Evidence map›Paper›PMID 41023998›Full record

ArticleBMC nursing2025

Childhood experience profiles and their impact on depression-burnout networks among nurses: a latent class and network analysis.

Jiao-Mei Xue, Ping-Zhen Lin, Wei Guo, Li-Hui Yang

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In one paragraph

Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Jiao-Mei XueSchool of Health and Elderly Care, Shandong Women's University, Jinan, 250300, China.ORCID http://orcid.org/0009-0004-4610-3088
Ping-Zhen LinDepartment of Nursing, Quanzhou First Hospital, Quanzhou, 362000, China.ORCID http://orcid.org/0009-0008-5497-6785
Wei GuoSchool of Education, Shandong Women's University, Jinan, 250300, China.ORCID http://orcid.org/0000-0003-4465-7648
Li-Hui YangRare Cancer Ward, Shandong Cancer Hospital and Institute, Jinan, 250117, China. yanglh@sd-cancer.com.ORCID http://orcid.org/0009-0000-4385-184X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aimed to use a person-centered approach to differentiate types of childhood experiences among nurses and explore whether the relationship between depression and burnout differs across these groups.

methodsThis study employed a cross-sectional design and conducted a questionnaire survey of 866 nurses using convenience sampling. Nurses in a general hospital were surveyed using the Adverse Childhood Experience (ACE) and Benevolent Childhood Experience (BCE) scales, Patient Health Questionnaire-9 (PHQ-9), and Maslach Burnout Inventory (MBI). Latent class analysis in Mplus 8.3 classified nurses by ACEs/BCEs patterns, and network analysis was conducted using the bootnet package in R 4.3.2 to visualize complex interactions between depression and burnout by constructing network diagrams.

resultsLatent class analysis identified two childhood experience profiles: Low ACEs/High BCEs (n = 648) and Moderate ACEs/Low BCEs (n = 218). Network analysis revealed stronger overall connections between depression and burnout symptoms in the Moderate ACEs/Low BCEs group, with Emotional Exhaustion acted as a bridge symptom, transmitting distress between depression and burnout, and thus representing a critical target for intervention. while Cynicism was also a key bridging symptom specifically in the Moderate ACEs/Low BCEs group.

conclusionsThese findings demonstrate that Chinese nurses’ childhood experiences cluster into distinct patterns, with Emotional Exhaustion and Cynicism representing critical intervention targets. Hospital administrators should prioritize monitoring emotional exhaustion and reducing cynicism, particularly among nurses with moderate ACEs/low BCEs, to safeguard workforce stability and patient care. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

BurnoutChildhood experiencesDepressionLatent class analysisNetwork analysisNurse

Identifiers

PMID41023998
PMCPMC12482161

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.