Accession Number:

ADA456361

Title:

Hazards of U.S. Navy Enlisted Occupations: A General Model

Descriptive Note:

Technical rept.

Corporate Author:

NAVAL HEALTH RESEARCH CENTER SAN DIEGO CA

Report Date:

2006-05-02

Pagination or Media Count:

30.0

Abstract:

The hospitalization rate for injuries varies widely across U.S. Navy enlisted occupations. Logic suggests that this variation is related to occupational demands. Previous research shows that higher accident rates occur in occupations that demand physical exertion and fast reaction times. However, the estimated effects of those demands may have been biased by the omission of other important contributors to accidents. The goal of this study was to construct a complete profile of occupational characteristics that predict accident rates. The profile must be complete to ensure unbiased estimates when modeling the influence of occupational characteristics on accident rates. The prior focus on ability demands was expanded to include generic tasks, working conditions, and activities. Accident rates for 57 entry-level occupations for the periods 1970-1974 and 1980-1994 were used. Ratings by senior enlisted personnel described tasks, working conditions, activities, and ability demands of each occupation. Correlation and regression analyses were used to identify occupational characteristics associated with higher accident rates. Results showed that six indices were reliable positive correlates of accident rates Physical Ability, Perceptual Speed and Skill, Work with Machinery, Poor Working Conditions, Manual Labor, and Miscellaneous. These six composites defined a single higher-order factor that predicted accident rates. But neither the composites nor any individual item in the original ratings was a consistent predictor of accident rates controlling for this general factor. The impact of omitted variable bias was evident in a sharp reduction in the estimated effect of physical ability demands on accident rates when the other hazard elements were included in the predictive model. The essential questions are whether the omitted variables correlate with accident rates and, if so, how much bias this introduces into the estimated effects of demands on accidental injury rates.

Subject Categories:

  • Personnel Management and Labor Relations
  • Medicine and Medical Research
  • Safety Engineering
  • Military Forces and Organizations

Distribution Statement:

APPROVED FOR PUBLIC RELEASE