Characteristics of undertriaged older patients in the emergency department: Retrospective study.

BACKGROUND: Older patients are more likely to be undertriaged as they often suffer from multiple diseases and complain of non-specific symptoms. Therefore, it is necessary to identify the characteristics of undertriaged older patients in emergency departments. METHODS: This descriptive study retrospectively reviewed and analyzed the electronic medical records of older patients who visited the emergency department of a general hospital in Seoul between January and December 2019. RESULTS: Approximately 29 % (n = 4,823) of older patients who visited the emergency department during the study period were classified as Korean Triage and Acuity Scale (KTAS) level 4 or 5, and approximately 8 % (n = 397) were undertriaged. Approximately 73 % (n = 288) of patients were hospitalized after visiting the emergency department. The undertriaged older patients exhibited nervous system symptoms such as dizziness and headache (28.8 %), cardiopulmonary symptoms such as chest discomfort, palpitations, and abdominal pain (28.4 %), head trauma (12.8 %), and respiratory symptoms such as cough and dyspnea (12.5 %). CONCLUSION: Triage nurses in emergency departments should carefully triage older patients as their chief complaints can be non-specific. In particular, when older patients visit the emergency department and exhibit symptoms such as dizziness, abnormal pain, chest discomfort, palpitations, and head trauma, they are more likely to be admitted to the intensive care unit. Therefore, meticulous care for older patients showing these symptoms is essential.

Dual mediating effects of anxiety to use and acceptance attitude of artificial intelligence technology on the relationship between nursing students' perception of and intention to use them: a descriptive study.

BACKGROUND: Artificial intelligence (AI)-based healthcare technologies are changing nurses' roles and enhancing patient care. However, nursing students may not be aware of the benefits, may not be trained to use AI-based technologies in their practice, and could have ethical concerns about using them. This study was conducted to identify the dual mediating effects of anxiety to use and acceptance attitude toward AI on the relationship between perception of and intentions to use AI among nursing students in South Korea. METHODS: The research model followed the PROCESS Macro model 6 proposed by Hayes. The participants were 180 nursing students in Gyeonggi-do. Data were collected from January 5-16, 2023, using self-reported questionnaires. Data were analyzed using the SPSS/WIN 25.0 program, with independent t-tests, one-way analysis of variance, Pearson's correlations, and Hayes's PROCESS macro method for mediation. RESULTS: AI perception positively correlated with acceptance attitude (r =.44, p <.001), intention to use AI (r =.38, p <.001) and negatively correlated with anxiety (r = -.27, p <.001). Anxiety about AI negatively correlated with an acceptance attitude toward AI (r = -.36, p <.001) and intentions to use AI (r = -.28, p <.001). Acceptance attitude toward AI positively correlated with intentions to use AI (r =.43, p <.001). Anxiety about AI and acceptance attitude toward AI had a dual mediating effect on the relationship between AI perception and intentions to use AI. CONCLUSIONS: It is necessary to develop systematic educational programs to improve the perception of AI. Thus, the competency and professionalism of nursing students regarding the use of AI in healthcare can be improved.

Effects of Handover Education Using the Outcome-Present State Test (OPT) Model and SBAR in Nursing Students: A Quasi-Experimental Design.

Background: Since most of nursing students lack clinical reasoning competency, for effective handover education, it is necessary to include a strategy to improve the clinical reasoning competency in the practical training course of the nursing department. Methods: This study used a quasi-experimental research design using a non-equivalent control group pretestposttest design to verify the effectiveness of the practice education program using the OPT model and SBAR. The subjects were 73 third-year students participating in clinical practice or clinical alternative practice in Korea. Results: The experimental group showed significantly better communication clarity (t=-12.262, P<.001), communication confidence (t=-12.486, P<.001), problem-solving processes (t=-13.100, P<.001), and team efficacy (t=-6.197, P<.001) compared to before the intervention. However, there was no significant difference between the pre- and post-intervention scores of the control group. Conclusion: In a situation where clinical practice is difficult for nursing students, the handover education program using the OPT model and SBAR can helps improve their communication clarity, communication confidence, problem-solving process, and team efficacy.

Factors associated with self-care behavior in patients with pre-dialysis or dialysis-dependent chronic kidney disease.

Self-care behavior plays a pivotal role in the management of chronic kidney disease. Improved self-care behavior in patients with chronic kidney disease is a key factor in health management and treatment adherence. This study aimed to evaluate the participants' general and medical condition-related characteristics, physiological indices and the level of health literacy affecting self-care behavior in patients with chronic kidney disease in South Korea. The data of 278 participants were analyzed using t-test, analysis of variance, correlation coefficient, and linear multiple regression analysis. There were significant differences in self-care behavior scores depending on participants' age and cohabitation status, employment, and smoking status as well as having dialysis due to end-stage kidney disease; number of comorbidities; levels of serum hemoglobin, calcium, and creatinine; and estimated glomerular filtration rate. The results of regression analysis revealed that not currently working, non-smoker, end-stage kidney disease, and positive response to the "actively managing my health" scale of the Health Literacy Questionnaire significantly affected self-care behavior in patients with chronic kidney disease, and the explanatory power of the model was 32.7%. Therefore, it is necessary to identify each patient's barriers or needs according to individual characteristics, such as age, cohabitation and employment status, and daily life circumstances, including smoking habits, comorbidities, social support, and level of health literacy to develop efficient support strategies for promoting adequate self-care behavior with CKD.

Influence of AI ethics awareness, attitude, anxiety, and self-efficacy on nursing students' behavioral intentions.

BACKGROUND: Artificial intelligence (AI) technology has recently seen rapid advancement, with an expanding role and scope in nursing education and healthcare. This study identifies the influence of AI ethics awareness, attitude toward AI, anxiety, and self-efficacy on nursing students' behavioral intentions to use AI-based healthcare technology. METHODS: The participants included 189 nursing students in Gyeonggi-do, with data collected from November to December 2021 using self-reported questionnaires. We analyzed the data using the SPSS/WIN 26.0 program, including a t-test, Pearson's correlation coefficient, and hierarchical multiple linear regression. RESULTS: The results revealed that AI ethical awareness (t = - 4.32, p < .001), positive attitude toward AI (t = - 2.60, p = .010), and self-efficacy (t = - 2.65, p = .009) scores of the third and fourth-year nursing students were higher, while their anxiety scores were lower (t = 2.30, p = .022) compared to the scores of the first and second-year nursing students. The factors influencing behavioral intention included a positive attitude toward AI (ß = 0.58) and self-efficacy (ß = 0.22). The adjusted R2 was 0.42. CONCLUSION: It is necessary to inculcate a positive attitude toward AI and self-efficacy by providing educational programs on AI-based technology in healthcare settings.

Nursing students' intent to use AI-based healthcare technology: Path analysis using the unified theory of acceptance and use of technology.

BACKGROUND: Marked advances in artificial intelligence (AI)-based technologies throughout industries, including healthcare, necessitate a broader understanding their use. Particularly, intent to use AI-based healthcare technologies and its predictors among nursing students, who are prospective healthcare professionals, is required to promote the utilization of AI. OBJECTIVE: This study conducted a path analysis to predict nursing students' intent to use AI-based healthcare technologies based on the unified theory of acceptance and use of technology. DESIGN: A cross-sectional survey was performed. PARTICIPANTS: The participants were 210 nursing students from two nursing schools in Korea. METHODS: This study established hypothetical paths for the influence of performance expectancy, effort expectancy, social influence, facilitating conditions, self-efficacy, and anxiety on intent to use AI-based technologies. Mediation of positive and negative attitudes and facilitating conditions' direct effects on intent to use were examined. RESULTS: Positive attitude toward AI (ß = 0.485, p = .009) and facilitating conditions (ß = 0.117, p = .045) predicted intent to use, whereas the path from negative attitude to intent to use was not significant. Performance expectancy, self-efficacy, and effort expectancy predicted positive attitude. Performance expectancy and self-efficacy had a negative effect on the path to negative attitude, whereas anxiety had a positive effect. Facilitating conditions did not significantly predict positive or negative attitude and only directly predicted intent to use. Social influence did not have a significant effect on intent to use. CONCLUSIONS: Intervention programs and other measures should be developed to provide education and information to boost performance expectancy, effort expectancy, facilitating conditions, and self-efficacy regarding the use of AI to lower anxiety and foster positive attitude toward AI-based health technologies.

Effect of Korean Advanced Life Support Education on Non-Technical and Technical Skills of Nursing Students: A Pilot Study.

This study aimed to investigate the effect of the Korean Advanced Life Support (KALS) education program on the non-technical skills and technical skills of nursing students. This one-group pretest-posttest experimental study included 46 participants who were fourth year nursing students at Shinsung University located in Dangjin-si, Chungcheongnam-do Province, Republic of Korea. Data were collected in April 2021 and analyzed via SPSS/WIN 25.0, using a paired samples t-test. The current study results report a significant improvement in the non-technical skills from 30.58 to 47.16 points (t = -5.892, p < 0.001). Furthermore, KALS training improved communication confidence from 23.45 to 35.77 points (t = -6.563, p < 0.001), critical thinking tendency from 96.71 to 107.16 points (t = -3.352, p = 0.002), and self-efficacy in performing cardiopulmonary resuscitation from 33.56 to 49.81 points (t = -13.242, p < 0.001). Lastly, technical skills also improved from 18.35 to 27.94 points (t = -28.439, p < 0.001). Therefore, the findings indicate that KALS education was effective in improving the non-technical and technical skills of these nursing students. However, this study did not analyze the effect of the stress level experienced by the study participants in emergency situations on their non-technical and technical skill performance. Thus, future studies should verify the effect of external stressors, caused by unpredictable emergencies, on non-technical and technical skill performance.

The Effect of Simulation Nursing Education Using the Outcome-Present State-Test Model on Clinical Reasoning, the Problem-Solving Process, Self-Efficacy, and Clinical Competency in Korean Nursing Students.

The purpose of this study was to assess the effect of a simulation nursing education program in terms of clinical reasoning, problem-solving process, self-efficacy, and clinical competency using the Outcome-Present State-Test (OPT) model in nursing students. The participants comprised 45 undergraduate nursing students recruited from two universities in Korea. The number of nursing students assigned to the experimental group and control group were 25 and 20, respectively. For a period of two weeks, the experimental group received a simulation nursing education program using the OPT model, while the control group received a traditional clinical practicum. The data were analyzed using prior homogeneity tests (Fisher's exact test and paired t-test); ANCOVA was performed to investigate the differences in dependent variables between the two groups. There was a significant improvement in clinical reasoning (F = 10.59, p = 0.002), problem-solving process (F = 30.92, p < 0.001), and self-efficacy (F = 36.03, p < 0.001) in the experimental group as compared to the control group (F = 10.59, p = 0.002). Moreover, the experimental group showed significantly higher scores in clinical competency than the control group (F = 11.07, p = 0.002). This study demonstrates that the simulation nursing education program using the OPT model for undergraduate students is very effective in promoting clinical reasoning, problem-solving processes, self-efficacy, and clinical competency.