Background: Treatment with oral anticoagulants (OACs) could prevent stroke in atrial fibrillation (AF), but side effects developed due to OACs may cause patients anxiety during decision making. This study aimed to investigate whether shared decision making (SDM) reduces anxiety and improves adherence to stroke prevention measures in patients with AF. Methods: A one-group pretest–posttest design using a questionnaire survey was applied at the outpatient cardiology clinic between July 2019 until September 2020. A Patient Decision Aid (PDA) tool was used for the completion of the questionnaire survey after health education and counseling. Ten questions were included for patients’ recognition of SDM, and a 5-point scoring method was used, where “very much” was scored as 5 points, and “totally not” was scored as 1 point. Results: Fifty-two patients with AF were enrolled. In terms of patients’ recognition of SDM, points of more than 4.17 out of 5 were noted, indicating recognition above the level of “very much.” The patients’ anxiety scores before SDM were 3.56 (1.2), with a decrease of 0.64 points (p < 0.001) to 2.92 (1.3) after SDM. After SDM, the number of patients who decided to take OAC increased from 76.9% to 88.5%, and the 15.4% answering “unclear” decreased to 1.9% (p = 0.006). The patients’ anxiety levels after SDM were associated with gender (p = 0.025). Conclusions: The approach using SDM enhanced our understanding of the pros and cons of OAC treatment and, in patients with AF, decreased anxiety about therapeutic decisions and increased willingness to accept treatment options.

The purpose of this study was to test the feasibility of utilizing the established perimenopausal fatigue self-management scale (P-MFSMS) to evaluate perimenopausal Taiwanese women’s vulnerability to fatigue syndrome. A cross-sectional study design was adopted to survey 220 perimenopausal Taiwanese women with a mean age of 51.8 ± 4.64 years and a mean body mass index of 23.07 ± 3.04 kg/m², 75.9% of whom were married, 52.3% had a college education or above, 80.4% had salaries, 81.3% had small families, and 96.4% were not using hormone therapy. The P-MFSMS consists of 25 questions based on six categories: (1) strive to maintain work energy and efficiency; (2) seek self-help from medical resources (doctor shopping); (3) strive to maintain the normal operation of the family (seeking help and support from family or significant other); (4) make time for activities or exercise in busy life; (5) slow down or adjust lifestyle; (6) frustration. For all of these six categories, the minimum loading of each question on the factor was calculated to be over 0.50, with a Cronbach’s α of 0.78 and a corrected total-item correlation of >0.50. The goodness of fit of the model was determined to be acceptable, with a chi-square/df value of <3.0 (χ² = 503.45 and df = 260), a root mean square error of approximation (RMSEA) value of 0.065 (0.90. There was no statistically significant difference in the difficulty between perimenopausal and postmenopausal women utilizing differential item function (DIF) analysis. Taken together, the 25-question P-MFSMS may be a potentially valid and reliable instrument for suitably evaluating perimenopausal Taiwanese women’s vulnerability to fatigue syndrome. Future studies will be conducted to test the effectiveness of the P-MFSMS for evaluating perimenopausal Taiwanese women’s vulnerability to fatigue syndrome in clinical practice.

The LACE index and HOSPITAL score models are the two most commonly used prediction models identifying patients at high risk of readmission with limited information for home care patients. This study compares the effectiveness of these two models in predicting 30-day readmission following acute hospitalization of such patients in Taiwan. A cohort of 57 home care patients were enrolled and followed-up for one year. We compared calibration, discrimination (area under the receiver operating curve, AUC), and net reclassification improvement (NRI) to identify patients at risk of 30-day readmission for both models. Moreover, the cost-effectiveness of the models was evaluated using microsimulation analysis. A total of 22 readmissions occurred after 87 acute hospitalizations during the study period (readmission rate = 25.2%). While the LACE score had poor discrimination (AUC = 0.598, 95% confidence interval (CI) = 0.488–0.702), the HOSPITAL score achieved helpful discrimination (AUC = 0.691, 95% CI = 0.582–0.785). Moreover, the HOSPITAL score had improved the risk prediction in 38.3% of the patients, compared with the LACE index (NRI = 0.383, 95% CI = 0.068–0.697, p = 0.017). Both prediction models effectively reduced readmission rates compared to an attending physician’s model (readmission rate reduction: LACE, 39.2%; HOSPITAL, 43.4%; physician, 10.1%; p < 0.001). The HOSPITAL score provides a better prediction of readmission and has potential as a risk management tool for home care patients.

Background: The COVID-19 pandemic disrupted clinical training for nursing students, leading to "reality shock" as they entered the workforce without sufficient hands-on experience. Design: This qualitative study employed a 120-minute focus group interview conducted in July 2022. Results: Nine senior nursing students from various educational institutions in Taiwan participated in the focus group interview. Most were female (88.9%) with an average age of 22. Thematic analysis revealed three major needs: (1) self-adjustment due to reduced clinical exposure, (2) more diverse, simulation-based teaching aligned with clinical realities, and (3) extended pre-employment training to compensate for practical skill gaps. Conclusion: The suspension of clinical placements during the pandemic left nursing students underprepared for professional practice. To support a smoother transition, nursing schools should adopt innovative, technology-enhanced teaching strategies, while hospitals must strengthen onboarding programs and mentorship. Addressing these gaps is essential to improving the readiness and retention of new nurses in the post-pandemic era. This study contributes insights into how educational and institutional support can be restructured to better equip students for professional nursing roles in crisis settings.

Background: Nurses are a high-risk group for overweight and obesity due to high stress, low-labor medical work, irregular diet, and lack of exercise. There is scarce information on relationship between job characteristics and overweight and obesity among nurses. This study aimed to answer the question. Does the nature of the work including job position, seniority relate to overweight and obesity among nurses? Their incidence was also investigated. Methods: We conducted a retrospective cohort study of nurses who underwent annual checkups during 2007 to 2016 in a medical center. Overweight was defined as a body mass index between 24 and 27 kg/m². Obesity was defined as a body mass index higher than 27 kg/m². We calculated the prevalence and incidence of overweight and obesity and estimated relative risks using logistic regression. Results: Overall, 4253 participants were enrolled for the incidence of overweight and obesity. We found that junior staff, administrative directors, working in intensive care units, and old age had a high possibility of overweight. Junior staff, administrative directors, old age, and male sex tend to be obesity. Overweight and obesity occurred rapidly in the first 2 years of their career. Conclusion: Our findings suggest that policies should be set up to achieve the goal of workplace health promotion. Health plans focusing on these factors may help nurses avoid obesity and overweight. The director of the hospital should keep track of the health checkup database to confirm the benefits of its long-term implementation.