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In the rapidly evolving healthcare landscape, the capacity to foster innovative work behavior among nurses is increasingly important. This study examined the dynamics between inclusive leadership, psychological safety, collectivism, and innovative work behavior among nurses.
The study used a cross-sectional, correlational design.
This study utilized data from 730 medical-surgical nurses who provided direct care to patients. Standardized instruments were used to assess key study variables. Statistical analyses, including moderated mediation regressions, were employed to investigate the complex interplay among these variables.
We found a positive association between inclusive leadership and innovative work behavior, and psychological safety mediated this relationship. Collectivism moderated inclusive leadership's direct relationship with psychological safety and its indirect relationship with innovative work behavior. The results revealed that nurses with lower levels of collectivism were more responsive to their managers' inclusive behaviors, strengthening the relation between inclusive leadership, psychological safety, and innovative work behavior.
Our findings suggest that promoting inclusive leadership behaviors among nurse managers to create a psychologically safe environment can motivate nurses to engage in innovative work behavior. However, it is also important to understand that the effectiveness of leadership may differ depending on the collectivist values of individual nurses.
Nurse managers should adopt inclusive leadership behaviors, such as valuing trust, open communication, and diversity, in order to foster psychological safety and innovative work behavior among nurses.
Inpatients need to recognize their fall risk accurately and objectively. Nurses need to assess how patients perceive their fall risk and identify the factors that influence patients' fall risk perception.
This study aims to explore the congruency between nurses' fall risk assessment and patients' perception of fall risk and identify factors related to the non-congruency of fall risk.
A descriptive and cross-sectional design was used. The study enrolled 386 patients who were admitted to an acute care hospital. Six nurses assessed the participants' fall risk. Congruency was classified using the Morse Fall Scale for nurses and the Fall Risk Perception Questionnaire for patients.
The nurses' fall risk assessments and patients' fall risk perceptions were congruent in 57% of the participants. Underestimation of the patient's risk of falling was associated with gender (women), long hospitalization period, department (orthopedics), low fall efficacy, and history of falls before hospitalization. Overestimation of fall risk was associated with age group, gender (men), department, and a high health literacy score. In the multiple logistic regression, the factors related to the underestimation of fall risk were hospitalization period and department, and the factors related to the overestimation of fall risk were health literacy and department.
Nurses should consider the patient's perception of fall risk and incorporate it into fall prevention interventions.
Nurses need to evaluate whether patients perceive the risk of falling consistently. For patients who underestimate or overestimate their fall risk, it may be helpful to consider clinical and fall-related characteristics together when evaluating their perception of fall risk.
The emergence of novel infectious diseases has amplified the urgent need for effective prevention strategies, especially ones targeting vulnerable populations such as children. Factors such as the high incidence of both emerging and existing infectious diseases, delays in vaccinations, and routine exposure in communal settings heighten children's susceptibility to infections. Despite this pressing need, a comprehensive exploration of research trends in this domain remains lacking. This study aims to address this gap by employing text mining and modeling techniques to conduct a comprehensive analysis of the existing literature, thereby identifying emerging research trends in infectious disease prevention among children.
A cross-sectional text mining approach was adopted, focusing on journal articles published between January 1, 2003, and August 31, 2022. These articles, related to infectious disease prevention in children, were sourced from databases such as PubMed, CINAHL, MEDLINE (Ovid), Scopus, and Korean RISS. The data underwent preprocessing using the Natural Language Toolkit (NLTK) in Python, with a semantic network analysis and topic modeling conducted using R software.
The final dataset comprised 509 journal articles extracted from multiple databases. The study began with a word frequency analysis to pinpoint relevant themes, subsequently visualized through a word cloud. Dominant terms encompassed “vaccination,” “adolescent,” “infant,” “parent,” “family,” “school,” “country,” “household,” “community,” “HIV,” “HPV,” “COVID-19,” “influenza,” and “diarrhea.” The semantic analysis identified “age” as a key term across infection, control, and intervention discussions. Notably, the relationship between “hand” and “handwashing” was prominent, especially in educational contexts linked with “school” and “absence.” Latent Dirichlet Allocation (LDA) topic modeling further delineated seven topics related to infectious disease prevention for children, encompassing (1) educational programs, (2) vaccination efforts, (3) family-level responses, (4) care for immunocompromised individuals, (5) country-specific responses, (6) school-based strategies, and (7) persistent threats from established infectious diseases.
The study emphasizes the indispensable role of personalized interventions tailored for various child demographics, highlighting the pivotal contributions of both parental guidance and school participation.
The study provides insights into the complex public health challenges associated with preventing and managing infectious diseases in children. The insights derived could inform the formulation of evidence-based public health policies, steering practical interventions and fostering interdisciplinary synergy for holistic prevention strategies.
This study aims to identify longitudinal patterns and predictors of cognitive function trajectories among Korean older adults with cardiovascular diseases.
This study is a longitudinal panel analysis based on secondary data. Data from the the Korean Longitudinal Study of Ageing (KLoSA) were used for analysis.
The KLoSA is a representative panel survey of older Koreans. We analyzed responses from 301 participants aged ≥65 years who completed the same survey more than three times out of five waves between 2012 and 2020.
Latent class growth modeling identified two trajectories of cognitive function in older people with cardiovascular diseases: “low and declining” (n = 81, 26.9%) and “high and declining” (n = 220, 73.1%). Participants in “the low and declining trajectory group” were more likely to have a low educational level, weak handgrip strength, depression, and low social participation at baseline than those in “the high and declining trajectory group.”
Our results indicate a need to develop community-based tailored interventions for improving handgrip strength, mental health, and social participation in delaying cognitive decline in older people with cardiovascular diseases considering their educational level.
Healthcare providers should be more concerned about older people with a weaker handgrip, depression, and low social activities as a high-risk group for cognitive decline over time in cardiovascular care. Therefore, it is necessary to evaluate them early with standardized tools and make subsequent strategies for the older population with cardiovascular diseases.
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