Nursing

Moral distress risk profiling in ICU nurses: A cross-sectional study.

BackgroundMoral distress is common among ICU nurses and has been linked to burnout, diminished care quality, and turnover. Which factors matter most - and how they combine to shape individual risk - remains poorly characterised.Research objectiveTo identify factors associated with moral distress in ICU nurses and develop a parsimonious, exploratory risk-profiling model.Research designMulticentre c...

Enhancing diagnostic safety: addressing knowledge gaps for using human factors tools in the safe and effective use of AI - a proposed research agenda.

INTRODUCTION: Identify knowledge gaps in applying artificial intelligence in clinical settings, using medical imaging as a primary use case to enhance diagnostic efficacy, efficiency, and patient and provider safety. METHODS: We convened a two-day workshop with 18 interdisciplinary experts from three countries. Experts represented quality and patient safety, human factors and systems engineering, ...

Nursing Students' Information Seeking Behavior in Saudi Arabia: A Mixed-Method Study.

INTRODUCTION: Nursing care plans are fundamental learning tools for assessing students' clinical judgment, yet documentation quality is influenced by ...

Architecting Enterprise Digital Infrastructure for Nursing Professional Development: The Registered Nurse Experience Platform as a Scalable Model for Standardizing Peer Feedback and Workforce Evaluation.

The RN (Registered Nurse) Experience Platform is an enterprise digital infrastructure developed to standardize peer feedback, self-assessment, and eva...

Artificial Intelligence (AI) and Pediatric Nursing: Benefits, Concerns, Next Steps.

Development and Validation of a Machine Learning-Based Bedside Score (IPA-2T2C2DW) for Invasive Pulmonary Aspergillosis in Critically Ill Non-Neutropenic Immunocompromised Hosts.

OBJECTIVE: To develop and validate machine learning-based diagnostic models for IPA using data available within 24 hours of ICU admission, construct t...

Messaging and Chatbot-Assisted Nursing Consultation (ChatACP) to Empower Family Members of Residents of Nursing Homes on Advance Care Planning: Protocol for a Mixed Methods Pilot Study.

BACKGROUND: Advance care planning (ACP) involves proactive communication about end-of-life care preferences among patients, families, and health care ...

A Large Language Model-Based Simulation Protocol Using ChatGPT for Training Novice Critical Care Nurses in Family Crisis Communication and De-escalation.

High-stress conversations with family members in distress are a common part of the intensive care unit (ICU) nursing environment. Novice critical care...

Inpatient Nurses' Anticipatory Perspectives on Assistive Robots: Qualitative Study.

BACKGROUND: Assistive robots have been proposed to support nursing work by offloading routine, logistical, and physically demanding tasks. However, ex...

Building a Natural Language Processing Augmented Information Support System to Enhance Supportive Care for Patients With Prostate Cancer and Families: User-Centered, Iterative Approach.

BACKGROUND: Patients with prostate cancer and their families face significant challenges during transitions from diagnosis to treatment and posttreatm...

Nurse-Led Ambient AI Scribe for Patient Safety Incident Investigation Reports (Project NARRATE): Retrospective Pre-Post Comparative Document-Quality Study.

BACKGROUND: Patient safety investigation reports support organizational learning only when they are complete, usable, and sufficiently detailed. Conve...

Evaluation of e-health interventions to strengthen nursing care in the neonatal intensive care unit: A systematic review.

PURPOSE: This review explores how e-health interventions are utilized within neonatal intensive care units to support nursing practice, with particula...

Construction and validation of a liquid neural network-based prediction model and bedside tool for spontaneous passage of common bile duct stones.

BACKGROUND: To construct and externally validate a liquid neural network (LNN)-based risk prediction model for spontaneous passage of common bile duct...

Large language models in respiratory care: safety and clinical integration.

BACKGROUND: Large language models (LLMs) are rapidly entering respiratory medicine workflows. Their clinical role remains unclear. A central concern i...

Analyzing Productivity Trends for Nursing Professional Development Practice.

Nursing professional development (NPD) work is strategically important yet frequently difficult to measure. This article describes a practical approac...

Ethical aspects of artificial intelligence use in neonatal intensive care units: a scoping review.

UNLABELLED: This study aims to map ethical, legal, social, professional, and implementation issues associated with artificial intelligence (AI) in neo...

ChatGPT and Large Language Models in Contemporary Nursing.

OBJECTIVES: This narrative review synthesizes published evidence on the applications, benefits, limitations and governance considerations of ChatGPT a...

Sociodemographic bias in LLMs' clinical decision-making for dizziness.

ObjectiveAs large language models (LLMs) enter clinical decision support, concerns persist about sociodemographic bias. We assessed whether LLM recomm...

From bedside queries to complex care: AI for decision-making in infectious diseases.

BACKGROUND: Infectious Diseases require rapid decisions based on heterogeneous and evolving clinical data. At the same time, the shortage of infectiou...

Clinical appraisal of handheld intestinal ultrasound in inflammatory bowel disease: Where are we now?

Gastroenterologist-performed intestinal ultrasound (IUS) is increasingly used to monitor inflammatory bowel disease (IBD) due to its noninvasive, real...