Analysis of a brief biodata scale as a predictor of job performance and its incremental validity over the Big Five and Dark Tetrad personality traits

The collection of biographical information (biodata) through CVs and application forms has many advantages, namely easiness of collection, acceptable validity, less prone to faking, and the fulfilment of legal requirements. However, its systematic use among practitioners is scarce. Two of the mains reasons is the overlap with other constructs like personality and the lack of validated biodata scales in articles and public repositories. Aimed to fill this gap, García-Izquierdo and colleagues developed an 8-item scale able to generate positive applicant reactions, but they did not provide empirical evidence that their scale is able to predict job performance. The present paper was developed for this purpose, investigating the scale’s relationship with four different dimensions of job performance (i.e., task performance, contextual performance, counterproductive behaviors, and adaptive performance) and its incremental validity with respect to Big Five and Dark Tetrad personality traits. The study comprises 528 employees from different organizations (M(age) = 39.51, SD = 14.25; 52.8% women, M(experience) = 17.06, SD = 13.27) which voluntarily agreed to participate filling a questionnaire with the variables of interest. Results provide evidence of the predictive validity of the biodata scale in a multi-occupational sample; identify that these biodata contribute to predicting two specific types of job performance: contextual performance and adaptive performance; shows that a brief job-related biodata scale achieves results comparable to those of most personality traits in predictive models of job performance dimensions; and provide evidence of the incremental predictive validity of biodata over the Big Five and the Dark Tetrad. As a whole, these results provide support for the use of the scale in researcher and applied settings, and contributes to the advance the knowledge of biodata for personnel selection.