Background: Sleep disorders and insomnia are prevalent worldwide, with negative health outcomes. The Pittsburgh Sleep Quality Index (PSQI) is a widely used self-report assessment tool for evaluating sleep quality, comprising seven subdomains. The Korean version of the PSQI (PSQI-K) has been tested for reliability and validity in small sample sizes but lacks large-scale validation using objective measures. Methods: This study was conducted with 268 Korean adults attending health check programs. Participants completed the PSQI-K questionnaire and wore Fitbit devices (Fitbit Inc., USA) to ascertain sleep parameters. Reliability was analyzed using the Cronbach’s α coefficient, and construct validity was determined through factor analysis. Criteria validity was assessed by correlating their index scores with Fitbit sleep parameters. We identified the optimal cutoff for detecting sleep disorders. Results: The Cronbach’s α coefficient was 0.61, indicating adequate internal consistency. Factor analysis revealed three factors, explaining 48.2% of sleep quality variance. The index scores were negatively correlated with Fitbit sleep efficiency, total sleep time, and number of awakenings (P<0.05). The optimal cutoff point for identifying sleep disorder groups was ≥6. Conclusion The PSQI-K demonstrated good reliability and validity when correlated with Fitbit sleep parameters, offering a practical screening tool for identifying sleep disorders among Korean adults. Cutoff scores can help identify patients for sleep interventions. However, further large-scale studies are required to validate these findings.

Background: Sleep disorders and insomnia are prevalent worldwide, with negative health outcomes. The Pittsburgh Sleep Quality Index (PSQI) is a widely used self-report assessment tool for evaluating sleep quality, comprising seven subdomains. The Korean version of the PSQI (PSQI-K) has been tested for reliability and validity in small sample sizes but lacks large-scale validation using objective measures. Methods: This study was conducted with 268 Korean adults attending health check programs. Participants completed the PSQI-K questionnaire and wore Fitbit devices (Fitbit Inc., USA) to ascertain sleep parameters. Reliability was analyzed using the Cronbach’s α coefficient, and construct validity was determined through factor analysis. Criteria validity was assessed by correlating their index scores with Fitbit sleep parameters. We identified the optimal cutoff for detecting sleep disorders. Results: The Cronbach’s α coefficient was 0.61, indicating adequate internal consistency. Factor analysis revealed three factors, explaining 48.2% of sleep quality variance. The index scores were negatively correlated with Fitbit sleep efficiency, total sleep time, and number of awakenings (P<0.05). The optimal cutoff point for identifying sleep disorder groups was ≥6. Conclusion The PSQI-K demonstrated good reliability and validity when correlated with Fitbit sleep parameters, offering a practical screening tool for identifying sleep disorders among Korean adults. Cutoff scores can help identify patients for sleep interventions. However, further large-scale studies are required to validate these findings.

Purpose: This study aimed to evaluate the performance of a clinical ladder system in a tertiary hospital by examining how nurses' clinical competence and perceptions of the system affect organizational commitment. Methods: The study involved 394 nurses working at a tertiary hospital. Data were collected from May 3 to July 10, 2023, using a self-reported questionnaire. Statistical analyses, including descriptive statistics, independent t-tests, one-way ANOVA, Kruskal-Wallis test, Scheffé post-hoc test, Pearson correlation, and hierarchical regression analysis, were performed using SPSS 27.0. Results: Nurses who applied for promotion to the CN III level and current CN III nurses reported higher clinical competence, perceptions of the clinical ladder system, and organizational commitment than those who did not and those at lower levels (p<.001). A positive correlation existed among all independent variables.Controlling for general characteristics, the effects of clinical competence and perceptions of the clinical ladder system explained 49% of organizational commitment variance (Adjusted R 2 =.49, F=33.43, p<.001). Conclusion Greater clinical competence and positive perceptions of the clinical ladder system are likely to enhance organizational commitment, emphasizing its effectiveness in fostering better organizational outcomes.

Purpose: This study aimed to evaluate the performance of a clinical ladder system in a tertiary hospital by examining how nurses' clinical competence and perceptions of the system affect organizational commitment. Methods: The study involved 394 nurses working at a tertiary hospital. Data were collected from May 3 to July 10, 2023, using a self-reported questionnaire. Statistical analyses, including descriptive statistics, independent t-tests, one-way ANOVA, Kruskal-Wallis test, Scheffé post-hoc test, Pearson correlation, and hierarchical regression analysis, were performed using SPSS 27.0. Results: Nurses who applied for promotion to the CN III level and current CN III nurses reported higher clinical competence, perceptions of the clinical ladder system, and organizational commitment than those who did not and those at lower levels (p<.001). A positive correlation existed among all independent variables.Controlling for general characteristics, the effects of clinical competence and perceptions of the clinical ladder system explained 49% of organizational commitment variance (Adjusted R 2 =.49, F=33.43, p<.001). Conclusion Greater clinical competence and positive perceptions of the clinical ladder system are likely to enhance organizational commitment, emphasizing its effectiveness in fostering better organizational outcomes.

Purpose: This study aimed to evaluate the performance of a clinical ladder system in a tertiary hospital by examining how nurses' clinical competence and perceptions of the system affect organizational commitment. Methods: The study involved 394 nurses working at a tertiary hospital. Data were collected from May 3 to July 10, 2023, using a self-reported questionnaire. Statistical analyses, including descriptive statistics, independent t-tests, one-way ANOVA, Kruskal-Wallis test, Scheffé post-hoc test, Pearson correlation, and hierarchical regression analysis, were performed using SPSS 27.0. Results: Nurses who applied for promotion to the CN III level and current CN III nurses reported higher clinical competence, perceptions of the clinical ladder system, and organizational commitment than those who did not and those at lower levels (p<.001). A positive correlation existed among all independent variables.Controlling for general characteristics, the effects of clinical competence and perceptions of the clinical ladder system explained 49% of organizational commitment variance (Adjusted R 2 =.49, F=33.43, p<.001). Conclusion Greater clinical competence and positive perceptions of the clinical ladder system are likely to enhance organizational commitment, emphasizing its effectiveness in fostering better organizational outcomes.

Background: Sleep disorders and insomnia are prevalent worldwide, with negative health outcomes. The Pittsburgh Sleep Quality Index (PSQI) is a widely used self-report assessment tool for evaluating sleep quality, comprising seven subdomains. The Korean version of the PSQI (PSQI-K) has been tested for reliability and validity in small sample sizes but lacks large-scale validation using objective measures. Methods: This study was conducted with 268 Korean adults attending health check programs. Participants completed the PSQI-K questionnaire and wore Fitbit devices (Fitbit Inc., USA) to ascertain sleep parameters. Reliability was analyzed using the Cronbach’s α coefficient, and construct validity was determined through factor analysis. Criteria validity was assessed by correlating their index scores with Fitbit sleep parameters. We identified the optimal cutoff for detecting sleep disorders. Results: The Cronbach’s α coefficient was 0.61, indicating adequate internal consistency. Factor analysis revealed three factors, explaining 48.2% of sleep quality variance. The index scores were negatively correlated with Fitbit sleep efficiency, total sleep time, and number of awakenings (P<0.05). The optimal cutoff point for identifying sleep disorder groups was ≥6. Conclusion The PSQI-K demonstrated good reliability and validity when correlated with Fitbit sleep parameters, offering a practical screening tool for identifying sleep disorders among Korean adults. Cutoff scores can help identify patients for sleep interventions. However, further large-scale studies are required to validate these findings.

Purpose: This study aimed to evaluate the performance of a clinical ladder system in a tertiary hospital by examining how nurses' clinical competence and perceptions of the system affect organizational commitment. Methods: The study involved 394 nurses working at a tertiary hospital. Data were collected from May 3 to July 10, 2023, using a self-reported questionnaire. Statistical analyses, including descriptive statistics, independent t-tests, one-way ANOVA, Kruskal-Wallis test, Scheffé post-hoc test, Pearson correlation, and hierarchical regression analysis, were performed using SPSS 27.0. Results: Nurses who applied for promotion to the CN III level and current CN III nurses reported higher clinical competence, perceptions of the clinical ladder system, and organizational commitment than those who did not and those at lower levels (p<.001). A positive correlation existed among all independent variables.Controlling for general characteristics, the effects of clinical competence and perceptions of the clinical ladder system explained 49% of organizational commitment variance (Adjusted R 2 =.49, F=33.43, p<.001). Conclusion Greater clinical competence and positive perceptions of the clinical ladder system are likely to enhance organizational commitment, emphasizing its effectiveness in fostering better organizational outcomes.

Background: Sleep disorders and insomnia are prevalent worldwide, with negative health outcomes. The Pittsburgh Sleep Quality Index (PSQI) is a widely used self-report assessment tool for evaluating sleep quality, comprising seven subdomains. The Korean version of the PSQI (PSQI-K) has been tested for reliability and validity in small sample sizes but lacks large-scale validation using objective measures. Methods: This study was conducted with 268 Korean adults attending health check programs. Participants completed the PSQI-K questionnaire and wore Fitbit devices (Fitbit Inc., USA) to ascertain sleep parameters. Reliability was analyzed using the Cronbach’s α coefficient, and construct validity was determined through factor analysis. Criteria validity was assessed by correlating their index scores with Fitbit sleep parameters. We identified the optimal cutoff for detecting sleep disorders. Results: The Cronbach’s α coefficient was 0.61, indicating adequate internal consistency. Factor analysis revealed three factors, explaining 48.2% of sleep quality variance. The index scores were negatively correlated with Fitbit sleep efficiency, total sleep time, and number of awakenings (P<0.05). The optimal cutoff point for identifying sleep disorder groups was ≥6. Conclusion The PSQI-K demonstrated good reliability and validity when correlated with Fitbit sleep parameters, offering a practical screening tool for identifying sleep disorders among Korean adults. Cutoff scores can help identify patients for sleep interventions. However, further large-scale studies are required to validate these findings.

Purpose: The purpose of this study was to explore and assess the experiences of cancer patients and their caregivers who had been admitted to comprehensive nursing care service wards. Methods: Data were collected from 10 patients and 10 caregivers by in-depth interviews. The data were analyzed using content analysis of Downe-Wamboldt. Results: Three categories and seven subcategories were extracted. 1) Realizing institutional limitations of comprehensive nursing care service: ‘Wishing for precise operating systems based on patient severity,’ ‘Anticipating active caregiver participation in treatment process,’ ‘Requiring a countermeasure for safety accidents,’ 2) Professional nursing service which provides relief: ‘Patient-centered professional nursing service,’ ‘Inpatient service that provides relief for patients and caregivers,’ 3) Anticipating continuous use of the service: ‘Inpatient service which users are willing to reuse,’ ‘Wishing for expansion and reinforcement of the service.’ Conclusion Cancer patients and their caregivers experienced institutional limitations while satisfied with professional nursing service and willing to reuse the service. To improve this situation, institutional support such as separate wards for severe patients, measures for active caregiver participation and prevention of safety accidents, and adequate staffing would be helpful for relatively severe level cancer patients and their caregivers.

Background: Bladder cancer is characterized by frequent mutations, which provide potential therapeutic targets for most patients. The effectiveness of emerging personalized therapies depends on an accurate molecular diagnosis, for which the accurate estimation of the neoplastic cell percentage (NCP) is a crucial initial step. However, the established method for determining the NCP, manual counting by a pathologist, is time-consuming and not easily executable. Methods: To address this, artificial intelligence (AI) models were developed to estimate the NCP using nine convolutional neural networks and the scanned images of 39 cases of urinary tract cancer. The performance of the AI models was compared to that of six pathologists for 119 cases in the validation cohort. The ground truth value was obtained through multiplexed immunofluorescence. The AI model was then applied to 41 cases in the application cohort that underwent next-generation sequencing testing, and its impact on the copy number variation (CNV) was analyzed. Results: Each AI model demonstrated high reliability, with intraclass correlation coefficients (ICCs) ranging from 0.82 to 0.88. These values were comparable or better to those of pathologists, whose ICCs ranged from 0.78 to 0.91 in urothelial carcinoma cases, both with and without divergent differentiation/ subtypes. After applying AI-driven NCP, 190 CNV (24.2%) were reclassified with 66 (8.4%) and 78 (9.9%) moved to amplification and loss, respectively, from neutral/minor CNV. The neutral/minor CNV proportion decreased by 6%. Conclusions These results suggest that AI models could assist human pathologists in repetitive and cumbersome NCP calculations.