Identifying critical defining characteristics of nursing diagnoses using magnitude estimation scaling

Authors

  • Dr. Marguerite Kinney,

    Corresponding author
    1. Marguerite Kinney, DNSc, RN, FAAN, is a professor and the coordinator of cardiovascular nursing in the School of Nursing, University of Alabama at Birmingham. Cathie E. Guzzetta, PhD, RN, CCRN, FAAN, was an associate professor and the chair of cardiovascular nursing in the School of Nursing, The Catholic University of America, Washington, DC when the study was conducted.
    • School of Nursing, University of Alabama at Birmingham, University Station, Birmingham, AL 35294
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  • Cathie E. Guzzetta

    1. Marguerite Kinney, DNSc, RN, FAAN, is a professor and the coordinator of cardiovascular nursing in the School of Nursing, University of Alabama at Birmingham. Cathie E. Guzzetta, PhD, RN, CCRN, FAAN, was an associate professor and the chair of cardiovascular nursing in the School of Nursing, The Catholic University of America, Washington, DC when the study was conducted.
    Search for more papers by this author

Abstract

The question addressed in this study was: Can the critical defining characteristics (CDCs) of nursing diagnoses be determined by magnitude estimation scaling (MES)? MES was used by having 32 nurse subjects numerically estimate the magnitude of each characteristic of anxiety and of sleep pattern disturbance on each of three concept dimensions: importance, frequency, and competency. Geometric means of the stimuli for each of the concept dimensions were computed and correlated with each other. Strong correlations between the characteristics and the concept dimensions were obtained. It was concluded that MES is a useful technique for identifying the CDCs and operational definitions of nursing diagnoses.

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