BMC Nursing (Apr 2025)
Latent profile analysis of missed nursing care and their predictors among neuro-oncology nurses: a multicenter cross-sectional study
Abstract
Abstract Purpose To explore potential profile characteristics associated with neuro-oncology nurses’ missed nursing care (MNC) and analyze differences in characteristics of neuro-oncology nurses across these profiles. Methods A cross-sectional study design using convenience sampling involved 446 neuro-oncology nurses from ten Grade A oncology hospitals across six provinces in China, conducted from April to June 2024. The General Information Questionnaire, the Oncology Missed Nursing Care Self-Rating Scale, the Practice Environment Scale, and the Psychological Capital Scale were employed for data collection. Latent profile analysis was performed to identify MNC profiles, followed by multinomial logistic regression analysis to examine predictors of MNC. Results The incidence of MNC among neuro-oncology nurses was found to be 36.4%. Three latent profiles were identified: “severe missed nursing care profile” (20.6%), “medium-risk missed nursing care profile” (51.3%), and ‘low-risk missed nursing care profile’ (28.1%). Compared with the “severe missed nursing care profile,” neuro-oncology nurses with a technical secondary school or junior college education, who expressed job satisfaction, good self-confidence, and mental resilience were more likely to fall into the “medium-risk missed nursing care profile.” Additionally, those aged 18–35 years were more likely to be categorized in the “low-risk missed nursing care profile,” and nurses working in a positive nursing work environment were also more likely to belong to the “medium-risk” or “low-risk missed nursing care profiles.” Conclusion There is notable heterogeneity in the levels of missed nursing care among neuro-oncology nurses. Nursing managers should prioritize addressing middle-risk missed nursing care and enhancing both the working environment and psychological support for neuro-oncology nurses. Tailored interventions based on the distribution of different profiles can improve nursing quality, increase job satisfaction, and enhance patient outcomes.
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