Healthcare professionals experience negative behaviors such as incivility from various sources within the hospital environment. However, little is known regarding the experience of unlicensed assistive personnel with these behaviors. Using a cross-sectional survey design, the research team aimed to examine the presence, sources, and impact of negative behaviors among registered nurses and unlicensed assistive personnel within a US hospital. Descriptive and inferential statistics were used to analyze quantitative data, while thematic analysis was used to analyze the qualitative responses. A total of 309 participants completed the survey, and 135 participants responded to three qualitative questions. Most respondents identified inadequate staffing/resources to handle workload (87%) and job stress leading to loss of control over behavior as contributing factors to lateral/vertical aggression in the work environment (71%). Impacts of negative behavior on job performance were related to both personal well-being and the work environment. Demoralization was identified as a common consequence of negative behaviors for individuals and within the work environment. The results suggested that registered nurses, unlicensed assistive personnel, and nursing leadership may benefit from system-wide approaches addressing negative behaviors such as incivility within the clinical environment. Specifically, efforts and policies aimed at aiding clinicians in responding to negative behaviors could potentially improve the clinical environment.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11270354PMC
http://dx.doi.org/10.3390/nursrep14030127DOI Listing

Publication Analysis

Top Keywords

negative behaviors
20
unlicensed assistive
16
assistive personnel
16
registered nurses
12
work environment
12
negative behavior
8
behaviors incivility
8
nurses unlicensed
8
clinical environment
8
negative
6

Similar Publications

Horse Innate Immunity in the Control of Equine Infectious Anemia Virus Infection: A Preliminary Study.

Viruses

November 2024

Istituto Zooprofilattico Sperimentale del Lazio e della Toscana "M. Aleandri", Via Appia Nuova 1411, 00178 Rome, Italy.

The mechanisms of the innate immunity control of equine infectious anemia virus in horses are not yet widely described. Equine monocytes isolated from the peripheral blood of three Equine infectious anemia (EIA) seronegative horses were differentiated in vitro into macrophages that gave rise to mixed cell populations morphologically referable to M1 and M2 phenotypes. The addition of two equine recombinant cytokines and two EIA virus reference strains, Miami and Wyoming, induced a more specific cell differentiation, and as for other species, IFNγ and IL4 stimulation polarized horse macrophages respectively towards the M1 and the M2 phenotypes.

View Article and Find Full Text PDF

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social interaction and communication. While many studies suggest that individuals with ASD struggle with emotion processing, the association between emotion processing and autistic traits in non-clinical populations is still unclear. We examine whether neurotypical adults' facial emotion recognition and expression imitation are associated with autistic traits.

View Article and Find Full Text PDF

Public transportation systems play a vital role in modern cities, but they face growing security challenges, particularly related to incidents of violence. Detecting and responding to violence in real time is crucial for ensuring passenger safety and the smooth operation of these transport networks. To address this issue, we propose an advanced artificial intelligence (AI) solution for identifying unsafe behaviours in public transport.

View Article and Find Full Text PDF

Cloud-edge-end computing architecture is crucial for large-scale edge data processing and analysis. However, the diversity of terminal nodes and task complexity in this architecture often result in non-independent and identically distributed (non-IID) data, making it challenging to balance data heterogeneity and privacy protection. To address this, we propose a privacy-preserving federated learning method based on cloud-edge-end collaboration.

View Article and Find Full Text PDF

In recent years, significant research has been directed towards the taxonomy of malware variants. Nevertheless, certain challenges persist, including the inadequate accuracy of sample classification within similar malware families, elevated false-negative rates, and significant processing time and resource consumption. Malware developers have effectively evaded signature-based detection methods.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!