Development and validation of a machine learning-based predictive model for compassion fatigue in Chinese nursing interns: a cross-sectional study utilizing latent profile analysis.

ABSTRACT:

Background

Compassion fatigue is a significant issue in nursing, affecting both registered nurses and nursing students, potentially leading to burnout and reduced quality of care. During internships, compassion fatigue can shape nursing students' career trajectories and intent to stay in the profession. Identifying those at high risk is crucial for timely interventions, yet existing tools often fail to account for within-group variability, limiting their ability to accurately predict compassion fatigue risk.

Objectives

This study aimed to develop and validate a predictive model for detecting the risk of compassion fatigue among nursing students during their placement.

Design

A cross-sectional study was used to capture the prevalence and associations of compassion fati

SUBMITTER: Yi L 

PROVIDER: S-EPMC11656937 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature