Intelligence and Accidents: A Multilevel Model

Abstract

Intelligence reduces the risk of accidents. Prior tests of this reasonable hypothesis have produced associations that are too weak to be of much theoretical or practical importance. However, intelligence is most valuable when complex patterns of information must be processed. In an occupational setting, intelligence may have a strong effect on accident rates only when work involves a complex set of hazards. The study hypothesis was that the association of intelligence with accidents would be strongest in occupations with complex workplace hazards. Accidental injury was investigated over the first-term enlistment of a cohort of 183,575 U.S. Navy recruits who entered the service between January 1, 1990, and December 31, 1998. The accident criterion was hospitalization for an injury with a Standard NATO Agreement code indicating that the injury was an accident. Intelligence was measured by Armed Forces Qualification Test scores with conversion from percentile rankings to equivalent normal scores. Occupational hazards were measured by job characteristic ratings provide by senior enlisted personnel familiar with the requirements of 54 entry-level occupations. The average AFQT for the occupation and the proportion of women were also included as occupational characteristics. Hierarchical generalized linear models were developed to represent the joint effects of individuallevel variables (i.e., gender, intelligence) and occupational characteristics (e.g., physical demands). Results The association of intelligence with accidents varied across occupations in the initial analyses. Follow-on analyses led to the development of a quadratic equation to describe the association of intelligence with accidents. The coefficients for intelligence in this revised equation were invariant across occupations. The intercept for the revised model varied across occupations, so the overall level of risk differed between occupations.

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Document Details

Document Type
Technical Report
Publication Date
May 06, 2006
Accession Number
ADA456227

Entities

People

  • A. Villasenor
  • R. R. Vickers

Organizations

  • Naval Health Research Center

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Accidents
  • Applied Psychology
  • Basic Training
  • Behavioral Sciences
  • Computer Programs
  • Data Science
  • Databases
  • Enlisted Personnel
  • Equations
  • Hazards
  • Health Services
  • Hospitalizations
  • Information Processing
  • Information Science
  • Naval Personnel
  • Patient Care
  • Risk

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