An Exploration of Psychological Resilience among Undergraduate Nursing Students Undertaking an Adult Nursing Virtual Practicum during the Coronavirus Pandemic in Taiwan: A Qualitative Study.

This qualitative study aimed to explore the psychological resilience of undergraduate nursing students partaking in a virtual practicum during the coronavirus pandemic (COVID-19) in Taiwan. The virtual practicum, a form of online learning, creates challenges compared to the traditional teaching-learning experience of an actual clinical placement. Exploring how students overcome learning difficulties and build resilience is necessary for a new learning environment or for future online learning. Constructivist grounded theory and the Standards for Reporting Qualitative Research checklist were followed. Purposive and theoretical sampling were used to recruit 18 student nurses for data saturation. Semi-structured, face-to-face interviews were conducted individually to collect data. Initial, focused, and theoretical coding and constant comparative data analysis were performed. Credibility, originality, resonance, and usefulness guided the assessment of the study's quality. The core category of psychological resilience in the virtual practicum was constructed to reflect Taiwanese nursing students' progress and experiences of learning during the virtual practicum. This core category consisted of three subcategories: (i) learning difficulties within one's inner self; (ii) staying positive and confident; and (iii) knowing what is possible. The findings identified psychological resilience as an important factor for students to adjust to the adverse experiences of a rapidly changing learning environment, such as the virtual practicum. The substantive theory of psychological resilience provided a frame of reference for coping with possible future difficulties. Correspondingly, psychological resilience reflected individuals' potential characteristics and may help students to enter and remain in the nursing profession.

Benchmarking of eight recurrent neural network variants for breath phase and adventitious sound detection on a self-developed open-access lung sound database-HF_Lung_V1.

A reliable, remote, and continuous real-time respiratory sound monitor with automated respiratory sound analysis ability is urgently required in many clinical scenarios-such as in monitoring disease progression of coronavirus disease 2019-to replace conventional auscultation with a handheld stethoscope. However, a robust computerized respiratory sound analysis algorithm for breath phase detection and adventitious sound detection at the recording level has not yet been validated in practical applications. In this study, we developed a lung sound database (HF_Lung_V1) comprising 9,765 audio files of lung sounds (duration of 15 s each), 34,095 inhalation labels, 18,349 exhalation labels, 13,883 continuous adventitious sound (CAS) labels (comprising 8,457 wheeze labels, 686 stridor labels, and 4,740 rhonchus labels), and 15,606 discontinuous adventitious sound labels (all crackles). We conducted benchmark tests using long short-term memory (LSTM), gated recurrent unit (GRU), bidirectional LSTM (BiLSTM), bidirectional GRU (BiGRU), convolutional neural network (CNN)-LSTM, CNN-GRU, CNN-BiLSTM, and CNN-BiGRU models for breath phase detection and adventitious sound detection. We also conducted a performance comparison between the LSTM-based and GRU-based models, between unidirectional and bidirectional models, and between models with and without a CNN. The results revealed that these models exhibited adequate performance in lung sound analysis. The GRU-based models outperformed, in terms of F1 scores and areas under the receiver operating characteristic curves, the LSTM-based models in most of the defined tasks. Furthermore, all bidirectional models outperformed their unidirectional counterparts. Finally, the addition of a CNN improved the accuracy of lung sound analysis, especially in the CAS detection tasks.

Healthcare Failure Mode and Effect Analysis (HFMEA) as an Effective Mechanism in Preventing Infection Caused by Accompanying Caregivers During COVID-19-Experience of a City Medical Center in Taiwan.

BACKGROUND AND OBJECTIVES: In response to the COVID-19 pandemic outbreak and to ensure the safety of epidemic prevention in the hospital, the hospital has established mitigation strategies in advance including risk assessment and effect analysis to control hospital visitors and accompanying persons. The study aims to assess the effectiveness of mitigation strategies implemented to effectively prevent the invasion and spread of the virus. METHOD: Conduct a status analysis in accordance with the Healthcare Failure Mode and Effect Analysis (HFMEA) 4-step model, construct a response workflow, confirm the failure mode and potential causes, perform hazard matrix analysis and decision tree analysis, and formulate risk control management measures. RESULTS: For the 4 main processes and 9 subprocesses of the accompanying carers and contract caregivers entering the hospital, 26 potential failure modes and 42 potential causes of failure were analyzed. Following implementing improvement measures including strategies targeting the accompanying person, mitigation workflow failure rates decreased from 42 to 13 items, the pass rate for the maximum body temperature cutoff increased from 53.1% to 90.8%, and the compliance rate of hand washing increased from 89.5% to 100%. CONCLUSION: The HFMEA model can effectively implement preventive risk assessment and workflow management of high-risk medical procedures. The model can adjudicate the health of hospital visitors during the epidemic/pandemic, provide epidemic/pandemic education training and preventive measure health education guidance for hospital visits, and improve their epidemic prevention cognition. When combined, these strategies can prevent nosocomial infection to achieve the best anti-epidemic effect.

Survey on perceived work stress and its influencing factors among hospital staff during the COVID-19 pandemic in Taiwan.

This study aimed to investigate the perceived work stress and its influencing factors among hospital staff during the novel coronavirus (COVID-19) pandemic in Taiwan. A web-based survey was conducted at one medical center and two regional hospitals in southern Taiwan, targeting physicians, nurses, medical examiners, and administrators. The questionnaire included items on the demographic characteristics of hospital staff and a scale to assess stress among healthcare workers caring for patients with a highly infectious disease. A total of 752 valid questionnaires were collected. The hospital staff reported a moderate level of stress and nurses had a highest level of stress compared to staff in the other three occupational categories. The five highest stress scores were observed for the items "rough and cracked hands due to frequent hand washing and disinfectant use," "inconvenience in using the toilet at work," "restrictions on eating and drinking at work," "fear of transmitting the disease to relatives and friends," and "fear of being infected with COVID-19." Discomfort caused by protective equipment was the major stressor for the participants, followed by burden of caring for patients. Among participants who experienced severe stress (n = 129), work stress was higher among those with rather than without minor children. The present findings may serve as a reference for future monitoring of hospital staff's workload, and may aid the provision of support and interventions.