Li Husheng, Qiao Yue, Wan Tianxiang, Shao Chun Hua, Wen Fule, Liu Xiaoxin
Department of Nursing, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, No. 241, West Huaihai Road, Xuhui District, Shanghai, 200030, China.
School of Nursing, Shanghai Jiao Tong University, No. 227, South Chongqing Road, Huangpu District, Shanghai, 200025, China.
BMC Nurs. 2025 Jan 22;24(1):77. doi: 10.1186/s12912-025-02716-7.
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 (χ= 15.307, p < 0.001), registering patents (χ= 17.163, p < 0.001), and winning Sci. & Tech awards (χ= 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.
创新行为是护士解决临床问题的关键前提条件。然而，目前关于临床护士创新行为的研究相对有限。
识别临床护士创新行为的类型和特征，探索相关预测因素以及与研究成果的关系。
于2023年4月至2023年5月对上海354名临床护士进行了一项多中心横断面研究（应答率98.06%）。采用护士创新行为量表（IBSN）测量创新行为，采用未来时间洞察力量表（FTPS）测量未来时间洞察力，采用乌得勒支工作投入量表-9（UWES-9）测量工作投入。通过自行设计的问卷收集社会人口学和专业数据以及研究成果指标。使用Mplus 7.0进行潜在类别分析（LPA）以识别创新行为的潜在类别。采用有序逻辑回归分析不同类别上的相关预测因素。然后使用Pearson卡方检验分析创新行为水平与研究成果之间的关联。
在受访者中，25至35岁的个体占55.9%，女性占94.6%。临床护士的创新行为可分为3组：低水平组（n = 108，30.51%）、中等水平组（n = 149，42.09%）和高水平组（n = 97，27.40%）。基于潜在类别分析结果，婚姻状况、教育水平、工作经验、月收入、夜班、未来时间洞察力得分和工作投入得分可作为不同类别创新行为的预测因素。创新行为水平与研究产出之间存在统计学显著关联，包括发表学术论文（χ = 15.307，p < 0.001）、申请专利（χ = 17.163，p < 0.001）和获得科技奖项（χ = 27.814，p < 0.001）。
根据我们的研究，临床护士有三种独特的创新行为类型。目前水平主要处于中等水平，不到30%表现出高水平创新。研究表明，更好的社会人口学状况和专业特征、未来时间洞察力和工作投入对临床护士的创新行为有积极影响。研究结果还突出了创新行为在促进护士研究产出方面可能具有的重要作用。
据我们所知，这可能是第一项采用潜在类别分析来阐明护士创新行为水平的异质性及其具体分布的研究。我们的研究结果可能为促进临床护士的创新行为提供一个新的视角。护理管理者应关注临床护士的创新行为，并制定针对性干预措施以提高其创新行为水平。
