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.

Background: The ongoing medical crisis in Korea has severely impacted the operational environment of intensive care units (ICU), posing significant challenges to quality care for critically ill patients. This study aimed to evaluate the effects of the ongoing crisis on ICUs. Methods: A survey was conducted in July 2024 among intensivists in charge of ICUs at institutions accredited by the Korean Society of Critical Care Medicine for critical care. The survey compared data from January 2024 (pre-crisis) and June 2024 (post-crisis) on the number ICU beds, staffing composition, work hours, and the number and roles of nurse practitioners. Results: Among the total of 71 participating ICUs, 22 experienced a reduction in the number of operational beds, with a median decrease of six beds per unit, totaling 127 beds across these ICUs. The numbers of residents and interns decreased from an average of 2.3 to 0.1 per ICU, and the average weekly working hours of intensivists increased from 62.3 to 78.8 hours. Nurse practitioners helped fill staffing gaps, with their numbers rising from 150 to 242 across ICUs, and their scope of practice expanded accordingly. Conclusions The medical crisis has led to major changes in the critical care system, including staffing shortages, increased workloads, and an expanded role for nurse practitioners. This is a critical moment to foster interest and engage in active discussions aimed at creating a sustainable and resilient ICU system.

Background: s/Aims: Reported incidence of extrahepatic bile duct cancer is higher in Asians than in Western populations. Korea, in particular, is one of the countries with the highest incidence rates of extrahepatic bile duct cancer in the world. Although research and innovative therapeutic modalities for extrahepatic bile duct cancer are emerging, clinical guidelines are currently unavailable in Korea. The Korean Society of Hepato-Biliary-Pancreatic Surgery in collaboration with related societies (Korean Pancreatic and Biliary Surgery Society, Korean Society of Abdominal Radiology, Korean Society of Medical Oncology, Korean Society of Radiation Oncology, Korean Society of Pathologists, and Korean Society of Nuclear Medicine) decided to establish clinical guideline for extrahepatic bile duct cancer in June 2021. Methods: Contents of the guidelines were developed through subgroup meetings for each key question and a preliminary draft was finalized through a Clinical Guidelines Committee workshop. Results: In November 2021, the finalized draft was presented for public scrutiny during a formal hearing. Conclusions The extrahepatic guideline committee believed that this guideline could be helpful in the treatment of patients.

Background: Hepatic stellate cells (HSCs) are the major cells which play a pivotal role in liver fibrosis. During injury, extracellular stimulators can induce HSCs transdifferentiated into active form. Phloretin showed its ability to protect the liver from injury, so in this research we would like to investigate the effect of phloretin on succinate-induced HSCs activation in vitro and liver fibrosis in vivo study. Methods: In in vitro, succinate was used to induce HSCs activation, and then the effect of phloretin on activated HSCs was examined. In in vivo, succinate was used to generated liver fibrosis in mouse and phloretin co-treated to check its protection on the liver. Results: Phloretin can reduce the increase of fibrogenic markers and inhibits the proliferation, migration, and contraction caused by succinate in in vitro experiments. Moreover, an upregulation of proteins associated with aerobic glycolysis occurred during the activation of HSCs, which was attenuated by phloretin treatment. In in vivo experiments, intraperitoneal injection of phloretin decreased expression of fibrotic and glycolytic markers in the livers of mice with sodium succinate diet-induced liver fibrosis. These results suggest that aerobic glycolysis plays critical role in activation of HSCs and succinate can induce liver fibrosis in mice, whereas phloretin has therapeutic potential for treating hepatic fibrosis. Conclusion Intraperitoneal injection of phloretin attenuated succinate-induced hepatic fibrosis and alleviates the succinate-induced HSCs activation.

Background: Remdesivir is a US Food and Drug Administration-approved drug for coronavirus disease 2019 (COVID-19). Clinical trials were conducted under strictly controlled situations for a selected population, and their reported adverse events may not fully represent conditions in real-world patients. We aimed to estimate the incidence of adverse drug events (ADEs) associated with remdesivir in hospitalized patients with COVID-19, including vulnerable subpopulations, such as those with impaired renal or hepatic function and pregnant women. Methods: This retrospective observational study included hospitalized patients with confirmed COVID-19 treated with remdesivir between January and December 2021 at ten hospitals. ADEs and severe ADEs (Common Toxicity Criteria for Adverse Events grade ≥ 3) were operationally defined and analyzed through laboratory investigations. The incidence of ADEs was compared with that of each matched control in subpopulations with renal or hepatic impairment and pregnant women. Results: Among 2,140 patients, 1,416 (66.2%) and 295 (13.8%) experienced at least one ADE and severe ADE, respectively. The most frequent ADE was 'hepatic injury' (42.9%), followed by anemia (27.6%). The most common severe ADEs were 'hypokalemia' (5.3%), 'hepatic injury' (2.9%), and 'anemia' (3.6%). There was no significant difference in the incidence of ADEs in patients relative to their respective matched-control groups, including those with renal impairment (80.0% vs. control 71.8%, P = 0.063), hepatic impairment (70.4% vs. control 75.0%, P = 0.623) and pregnant women (78.6% vs. control 63.7%, P = 0.067). However, severe ADE incidence was significantly higher in patients with renal impairment (40.8% vs. 16.0%, P < 0.001). The most common severe ADEs in those were 'anemia' (15.3%), 'hypokalemia' (10.5%), and 'thrombocytopenia' (8.9%). There was no statistically significant difference in the incidence of severe ADEs in patients with hepatic impairment or in pregnancy (P = 0.230; P = 0.085). Conclusion A significant proportion of patients with COVID-19 treated with remdesivir experienced ADEs and severe ADEs. Given the high incidence of severe ADEs, caution is required in patients with renal impairment. Further studies are needed to investigate ADEs in pregnant women and patients with hepatic impairment.