Latent Profile Analysis and Influencing Factors of Positive Mental Health Among Undergraduate Nursing Students

Objective: To explore the latent profile characteristics of positive mental health among undergraduate nursing students and its influencing factors, aiming to provide a scientific basis for mental health education in universities. Methods: A convenience sampling method was used to survey 655 undergraduate nursing students from a university in Zhengzhou between October and December 2022. A general information questionnaire and the Warwick-Edinburgh Mental Well-being Scale (WEMWBS) were used for data collection. Latent Profile Analysis (LPA) was employed to identify the latent categories of positive mental health, and multivariate logistic regression analysis was conducted to examine the influencing factors. Results: The positive psychological health of undergraduate nursing students can be categorized into three latent profiles: low-level positive (45.80%), moderate-level positive (43.21%), and high-level positive (10.99%), indicating significant group heterogeneity. Multivariate logistic regression analysis revealed that household registration (hukou) and chronic constipation were significant influencing factors for different categories of positive psychological health among these students (P < 0.05). Conclusion: The overall level of positive psychological health among undergraduate nursing students exhibits heterogeneity. Relevant universities should design stratified psychological intervention programs based on the diverse psychological characteristics of these students, in order to comprehensively improve their mental health and future professional competency.

Authors

Publication Details

Journal
Journal of Contemporary Medical Practice
Published
2025-09-27
DOI
https://doi.org/10.53469/jcmp.2025.07(09).37
Primary Topic
Psychological Well-being and Life Satisfaction
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Latent Profile Analysis and Influencing Factors of Positive Mental Health Among Undergraduate Nursing Students

Yaru Feng, Yingdong Cao, Mengyuan Li, Jingjie Ren
Journal of Contemporary Medical Practice
Psychological Well-being and Life Satisfaction
article

Latent Profile Analysis and Influencing Factors of Positive Mental Health Among Undergraduate Nursing Students

Yaru Feng, Yingdong Cao, Mengyuan Li, Jingjie Ren
article en

Abstract

Objective: To explore the latent profile characteristics of positive mental health among undergraduate nursing students and its influencing factors, aiming to provide a scientific basis for mental health education in universities. Methods: A convenience sampling method was used to survey 655 undergraduate nursing students from a university in Zhengzhou between October and December 2022. A general information questionnaire and the Warwick-Edinburgh Mental Well-being Scale (WEMWBS) were used for data collection. Latent Profile Analysis (LPA) was employed to identify the latent categories of positive mental health, and multivariate logistic regression analysis was conducted to examine the influencing factors. Results: The positive psychological health of undergraduate nursing students can be categorized into three latent profiles: low-level positive (45.80%), moderate-level positive (43.21%), and high-level positive (10.99%), indicating significant group heterogeneity. Multivariate logistic regression analysis revealed that household registration (hukou) and chronic constipation were significant influencing factors for different categories of positive psychological health among these students (P < 0.05). Conclusion: The overall level of positive psychological health among undergraduate nursing students exhibits heterogeneity. Relevant universities should design stratified psychological intervention programs based on the diverse psychological characteristics of these students, in order to comprehensively improve their mental health and future professional competency.

Journal of Contemporary Medical PracticeVol. 7(9)
Openalex Percentile: Top 69%
Psychological Well-being and Life Satisfaction
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.