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Review Article
A Review on the Use of Effect Size in Nursing Research
Hyuncheol Kang, Kyupil Yeon, Sang-Tae Han
J Korean Acad Nurs 2015;45(5):641-649.   Published online October 30, 2015
DOI: https://doi.org/10.4040/jkan.2015.45.5.641
AbstractAbstract PDF
Purpose

The purpose of this study was to introduce the main concepts of statistical testing and effect size and to provide researchers in nursing science with guidance on how to calculate the effect size for the statistical analysis methods mainly used in nursing.

Methods

For t-test, analysis of variance, correlation analysis, regression analysis which are used frequently in nursing research, the generally accepted definitions of the effect size were explained.

Results

Some formulae for calculating the effect size are described with several examples in nursing research. Furthermore, the authors present the required minimum sample size for each example utilizing G*Power 3 software that is the most widely used program for calculating sample size.

Conclusion

It is noted that statistical significance testing and effect size measurement serve different purposes, and the reliance on only one side may be misleading. Some practical guidelines are recommended for combining statistical significance testing and effect size measure in order to make more balanced decisions in quantitative analyses.

Citations

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Close layer
Original Articles
Impact of Nurse, Nurses' Aid Staffing and Turnover Rate on Inpatient Health Outcomes in Long Term Care Hospitals
Yunmi Kim, Ji Yun Lee, Hyuncheol Kang
J Korean Acad Nurs 2014;44(1):21-30.   Published online February 28, 2014
DOI: https://doi.org/10.4040/jkan.2014.44.1.21
AbstractAbstract PDF
Purpose

This study was conducted to explore the impact of registered nurse/nurses' aid (RN/NA) staffing and turnover rate on inpatient health outcomes in long term care hospitals.

Methods

A secondary analysis was done of national data from the Health Insurance Review and Assessment Services including evaluation of long term care hospitals in October-December 2010 and hospital general characteristics in July-September 2010. Final analysis of data from 610 hospitals included RN/NA staffing, turnover rate of nursing staff and 5 patient health outcome indicators.

Results

Finding showed that, when variables of organization and community level were controlled, patients per RN was a significant indicator of decline in ADL for patients with dementia, and new pressure ulcer development in the high risk group and worsening of pressure ulcers. Patients per NA was a significant indicator for new pressure ulcer development in the low risk group. Turnover rate was not significant for any variable.

Conclusion

To maintain and improve patient health outcomes of ADL and pressure ulcers, policies should be developed to increase the staffing level of RN. Studies are also needed to examine causal relation of NA staffing level, RN staffing level and patient health outcomes with consideration of the details of nursing practice.

Citations

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A Guide on the Use of Factor Analysis in the Assessment of Construct Validity
Hyuncheol Kang
J Korean Acad Nurs 2013;43(5):587-594.   Published online October 31, 2013
DOI: https://doi.org/10.4040/jkan.2013.43.5.587
AbstractAbstract PDF
Purpose

The purpose of this study is to provide researchers with a simplified approach to undertaking exploratory factor analysis for the assessment of construct validity.

Methods

All articles published in 2010, 2011, and 2012 in Journal of Korean Academy of Nursing were reviewed and other relevant books and articles were chosen for the review.

Results

In this paper, the following were discussed: preliminary analysis process of exploratory factor analysis to examine the sample size, distribution of measured variables, correlation coefficient, and results of KMO measure and Bartlett's test of sphericity. In addition, other areas to be considered in using factor analysis are discussed, including determination of the number of factors, the choice of rotation method or extraction method of the factor structure, and the interpretation of the factor loadings and explained variance.

Conclusion

Content validity is the degree to which elements of an assessment instrument are relevant to and representative of the targeted construct for a particular assessment purpose. This measurement is difficult and challenging and takes a lot of time. Factor analysis is considered one of the strongest approaches to establishing construct validity and is the most commonly used method for establishing construct validity measured by an instrument.

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