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Objective Shift work frequently contributes to sleep disorders and mental health issues in nurses. Modifying environmental conditions may offer a strategy to mitigate these problems. This study investigates the initial relationships between aspects of environmental conditions, sleep patterns, and psychological well-being in nurses.Material and Methods We plan to recruit 364 nurses. Data on environmental conditions (light, noise, green/blue spaces, air pollution) were gathered via questionnaire and real-time devices. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) and the Insomnia Severity Index (ISI), while anxiety and depression symptoms were evaluated using the Hospital Anxiety and Depression Scale (HADS), with higher scores indicating greater severity. Multiple linear regression analyses were employed to explore the associations between the environmental variables, sleep quality measures, and psychological health outcomes.Results To date, preliminary data from 81 recruited nurses are available. These findings indicate that 72.8% of participants reported poor sleep quality, and 59.3% experienced insomnia symptoms. Furthermore, 44.4% displayed signs of anxiety and depression. Increased satisfaction with workplace light quality was significantly associated with lower PSQI (adjusted β: -0.162) and ISI scores (adjusted β: -0.209). Similarly, higher satisfaction with workplace noise levels correlated significantly with lower PSQI (adjusted β: -0.196) and ISI scores (adjusted β: -0.252). Additionally, nurses satisfied with noise levels reported significantly reduced anxiety symptom scores (adjusted β: -0.227). Green/blue spaces and air pollution perceptions showed no significant associations in this preliminary stage.Conclusions These preliminary results suggest that specific environmental factors in the workplace, particularly lighting and noise, may be linked to sleep quality and mental health among nurses. Future publications will incorporate additional data, including real-time environmental monitoring, circadian rhythm metrics, and relevant biomarker data.