Conectar
To evaluate the research capability of clinical nurses in China and identify the determinants associated with their capability.
As nursing evolves into an increasingly independent discipline, the research capability of clinical nurses has become critical for the development of the profession, advancing evidence-based practice and improving patient care quality.
A multicentre cross-sectional survey was conducted using convenience sampling from September 2023 to February 2024, among clinical nurses in tertiary hospitals across three provinces in China. The Nursing Research Capability Self-Assessment Scale was used to assess the research capability of the nurses. Chi-square tests, one-way analysis of variance and multiple linear regression were used to examine factors associated with research capability. The Strengthening the Reporting of Observational Studies in Epidemiology was followed.
A total of 1074 clinical nurses participated. The mean research capability score was 89.11 ± 27.69, reflecting a moderate level of research capability. However, two dimensions of research questions and literature review received lower scores. Multiple linear regression analysis identified that education level, professional title, administrative position and nursing job title (all p < 0.05) were independent predictors of research capability.
Clinical nurses exhibit moderate research capability, with notable deficiencies in formulating research questions and conducting literature reviews. Key factors influencing research capability include education, professional title, administrative position, and job title. Targeted training and development programmes should address these factors to enhance nurses' research competence and advance nursing science.
To conceptualise information distortion in Electronic Health Records (EHRs), with the goal of providing a theoretical foundation for improving documentation practices.
A concept analysis.
Walker and Avant's strategy for concept analysis was used. The defining attributes, antecedents and consequences were identified.
A comprehensive search was conducted across PubMed, Web of Science, Embase, CINAHL and Scopus from their inception to December 2024. Studies published in English that addressed information distortion in EHRs were included.
A total of 37 studies were included. The three defining attributes were: real-world health truth, representation of reality and mismatch relationship. Antecedents were divided into five categories: people-related factors, equipment factors, regulatory factors, working environment factors and management factors. The consequences of information distortion in EHRs included threats to patient safety, poor operational performance, eroded trust, compromised research quality and health inequity.
This concept analysis enhances the understanding of information distortion in EHRs and provides a foundation for further empirical validation. The findings may contribute to the development of measurement instruments and strategies to mitigate information distortion in healthcare settings.
By undertaking a concept analysis of information distortion in EHRs, healthcare professionals will be better equipped to recognise and assess this ethical phenomenon, thereby supporting the development of targeted interventions to mitigate potential harms to healthcare practices. In addition, the clarity of this concept could provide a new angle from which to analyse the origins of flawed EHR documentation and its ripple effects across healthcare systems.
No patient or public involvement.
FreshRSS 