JMIR nursing最新文献

Background: Taiwan has insufficient nursing resources due to the high turnover rate of health care providers. Therefore, reducing the heavy workload of these employees is essential. Herein, speech transcription, which has various potential clinical applications, was employed for the documentation of nursing records. The requirement of including only one speaker per transcription facilitated data collection and system development. Moreover, authorization from patients was unnecessary.

Objective: The aim of this study was to construct a speech recognition system for nursing records such that health care providers can complete nursing records without typing or with only a few edits.

Methods: Nursing records in Taiwan are mainly written in Mandarin, with technical terms and abbreviations presented in both Mandarin and English. Therefore, the training set consisted of English code-switching information. Next, transfer learning (TL) and meta-TL (MTL) methods, which perform favorably in code-switching scenarios, were applied.

Results: As of September 2021, the China Medical University Hospital Artificial Intelligence Speech (CMaiSpeech) data set was established by manually annotating approximately 100 hours of recordings from 525 speakers. The word error rate (WER) of the benchmark model of syllable-based TL was 29.54% in code-switching. The WER of the proposed model of syllable-based MTL was 22.20% in code-switching. The test set comprised 17,247 words. Moreover, in a clinical case, the proposed model of syllable-based MTL yielded a WER of 31.06% in code-switching. The clinical test set contained 1159 words.

Conclusions: This paper has two main contributions. First, the CMaiSpeech data set-a Mandarin-English corpus-has been established. Health care providers in Taiwan are often compelled to use a mixture of Mandarin and English in nursing records. Second, an automatic speech recognition system for nursing record document conversion was proposed. The proposed system can shorten the work handover time and further reduce the workload of health care providers.

Background: Digital health literacy is the use of information and communication technology to support health and health care. Digital health literacy is becoming increasingly important as individuals continue to seek medical advice from various web-based sources, especially social media, during the pandemics such as COVID-19.

Objective: The study aimed to assess health professionals' digital health literacy level and associated factors in Southwest Ethiopia in 2021.

Methods: An institution-based cross-sectional study was conducted from January to April 2021 in Ethiopia. Simple random sampling technique was used to select 423 study participants among health professionals. SPSS (version 20) software was used for data entry and analysis. A pretested self-administered questionnaire was used to collect the required data. Multivariable logistic regression was used to examine the association between the digital health literacy skill and associated factors. Significance value was obtained at 95% CI and P<.05.

Results: In total, 401 study subjects participated in the study. Overall, 43.6% (n=176) of respondents had high digital health literacy skills. High computer literacy (adjusted odds ratio [AOR] 4.43, 95% CI 2.34-5.67; P=.01); master's degree and above (AOR 3.42, 95% CI 2.31-4.90; P=.02); internet use (AOR 4.00, 95% CI 1.78-4.02; P=.03); perceived ease of use (AOR 2.65, 95% CI 1.35-4.65; P=.04); monthly income of >15,000 Ethiopian birr (>US $283.68; AOR 7.55, 95% CI 6.43-9.44; P<.001); good knowledge of eHealth (AOR 2.22, 95% CI 1.32-4.03; P=.04); favorable attitudes (AOR 3.11, 95% CI 2.11-4.32; P=.04); and perceived usefulness (AOR 3.43, 95% CI 2.43-5.44; P=.02) were variables associated with eHealth literacy level.

Conclusions: In general, less than half of the study participants had a high digital health literacy level. High computer literacy, master's degree and above, frequent internet use, perceived ease to use, income of >15,000 Ethiopian birr (>US $283.68), good knowledge of digital health literacy, favorable attitude, and perceived usefulness were the most determinant factors in the study. Having high computer literacy, frequent use of internet, perceived ease of use, perceived usefulness, favorable attitude, and a high level of education will help to promote a high level of digital health literacy.

Background: The nursing role significantly changed following reforms in the nurse training process. Nowadays, nurses are increasingly trained to promote and improve the quality of clinical practice and to provide support in the assistance of patients and communities. Opportunities and threats are emerging as a consequence of the introduction of new disruptive technologies in public health, which requires the health care staff to develop new digital skills.

Objective: The aim of this paper is to review and define the role of nurses and the skills they are asked to master in terms of new methodological approaches and digital knowledge in a continuously evolving health care scenario that relies increasingly more on technology and digital solutions.

Methods: This scoping review was conducted using a thematic summary of previous studies. Authors collected publications through a cross-database search (PubMed, Web of Science, Google Scholar) related to new telemedicine approaches impacting the nurses' role, considering the time span of 2011-2021 and therefore including experiences and publications related to the first phase of the COVID-19 pandemic.

Results: The assessment was completed between April and July 2021. After a cross-database search, authors reviewed a selection of 60 studies. The results obtained were organized into 5 emerging macro areas: (1) leadership (nurses are expected to show leadership capabilities when introducing new technologies in health care practices, considering their pivotal role in coordinating various professional figures and the patient), (2) soft skills (new communication skills, adaptiveness, and problem solving are needed to adapt the interaction to the level of digital skills and digital knowledge of the patient), (3) training (specific subjects need to be added to nursing training to boost the adoption of new communication and technological skills, enabling health care professionals to largely and effectively use new digital tools), (4) remote management of COVID-19 or chronic patients during the pandemic (a role that has proved to be fundamental is the community and family nurse and health care systems are adopting novel assistance models to support patients at home and to enable decentralization of services from hospitals to the territory), and (5) management of interpersonal relationships with patients through telemedicine (a person-centered approach with an open and sensitive attitude seems to be even more important in the framework of telemedicine where a face-to-face session is not possible and therefore nonverbal indicators are more problematic to be noticed).

Conclusions: Further advancing nurses' readiness in adopting telemedicine requires an integrated approach, including combination of technical knowledge, management abilities, soft skills, and communication skills. This scoping review provides a

Background: Patient mobility is an evidenced-based physical activity intervention initiated during intensive care unit (ICU) admission and continued throughout hospitalization to maintain functional status, yet mobility is a complex intervention and not consistently implemented. Cognitive work analysis (CWA) is a useful human factors framework for understanding complex systems and can inform future technology design to optimize outcomes.

Objective: The aim of this study is to understand the complexity and constraints of the ICU work environment as it relates to nurses carrying out patient mobility interventions, using CWA.

Methods: We conducted a work domain analysis and completed an abstraction hierarchy using the CWA framework. Data from documents, observation (32 hours), and interviews with nurses (N=20) from 2 hospitals were used to construct the abstraction hierarchy.

Results: Nurses seek information from a variety of sources and integrate patient and unit information to inform decision-making. The completed abstraction hierarchy depicts multiple high-level priorities that nurses balance, specifically, providing quality, safe care to patients while helping to manage unit-level throughput needs. Connections between levels on the abstraction hierarchy describe how and why nurses seek patient and hospital unit information to inform mobility decision-making. The analysis identifies several opportunities for technology design to support nurse decision-making about patient mobility.

Conclusions: Future interventions need to consider the complexity of the ICU environment and types of information nurses need to make decisions about patient mobility. Considerations for future system redesign include developing and testing clinical decision support tools that integrate critical patient and unit-level information to support nurses in making patient mobility decisions.

Background: In the master's program of advanced practice nursing at a Norwegian university college, the learning activity reflection groups were converted into virtual reflection group (VRG) meetings during the COVID-19 pandemic. Regardless of the students' clinical practices in different hospitals, they could participate in the same VRG meeting on the web together with the educator from the university college, and the clinical supervisors were invited to participate. The students were in the process of developing the core competence required in their role as advanced practice nurses (APNs), and they had increased responsibility in the implementation of the VRG meetings.

Objective: In this study, we aimed to explore how master's students of advanced practice nursing experienced VRG meetings during the COVID-19 pandemic.

Methods: A qualitative exploratory design was adopted using focus group interviews. A group of students in the master's program of advanced practice nursing participated in an interview that lasted for 60 minutes. They had experienced participating in the VRG meetings following a rigorous guide during their clinical practice. The data from the focus group were analyzed using qualitative content analysis.

Results: The main findings of this study highlighted the importance of structure in VRG meetings, the role of increased responsibility in students' learning processes, the development of APN students' competencies, and increased professional collaboration with clinical supervisors. The APN students and clinical supervisors also continued their discussions in the clinical setting afterward, which strengthened the collaboration between students' education in the master's program and their clinical practice.

Conclusions: VRG meetings gave the students the opportunity to lead professional discussions while reflecting thoroughly on the chosen patient cases from clinical practice. They experienced receiving feedback from fellow students, supervisors, and educators as stimulating their critical thinking development.

Background: The COVID-19 pandemic has accelerated the uptake of digital health innovations due to the availability of various technologies and the urgent health care need for treatment and prevention. Although numerous studies have investigated digital health adoption and the associated challenges and strategies during the pandemic, there is a lack of evidence on the impact on the nursing workforce.

Objective: This study aims to identify the impact of digital health transformation driven by COVID-19 on nurses.

Methods: The online software Covidence was used to follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. Relevant scientific health and computing databases were searched for papers published from January 2020 to November 2021. Using the 8D sociotechnical approach for digital health in health care systems, the papers were analyzed to identify gaps in applying digital health in nursing practice.

Results: In total, 21 papers were selected for content analysis. The analysis identified a paucity of research that quantifies the impact of the digital health transformation on nurses during the pandemic. Most of the initiatives were teleconsultation, followed by tele-intensive care unit (tele-ICU), and only 1 (5%) study explored electronic medical record (EMR) systems. Among the sociotechnical elements, the human-related factor was the most explored and the system measurement was the least studied item.

Conclusions: The review identified a significant gap in research on how implementing digital health solutions has impacted nurses during the COVID-19 pandemic. This gap needs to be addressed by further research to provide strategies for empowering the nursing workforce to be actively involved in digital health design, development, implementation, use, and evaluation.

Background: Online support groups (OSGs) are distance-delivered, easily accessible health interventions offering emotional, informational, and experience-based support and companionship or network support for caregivers managing chronic mental and physical health conditions.

Objective: This study aimed to examine the relative contribution of extraversion, agreeableness, neuroticism, positive attitudes toward OSGs on social networking sites, and typical past OSG use patterns in predicting perceived OSG benefit in an OSG for parents and caregivers of children with neurodevelopmental disorders.

Methods: A mixed methods, longitudinal design was used to collect data from 81 parents across Canada. Attitudes toward OSGs and typical OSG use patterns were assessed using the author-developed Attitudes Toward OSGs subscale (eg, "Online support groups are a place to get and give emotional support") and Past Behaviors in OSGs subscale (eg, "How often would you typically comment on posts?") administered at baseline-before OSG membership. The personality traits of extraversion, agreeableness, and neuroticism were assessed at baseline using the Ten-Item Personality Inventory. Perceived OSG benefit was assessed using the author-developed Perceived OSG Benefit scale (eg, "Overall, did you feel supported by other members in this group?"), administered 2 months after the initiation of OSG membership.

Results: A hierarchical regression analysis found that extraversion was the only variable that significantly predicted perceived OSG benefit (R²=0.125; P<.001).

Conclusions: The key suggestions for improving future OSGs were facilitating more in-depth, customized, and interactive content in OSGs.