Research Article

The importance of supervision in retention of CNAs†‡

  1. JiSun Choi1,§,*,
  2. Meg Johantgen2,¶

Article first published online: 19 JAN 2012

DOI: 10.1002/nur.21461

Additional Information

How to Cite

Choi, J. and Johantgen, M. (2012), The importance of supervision in retention of CNAs. Research in Nursing & Health. doi: 10.1002/nur.21461

Author Information

  1. 1

    National Database of Nursing Quality Indicators, University of Kansas Medical Center, School of Nursing, 3901 Rainbow Blvd, MS 3060, Kansas City, Kansas 66160

  2. 2

    Department of Organizational Systems and Adult Health, University of Maryland School of Nursing, Baltimore, Maryland 21201

  1. §

    Post-doctoral fellow.

  2. Associate Professor.

*National Database of Nursing Quality Indicators, University of Kansas Medical Center, School of Nursing, 3901 Rainbow Blvd, MS 3060, Kansas City, Kansas 66160.

  1. †

    Conflict of interest: The authors declare no conflicts of interest.

  2. ‡

    Disclaimer: The findings and conclusions in this paper are those of the authors and do not necessarily represent the views of the Research Data Center, the National Center for Health Statistics, or the Center for Disease Control and Prevention.

Publication History

  1. Article first published online: 19 JAN 2012
  2. Manuscript Accepted: 29 DEC 2011

Funded by

  • Global Korean Nursing Foundation—US

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Keywords:

  • certified nursing assistants (CNAs);
  • nursing homes;
  • job satisfaction;
  • intent to leave;
  • multilevel modeling

Abstract

Certified nursing assistants (CNAs) provide the majority of direct care in nursing homes, yet recruiting and retaining CNAs has been difficult. Retaining CNAs is important because it has been linked to the better quality of resident care in nursing homes. In this study, the investigators examined the relationships of work-related and personal factors to CNA job satisfaction and intent to leave. Linked data from the 2004 National Nursing Home Survey and the 2004 National Nursing Assistant Survey were analyzed using multilevel logistic regression. Personal factors such as age, education, and job history, were related to intent to leave but not to job satisfaction. Supportive supervision was a significant predictor of both job satisfaction and intent to leave. © 2012 Wiley Periodicals, Inc. Res Nurs Health

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