Latent profile analysis of clinical nurses’ reflective ability in relation to dual work stress

J Jingru Song J Junxian Wu J Jing Yu (Institute for Digital Molecular Analytics and Science (IDMxS), Nanyang Technological University, 59 Nanyang Drive, Singapore 636921, Singapore) L Lin Li M Mingfang Zhang Q Qin Shen

Abstract

Objective The aim of this study is to identify the latent profiles of reflective ability in clinical nurses and examine their association with dual work stress. Methods A cross-sectional survey was conducted using convenience sampling between October 2023 and January 2024. Clinical nurses from three tertiary general hospitals in Jiaxing, Zhejiang Province, were recruited for the study. Data were collected using a general information questionnaire, the Clinical Nurses’ Reflective Capacity Scale, and the Dual Work Stress Scale. Latent profile analysis (LPA) was used to identify distinct reflective capacity profiles. Univariate analysis and logistic regression were employed to examine influencing factors. Results A total of 843 nurses participated in the study, with a mean reflective capacity score of 56.15 ± 19.39. Four latent profiles were identified: Low-Level Negative Type (65.0%), High-Recall Insightful Type (7.0%), Low-Recall Introspective Type (4.0%), and High-Level Balanced Type (24.0%). Logistic regression analysis showed that challenge stress, hindrance stress, gender, professional title, participation in reflection training, the habit of keeping a reflective journal, and job satisfaction were significant factors influencing the latent profiles of reflective capacity (P < 0.05). Conclusion Reflective capacity among clinical nurses exhibits heterogeneity, with four distinct latent profiles identified. Nursing managers should tailor interventions based on the influencing factors of different profiles to enhance reflective capacity in clinical nurses.

Article Details

Journal PLoS ONE
Volume / Issue Vol. 20, Issue 9
Published September 11, 2025
Pages e0332077
ISSN 1932-6203
Publisher Public Library of Science

Journal Info

PLoS ONE

Public Library of Science

ISSN: 1932-6203 Open Access Health Sciences

Authors (6)

J

Jingru Song

J

Junxian Wu

J

Jing Yu

Institute for Digital Molecular Analytics and Science (IDMxS), Nanyang Technological University, 59 Nanyang Drive, Singapore 636921, Singapore

L

Lin Li

M

Mingfang Zhang

Q

Qin Shen