ArticleFrontiers in public health2026
Latent class analysis of sleep-related worry and its influencing factors among shift work nurses: a cross-sectional study.
Article in Frontiers in public health, 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
Objective: To identify the distinct profiles of sleep-related worry among shift-work nurses and explore their influencing factors, thereby providing a basis for developing targeted interventions for nursing management. Methods: A convenience sampling method was used to select 653 shift nurses from three tertiary grade A hospitals in Shandong Province from March to July 2025 as the study participants. Data were collected using a general information questionnaire, the Anxiety and Preoccupation about Sleep Questionnaire, the Self-regulatory Fatigue Scale, the Pittsburgh Sleep Quality Index, and the Stanford Presenteeism Scale-6. Latent Class Analysis was employed to identify distinct subgroups of sleep-related worry. Influencing factors across the identified classes were examined using univariate analysis and multinomial logistic regression. Results: The sleep-related worry score of the 653 shift nurses was (35.27 ± 9.07) points. They could be divided into three classes: the "emotionally healthy" sleep-related worry group (16.54%), the "consequence worry" sleep-related worry group (25.11%), and the "generalized dysregulation" sleep-related worry group (58.35%). The results of multinomial logistic regression analysis showed that sleep quality, self-regulatory fatigue, sleep-related training, average monthly income, and overtime work were influencing factors of the latent classes of sleep-related worry among shift nurses ( Conclusion: Shift-work nurses report a moderate to high level of sleep-related worry, which manifests in heterogeneous profiles. Nursing managers should accurately identify the differential needs of nurses across these distinct worry categories and implement tailored interventions to improve both sleep health and nursing care quality.
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