Exploring the challenges of taiwanese nurses in the COVID-19 post-pandemic era.

In the wake of the COVID-19 pandemic, the fluctuating nurse resignation rates highlighted an understudied area in healthcare: post-pandemic challenges in clinical settings. This study, conducted from May to November 2023, employed a qualitative inquiry using focus groups to delve into these challenges. Six focus group sessions, involving 33 nurse participants recruited through snowball sampling from various hospital settings were conducted to explore their clinical experiences during and after the pandemic. Thematic analysis revealed two primary themes: the 'Invisibility of Nurses' within the healthcare system and the 'Moral Duty of Nursing Practice'. These findings illuminate a tension between the overlooked role of nurses and their ethical obligations, underscoring a critical need for policy reassessment. The study advocates for systemic changes, particularly in the undervaluation of the nursing profession and the National Health Insurance system, to address the poor working environment and mitigate long-term nursing shortages. This research deepens understanding of post-pandemic nursing workforce challenges in Taiwan, highlighting the need for policy evolution to enhance recognition and support for the nursing industry. It is suggested to provide tangible compensation to acknowledge nurses' daily care and health education for patients. A healthier working environment can be enhanced by collaborative efforts between healthcare institutions and nurses.

[The Future of Nursing Education: Necessary Elements and Implementation Strategies for Learning Artificial Intelligence].

As populations age, average life expectancy increases and the complexity of diseases rises, leading to nursing care and healthcare systems facing severe challenges related to inadequate resources. Artificial intelligence (AI), including elements such as investigation, integration, learning, prediction, and decision-making, holds significant potential for application in clinical care not only to enhance care quality but also to help guide the future direction of healthcare. AI applications are already being increasingly utilized to improve the quality of clinical care and to streamline workflows. However, because nursing education has lagged behind in terms of adopting AI, greater attention must be given to training up nursing students with AI-related knowledge and application skills. AI technologies should be integrated into nursing curricula and clinical internships to adapt to the rapidly changing high-tech healthcare environment, enabling the more-effective use of AI technology in providing high-quality and safe nursing care.

Predictors for psychological distress of young burn survivors across three years: A cohort study of a burn disaster in Taiwan.

PURPOSE: The study aims to investigate long-term psychological distress and its risk factors in the burn survivors. DESIGN: A longitudinal study with follow-up interviews was conducted from November 2015-June 2018. A post-burn baseline interview was conducted 6 months after the event, followed by annual surveys for three years. METHODS: The burn survivors received structured assessment through telephone in the four-wave interviews, including the five-item Brief Symptom Rating Scale (BSRS-5); two-item Patient Health Questionnaire (PHQ-2); four-item Startle, Physiological Arousal, Anger, and Numbness Scale (SPAN-4); and six-item Impact of Event Scale (IES-6) alongside demographic data and other health-related assessment. FINDINGS: A total of 180 respondents with the mean age of 23 years old completed the four waves of interview. Using the BSRS-5 as the outcome, each variable had different input in psychological distress during the follow-up years. The main finding was that the SPAN-4 score could predict more than 62% of psychological distress between 6 months and 3 years after the disaster. The generalized estimating equation demonstrated that SPAN-4, IES-6, family functioning impairment, hypnotics use, adaptation to the event, and PHQ-2 could predict psychological distress. However, the variable of follow-up year did not exemplify significant estimation in the model. CONCLUSIONS: The results indicated that different factors had various influences on psychological distress across the four follow-up stages. PTSD-like symptoms, depression, and anxiety were the most common psychological problems experienced by the young burn cohort in the longitudinal post-traumatic period. CLINICAL RELEVANCE: Healthcare providers should be aware of psychological consequences of traumatic events within up to a 3-year post-burn period, particularly post-traumatic stress, depression, and anxiety symptoms.