Objective: In South Korea, there is a significant gap in systematic, evidence-based research on intensive case management (ICM) for individuals with severe mental illness (SMI). This study aims to evaluate the effectiveness of ICM through a randomized controlled trial (RCT) comparing ICM with standard case management (non-ICM). Methods: An RCT was conducted to assess the effectiveness of Seoul-intensive case management (S-ICM) vs. non-ICM in individuals with SMI in Seoul. A total of 78 participants were randomly assigned to either the S-ICM group (n=41) or the control group (n=37). Various clinical assessments, including the Brief Psychiatric Rating Scale (BPRS), Montgomery–Åsberg Depression Rating Scale, Health of the Nation Outcome Scale, and Clinical Global Impression-Improvement (CGI-I), along with quality-of-life measures such as the WHO Disability Assessment Schedule, WHO Quality of Life scale, and Multidimensional Scale of Perceived Social Support (MSPSS) were evaluated over a 3-month period. Statistical analyses, including analysis of covariance and logistic regression, were used to determine the effectiveness of S-ICM. Results: The S-ICM group had significantly lower odds of self-harm or suicidal attempts compared to the control group (adjusted odds ratio [aOR]=0.30, 95% confidence interval [CI]: 0.21–1.38). Psychiatric symptoms measured by the BPRS and perceived social support measured by the MSPSS significantly improved in the S-ICM group. The S-ICM group also had significantly higher odds of CGI-I compared to the control group (aOR=8.20, 95% CI: 2.66–25.32). Conclusion This study provides inaugural evidence on the effectiveness of S-ICM services, supporting their standardization and potential nationwide expansion.

Objective: In South Korea, there is a significant gap in systematic, evidence-based research on intensive case management (ICM) for individuals with severe mental illness (SMI). This study aims to evaluate the effectiveness of ICM through a randomized controlled trial (RCT) comparing ICM with standard case management (non-ICM). Methods: An RCT was conducted to assess the effectiveness of Seoul-intensive case management (S-ICM) vs. non-ICM in individuals with SMI in Seoul. A total of 78 participants were randomly assigned to either the S-ICM group (n=41) or the control group (n=37). Various clinical assessments, including the Brief Psychiatric Rating Scale (BPRS), Montgomery–Åsberg Depression Rating Scale, Health of the Nation Outcome Scale, and Clinical Global Impression-Improvement (CGI-I), along with quality-of-life measures such as the WHO Disability Assessment Schedule, WHO Quality of Life scale, and Multidimensional Scale of Perceived Social Support (MSPSS) were evaluated over a 3-month period. Statistical analyses, including analysis of covariance and logistic regression, were used to determine the effectiveness of S-ICM. Results: The S-ICM group had significantly lower odds of self-harm or suicidal attempts compared to the control group (adjusted odds ratio [aOR]=0.30, 95% confidence interval [CI]: 0.21–1.38). Psychiatric symptoms measured by the BPRS and perceived social support measured by the MSPSS significantly improved in the S-ICM group. The S-ICM group also had significantly higher odds of CGI-I compared to the control group (aOR=8.20, 95% CI: 2.66–25.32). Conclusion This study provides inaugural evidence on the effectiveness of S-ICM services, supporting their standardization and potential nationwide expansion.

Objective: In South Korea, there is a significant gap in systematic, evidence-based research on intensive case management (ICM) for individuals with severe mental illness (SMI). This study aims to evaluate the effectiveness of ICM through a randomized controlled trial (RCT) comparing ICM with standard case management (non-ICM). Methods: An RCT was conducted to assess the effectiveness of Seoul-intensive case management (S-ICM) vs. non-ICM in individuals with SMI in Seoul. A total of 78 participants were randomly assigned to either the S-ICM group (n=41) or the control group (n=37). Various clinical assessments, including the Brief Psychiatric Rating Scale (BPRS), Montgomery–Åsberg Depression Rating Scale, Health of the Nation Outcome Scale, and Clinical Global Impression-Improvement (CGI-I), along with quality-of-life measures such as the WHO Disability Assessment Schedule, WHO Quality of Life scale, and Multidimensional Scale of Perceived Social Support (MSPSS) were evaluated over a 3-month period. Statistical analyses, including analysis of covariance and logistic regression, were used to determine the effectiveness of S-ICM. Results: The S-ICM group had significantly lower odds of self-harm or suicidal attempts compared to the control group (adjusted odds ratio [aOR]=0.30, 95% confidence interval [CI]: 0.21–1.38). Psychiatric symptoms measured by the BPRS and perceived social support measured by the MSPSS significantly improved in the S-ICM group. The S-ICM group also had significantly higher odds of CGI-I compared to the control group (aOR=8.20, 95% CI: 2.66–25.32). Conclusion This study provides inaugural evidence on the effectiveness of S-ICM services, supporting their standardization and potential nationwide expansion.

Objective: In South Korea, there is a significant gap in systematic, evidence-based research on intensive case management (ICM) for individuals with severe mental illness (SMI). This study aims to evaluate the effectiveness of ICM through a randomized controlled trial (RCT) comparing ICM with standard case management (non-ICM). Methods: An RCT was conducted to assess the effectiveness of Seoul-intensive case management (S-ICM) vs. non-ICM in individuals with SMI in Seoul. A total of 78 participants were randomly assigned to either the S-ICM group (n=41) or the control group (n=37). Various clinical assessments, including the Brief Psychiatric Rating Scale (BPRS), Montgomery–Åsberg Depression Rating Scale, Health of the Nation Outcome Scale, and Clinical Global Impression-Improvement (CGI-I), along with quality-of-life measures such as the WHO Disability Assessment Schedule, WHO Quality of Life scale, and Multidimensional Scale of Perceived Social Support (MSPSS) were evaluated over a 3-month period. Statistical analyses, including analysis of covariance and logistic regression, were used to determine the effectiveness of S-ICM. Results: The S-ICM group had significantly lower odds of self-harm or suicidal attempts compared to the control group (adjusted odds ratio [aOR]=0.30, 95% confidence interval [CI]: 0.21–1.38). Psychiatric symptoms measured by the BPRS and perceived social support measured by the MSPSS significantly improved in the S-ICM group. The S-ICM group also had significantly higher odds of CGI-I compared to the control group (aOR=8.20, 95% CI: 2.66–25.32). Conclusion This study provides inaugural evidence on the effectiveness of S-ICM services, supporting their standardization and potential nationwide expansion.

Objective: In South Korea, there is a significant gap in systematic, evidence-based research on intensive case management (ICM) for individuals with severe mental illness (SMI). This study aims to evaluate the effectiveness of ICM through a randomized controlled trial (RCT) comparing ICM with standard case management (non-ICM). Methods: An RCT was conducted to assess the effectiveness of Seoul-intensive case management (S-ICM) vs. non-ICM in individuals with SMI in Seoul. A total of 78 participants were randomly assigned to either the S-ICM group (n=41) or the control group (n=37). Various clinical assessments, including the Brief Psychiatric Rating Scale (BPRS), Montgomery–Åsberg Depression Rating Scale, Health of the Nation Outcome Scale, and Clinical Global Impression-Improvement (CGI-I), along with quality-of-life measures such as the WHO Disability Assessment Schedule, WHO Quality of Life scale, and Multidimensional Scale of Perceived Social Support (MSPSS) were evaluated over a 3-month period. Statistical analyses, including analysis of covariance and logistic regression, were used to determine the effectiveness of S-ICM. Results: The S-ICM group had significantly lower odds of self-harm or suicidal attempts compared to the control group (adjusted odds ratio [aOR]=0.30, 95% confidence interval [CI]: 0.21–1.38). Psychiatric symptoms measured by the BPRS and perceived social support measured by the MSPSS significantly improved in the S-ICM group. The S-ICM group also had significantly higher odds of CGI-I compared to the control group (aOR=8.20, 95% CI: 2.66–25.32). Conclusion This study provides inaugural evidence on the effectiveness of S-ICM services, supporting their standardization and potential nationwide expansion.

Purpose: This study aimed to analyze the factors influencing the well-being of middle-aged non-shift female workers using health-determinant models. Methods: This study analyzed data from the fifth Korean Working Conditions Survey (KWCS), involving 5,449 participants. A hierarchical multiple regression analysis was employed to examine the relationships between various factors and well-being. Results: The analysis identified key factors affecting well-being in middle-aged female non-shift workers, including supervisor support, presenteeism, satisfaction with the working environment, autonomy in working hours, support from coworkers, workplace discrimination, occupation, work-life balance, sleep problems, workplace size, weekly work hours, and sickness absence. This study confirms that the well-being of middle-aged non-shift female workers is influenced by factors at the individual, social, and community levels as well as by conditions related to love. Conclusion To enhance the well-being of middle-aged female non-shift workers, it is essential to reinforce positive factors such as support from coworkers and superiors. Additionally, addressing and mitigating negatively influencing factors such as workplace discrimination and sleep problems is crucial in promoting well-being. By implementing measures to improve these aspects, organizations and policymakers can contribute to a healthier and more supportive work environment for middle-aged, non-shift female workers.

Purpose: This study aimed to analyze the factors influencing the well-being of middle-aged non-shift female workers using health-determinant models. Methods: This study analyzed data from the fifth Korean Working Conditions Survey (KWCS), involving 5,449 participants. A hierarchical multiple regression analysis was employed to examine the relationships between various factors and well-being. Results: The analysis identified key factors affecting well-being in middle-aged female non-shift workers, including supervisor support, presenteeism, satisfaction with the working environment, autonomy in working hours, support from coworkers, workplace discrimination, occupation, work-life balance, sleep problems, workplace size, weekly work hours, and sickness absence. This study confirms that the well-being of middle-aged non-shift female workers is influenced by factors at the individual, social, and community levels as well as by conditions related to love. Conclusion To enhance the well-being of middle-aged female non-shift workers, it is essential to reinforce positive factors such as support from coworkers and superiors. Additionally, addressing and mitigating negatively influencing factors such as workplace discrimination and sleep problems is crucial in promoting well-being. By implementing measures to improve these aspects, organizations and policymakers can contribute to a healthier and more supportive work environment for middle-aged, non-shift female workers.

Purpose: This study aimed to analyze the factors influencing the well-being of middle-aged non-shift female workers using health-determinant models. Methods: This study analyzed data from the fifth Korean Working Conditions Survey (KWCS), involving 5,449 participants. A hierarchical multiple regression analysis was employed to examine the relationships between various factors and well-being. Results: The analysis identified key factors affecting well-being in middle-aged female non-shift workers, including supervisor support, presenteeism, satisfaction with the working environment, autonomy in working hours, support from coworkers, workplace discrimination, occupation, work-life balance, sleep problems, workplace size, weekly work hours, and sickness absence. This study confirms that the well-being of middle-aged non-shift female workers is influenced by factors at the individual, social, and community levels as well as by conditions related to love. Conclusion To enhance the well-being of middle-aged female non-shift workers, it is essential to reinforce positive factors such as support from coworkers and superiors. Additionally, addressing and mitigating negatively influencing factors such as workplace discrimination and sleep problems is crucial in promoting well-being. By implementing measures to improve these aspects, organizations and policymakers can contribute to a healthier and more supportive work environment for middle-aged, non-shift female workers.

Purpose: This study aimed to analyze the factors influencing the well-being of middle-aged non-shift female workers using health-determinant models. Methods: This study analyzed data from the fifth Korean Working Conditions Survey (KWCS), involving 5,449 participants. A hierarchical multiple regression analysis was employed to examine the relationships between various factors and well-being. Results: The analysis identified key factors affecting well-being in middle-aged female non-shift workers, including supervisor support, presenteeism, satisfaction with the working environment, autonomy in working hours, support from coworkers, workplace discrimination, occupation, work-life balance, sleep problems, workplace size, weekly work hours, and sickness absence. This study confirms that the well-being of middle-aged non-shift female workers is influenced by factors at the individual, social, and community levels as well as by conditions related to love. Conclusion To enhance the well-being of middle-aged female non-shift workers, it is essential to reinforce positive factors such as support from coworkers and superiors. Additionally, addressing and mitigating negatively influencing factors such as workplace discrimination and sleep problems is crucial in promoting well-being. By implementing measures to improve these aspects, organizations and policymakers can contribute to a healthier and more supportive work environment for middle-aged, non-shift female workers.

Purpose: This study aimed to analyze the factors influencing the well-being of middle-aged non-shift female workers using health-determinant models. Methods: This study analyzed data from the fifth Korean Working Conditions Survey (KWCS), involving 5,449 participants. A hierarchical multiple regression analysis was employed to examine the relationships between various factors and well-being. Results: The analysis identified key factors affecting well-being in middle-aged female non-shift workers, including supervisor support, presenteeism, satisfaction with the working environment, autonomy in working hours, support from coworkers, workplace discrimination, occupation, work-life balance, sleep problems, workplace size, weekly work hours, and sickness absence. This study confirms that the well-being of middle-aged non-shift female workers is influenced by factors at the individual, social, and community levels as well as by conditions related to love. Conclusion To enhance the well-being of middle-aged female non-shift workers, it is essential to reinforce positive factors such as support from coworkers and superiors. Additionally, addressing and mitigating negatively influencing factors such as workplace discrimination and sleep problems is crucial in promoting well-being. By implementing measures to improve these aspects, organizations and policymakers can contribute to a healthier and more supportive work environment for middle-aged, non-shift female workers.