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Individuals differ from one another behaviorally in myriad ways. Differential psychology, the scientific study of these individual differences, provides an organizational structure for this vast array of psychological attributes. By examining broad behavioral patterns and using systematic assessments of relatively stable personal attributes, differential psychology allows longitudinal forecasting of a variety of important life outcomes. Because much of the research in this area focuses particular attention on predicting long-term life outcomes, and because work is such a large and important feature of adult life, the relationships between many commonly investigated individual difference constructs and various aspects of work behavior (e.g., educational-vocational choice, acquisition of job-related knowledge, job performance, job satisfaction and tenure) are well understood.

Measurement Methods

Traditionally, the measurement of individual differences has relied on psychometric scales based on the aggregation of many items. Because any single item on a scale represents only a sliver of information about a personal attribute, aggregation is used to create a composite of several lightly correlated items. This approach distills the communality running through the items and constitutes highly reliable and useful information about the human characteristic under analysis.

Although individuals are commonly described in the more popular press in terms of types, implying that people are members of distinct categories (e.g., extraverts or introverts), individual difference variables are rarely observed as discrete classes. Rather, the majority of individuals are found near the center of a continuous distribution, with few observations at either extreme. The distributional pattern of most individual difference variables is well represented by the normal (bell-shaped) curve.

Major Domains

The major dimensions of individual differences can be classified into three overlapping clusters: cognitive abilities, preferences (interests and values), and personality. Each will be reviewed in turn, but cognitive abilities will be focused on here because of their importance for industrial/organizational psychologists.

Cognitive Abilities

General Intelligence. The predominant scientific conceptualization of cognitive abilities involves a hierarchical organization. Various models of additional specific abilities have been proposed, but the hierarchical nature of human abilities is salient in each. For example, John Carroll factor analyzed more than 460 data sets collected throughout the 20th century and found a general factor (g) at the apex that explained approximately half of the common variance among a heterogeneous collection of tests, revealing a communality running through many different types of more specialized abilities and the tests designed to measure them.

This general intelligence factor exhibits an extensive range of external correlates, implicating it as arguably the most scientifically significant dimension of human psychological diversity uncovered by differential psychology to date. It has repeatedly demonstrated its utility in the prediction of educationally and vocationally relevant outcomes, including the acquisition of job-related knowledge and job performance. For example, in a meta-analysis of 85 years of research on personnel selection methods, Frank Schmidt and John Hunter reported that g is the best single predictor of performance in job-training programs, exhibiting an average validity coefficient of .56. Schmidt and Hunter further reported that the validity of g in predicting job performance is second only to that of work sample measures. However, because the use of work samples is limited to use with incumbents and is much costlier to implement, g is usually considered more efficient.

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