改善数据科学学生的 IP 提出了一些启示。
