Trends of Nursing Research on Accidental Falls: A Topic Modeling Analysis

A Study on Internet News for Patient Safety Campaigns: Focusing on Text Network Analysis and Topic Modeling

Background/Objectives: This study aimed to identify the main issues related to public patient safety campaigns reflected in Korean online news. This study utilized a text-mining method to identify keywords and topics related to patient safety campaigns. Methods: The data collection period was from 1 January 2022 to 31 December 2023, and 4110 news articles were extracted. Through data preprocessing, 2661 duplicated news and 1213 unrelated news were removed, and 236 news were selected. Using the NetMiner program, keyword co-occurrence frequency calculation, keyword centrality analysis, and topic modeling analysis were performed. Results: The results showed that the most frequently mentioned keywords with high degree centrality, betweenness centrality, and closeness centrality in online news were "hospital", "medical", "medicine", "project", and "treatment". The topics of online news related to the patient safety campaign were "patient-centered care for medical safety", "health promotion projects at a regional institution", "hand hygiene education to prevent infection", "healthcare quality improvement through the Mint Festival", and "safe use of medicines". Conclusions: This study analyzed patient safety campaign news topics using text network analysis and topic modeling. It was confirmed that patient safety campaigns are essential for fostering a patient safety culture, improving medical quality, and encouraging patient participation in hospitals. Therefore, to build a safe medical environment, it is necessary to establish an effective patient safety campaign for not only medical staff providing medical care, but also patients and their caregivers, and for this, cooperation and participation from various professional occupations are necessary.

Meteorological parameters and hospital-acquired falls-A multicenter retrospective study based on 10 years of adverse events reporting system data

Objective and rationale

Hospital-acquired falls are common and serious adverse events in medical institutions, with high incidence and injury rates. Studying the occurrence patterns of hospital-acquired falls is important for preventing falls in hospitalized patients. However, the effect of meteorological factors on hospital-acquired falls has not been elucidated. Therefore, this study explored the impact of meteorological parameters on hospital-acquired falls in Chongqing, China, and provided new ideas for the clinical prevention of falls in patients.

Methods

Correlation analysis and distributed lag nonlinear models were employed to analyze the relationship between 3890 cases of hospital-acquired falls and meteorological data in 13 hospitals in 11 districts and counties in Chongqing from January 2013 to April 2023.

Results

The number of hospital-acquired falls demonstrated a nonlinear correlation with the daily average relative humidity and negatively correlated with sunshine duration; however, temperature, air pressure, and wind speed were not correlated. Compared to the reference humidity (87 %), the immediate effects of daily average relative humidity (65-68 % and 90-97 %) increased the risk of hospital-acquired falls on the same day (relative risk [RR]:1.027-1.243). When the daily average relative humidity was 95-97 %, lags of 0-1 d and 8-12 d had greater effects on falls (RR:1.073-1.243). The daily average relative humidities of 62-74 % and 91-97 % were statistically significant at cumulative relative risk (CRR)of 4, 7, 10, and 14 d with a cumulative lag (CRR: 1.111-4.277). On sex and age stratification, the lag and cumulative effects of relative humidity more significantly impacted falls in women and patients aged ≥65 years.

Conclusion

Daily average relative humidity had a nonlinear correlation and lag effect on hospital-acquired falls; therefore, medical institutions should pay attention to the effect of relative humidity on hospital-acquired falls in patients, especially old and female patients.

Exploratory mapping of tumor associated macrophage nanoparticle article abstracts using an eLDA topic modeling machine learning approach

The role of macrophages in regulating the tumor microenvironment has spurned the exponential generation of nanoparticle targeting technologies. With the large amount of literature and the speed at which it is generated it is difficult to remain current with the most up-to-date literature. In this study we performed a topic modeling analysis of 854 abstracts of peer-reviewed literature for the most common usages of nanoparticle targeting of tumor associated macrophages (TAMs) in solid tumors. The data spans 20 years of literature, providing a broad perspective of the nanoparticle strategies. Our topic model found 6 distinct topics: Immune and TAMs, Nanoparticles, Imaging, Gene Delivery and Exosomes, Vaccines, and Multi-modal Therapies. We also found distinct nanoparticle usage, tumor types, and therapeutic trends across these topics. Moreover, we established that the topic model could be used to assign new papers into the existing topics, thereby creating a Living Review. This type of "birds-eye-view" analysis provides a useful assessment tool for exploring new and emerging themes within a large field.

Data Analysis of Psychological Approaches to Soccer Research: Using LDA Topic Modeling

This study identifies the topical areas of research that have attempted a psychological approach to soccer research over the last 33 years (1990-2022) and explored the growth and stagnation of the topic as well as research contributions to soccer development. Data were obtained from 1863 papers from the Web of Science database. The data were collected through keyword text mining and data preprocessing to determine the keywords needed for analysis. Based on the keywords, latent Dirichlet allocation-based topic modeling analysis was performed to analyze the topic distribution of papers and explore research trends by topic area. The topic modeling process included four topic area and fifty topics. The "Coaching Essentials in Football" topic area had the highest frequency, but it was not statistically identified as a trend. However, coaching, including training, is expected to continue to be an important research topic, as it is a key requirement for success in the highly competitive elite football world. Interest in the research field of "Psychological Skills for Performance Development" has waned in recent years. This may be due to the predominance of other subject areas rather than a lack of interest. Various high-tech interventions and problem-solving attempts are being made in this field, providing opportunities for qualitative and quantitative expansion. "Motivation, cognition, and emotion" is a largely underrated subject area in soccer psychology. This could be because survey-based psychological evaluation attempts have decreased as the importance of rapid field application has been emphasized in recent soccer-related studies. However, measuring psychological factors contributes to the study of football psychology through a new methodology and theoretical background. Recognizing the important role of psychological factors in player performance and mental management, as well as presenting new research directions and approaches that can be directly applied to the field, will advance soccer psychology research.