Background: Artificial intelligence (AI) can improve the health and well-being of older adults and has the potential to assist and improve nursing care. In recent years, research in this area has been increasing. Therefore, it is necessary to understand the status of development and main research hotspots and identify the main contributors and their relationships in the application of AI in geriatric care via bibliometric analysis. Objective: Using bibliometric analysis, this study aims to examine the current research hotspots and collaborative networks in the application of AI in geriatric care over the past 23 years. Methods: The Web of Science Core Collection database was used as a source. All publications from inception to August 2022 were downloaded. The external characteristics of the publications were summarized through HistCite and the Web of Science. Keywords and collaborative networks were analyzed using VOSviewers and Citespace. Results: We obtained a total of 230 publications. The works originated in 499 institutions in 39 countries, were published in 124 journals, and were written by 1216 authors. Publications increased sharply from 2014 to 2022, accounting for 90.87% (209/230) of all publications. The United States and the International Journal of Social Robotics had the highest number of publications on this topic. The 1216 authors were divided into 5 main clusters. Among the 230 publications, 4 clusters were modeled, including Alzheimer disease, aged care, acceptance, and the surveillance and treatment of diseases. Machine learning, deep learning, and rehabilitation had also become recent research hotspots. Conclusions: Research on the application of AI in geriatric care has developed rapidly. The development of research and cooperation among countries/regions and institutions are limited. In the future, strengthening the cooperation and communication between different countries/regions and institutions may further drive this field’s development. This study provides researchers with the information necessary to understand the current state, collaborative networks, and main research hotspots of the field. In addition, our results suggest a series of recommendations for future research.

Aim: This study aimed to describe and visualize the current research state and collaborative networks in home care safety for older adults over the past 11 years to analyse the gaps of research and future research trends.Background: The amount of research on safety in home care for older adults is increasing. It is necessary to understand the status of development and main research topics and identify the main contributors and their relationships.Methods: A total of 2,631 publications were retrieved from the Web of Science. The external characteristics of the publications were summarized with the Web of Science and Histcite. Collaborative networks and keywords were analysed and visually displayed using analysis tools.Results: The number of articles increased over the years. Articles were identified from 79 countries, 3,630 institutions, 647 journals and 11,691 authors, and complex cooperative relations among them and five research topics were identified.Conclusion: Research on home care safety for older adults is developing steadily, and this field may be understood to a greater extent in the future. Countries, institutions and scholars need to cooperate more in this research field.Implications for Nursing Management: This study contributes important information for understanding achievements in the research field of home care safety and provides insights into future research.

Objectives: This study aimed to measure the patient safety culture and the current practice of patient safety goals in China. Methods: This cross-sectional survey was conducted between November 2020 and November 2021. The 12-dimensions Hospital Survey on Patient Safety Culture questionnaire and the 14-items Survey on the Current Practice of Patient Safety Goal questionnaire were electronically distributed to 8164 healthcare providers across 26 provinces in China. Data were analyzed using descriptive statistics, correlation analysis, and multivariate linear regression. Results: A total of 8164 surveys were received, of which 7765 were valid and analyzed. The average positive response rate for the Hospital Survey on Patient Safety Culture survey was 69.68% (43.41%–91.54%). The percentage of positive responses in 5 dimensions (organizational learning, teamwork within units, feedback about error, management support for safety, and teamwork across units) was above the control limits, and 3 (nonpunitive response to error, staffing, and frequency of event reporting) were below the control limits. The average positive response rate for the Survey on the Current Practice of Patient Safety Goal survey was 96.11%. Patient safety culture was positively related to the current practice of patient safety goals (r = 0.34, P < 0.001). Conclusions: Our study concludes that although healthcare providers in China feel positively toward patient safety culture and practicably toward patient safety goals, considerable work is still needed to promote a patient safety movement.

Background: Change is prevalent in nursing environments and often leads to change fatigue among nurses while aiming to improve service quality and efficiency. Change fatigue is a significant stressor affecting nurses’ work and psychology, and it is a crucial factor influencing organizational change. However, the concept of change fatigue among nurses has not yet been clearly defined or analyzed.Aim: This analysis aims to differentiate, clarify, and clearly identify the specific concept of change fatigue among nurses, which will provide nursing administrators and researchers with a comprehensive understanding of the concept of change fatigue among nurses, ultimately facilitating relevant measurements and interventions.Methods: This study employed Walker and Avant’s concept analysis method.Results: A total of 29 papers were included in the study. The four defining attributes of change fatigue among nurses were identified as nurses’ exposure to constant change, exhaustion, decreased agency, and passive acceptance of change. Antecedents were categorized into nurses’ personal factors and those related to the organizational environment. The consequences of change fatigue were distinguished between individual‐level and organizational‐level impacts.Conclusions: This study provides a clearer understanding of the concept of change fatigue among nurses by outlining its antecedents, attributes, and consequences. An operational definition and conceptual understanding of change fatigue will aid future research in developing effective prevention strategies.

Oral health is a critical area in healthy aging. Oral health literacy (OHL) plays an important role in improving oral health behaviors and oral health status. However, few studies have investigated OHL among community-dwelling older adults and the influential mechanism of OHL on oral health behaviors has not been clarified. The aim of this study is to explore the interaction pathways through which OHL influences oral health behaviors among community-dwelling older adults. This is a cross-sectional study. 429 community-dwelling older adults were recruited by a convenience sampling method from the activity service center in Zhenjiang, Southern China. The data were collected between September and November 2021 using the Oral Health Literacy Adult Questionnaire (OHL-AQ) and other sophisticated scale assessments. A theoretical model based on the information-motivation-behavioral skills model (IMB model) and previous research was developed and then validated using a structural equation model with AMOS v24.0. The proposed model revealed a good fit to the data (χ2/df = 3.349, goodness of fit index = 0.957, adjusted goodness of fit index = 0.921, root mean squared error of approximation = 0.074, comparative fit index = 0.955, normed fit index = 0.938). Oral health information (β = 0.23) and motivation (β = 0.56) positively affected OHL. OHL (β = 0.20) and motivation (β = 0.25) positively affected self-efficacy; self-efficacy (β = 0.98) had a direct effect on oral health behavior. OHL had an indirect effect on oral health behaviors through self-efficacy (β = 0.19). Motivation can both directly influence oral health behavior (β = 0.18) and indirectly influence oral health behavior through OHL and self-efficacy(β = 0.35). The study findings make a valuable contribution to the influential mechanism of OHL on oral health behaviors. OHL improved oral health behaviors through self-efficacy among community-dwelling older adults. Oral health information directly affected OHL. Motivation directly affected oral health behaviors as well as influence oral health behaviors by changing OHL.