Latent profile analysis of self-regulatory fatigue among oncology nurses: a multicenter cross-sectional study

This study identified latent categories of self-regulatory fatigue among oncology nurses, clarified their characteristic differences, and examined associated factors to inform targeted interventions. A cross-sectional design with convenience sampling was employed. From January to June 2025, 675 nurses from oncology specialized hospitals in Guangdong Province, China, completed a general information questionnaire, the Nurse Self-Depletion Scale, the Perceived Social Support Scale, the Differential Atmosphere Scale, and the Trait Anxiety Inventory. Latent profile analysis classified self-regulatory fatigue, and ordinal multinomial logistic regression assessed associated factors. Three fatigue profiles emerged: “low depletion” (n = 248, 36.74%); “moderate depletion” (n = 111, 16.44%); and “high depletion” (n = 316, 46.82%). Ordinal multinomial logistic regression revealed that education level, employment status, work environment, trait anxiety, perceived social support, and perception of differential atmosphere significantly influenced self-regulatory fatigue. Individual oncology nurses present distinct self-regulatory fatigue profiles. Nursing administrators should conduct routine screening and evaluation, and implement interventions targeting these determinants to mitigate self-depletion, thereby advancing nurses’ professional well-being and nursing service quality.