Identifying the Knowledge Structure and Trends of Nursing Informatics: A Text Network Analysis

Exploring Nurse Use of Digital Nursing Technology

Technological developments and nursing shortages have become global trends. To solve the problem of shortage of healthcare professionals, technology may be used as a backup. Nurses constitute the largest working group in the healthcare system. Therefore, nurses are very important to the success of implementing digitization in hospitals. This cross-sectional study used the characteristics and adoption roles of innovation diffusion theory to understand technology use within the organization. Data were collected through structured questionnaires and open-ended questions from March 21 to May 31, 2022, in two hospitals in Taiwan. In total, 159 nurses agreed to participate in the study. The results of this study revealed that observability, simplicity, advantage, trialability, and compatibility positively improved the acceptance of digital nursing technology. In the distribution of users' innovative roles, early adopters had a significant impact on innovation characteristics and technology acceptance. Nurses in acute and critical care units perceived a greater comparative advantage and trial availability of digital nursing technology use than did those in general wards and outpatient clinics. In addition, based on user opinions and suggestions, the development of smart healthcare and the use of digital technology are expected to improve the quality of nursing care.

Temporal Exploration of New Nurses' Field Adaptation Using Text Network Analysis

PURPOSE

This study aimed to analyze the experiences of new nurses during their first year of hospital employment to gather data for the development of an evidence-based new nurse residency program focused on adaptability.

METHODS

This study was conducted at a tertiary hospital in Korea between March and August 2021 with 80 new nurses who wrote in critical reflective journals during their first year of work. NetMiner 4.5.0 was used to conduct a text network analysis of the critical reflective journals to uncover core keywords and topics across three periods.

RESULTS

In the journals, over time, degree centrality emerged as "study" and "patient understanding" for 1 to 3 months, "insufficient" and "stress" for 4 to 6 months, and "handover" and "preparation" for 7 to 12 months. Major sub-themes at 1 to 3 months were: "rounds," "intravenous-cannulation," "medical device," and "patient understanding"; at 4 to 6 months they were "admission," "discharge," "oxygen therapy," and "disease"; and at 7 to 12 months they were "burden," "independence," and "solution."

CONCLUSION

These results provide valuable insights into the challenges and experiences encountered by new nurses during different stages of their field adaptation process. This information may highlight the best nurse leadership methods for improving institutional education and supporting new nurses' transitions to the hospital work environment.

Navigating the Landscape of Telemedicine Research: A Topic Modeling Approach for the Present and Future

Introduction: Telemedicine, which is the provision of remote clinical services via telecommunication technology, has undergone an upsurge since the COVID-19 pandemic. To capture this paradigm, this study surveyed telemedicine literature, including postpandemic publications, to identify dominant research themes and temporal trends and suggest directions for future research. Methods: A corpus of 56,445 telemedicine studies is sourced from PubMed. Latent Dirichlet allocation (LDA) topic modeling performed using the Konstanz Information Miner platform. The textual data for topic modeling were processed by following standard procedures for natural language processing. Moreover, the term frequency-inverse document frequency approach was used to capture the importance of words within the corpus. We assessed perplexity, coherence, and the elbow method to determine the optimal number of topics for modeling. Results: The findings confirm the surge in telemedicine research after 2020, signifying its prominence. LDA topic modeling reveals seven distinct research themes, with the most prominent topic being "patient satisfaction" (21.38%) followed by "perspectives and challenges" (17.95%), and "smartphone apps" (14.32%). Furthermore, the results demonstrate a noticeable shift in topics from screening to therapeutic applications of telemedicine. Conclusions: This study serves as a guide for a broad range of telemedicine research topics. This synthesis of themes reflects the commitment of scholars to address the changing dynamics and health care needs, such as the COVID-19 pandemic, aging in place, smartphone usage, and technological advancement. The analysis also reveals flexible research responses to policy and contextual shifts, highlighting the collective drive to broaden the application of telemedicine in community health care.