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The purpose of this study is to describe the development and psychometric properties of a novel game- and video-based assessment of social attributes. Despite their increasing adaption, little research is available on the suitability of games and video analytics for measuring noncognitive attributes in the selection context.

The authors describe three novel assessments and their psychometric properties in a sample of 1,300 participants: a game-based adaptation of an Emotion Recognition Task, a chatbot-based situational judgment test for emotion management and a video-based conscientiousness assessment.

The novel assessments show good to moderate convergent validity for Emotional Recognition (r = 0.42), Emotion Management (r = 0.39) and Conscientiousness (r = 0.21). The video-based assessment demonstrates preliminary predictive validity for self-reported work performance. Novel game-based assessments (GBAs) are perceived as better designed and more immersive than traditional questionnaires. Adverse impact analysis indicates small group differences by age, gender and ethnicity.

Predictive validity findings need to be replicated using objective measures of performance, such as performance ratings by supervisors and extended to the GBAs. Adverse impact should be evaluated using a real-life applicant pool and extended to additional groups.

Evidence for the psychometric validity of novel assessment formats supports their adoption in selection and recruitment. Improved user experience and shortened assessment times open up new areas of application.

This study gives first insights into psychometric properties of video- and game-based assessments of social attributes.