Purpose: This study aimed to develop and implement an antimicrobial stewardship education program for physician assistant nurses and to evaluate its effects on their knowledge and clinical performance. Methods: A quasi-experimental, single-group pre-post design was conducted with 50 physician assistant nurses at a university hospital in Seoul, Republic of Korea. The antimicrobial stewardship education program, developed using the ADDIE model, consisted of 12 sessions including lectures and case-based learning (CBL)-based discussions.Knowledge was measured before and immediately after the intervention, while performance was assessed pre-intervention and four weeks post-program. Data were analyzed using paired t-tests, Wilcoxon signed-rank tests, and analysis of covariance (ANCOVA). Results: Knowledge scores significantly improved from 44.65±7.45 to 58.50±10.11 (p<.001), and all subdomains showed significant increases (p<.001). Performance scores increased from 3.68±0.77 to 4.28±0.68 (p<.001). Knowledge gain did not differ significantly between the medical and surgical departments (p=.710). Likewise, after adjusting for pre-test scores, no significant difference in performance improvement was observed between the two departments (ANCOVA, p=.170). These results indicate that the program was effective across both departments regardless of their characteristics. Conclusion The antimicrobial stewardship education program improved both knowledge and performance among physician assistant nurses. This program may contribute to the standardization of antimicrobial stewardship education and to appropriate antimicrobial use and the reduction of antimicrobial resistance.

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.

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: Esophagojejunostomy leakage (EJL) remains one of the most critical complications following total gastrectomy for gastric cancer. This study aimed to evaluate the evolving therapeutic approaches and clinical outcomes of EJL using data from a large-scale multicenter retrospective cohort. Methods: Among 6,577 patients who underwent total gastrectomy or proximal gastrectomy with double tract reconstruction at nine institutions from 2003 to 2024, 196 (3.0%) developed EJL. Of these, 162 patients with comprehensive clinical data were included in the final analysis. The study examined treatment modalities, changes in management over time, patient characteristics, surgical variables, and clinical outcomes. Four groups were defined according to treatment approach: conservative, endoscopic, reoperation, and multimodal (combined) therapy. Results: Endoscopic therapy was first introduced in 2011 and has progressively supplanted reoperation, now comprising 32.5% of cases. The average time to EJL diagnosis was 8.4 days after surgery. Overall in-hospital mortality was 6.1% (10/162). When conservative management was excluded, endoscopic treatment demonstrated the highest rate of therapeutic success (94.3%, p = 0.004). Both the duration until diet resumption and length of hospital stay were notably reduced in the endoscopic and conservative groups compared with reoperation and multimodal therapy (p < 0.001). Moreover, although the highest post-leakage hospitalization costs were observed with multimodal treatment (p < 0.001), overall hospitalization expenses were significantly lower for patients managed conservatively or with endoscopic intervention (p < 0.001). Conclusion Over the past two decades, management of EJL has shifted toward endoscopic approaches. Endoscopic therapies yield superior clinical outcomes and should be considered a primary option for appropriate candidates.

OBJECTIVES: Long-term care facilities (LTCFs) are communal environments for patients with chronic diseases or older adults, making them particularly susceptible to significant harm during infectious disease outbreaks. Nonetheless, LTCFs have historically been subject to less stringent infection prevention and control (IPC) mandates. This study aimed to assess the current state of LTCFs and to develop an IPC system tailored for these facilities following the coronavirus disease 2019 (COVID-19) pandemic. METHODS: We conducted an online survey of 11,366 LTCFs in Korea from December 30, 2022 to January 20, 2023, to evaluate the components of IPC in LTCFs. The infectious diseases targeted for IPC included COVID-19, influenza, and scabies. Additionally, we compared institution-based and home-based long-term care insurance facilities. RESULTS: Overall, 3,537 (31.1%) LTCFs responded to the survey, comprising 1,819 (51.4%) institution-based and 1,718 (48.6%) home-based facilities. A majority (87.4%, 2,376/2,720) of these facilities experienced COVID-19 outbreaks. However, only 42.2% of home-based facilities, in contrast to 90.6% of institution-based facilities, were equipped to manage concurrent COVID-19 cases. Similarly, while 92.1% of institution-based facilities were capable of managing influenza, only 50.5% of home-based facilities could do the same. The incidence of scabies was significantly higher in institution-based facilities than in home-based ones (26.1 vs. 4.3%). Additionally, 88.7% of institution-based facilities managed scabies cases effectively, compared to only 42.1% of home-based facilities. CONCLUSIONS Approximately half of the LTCFs had a basic capacity to respond to infectious diseases. However, there were differences in response capabilities between institution-based facilities and home-based facilities.

OBJECTIVES: Long-term care facilities (LTCFs) are communal environments for patients with chronic diseases or older adults, making them particularly susceptible to significant harm during infectious disease outbreaks. Nonetheless, LTCFs have historically been subject to less stringent infection prevention and control (IPC) mandates. This study aimed to assess the current state of LTCFs and to develop an IPC system tailored for these facilities following the coronavirus disease 2019 (COVID-19) pandemic. METHODS: We conducted an online survey of 11,366 LTCFs in Korea from December 30, 2022 to January 20, 2023, to evaluate the components of IPC in LTCFs. The infectious diseases targeted for IPC included COVID-19, influenza, and scabies. Additionally, we compared institution-based and home-based long-term care insurance facilities. RESULTS: Overall, 3,537 (31.1%) LTCFs responded to the survey, comprising 1,819 (51.4%) institution-based and 1,718 (48.6%) home-based facilities. A majority (87.4%, 2,376/2,720) of these facilities experienced COVID-19 outbreaks. However, only 42.2% of home-based facilities, in contrast to 90.6% of institution-based facilities, were equipped to manage concurrent COVID-19 cases. Similarly, while 92.1% of institution-based facilities were capable of managing influenza, only 50.5% of home-based facilities could do the same. The incidence of scabies was significantly higher in institution-based facilities than in home-based ones (26.1 vs. 4.3%). Additionally, 88.7% of institution-based facilities managed scabies cases effectively, compared to only 42.1% of home-based facilities. CONCLUSIONS Approximately half of the LTCFs had a basic capacity to respond to infectious diseases. However, there were differences in response capabilities between institution-based facilities and home-based facilities.

OBJECTIVES: Long-term care facilities (LTCFs) are communal environments for patients with chronic diseases or older adults, making them particularly susceptible to significant harm during infectious disease outbreaks. Nonetheless, LTCFs have historically been subject to less stringent infection prevention and control (IPC) mandates. This study aimed to assess the current state of LTCFs and to develop an IPC system tailored for these facilities following the coronavirus disease 2019 (COVID-19) pandemic. METHODS: We conducted an online survey of 11,366 LTCFs in Korea from December 30, 2022 to January 20, 2023, to evaluate the components of IPC in LTCFs. The infectious diseases targeted for IPC included COVID-19, influenza, and scabies. Additionally, we compared institution-based and home-based long-term care insurance facilities. RESULTS: Overall, 3,537 (31.1%) LTCFs responded to the survey, comprising 1,819 (51.4%) institution-based and 1,718 (48.6%) home-based facilities. A majority (87.4%, 2,376/2,720) of these facilities experienced COVID-19 outbreaks. However, only 42.2% of home-based facilities, in contrast to 90.6% of institution-based facilities, were equipped to manage concurrent COVID-19 cases. Similarly, while 92.1% of institution-based facilities were capable of managing influenza, only 50.5% of home-based facilities could do the same. The incidence of scabies was significantly higher in institution-based facilities than in home-based ones (26.1 vs. 4.3%). Additionally, 88.7% of institution-based facilities managed scabies cases effectively, compared to only 42.1% of home-based facilities. CONCLUSIONS Approximately half of the LTCFs had a basic capacity to respond to infectious diseases. However, there were differences in response capabilities between institution-based facilities and home-based facilities.

OBJECTIVES: Long-term care facilities (LTCFs) are communal environments for patients with chronic diseases or older adults, making them particularly susceptible to significant harm during infectious disease outbreaks. Nonetheless, LTCFs have historically been subject to less stringent infection prevention and control (IPC) mandates. This study aimed to assess the current state of LTCFs and to develop an IPC system tailored for these facilities following the coronavirus disease 2019 (COVID-19) pandemic. METHODS: We conducted an online survey of 11,366 LTCFs in Korea from December 30, 2022 to January 20, 2023, to evaluate the components of IPC in LTCFs. The infectious diseases targeted for IPC included COVID-19, influenza, and scabies. Additionally, we compared institution-based and home-based long-term care insurance facilities. RESULTS: Overall, 3,537 (31.1%) LTCFs responded to the survey, comprising 1,819 (51.4%) institution-based and 1,718 (48.6%) home-based facilities. A majority (87.4%, 2,376/2,720) of these facilities experienced COVID-19 outbreaks. However, only 42.2% of home-based facilities, in contrast to 90.6% of institution-based facilities, were equipped to manage concurrent COVID-19 cases. Similarly, while 92.1% of institution-based facilities were capable of managing influenza, only 50.5% of home-based facilities could do the same. The incidence of scabies was significantly higher in institution-based facilities than in home-based ones (26.1 vs. 4.3%). Additionally, 88.7% of institution-based facilities managed scabies cases effectively, compared to only 42.1% of home-based facilities. CONCLUSIONS Approximately half of the LTCFs had a basic capacity to respond to infectious diseases. However, there were differences in response capabilities between institution-based facilities and home-based facilities.