Aims: The purpose of this study is to investigate the impact of nurses’ stress situation coping levels on somatization symptoms, the mediating effect of depression, and the moderating effect of perceived social support. Background: As a core part of the global healthcare system, nurses are crucial to patient health and rehabilitation outcomes. However, due to heavy workloads, unreasonable staffing structures, and constant exposure to occupational risks in their workplaces, these factors often place nurses in a high-intensity, high-stress environment, which directly affects their physical and mental health and professional burnout. Coping with stress situations is an important means to help individuals effectively manage stress, reduce negative impacts, and maintain mental health. However, research on the impact of nurses’ stress situation coping methods on somatization symptoms is limited. Methods: This study conducted a cross-sectional survey from December 2022 to April 2023, and finally included 293 nurses working on the front line of tertiary hospitals. Data was collected through questionnaires and analyzed using SPSS 24.0 and the SPSS macro program’s Models 7 and 14. This study is an observational study, strictly prepared and presented according to the STROBE checklist. Results: The somatization symptom scores of the nurses were (27.27 ± 7.33) points, the stress situation coping scores were (59.90 ± 9.64) points, the perceived social support scores were (65.64 ± 12.90) points, and the depression scores were (4.42 ± 4.12) points. The somatization symptom scores of the nurses were positively correlated with the stress situation coping scores and depression scores, and negatively correlated with the perceived social support scores, with correlation coefficients of 0.200, 0.851, and −0.302, respectively. The stress coping level of the nurses had a direct positive impact on somatization symptoms (β = 0.081, p = 0.009), and a direct positive impact on nurse depression (β = 0.202, p = 0.001). Depression had a significant positive impact on somatization symptoms (β = 0.823, p = 0.000), and depression played a mediating role. Perceived social support had a significant negative impact on depression (β = −0.383, p = 0.000). Perceived social support had a significant moderating effect on the relationship between the stress situation coping level and depression (β = −0.121, p = 0.003). Conclusion: In this study, the stress situation coping methods of nurses had a positive impact on somatization symptoms, had a complete mediating effect on the depression level of nurses, and perceived social support had a significant moderating effect in the pathway from the stress situation coping methods of nurses to depression-mediated somatization symptoms.

With the development of central-private enterprises integration, selecting suitable key suppliers are able to provide core components for smart complex equipment. We consider selecting suitable key suppliers from matching perspective, for it not only satisfies natural development of smart complex equipment, it is also a good implementation of equipment project in central-private enterprises integration context. In in this paper, we carry out two parts of research, one is evaluation attributes based on comprehensive analysis, and the other is matching process between key suppliers and core components based on the matching attribute. In practical analysis process, we employ comprehensive evaluated analysis methods to acquire relevant attributes for the matching process that follows. In the analysis process, we adopt entropy-maximum deviation method (MDM)-decision-making trial and evaluation laboratory (DEMATEL)-technique for order preference by similarity to an ideal solution (TOPSIS) to obtain a comprehensive analysis. The entropy-MDM is applied to get weight value, DEMATEL is utilized to obtain internal relations, and TOPSIS is adopted to get ideal evaluated solution. We consider aggregating two types of evaluation information according to similarities of smart complex equipment based on the combination between geometric mean and arithmetic mean. Moreover, based on the aforementioned attributes and generalized power Heronian mean operator, we aggregate preference information to acquire relevant satisfaction degree, then combine the constructed matching model to get suitable key supplier. Through comprehensive analysis of selecting suitable suppliers, we know that two-sided matching and information aggregation can provide more research perspectives for smart complex equipment. Through analysis for relevant factors, we find that leading role and service level are also significant for the smart complex equipment development process.