This article is being retracted as a part of the manuscript was a 'duplicate publication' from an earlier publication.

PURPOSE: The purpose of this study was to identify the features, risk scores and risk factors for deep vein thrombosis in critically ill patients who developed deep vein thrombosis in their lower extremities. METHODS: The participants in this prospective descriptive study were 175 adult patients who did not receive any prophylactic medication or mechanical therapy during their admission in the intensive care unit. RESULTS: The mean age was 62.24 (+/-17.28) years. Men made up 54.9% of the participating patients. There were significant differences in age, body mass index, and leg swelling between patients who developed deep vein thrombosis and those who did not have deep vein thrombosis. The mean risk score was 6.71(+/-2.94) and they had on average 4.01(+/-1.35) risk factors. In the multiple logistic regression, body mass index (odds ratio=1.14) and leg swelling (odds ratio=6.05) were significant predictors of deep vein thrombosis. CONCLUSION: Most critically ill patients are in the potentially high risk group for deep vein thrombosis. However, patients who are elderly, obese or have leg edema should be closely assessed and more than one type of active prophylactic intervention should be provided.
Adolescent ; Adult ; Age Factors ; Aged ; Aged, 80 and over ; Body Mass Index ; *Critical Illness ; Female ; Humans ; Leg/*blood supply ; Logistic Models ; Male ; Middle Aged ; Odds Ratio ; Predictive Value of Tests ; Prospective Studies ; Risk Factors ; Venous Thrombosis/diagnosis/*etiology ; Young Adult

PURPOSE: Regarding the respiratory function of patients with an artificial airway, this study compared the effects between normal saline with chest vibration and normal saline with expectorant mixture, administered before endotracheal suction. METHODS: The study was conducted in the ICUs of one university hospital located in Incheon. The experimental group I received normal saline with chest vibration administered before endotracheal suction while the experimental group II received normal saline with expectorant mixture administered before endotracheal suction. For respiratory function, PaO2, PaCO2, and O2 saturation were measured by ABGA at 3 minutes after endotracheal suction for both pre-test and post-test. RESULTS: The two groups were not different significantly regarding PaO2 level and O2 saturation after the treatments, while, the experimental group II had lower PaCO2 level than the experimental group I after the treatments (t = 2.075, p = .042). For experimental group II, post-test score of PaCO2 level was significantly lower than that of the pre-test score (t = 1.842, p = .075). CONCLUSION: The administration of normal saline with expectorant mixture before endotracheal suction reduced PaCO2 level and improved the respiratory function.
Humans ; Suction ; Thorax ; Vibration

PURPOSE: Regarding the respiratory function of patients with an artificial airway, this study compared the effects between normal saline with chest vibration and normal saline with expectorant mixture, administered before endotracheal suction. METHODS: The study was conducted in the ICUs of one university hospital located in Incheon. The experimental group I received normal saline with chest vibration administered before endotracheal suction while the experimental group II received normal saline with expectorant mixture administered before endotracheal suction. For respiratory function, PaO2, PaCO2, and O2 saturation were measured by ABGA at 3 minutes after endotracheal suction for both pre-test and post-test. RESULTS: The two groups were not different significantly regarding PaO2 level and O2 saturation after the treatments, while, the experimental group II had lower PaCO2 level than the experimental group I after the treatments (t = 2.075, p = .042). For experimental group II, post-test score of PaCO2 level was significantly lower than that of the pre-test score (t = 1.842, p = .075). CONCLUSION: The administration of normal saline with expectorant mixture before endotracheal suction reduced PaCO2 level and improved the respiratory function.
Humans ; Suction ; Thorax ; Vibration

No abstract available.
Cerebral Hemorrhage ; Parkinson Disease

No abstract available.
Hernia, Abdominal ; Herpes Zoster

Purpose: This study aimed to empirically verify the impact of measurement model selection on research outcomes and their interpretation through an analysis of children’s emotional and social problems measured by the Pediatric Symptom Checklist (PSC) using both reflective and formative measurement models. These models were represented by covariance-based structural equation modeling (CB-SEM) and partial least squares SEM (PLS-SEM), respectively. Methods: This secondary data analysis evaluated children’s emotional and social problems as both reflective and formative constructs. Reflective models were analyzed using CB-SEM, while formative models were assessed using PLS-SEM. Comparisons between these two approaches were based on model fit and parameter estimates. Results: In the CB-SEM analysis, which assumed a reflective measurement model, a model was not identified due to inadequate fit indices and a Heywood case, indicating improper model specification. In contrast, the PLS-SEM analysis, assuming a formative measurement model, demonstrated adequate reliability and validity with significant path coefficients, supporting the appropriateness of the formative model for the PSC. Conclusion The findings indicate that the PSC is more appropriately analyzed as a formative measurement model using PLS-SEM, rather than as a reflective model using CB-SEM. This study highlights the necessity of selecting an appropriate measurement model based on the theoretical and empirical characteristics of constructs in nursing research. Future research should ensure that the nature of measurement variables is accurately reflected in the choice of statistical models to improve the validity of research outcomes.

Purpose: This study aimed to empirically verify the impact of measurement model selection on research outcomes and their interpretation through an analysis of children’s emotional and social problems measured by the Pediatric Symptom Checklist (PSC) using both reflective and formative measurement models. These models were represented by covariance-based structural equation modeling (CB-SEM) and partial least squares SEM (PLS-SEM), respectively. Methods: This secondary data analysis evaluated children’s emotional and social problems as both reflective and formative constructs. Reflective models were analyzed using CB-SEM, while formative models were assessed using PLS-SEM. Comparisons between these two approaches were based on model fit and parameter estimates. Results: In the CB-SEM analysis, which assumed a reflective measurement model, a model was not identified due to inadequate fit indices and a Heywood case, indicating improper model specification. In contrast, the PLS-SEM analysis, assuming a formative measurement model, demonstrated adequate reliability and validity with significant path coefficients, supporting the appropriateness of the formative model for the PSC. Conclusion The findings indicate that the PSC is more appropriately analyzed as a formative measurement model using PLS-SEM, rather than as a reflective model using CB-SEM. This study highlights the necessity of selecting an appropriate measurement model based on the theoretical and empirical characteristics of constructs in nursing research. Future research should ensure that the nature of measurement variables is accurately reflected in the choice of statistical models to improve the validity of research outcomes.

Purpose: This study aimed to empirically verify the impact of measurement model selection on research outcomes and their interpretation through an analysis of children’s emotional and social problems measured by the Pediatric Symptom Checklist (PSC) using both reflective and formative measurement models. These models were represented by covariance-based structural equation modeling (CB-SEM) and partial least squares SEM (PLS-SEM), respectively. Methods: This secondary data analysis evaluated children’s emotional and social problems as both reflective and formative constructs. Reflective models were analyzed using CB-SEM, while formative models were assessed using PLS-SEM. Comparisons between these two approaches were based on model fit and parameter estimates. Results: In the CB-SEM analysis, which assumed a reflective measurement model, a model was not identified due to inadequate fit indices and a Heywood case, indicating improper model specification. In contrast, the PLS-SEM analysis, assuming a formative measurement model, demonstrated adequate reliability and validity with significant path coefficients, supporting the appropriateness of the formative model for the PSC. Conclusion The findings indicate that the PSC is more appropriately analyzed as a formative measurement model using PLS-SEM, rather than as a reflective model using CB-SEM. This study highlights the necessity of selecting an appropriate measurement model based on the theoretical and empirical characteristics of constructs in nursing research. Future research should ensure that the nature of measurement variables is accurately reflected in the choice of statistical models to improve the validity of research outcomes.

Purpose: This study aimed to empirically verify the impact of measurement model selection on research outcomes and their interpretation through an analysis of children’s emotional and social problems measured by the Pediatric Symptom Checklist (PSC) using both reflective and formative measurement models. These models were represented by covariance-based structural equation modeling (CB-SEM) and partial least squares SEM (PLS-SEM), respectively. Methods: This secondary data analysis evaluated children’s emotional and social problems as both reflective and formative constructs. Reflective models were analyzed using CB-SEM, while formative models were assessed using PLS-SEM. Comparisons between these two approaches were based on model fit and parameter estimates. Results: In the CB-SEM analysis, which assumed a reflective measurement model, a model was not identified due to inadequate fit indices and a Heywood case, indicating improper model specification. In contrast, the PLS-SEM analysis, assuming a formative measurement model, demonstrated adequate reliability and validity with significant path coefficients, supporting the appropriateness of the formative model for the PSC. Conclusion The findings indicate that the PSC is more appropriately analyzed as a formative measurement model using PLS-SEM, rather than as a reflective model using CB-SEM. This study highlights the necessity of selecting an appropriate measurement model based on the theoretical and empirical characteristics of constructs in nursing research. Future research should ensure that the nature of measurement variables is accurately reflected in the choice of statistical models to improve the validity of research outcomes.