Improving I-O Science Through Synthetic Validity

The purpose of this comment is to advocate for the development of a synthetic validity database along the lines described by Johnson et al. (2010), not only because of its practical utility but also because of its potential contribution to the science of industrial and organizational (I-O) psychology generally. Specifically, one of the core scientific pursuits of psychology is the understanding of individual differences (IDs). Knowledge of the context in which specific IDs matter (i.e., in terms of level of behaviors exhibited) can provide information about the nature of those IDs. For example, if the degree to which a job requires continuous learning of symbolic material is related to the predictive validity of general cognitive ability (g; i.e., learning context moderates the g–performance relationship), it is likely that g has something to do with the acquisition of new knowledge. Alternatively, or additionally, if the degree to which a job requires making decisions among large numbers of multi-attribute options is related to the validity of g as a predictor of job performance, it implies that g involves information processing capacity (and perhaps it is via this mechanism that g is related to learning). That is, evidence of the moderator effects of context (i.e., conditions on which jobs or tasks vary) on ID–performance relationships provides information about the nature of the ID construct, as well as whether the ID construct is likely to be predictive of performance in any particular context. This is another reason to develop a database that indicates what context variables predict the validities of ID constructs.