INCORPORATING GENERAL INTELLIGENCE INTO EPIDEMIOLOGY AND THE SOCIAL-SCIENCES

The purpose of this article is to demonstrate the value of examining a variety of pressing behavioral, medical, and social phenomena as they relate to gradations in general intelligence. Although few (if any) v ariables in the social sciences can compete with the construct of gene ral intelligence in its ability to forecast an array of socially value d attributes and outcomes, measures of general intelligence are seldom incorporated into correlational and experimental designs aimed at und erstanding maladaptive behavior (e.g., crime, dropping out of high sch ool, unwise financial planning, health-risk behaviors, poor parenting, and vocational discord) or its opposite, highly adaptive behavior. We contend that, if consulted more often, the construct of general intel ligence would contribute to understanding many puzzling human phenomen a, because successive gradations of intelligence reflect successive de grees of risk. A method is provided for uncovering group trends, one e xpressly designed to reveal the range and prevalence of the many diffe rent kinds of human phenomena that vary as a function of intellectual gradations. By employing this method, policymakers and the public can more readily apprehend the significant, but often unsuspected, contrib ution made by general intelligence to many socially important outcomes . Our approach is similar to traditional epidemiological research aime d at ascertaining antecedents to maladies through the defining feature s of high-risk groups (e.g., for lung cancer, smokers and passive smok ers; for AIDS victims, participants in unsafe sex; for academic medioc rity, among the intellectually gifted in nonaccelerative educational t racks; for mental retardation, high blood-lead levels). Once Such high -risk groups are defined (i.e., groups of persons whose behavioral dis positions predispose them, and often others around them, to unfortunat e outcomes), policymakers and scientists are in a better position to d isentangle genuine causes from families of correlations and can concen trate ameliorative resources more effectively. Data from educational a nd medical contexts are analyzed to show how measures of general intel ligence, and other dimensions from differential psychology, can comple ment epidemiological and social science inquiry. We also argue that by incorporating such measures of human variation into policy developmen t and research, policymakers are more likely to forestall ''iatrogenic effects'' (maladies caused by treatment).