Objective To observe the effect of 5G enabled intelligent virtual reality(VR)technology in the intervention of patients with delirium in intensive care unit(ICU),and to provide theoretical reference for the development of delirium prevention and management measures in ICU.Methods A total of 84 cases of critically ill patients admitted to the ICU of Zhejiang Cancer Hospital from October 2022 to October 2023 were selected as the study objects.All patients were divided into control group and experimental group according to different intervention methods,with 42 cases in each group.The patients in the control group received routine sedation and analgesia intervention,while the patients in the experimental group received intervention based on 5G enabled intelligent VR.The self-rating anxiety scale(SAS)was used to assess patients' anxiety.The Sleep quality of ICU patients was assessed by Richards-Campbell sleep questionnaire(RCSQ).The confusion assessment method(CAM)was used to assess the degree of delirium in ICU patients.The differences of SAS score,RCSQ score(sleep depth score,sleep difficulty score,wake frequency score,sleep back difficulty score,overall sleep quality score)and CAM score between the two groups were compared.Results Before intervention,there were no significant differences in SAS score,RCSQ score(sleep depth score,sleep difficulty score,wake frequency score,sleep back difficulty score,overall sleep quality score)and CAM score between the two groups(all P>0.05).After intervention,the SAS scores and CAM scores in both groups were significantly lower than before intervention,after the intervention,the changes of SAS score and CAM score of the experimental group were more obvious than those of the control group(SAS score:32.36±3.74 vs.52.29±4.14,CAM score:2.25±0.44 vs.6.37±1.05,both P<0.05).After the intervention,RCSQ scores of the experimental group(sleep depth scores,sleep difficulty scores,wake frequency scores,sleep back difficulty score,and overall sleep quality scores)were significantly higher than the control group(sleep depth score:17.13±2.01 vs.10.09±1.14,sleep difficulty score:17.89±1.78 vs.9.45±1.22,wake frequency score:18.20±1.58 vs.10.66±1.09,sleep back difficulty score:17.92±1.83 vs.11.51±1.55,overall sleep quality score:18.45±1.41 vs.10.24±1.18,all P<0.05).Conclusion 5G enabled intelligent VR technology can alleviate anxiety,improve sleep quality and relieve delirium in ICU patients,which is worthy of clinical promotion.

Objective To investigate the teaching effects of flipped class model on the Surgery Intensive Care Unit (SICU) nurses' ability of autonomic learning. Methods From July to December 2015, a total of 38 nurses who worked in SICU of Zhejiang Cancer Hospital were selected as the research objects by convenience sampling method. The nurses were trained in postoperative pain management knowledge by flipped class model, and were evaluated before and after the training by rating scale of self-directed learning competence for nurses. Results The total score of rating scale of self-directed learning competence for nurses, self motivation belief, task analysis, self monitoring and regulation, self evaluation were (128.26±18.69), (54.50±7.65), (22.05±3.66), (37.57±5.82) and (14.13±2.67) after the training, which all improved than (108.89±15.71), (47.18±6.61), (18.03±3.33), (31.37±5.24) and (12.32±2.14) respectively before training. The differences were statistically significant (t=-4.889, -4.460, -5.013, -4.883, -3.266; P<0.05). Conclusions Flipped class teaching model improves nurses' autonomous learning ability comprehensively and provide a new teaching mode for nurses' training.