The Impostor Phenomenon: A Descriptive Study of Its Incidence Among Registered Nurse Preceptors.

Abstract

Intelligent high-achievers, who believe they are less intelligent and less competent than others perceive them, may suffer from the impostor phenomenon. The impostor phenomenon describes an internal experience of intellectual phoniness. Impostors hide deep feelings of inadequacy, fearful others will discover their secret. The study used a descriptive correlational design to determine the incidence of the impostor phenomenon among registered nurse preceptors. Nursing preceptors are usually high-achieving professionals tasked with the responsibilities of their patient care assignments as well as teaching, counseling, inspiring, role modeling, and supporting the growth and development of new nurses within the clinical setting. Pender's 1996 Health Promotion Model served as the conceptual framework. One hundred twenty-nine RN preceptors practicing throughout Texas (N = 129) completed a two-part questionnaire, consisting of the Clance Impostor Phenomenon Scale and items associated with preceptors' self-reported feelings and experiences. Using parametric and non-parametric statistics and descriptive methods, data analysis revealed that about 10% (n = 13) of the participants experienced moderate to intense levels of the impostor phenomenon. A significant negative correlation was found between impostorism and self-perceived qualification for the preceptor role. This study further compared the use of a specific cutoff score to determine impostorism in lieu of dividing the sample at the median into high-level and low-level impostor groups. Findings are useful in understanding nurse preceptors' stressors and need for support.

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Document Details

Document Type
Technical Report
Publication Date
May 25, 1999
Accession Number
ADA364098

Entities

People

  • Michele M. Evan

Organizations

  • Texas Tech University

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  • Administrative Personnel
  • Data Analysis
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Fields of Study

  • Education

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  • Educational Psychology
  • Medical or Health Care Field.
  • Regression Analysis.