Model Setting and Interpretation of Results in Research Using Structural Equation Modeling: A Checklist with Guiding Questions for Reporting

Purpose@#This study develops a checklist with guidelines for the methods and important factors to consider in research using structural equation modeling (SEM).MethodThe paper discusses the factors to consider in the process across the three stages of 1) model setting, 2) model evaluation and modification, and 3) interpretation and reporting of SEM-based studies. @*Results@#The authors present a checklist for researchers during the stages of model setting, model evaluation and modification, result analysis, and reporting, along with examples of figures and tables with explanations. @*Conclusion@#A checklist will help to improve the reporting quality of SEM-based studies.

Model Setting and Interpretation of Results in Research Using Structural Equation Modeling: A Checklist with Guiding Questions for Reporting

Purpose@#This study develops a checklist with guidelines for the methods and important factors to consider in research using structural equation modeling (SEM).MethodThe paper discusses the factors to consider in the process across the three stages of 1) model setting, 2) model evaluation and modification, and 3) interpretation and reporting of SEM-based studies. @*Results@#The authors present a checklist for researchers during the stages of model setting, model evaluation and modification, result analysis, and reporting, along with examples of figures and tables with explanations. @*Conclusion@#A checklist will help to improve the reporting quality of SEM-based studies.

Developing a Prediction Model for Family Health in Families of Patients with Schizophrenia / 정신간호학회지

PURPOSE: The purpose of this study was to identify factors related to family health and develop a prediction model with an ability to explain family health in families of patients with schizophrenia.METHODS: A hypothesized model with twelve pathway forms was developed based on literature review. Family stress and social stigma were included as two exogenous variables; whereas family resilience, family empowerment, self-esteem, community integration, and family health were included as endogenous variables. Data were collected using a self-report questionnaire from 206 families of patients with schizophrenia living in Republic of Korea. Data were analyzed with PASW/WIN 18.0 and AMOS 18.0 programs.RESULTS: Social stigma had a negatively indirect and total effect on family health. Family resilience, self-esteem, and community integration had positive and direct and overall effects on family health.CONCLUSION: A prediction model for families of patients with schizophrenia is proposed and social stigma, family resilience, self-esteem, and community integration are presented as predicting factors for family health. Nursing interventions and support programs should be developed to overcome social stigma and improve family resilience, self-esteem, and community integration.

A Review on the Use of Effect Size in Nursing Research

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.

Impact of Nurse, Nurses' Aid Staffing and Turnover Rate on Inpatient Health Outcomes in Long Term Care Hospitals

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.

A Guide on the Use of Factor Analysis in the Assessment of Construct Validity

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.

Factors Influencing Sleep Quality in Clinical Nurses / 정신간호학회지

PURPOSE: The purpose of this study was to identify sleep quality, job stress, symptoms of stress (SOS), and coping and to examine factors influencing sleep quality in clinical nurses. METHODS: A cross-sectional study was conducted with 265 clinical nurses at three general hospitals. A self-administrated questionnaire was used for data collection, and data were analyzed using descriptive statistics, Pearson correlation coefficients, t-test, ANOVA, and backward multiple regression with the SAS statistical program. RESULTS: Sleep quality showed significant differences according to the sociodemographic characteristics of age, length of work, education, current workplace, current job position, shift work, and marital status. Sleep quality was negatively associated with SOS and job stress. Significant factors influencing sleep quality of the clinical nurses were cognitive-behavioral SOS, physiological SOS, inappropriate rewards, physical work environment, and shift work. CONCLUSION: The findings indicate that cognitive-behavioral SOS, physiological SOS, job stress regarding inappropriate rewards and physical work environment, and shift work are useful to predict levels of sleep quality of clinical nurses. These factors should be considered when developing nursing interventions to improve sleep quality of clinical nurses through stress management.