ArticleNursing open2026
Profiles of Innovative Behaviour Among Community Nurses and Associated Factors: A Cross-Sectional Study.
Article in Nursing open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundInnovative behaviour is pivotal for advancing community nursing, yet it is predominantly examined as a monolithic, variable-centred construct. This traditional approach overlooks the inherent heterogeneity in how individual nurses innovate. A person-centred paradigm is therefore crucial to identify distinct subgroups of innovators within the workforce.
aimsThis study aimed to identify distinct latent profiles of innovative behaviour among Chinese community nurses and examine how individual antecedents (such as professional identity and telehealth readiness) and organizational antecedents (such as perceived support and knowledge sharing) are associated with profile membership.
designA cross-sectional descriptive survey design was employed.
methodsA cross-sectional survey was conducted with 395 community nurses recruited via convenience sampling from 87 community health centres in Shenzhen, China. Participants completed validated scales including the nurse innovative behaviour scale (NIBS), the professional identity Scale, the telehealth readiness assessment tools-Chinese, and the Perceived Organizational Support Scale, along with demographic and key work-related antecedents including training access and managerial knowledge sharing. Latent profile analysis (LPA) was conducted using the dimensions of the NIBS as indicators. Multinomial logistic regression was employed to analyse the associated factors of profile membership.
resultsA two-profile solution provided the best model fit. Profile 1 was labelled the Moderate Innovation Profile (50.4%) and was characterized by a consistent, modest pattern of innovation activity, whereas Profile 2 was labelled the High Innovation Profile (49.6%) and exhibited a proactive, high-level pattern across all dimensions. Multinomial logistic regression with the Moderate Innovation Profile as the reference revealed that higher education, prior general hospital experience, research participation, access to innovation training, managerial knowledge sharing, stronger professional identity and higher telehealth readiness were significant predictors for membership in the High Innovation Profile.
conclusionCommunity nurses' innovative behaviour is not uniform but manifests in two distinct profiles. This finding challenges the traditional one-size-fits-all approach to nursing management. The results provide actionable insights indicating that interventions should be tailored to key antecedents. To cultivate the High Innovation Profile, healthcare organizations should prioritize enhancing digital and telehealth readiness and promoting managerial knowledge sharing, alongside fostering research engagement.
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