Purpose: This study aimed to explore nurses’ experience in caring for COVID-19 patients. Methods: A total of 10 nurses working in a COVID-19 ward of a public hospital in South Korea were recruited using purposeful sampling. Individual telephone interviews were conducted and then transcribed verbatim. Data were analyzed using qualitative content analysis. Results: Two categories of nurses’ experience in caring for COVID-19 patients emerged; “unstable psychological status” and “adaptation and self-esteem”. “Shortage of staff due to the increase in infected people”, “poor environment due to the urgent construction of a COVID-19 ward”, “unstable operating system”, and “excessive demands and verbal abuse from patients” were “obstacles”, while “cooperation and consideration between colleagues” and “interest and support from the manager” were found to be “sources to boost morale” for nurses in caring for COVID-19 patients. Conclusion This study can be fundamental data for a deeper understanding of the experiences and challenges faced by frontline nurses caring for COVID-19 patients. It is necessary to provide psychological support for nurses and establish a well-structured nursing care system in order to fight a pandemic such as COVID-19.

Purpose: This study examined the direct effects of fetal attachment, social support, and antepartum depression on anxiety in pregnant women with high-risk pregnancy-related conditions and their husbands. Furthermore, it aimed to explore the serial mediation effects of social support and antepartum depression in the relationship between fetal attachment and anxiety. Methods: A survey-based study was conducted among pregnant women diagnosed with high-risk pregnancy conditions at 24–32 weeks and their husbands, recruited from a pregnant women’s online community between January 20, 2021 and July 20, 2022. Data were collected from 294 individuals (147 couples) using self-report questionnaires. Correlations between variables were analyzed using the IBM SPSS software ver. 26.0 (IBM Corp.), and the mediation effects were assessed using the PROCESS macro, model 6. Results: In the maternal model, maternal-fetal attachment directly affected anxiety (p=.005), with antepartum depression partially mediating this relationship (95% confidence interval [CI], –0.26 to –0.01). In the paternal model, paternal-fetal attachment had no direct effect on anxiety (p=.458). However, social support and antepartum depression fully mediated the relationship between paternal-fetal attachment and anxiety (95% CI, –0.14 to –0.03). Conclusion The findings indicate that social support in the relationship between fetal attachment and depression in high-risk pregnant women and their partners can have direct or indirect effects on the negative emotions of high-risk pregnant couples. It is necessary to assess the level of anxiety in couples experiencing high-risk pregnancies and provide comprehensive nursing interventions that address fetal attachment, social support, and antepartum depression in order to reduce anxiety.

Purpose: This study examined the direct effects of fetal attachment, social support, and antepartum depression on anxiety in pregnant women with high-risk pregnancy-related conditions and their husbands. Furthermore, it aimed to explore the serial mediation effects of social support and antepartum depression in the relationship between fetal attachment and anxiety. Methods: A survey-based study was conducted among pregnant women diagnosed with high-risk pregnancy conditions at 24–32 weeks and their husbands, recruited from a pregnant women’s online community between January 20, 2021 and July 20, 2022. Data were collected from 294 individuals (147 couples) using self-report questionnaires. Correlations between variables were analyzed using the IBM SPSS software ver. 26.0 (IBM Corp.), and the mediation effects were assessed using the PROCESS macro, model 6. Results: In the maternal model, maternal-fetal attachment directly affected anxiety (p=.005), with antepartum depression partially mediating this relationship (95% confidence interval [CI], –0.26 to –0.01). In the paternal model, paternal-fetal attachment had no direct effect on anxiety (p=.458). However, social support and antepartum depression fully mediated the relationship between paternal-fetal attachment and anxiety (95% CI, –0.14 to –0.03). Conclusion The findings indicate that social support in the relationship between fetal attachment and depression in high-risk pregnant women and their partners can have direct or indirect effects on the negative emotions of high-risk pregnant couples. It is necessary to assess the level of anxiety in couples experiencing high-risk pregnancies and provide comprehensive nursing interventions that address fetal attachment, social support, and antepartum depression in order to reduce anxiety.

Purpose: This study examined the direct effects of fetal attachment, social support, and antepartum depression on anxiety in pregnant women with high-risk pregnancy-related conditions and their husbands. Furthermore, it aimed to explore the serial mediation effects of social support and antepartum depression in the relationship between fetal attachment and anxiety. Methods: A survey-based study was conducted among pregnant women diagnosed with high-risk pregnancy conditions at 24–32 weeks and their husbands, recruited from a pregnant women’s online community between January 20, 2021 and July 20, 2022. Data were collected from 294 individuals (147 couples) using self-report questionnaires. Correlations between variables were analyzed using the IBM SPSS software ver. 26.0 (IBM Corp.), and the mediation effects were assessed using the PROCESS macro, model 6. Results: In the maternal model, maternal-fetal attachment directly affected anxiety (p=.005), with antepartum depression partially mediating this relationship (95% confidence interval [CI], –0.26 to –0.01). In the paternal model, paternal-fetal attachment had no direct effect on anxiety (p=.458). However, social support and antepartum depression fully mediated the relationship between paternal-fetal attachment and anxiety (95% CI, –0.14 to –0.03). Conclusion The findings indicate that social support in the relationship between fetal attachment and depression in high-risk pregnant women and their partners can have direct or indirect effects on the negative emotions of high-risk pregnant couples. It is necessary to assess the level of anxiety in couples experiencing high-risk pregnancies and provide comprehensive nursing interventions that address fetal attachment, social support, and antepartum depression in order to reduce anxiety.

Purpose: This study examined the direct effects of fetal attachment, social support, and antepartum depression on anxiety in pregnant women with high-risk pregnancy-related conditions and their husbands. Furthermore, it aimed to explore the serial mediation effects of social support and antepartum depression in the relationship between fetal attachment and anxiety. Methods: A survey-based study was conducted among pregnant women diagnosed with high-risk pregnancy conditions at 24–32 weeks and their husbands, recruited from a pregnant women’s online community between January 20, 2021 and July 20, 2022. Data were collected from 294 individuals (147 couples) using self-report questionnaires. Correlations between variables were analyzed using the IBM SPSS software ver. 26.0 (IBM Corp.), and the mediation effects were assessed using the PROCESS macro, model 6. Results: In the maternal model, maternal-fetal attachment directly affected anxiety (p=.005), with antepartum depression partially mediating this relationship (95% confidence interval [CI], –0.26 to –0.01). In the paternal model, paternal-fetal attachment had no direct effect on anxiety (p=.458). However, social support and antepartum depression fully mediated the relationship between paternal-fetal attachment and anxiety (95% CI, –0.14 to –0.03). Conclusion The findings indicate that social support in the relationship between fetal attachment and depression in high-risk pregnant women and their partners can have direct or indirect effects on the negative emotions of high-risk pregnant couples. It is necessary to assess the level of anxiety in couples experiencing high-risk pregnancies and provide comprehensive nursing interventions that address fetal attachment, social support, and antepartum depression in order to reduce anxiety.

Objectives: Nursing documentation consumes approximately 30% of nurses’ professional time, making improvements in efficiency essential for patient safety and workflow optimization. This study compares traditional nursing documentation methods with a generative artificial intelligence (AI)-based system, evaluating its effectiveness in reducing documentation time and ensuring the accuracy of AI-suggested entries. Furthermore, the study aims to assess the system’s impact on overall documentation efficiency and quality. Methods: Forty nurses with a minimum of 6 months of clinical experience participated. In the pre-assessment phase, they documented a nursing scenario using traditional electronic nursing records (ENRs). In the post-assessment phase, they used the SmartENR AI version, developed with OpenAI’s ChatGPT 4.0 API and customized for domestic nursing standards; it supports NANDA, SOAPIE, Focus DAR, and narrative formats. Documentation was evaluated on a 5-point scale for accuracy, comprehensiveness, usability, ease of use, and fluency. Results: Participants averaged 64 months of clinical experience. Traditional documentation required 467.18 ± 314.77 seconds, whereas AI-assisted documentation took 182.68 ± 99.71 seconds, reducing documentation time by approximately 40%. AI-generated documentation received scores of 3.62 ± 1.29 for accuracy, 4.13 ± 1.07 for comprehensiveness, 3.50 ± 0.93 for usability, 4.80 ± 0.61 for ease of use, and 4.50 ± 0.88 for fluency. Conclusions Generative AI substantially reduces the nursing documentation workload and increases efficiency. Nevertheless, further refinement of AI models is necessary to improve accuracy and ensure seamless integration into clinical practice with minimal manual modifications. This study underscores AI’s potential to improve nursing documentation efficiency and accuracy in future clinical settings.

Objectives: Nursing documentation consumes approximately 30% of nurses’ professional time, making improvements in efficiency essential for patient safety and workflow optimization. This study compares traditional nursing documentation methods with a generative artificial intelligence (AI)-based system, evaluating its effectiveness in reducing documentation time and ensuring the accuracy of AI-suggested entries. Furthermore, the study aims to assess the system’s impact on overall documentation efficiency and quality. Methods: Forty nurses with a minimum of 6 months of clinical experience participated. In the pre-assessment phase, they documented a nursing scenario using traditional electronic nursing records (ENRs). In the post-assessment phase, they used the SmartENR AI version, developed with OpenAI’s ChatGPT 4.0 API and customized for domestic nursing standards; it supports NANDA, SOAPIE, Focus DAR, and narrative formats. Documentation was evaluated on a 5-point scale for accuracy, comprehensiveness, usability, ease of use, and fluency. Results: Participants averaged 64 months of clinical experience. Traditional documentation required 467.18 ± 314.77 seconds, whereas AI-assisted documentation took 182.68 ± 99.71 seconds, reducing documentation time by approximately 40%. AI-generated documentation received scores of 3.62 ± 1.29 for accuracy, 4.13 ± 1.07 for comprehensiveness, 3.50 ± 0.93 for usability, 4.80 ± 0.61 for ease of use, and 4.50 ± 0.88 for fluency. Conclusions Generative AI substantially reduces the nursing documentation workload and increases efficiency. Nevertheless, further refinement of AI models is necessary to improve accuracy and ensure seamless integration into clinical practice with minimal manual modifications. This study underscores AI’s potential to improve nursing documentation efficiency and accuracy in future clinical settings.

Objectives: Nursing documentation consumes approximately 30% of nurses’ professional time, making improvements in efficiency essential for patient safety and workflow optimization. This study compares traditional nursing documentation methods with a generative artificial intelligence (AI)-based system, evaluating its effectiveness in reducing documentation time and ensuring the accuracy of AI-suggested entries. Furthermore, the study aims to assess the system’s impact on overall documentation efficiency and quality. Methods: Forty nurses with a minimum of 6 months of clinical experience participated. In the pre-assessment phase, they documented a nursing scenario using traditional electronic nursing records (ENRs). In the post-assessment phase, they used the SmartENR AI version, developed with OpenAI’s ChatGPT 4.0 API and customized for domestic nursing standards; it supports NANDA, SOAPIE, Focus DAR, and narrative formats. Documentation was evaluated on a 5-point scale for accuracy, comprehensiveness, usability, ease of use, and fluency. Results: Participants averaged 64 months of clinical experience. Traditional documentation required 467.18 ± 314.77 seconds, whereas AI-assisted documentation took 182.68 ± 99.71 seconds, reducing documentation time by approximately 40%. AI-generated documentation received scores of 3.62 ± 1.29 for accuracy, 4.13 ± 1.07 for comprehensiveness, 3.50 ± 0.93 for usability, 4.80 ± 0.61 for ease of use, and 4.50 ± 0.88 for fluency. Conclusions Generative AI substantially reduces the nursing documentation workload and increases efficiency. Nevertheless, further refinement of AI models is necessary to improve accuracy and ensure seamless integration into clinical practice with minimal manual modifications. This study underscores AI’s potential to improve nursing documentation efficiency and accuracy in future clinical settings.

This study was performed to investigate the effects of very low calorie diet (VLCD) using newly meal replacements that contain the wild grass extracts based on Samul-tang ingredients on weight reduction and health in the obese adult women (BMI > or = 25 kg/m2) for four weeks. Seventy five women participated in this experiment. Subjects were randomly classified three groups: 1) General Diet group (GD group, n = 25) consumed 3 regular meals within 600 kcal/day, 2) Meal replacements group (MR group, n = 25) consumed 1 regular meal and 2 meal replacements within 600 kcal/ day, 3) Herbal Meal replacements group (HMR group, n = 25) consumed 1 regular meal and 2 meal replacements within 600 kcal/day. Anthropometric measurements, body composition, biochemical measurements and body symptoms were assessed before (the initial) and after (the 4th week) the study. Anthropometry measurements such as weight, waist and hip circumference, and BMI and body composition such as body fat percent, fat mass significantly decreased in all groups after diet intervention. Anthropometric measurements and body composition of the HMR group significantly more than those of GD and MR groups. Serum Total cholesterol was significantly decreased in all groups. However, there was no significant difference among three groups during the experimental period. HMR group had significantly less felt a pain than GD and MR groups in body symptoms such as anemia, powerlessness, vomiting, constipation and dryness of skin during the experimental period. Therefore, very low calorie diet (VLCD) using meal replacements that contain the wild grass extracts based on Samul-tang ingredients was very effective on weight reduction and health in the obese adult women.
Adipose Tissue ; Adult* ; Anemia ; Anthropometry ; Body Composition ; Caloric Restriction* ; Cholesterol ; Constipation ; Diet ; Female ; Hip ; Humans ; Meals* ; Poaceae ; Skin ; Vomiting ; Weight Loss*

This study was performed to investigate the effects of very low calorie diet (VLCD) using meal replacements that contain the wild grass extracts based on Samul-tang ingredients on psychological factors and quality of life in the obese women (BMI > or = 25 kg/m2) for four weeks. Seventy five women (20 < or = age < 26) participated in this experiment. Subjects were randomly classified three groups: 1) General diet group (GD group, n = 27) consumed 3 regular meals within 600 kcal/day 2) Meal replacements group (MR group, n = 27) consumed 1 regular meal and 2 meal replacements within 600 kcal/day 3) Herbal Meal replacements group (HMR group, n = 27) consumed 1 regular meal and 2 meal replacements within 600 kcal/day. Physical factors (weight, BMI, fat(%)) of the HMR group significantly decreased more than those of GD and MR groups. Moreover, binge eating habit and environmental factors (surrounding support, emotional reaction, expression of opinion) of the HMR group significantly decreased more than those of GD and MR groups. Psychological factor and quality of life were no significant differences among three groups during the experimental period, because both were significantly decreased in all groups after 4 weeks. Therefore, very low calorie diet using meal replacements that contain the wild grass extracts based on Samul-tang ingredients for 4 weeks was effective on improvement of psychological factor and quality of life as well as weight reduction in the obese premenopausal women.
Bulimia ; Caloric Restriction* ; Diet ; Female ; Humans ; Meals* ; Poaceae ; Psychology* ; Quality of Life* ; Weight Loss