Survey of Total Army Military Personnel: Analyses of Active Duty and Reserve/Guard Army Nurse Corps Data.

Abstract

Data collected from Army Registered Nurses (RNs) as part of the Survey of Total Army Military Personnel (STAMP) are examined in this report. The principal goal of the analyses was to isolate those factors related to retention decisions. That is, what are the correlates with the decision to remain in or leave the Army Nurse Corps (ANC). Because of the large volume of data collected as part of STAMP, a series of factor analyses were performed. For Active Duty personnel; 33 composites were formed; 26 were found for the Reserves. These were then entered into a series of multiple regressions along with individual variables that did not load on any of the factors. For both components, anxiety regarding the downsizing, job satisfaction and commitment, years, of service, and whether one anticipated serving during combat were significant predictors of retention plans. Family-related concerns entered into prediction equation for Active Duty personnel; concerns over future mobilizations were important for Reserve ANC officers. The conclusions suggest that Operations Desert Shield/Storm had little direct impact on the future plans of these nurses; however, they did appear to highlight the possibility of other deployments that, in turn, had an impact on retention decisions.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1995
Accession Number
ADA295899

Entities

People

  • Ani S. Difazio
  • Peter R. Ramsberger

Organizations

  • Human Resources Research Organization

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Active Duty
  • Administrative Personnel
  • Army Personnel
  • Employment
  • Enlisted Personnel
  • Factor Analysis
  • Information Science
  • Job Satisfaction
  • Management Personnel
  • Medical Personnel
  • Military Personnel
  • Personnel Management
  • Recruiting
  • Regression Analysis
  • Social Sciences
  • Surveys
  • United States

Fields of Study

  • Psychology

Readers

  • Computational Modeling and Simulation
  • Medical or Health Care Field.
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