Accession Number:

ADA633592

Title:

The Retention of Recalled Navy Nurse Reservists following Operation Iraqi Freedom

Descriptive Note:

Final rept. 4 Jun 2006-30 Jun 2008

Corporate Author:

GEORGETOWN UNIV WASHINGTON DC

Personal Author(s):

Report Date:

2008-06-30

Pagination or Media Count:

78.0

Abstract:

Purpose The purpose of this study was to identify factors that contribute to the retention of mobilized NNC reservists, because a negative experience with a recall to active duty could make a nurse reservist resign hisher commission. The specific aims of this study were to compare the factors that predict intent to stay of NNC reservists to determine the scope of the problem of nurses-- intent to stay in the Reserves after return from deployment test a causal model of voluntary turnover with a sample of NNC reservists who have returned from deployment and offer an opportunity for mobilized reservists to describe any additional factors influencing ones intent to stay in the Navy Reserves. Design This project utilized a non-experimental, retrospective, cross-sectional study design. Methods The mailing procedure of the questionnaire via a survey firm consisted of the five-step compatible contacts process that Dillman 2000 advocates for maximizing response rates. Sample Subjects who met the inclusion criteria --NNC reservists who were involuntarily recalled to active duty in support of OIFOEF -- were recruited. Exclusion criteria were nurses not recalled, or those who volunteered to be recalled, for OIFOEF. Of the 437 recalled NNC reservists, only 383 were eligible to participate in this study. 264 subjects were ultimately enrolled, yielding a response rate of 69 264 383 0.6893. Instrumentation Price and Muellers Causal Model of Voluntary Turnover 1981, 1986 was used for this study since it addressed factors that may influence job satisfaction, organizational commitment, and intent to stay and has been adapted for use in the military setting. Analysis Data were collected by questionnaires and analyzed via descriptive statistics, exploratory factor analysis, multiple regression analysis, structural equation modeling SEM, and content analysis.

Subject Categories:

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

Distribution Statement:

APPROVED FOR PUBLIC RELEASE