Nursing Student and Faculty Attitudes, Perceptions, and Behavioral Intentions of Artificial Intelligence Use in Nursing Education: An Integrative Review.

Aim: This integrative review critiques and synthesizes current research on nursing faculty and students' attitudes, perceptions, and behavioral intentions toward artificial intelligence (AI)-based tools in nursing education.

Background: AI's rapid integration into health care offers transformative potential in nursing across clinical care, education, policy, and research.

Method: Following Whittemore and Knafl's methodology, Pubmed, CINAHL, and ERIC were searched for studies written in English assessing attitudes, perceptions, and behavioral intentions of nursing students and faculty regarding AI use in nursing education.

Examination of the Structural Validity of the Clinical Learning Environment Inventory Using Exploratory Factor Analysis.

Background And Purpose: This study tested the psychometrics of the Clinical Learning Environment Inventory (CLEI- version), a tool designed to measure the perceptions of nursing students' clinical learning. The developer of the CLEI did not report structural validity.

Method: Exploratory factor analysis (EFA) was performed using data from 311 licensure nursing students to assess the CLEI's proposed dimensions or structural validity.

Reading the phase of a Raman excitation with a multi-state atomic interferometer.

Atomic memories for flying photonic qubits are an essential ingredient for many applications like e.g. quantum repeaters.

Experimental realization of quantum zeno dynamics.

It is generally impossible to probe a quantum system without disturbing it. However, it is possible to exploit the back action of quantum measurements and strong couplings to tailor and protect the coherent evolution of a quantum system. This is a profound and counterintuitive phenomenon known as quantum Zeno dynamics.