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Open access
volume 24 issue 1 publication number 77

Profiles of innovative behavior and associated predictors among clinical nurses: a multicenter study using latent profile analysis

Publication typeJournal Article
Publication date2025-01-22
scimago Q1
wos Q1
SJR1.272
CiteScore4.5
Impact factor3.9
ISSN14726955
Abstract
Innovative Behavior (IB) is a key prerequisite for nurses in solving clinical problems. However, existing research on IB among clinical nurses is relatively limited. To identify profiles and characteristics of IB among clinical nurses and explore the associated predictors, as well as the relationships with research outputs. A multicenter cross-sectional study was conducted on 354 clinical nurses in Shanghai from April 2023 to May 2023 (response rate 98.06%). IB was measured by the Innovative Behavior Scale for Nurses (IBSN), future time perspective was measured by the Future Time Perspective Scale (FTPS), and work engagement was measured by the Utrecht Work Engagement Scale-9 (UWES-9). Socio-demographic and professional data and research output indicators were measured by a self-designed questionnaire. We used latent profile analysis (LPA) by Mplus 7.0 to identify latent classes of IB. Ordinal logistic regression analysis was used to analyze the relevant predictors on the different profiles. And then Pearson’s chi-squared was used to analyze the association between IB level and research output. Among the respondents, individuals aged 25 to 35 accounted for 55.9%, and females comprised 94.6%. IB of clinical nurses can be identified into 3 groups: low-level (n = 108, 30.51%), moderate-level (n = 149, 42.09%), and high-level (n = 97, 27.40%) groups. Based on the results of LPA, marital status, education level, work experience, monthly income, night shifts, future time perspective scores, and work engagement scores can be the predictors of IB among different profiles. Statistically significant associations were found between IB level and research productivity, including publishing academic papers (χ2 = 15.307, p < 0.001), registering patents (χ2 = 17.163, p < 0.001), and winning Sci. & Tech awards (χ2 = 27.814, p < 0.001). According to our research, clinical nurses have three unique IB profiles. The current level is predominantly at a moderate level, with less than 30% demonstrating a high level of innovation. It revealed that better socio-demographic status and professional characteristics, future time perspective, and work engagement positively influenced innovative behavior among clinical nurses. The findings also highlight the potentially important role of IB in contributing to nurses’ research output. As far as we know, it might be the first study to employ LPA to clarify the heterogeneity in the levels of IB and their specific distribution among nurses. Our findings may provide a new viewpoint for promoting IB among clinical nurses. Nursing administrators should pay attention to IB of clinical nurses and develop targeted interventions to enhance their IB levels.
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BMC Nursing
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GOST Copy
Li H. et al. Profiles of innovative behavior and associated predictors among clinical nurses: a multicenter study using latent profile analysis // BMC Nursing. 2025. Vol. 24. No. 1. 77
GOST all authors (up to 50) Copy
Li H., Qiao Y., Wan T., Shao C. H., Wen F., Liu X. Profiles of innovative behavior and associated predictors among clinical nurses: a multicenter study using latent profile analysis // BMC Nursing. 2025. Vol. 24. No. 1. 77
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RIS Copy
TY - JOUR
DO - 10.1186/s12912-025-02716-7
UR - https://bmcnurs.biomedcentral.com/articles/10.1186/s12912-025-02716-7
TI - Profiles of innovative behavior and associated predictors among clinical nurses: a multicenter study using latent profile analysis
T2 - BMC Nursing
AU - Li, Husheng
AU - Qiao, Yue
AU - Wan, Tianxiang
AU - Shao, Chun Hua
AU - Wen, Fule
AU - Liu, Xiaoxin
PY - 2025
DA - 2025/01/22
PB - Springer Nature
IS - 1
VL - 24
SN - 1472-6955
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@article{2025_Li,
author = {Husheng Li and Yue Qiao and Tianxiang Wan and Chun Hua Shao and Fule Wen and Xiaoxin Liu},
title = {Profiles of innovative behavior and associated predictors among clinical nurses: a multicenter study using latent profile analysis},
journal = {BMC Nursing},
year = {2025},
volume = {24},
publisher = {Springer Nature},
month = {jan},
url = {https://bmcnurs.biomedcentral.com/articles/10.1186/s12912-025-02716-7},
number = {1},
pages = {77},
doi = {10.1186/s12912-025-02716-7}
}