Dyslipidemia dramatically increases the risk of cardiovascular diseases, necessitating appropriate treatment techniques. Generative AI (GenAI), an advanced AI technology that can generate diverse content by learning from vast datasets, provides promising new opportunities to address this challenge. GenAI-powered frequently asked questions systems and chatbots offer continuous, personalized support by addressing lifestyle modifications and medication adherence, which is crucial for patients with dyslipidemia. These tools also help to promote health literacy by making information more accessible and reliable.GenAI helps healthcare providers construct clinical case scenarios, training materials, and evaluation tools, which supports professional development and evidence-based practice.Multimodal GenAI technology analyzes food images and nutritional content to deliver personalized dietary recommendations tailored to each patient's condition, improving long-term nutritional management for those with dyslipidemia. Moreover, using GenAI for image generation enhances the visual quality of educational materials for both patients and professionals, allowing healthcare providers to create real-time, customized visual aids. To apply successfully, healthcare providers must develop GenAI-related abilities, such as prompt engineering and critical evaluation of GenAI-generated data.

Dyslipidemia dramatically increases the risk of cardiovascular diseases, necessitating appropriate treatment techniques. Generative AI (GenAI), an advanced AI technology that can generate diverse content by learning from vast datasets, provides promising new opportunities to address this challenge. GenAI-powered frequently asked questions systems and chatbots offer continuous, personalized support by addressing lifestyle modifications and medication adherence, which is crucial for patients with dyslipidemia. These tools also help to promote health literacy by making information more accessible and reliable.GenAI helps healthcare providers construct clinical case scenarios, training materials, and evaluation tools, which supports professional development and evidence-based practice.Multimodal GenAI technology analyzes food images and nutritional content to deliver personalized dietary recommendations tailored to each patient's condition, improving long-term nutritional management for those with dyslipidemia. Moreover, using GenAI for image generation enhances the visual quality of educational materials for both patients and professionals, allowing healthcare providers to create real-time, customized visual aids. To apply successfully, healthcare providers must develop GenAI-related abilities, such as prompt engineering and critical evaluation of GenAI-generated data.

Dyslipidemia dramatically increases the risk of cardiovascular diseases, necessitating appropriate treatment techniques. Generative AI (GenAI), an advanced AI technology that can generate diverse content by learning from vast datasets, provides promising new opportunities to address this challenge. GenAI-powered frequently asked questions systems and chatbots offer continuous, personalized support by addressing lifestyle modifications and medication adherence, which is crucial for patients with dyslipidemia. These tools also help to promote health literacy by making information more accessible and reliable.GenAI helps healthcare providers construct clinical case scenarios, training materials, and evaluation tools, which supports professional development and evidence-based practice.Multimodal GenAI technology analyzes food images and nutritional content to deliver personalized dietary recommendations tailored to each patient's condition, improving long-term nutritional management for those with dyslipidemia. Moreover, using GenAI for image generation enhances the visual quality of educational materials for both patients and professionals, allowing healthcare providers to create real-time, customized visual aids. To apply successfully, healthcare providers must develop GenAI-related abilities, such as prompt engineering and critical evaluation of GenAI-generated data.

Dyslipidemia dramatically increases the risk of cardiovascular diseases, necessitating appropriate treatment techniques. Generative AI (GenAI), an advanced AI technology that can generate diverse content by learning from vast datasets, provides promising new opportunities to address this challenge. GenAI-powered frequently asked questions systems and chatbots offer continuous, personalized support by addressing lifestyle modifications and medication adherence, which is crucial for patients with dyslipidemia. These tools also help to promote health literacy by making information more accessible and reliable.GenAI helps healthcare providers construct clinical case scenarios, training materials, and evaluation tools, which supports professional development and evidence-based practice.Multimodal GenAI technology analyzes food images and nutritional content to deliver personalized dietary recommendations tailored to each patient's condition, improving long-term nutritional management for those with dyslipidemia. Moreover, using GenAI for image generation enhances the visual quality of educational materials for both patients and professionals, allowing healthcare providers to create real-time, customized visual aids. To apply successfully, healthcare providers must develop GenAI-related abilities, such as prompt engineering and critical evaluation of GenAI-generated data.

Purpose: This study aims to explore the factors influencing nursing professionalism among nursing students, focusing on the image of nurses, satisfaction with their major, and career metacognition. Methods: We conducted a descriptive survey with 185 nursing students from D city and K region on June 10–30, 2024. Data were analyzed using IBM SPSS ver. 27.0 (IBM Corp.), employing descriptive statistics, t tests, one-way ANOVA, Scheffé tests, Pearson’s correlation coefficients, and regression analysis. Multiple linear regression analysis was used to identify factors affecting nursing professionalism among nursing students. Results: The regression analysis revealed that the image of nurses (β=.69, p<.001) and monitoring aspect of career metacognition (β=.13, p=.025) were significant predictors of nursing professionalism, accounting for 64.5% of the variance. Conclusion The findings indicate that the image of nurses and monitoring component of career metacognition are critical in shaping nursing professionalism among nursing students. Therefore, nursing education programs should aim to improve the image of nurses and promote self-reflective career practices as strategies to foster professionalism among nursing students.

Purpose: : The demand for skilled critical care nurses and the significant impact of the practice-readiness gap underscore the need for educational programs bridging nursing education and clinical practice. This would ensure safe, high-quality patient care and a stable workforce. This study aimed to explore the educational needs of critical care nurses to develop an essential nursing education program for nursing students, addressing the practice-readiness gap they may encounter as new nurses. Methods: : The study espoused a qualitative approach by utilizing focus group interviews conducted in South Korea in April and May 2022. A total of 11 nurses participated in the study. Data were collected from three focus groups, each consisting of three to four nurses from intensive care units. Focus group interviews were conducted using a semi-structured questionnaire. Content analysis was performed on the interview data using thematic analysis. Ethical approval for the study was obtained from the institutional review board. Results: : Nursing education programs in intensive care units should prioritize fundamental nursing competencies such as basic nursing and physical examinations. Participants’ critical care nursing education needs were categorized into four main themes: holistic nursing competency, advancement of practical education, skilled communication, and systematic critical care nursing education. Conclusion : The study’s findings provide valuable insights and guidelines for developing critical and intensive care nursing education programs tailored for nursing students.

Objective: This study was a preliminary study for the prevention programs for farmers' occupational diseases. It selected the priorities recognized by farmers, such as occupational diseases, and also identifies the effectiveness and feasibility of prevention programs among diseases recognized by farmers. Therefore, we plan to use it as basis data for future farmer safety and health programs.Method: The subjects of the study were farmers living in the region, selected through a snowball recruitment method, and a total of 671 people were targeted. The priority selection method was the Basic Priority Rating System (BPRS) method, and among the occupational diseases, programs to prevent musculoskeletal diseases, cardiovascular and respiratory diseases, and pesticide poisoning were surveyed on the effectiveness and feasibility of farmers. Results: Among occupational diseases, the highest priority was musculo-skeletal disease, followed by respiratory disease and pesticide poisoning. Among the programs for musculoskeletal disease, 'use of agricultural work convenience equipment and auxiliary tools' had the highest perceived effectiveness and feasibility. Among the five programs for pesticide poisoning, ‘equipment of protective equipment such as pesticide protective clothing/glove’ had the highest effectiveness at 67.4%, and ‘compliance with pesticide use instructions’ had the highest level of feasibility at 64.3%. Among the four programs to prevent respiratory diseases, ‘wearing a dust mask or gas mask’ was the highest at 65.5% in terms of both effectiveness and feasibility. Conclusion When carrying out safety and health programs for farmers, the priorities recognized by farmers should be taken into consideration, and the program contents should also be developed taking into account the size of effect and feasibility recognized by farmers.

Objective: This study was conducted to investigate the awareness of work-related disease prevention of farmers.Method: As a research method, a qualitative focus group interview was conducted in 18 participants. Results: Prevention and management services for work-related diseases of farmers mostly are based on research from other fields and so are not highly effective because their content is not relevant to agricultural work. It has been suggested that such program designers be required to have some appropriate related knowledge, and that incentives and a certification system for participation in such education be established. To analyze work-related diseases of farmers, fields of prevention, diagnosis, treatment, and rehabilitation should be created. They demanded the designation of hospitals and the actualization of compensation for farmers' safety insurance. The work-related diseases to address were include musculoskeletal diseases, pesticide poisoning-related diseases (cardiovascular disease, respiratory disease), psychiatric diseases such as depression, and allergic diseases. However, this must have been the result of the harmful factors they felt during agricultural work. And for farmer patients diagnosed with work-related diseases, it was said to strengthen farmer safety insurance. Conclusion In order to increase the safely and health effects of agricultural work, it is necessary to prevent and manage work-related diseases of farmers. Projects should be developed in consideration of cultural and economic barriers of farmers and the characteristics of the work.

Objective: This study aimed to provide basic data for preventing and managing sarcopenia by identifying the relationship between sarcopenia, malnutrition, and psychosocial factors among the elderly in the community. Methods: The study included 1,019 subjects aged 60 and over. “Possible sarcopenia” was defined by low handgrip strength with or without reduced physical performance. Nutrition was evaluated according to the mini nutrition assessment (MNA), and the psychosocial factors examined were self-efficacy, social isolation, fear of falling, and social capital (trust and participation). A logistic regression analysis was also performed on the relationship between risk of malnutrition, psychosocial factors, and sarcopenia. Results: MNA was significantly associated with social participation (OR = 1.747, p <0.001), fear of falling (OR = 2.905, p <0.001), and self-efficacy (high/low, OR = 0.654, p = 0.011). In model 3, which included both MNA and psychosocial factors, sarcopenia was significantly associated with MNA (OR = 2.529, p <0.001) and fear of falling (OR = 1.544, p = 0.045). Compared with the low self-efficacy group, the high group (OR = 0.589, p = 0.009) was significant. The factors related to possible sarcopenia include risk of malnutrition, fear of falls, and low self-efficacy. Conclusion It will be necessary to improve self-efficacy so that individuals feel they can do activities of daily living themselves and to reduce their fear of falling through muscle strength and balance exercises.Finally, it is also necessary to increase regular participation in community social activities.

Purpose: This study analyzed the relationship between degree of disability and edema index [extracellular water/total body water (ECW/TBW) ratio] values in a rural population of older adult patients with osteopenia, sarcopenia, or osteosarcopenia (OS). Materials and Methods: This study used data from the Namgaram-2 cohort. The degree of disability was measured using the World Health Organization Disability Assessment Schedule (WHODAS) 12, and ECW/TBW ratio was calculated using bioelectrical impedance analysis. Based on ECW/TBW ratio, the participants were stratified into normal (<0.391) and abnormal (≥0.391) groups, and the mean WHODAS 12 scores were compared between the two groups. Multiple regression analysis corrected for demographic factors, smoking history, hypertension, diabetes, and serological test results was also conducted. Results: Significant differences in mean WHODAS 12 scores were observed in the healthy group (5.8±7.4 vs. 9.2±9.7, p=0.008), the osteopenia only group (7.4±8.7 vs. 12.9±12.0, p<0.001), and the OS group (16.0±13.2 vs. 23.1±17.1, p=0.004). However, no significant difference in mean WHODAS 12 score was observed in the sarcopenia only group (14.9±13.4 vs. 20.7±14.8, p= 0.051). There were significant differences in ECW/TBW ratio values between the abnormal and normal groups in the osteopenia only group (B=4.646 and p=0.001), the sarcopenia only group (B=5.097 and p=0.016), and the OS group (B=5.653 and p=0.043). Conclusion This study found that the degree of disability is related to the edema index in older patients with osteopenia, sarcopenia, or OS. Since the edema index indicates the nutritional status of an individual, proper nutrition and fluid intake are important to reduce disability.