Objective To explore the risk factors for postoperative respiratory failure (RF) in patients with esophageal cancer, construct a predictive model based on the least absolute shrinkage and selection operator (LASSO)-logistic regression, and visualize the constructed model. Methods A retrospective analysis was conducted on patients with esophageal cancer who underwent surgical treatment in the Department of Thoracic Surgery, Sun Yat-sen University Cancer Center Gansu Hospital from 2020 to 2023. Patients were divided into a RF group and a non-RF (NRF) group according to whether RF occurred after surgery. Clinical data of the two groups were collected, and LASSO-logistic regression was used to optimize feature selection and construct the predictive model. The model was internally validated by repeated sampling 1000 times based on the Bootstrap method. Results A total of 217 patients were included, among which 24 were in the RF group, including 22 males and 2 females, with an average age of (63.33±9.10) years; 193 were in the NRF group, including 161 males and 32 females, with an average age of (62.14±8.44) years. LASSO-logistic regression analysis showed that the percentage of forced expiratory volume in one second/forced vital capacity (FEV1/FVC) to predicted value (FEV1/FVC%pred) [OR=0.944, 95%CI (0.897, 0.993), P=0.026], postoperative anastomotic fistula [OR=4.106, 95%CI (1.457, 11.575), P=0.008], and postoperative lung infection [OR=3.776, 95%CI (1.373, 10.388), P=0.010] were risk factors for postoperative RF in patients with esophageal cancer. Based on the above risk factors, a predictive model was constructed, with an area under the receiver operating characteristic curve of 0.819 [95%CI (0.737, 0.901)]. The Hosmer-Lemeshow test for the calibration curve showed that the model had good goodness of fit (P=0.527). The decision curve showed that the model had good clinical net benefit when the threshold probability was between 5% and 50%. Conclusion FEV1/FVC%pred, postoperative anastomotic fistula, and postoperative lung infection are risk factors for postoperative RF in patients with esophageal cancer. The predictive model constructed based on LASSO-logistic regression analysis is expected to help medical staff screen high-risk patients for early individualized intervention.

Objective To construct a usability scale for smart hospital platforms based on Quality of Experience(QoE)theory,and provide scientific measurement tool for the construction,operation,and improvement of smart hospitals.Method Literature review,focus meeting method,and pre survey were used to screen and revise the scale items,forming a formal scale.Using convenience sampling method,1 000 users from 8 smart hospital platforms in Shandong Province were selected as the research subjects to evaluate the reliability and validity of the scale.Result The availability scale of the smart hospital platform includes 6 dimensions and 24 items.Exploratory factor extraction identified 6 common factors,with a cumulative variance contribution rate of 64.045%.The overall Cronbach's with a coefficient of 0.941 for 6 dimensions.The coefficient is between 0.782 and 0.963,and the retest reliability is 0.967.The Average Standardized Content Validity Index is 0.972,and the Item-level Content Validity Index is between 0.86 and 1.00.The correlation coefficient between the six dimensions of the scale and the System Usability Scale is 0.606-0.653,and the overall correlation coefficient is 0.647.Conclusion The usability scale of the smart hospital platform developed based on QoE theory has good reliability and validity,and can be used to measure the user experience of the smart hospital platform.

Objective To construct a usability scale for smart hospital platforms based on Quality of Experience(QoE)theory,and provide scientific measurement tool for the construction,operation,and improvement of smart hospitals.Method Literature review,focus meeting method,and pre survey were used to screen and revise the scale items,forming a formal scale.Using convenience sampling method,1 000 users from 8 smart hospital platforms in Shandong Province were selected as the research subjects to evaluate the reliability and validity of the scale.Result The availability scale of the smart hospital platform includes 6 dimensions and 24 items.Exploratory factor extraction identified 6 common factors,with a cumulative variance contribution rate of 64.045%.The overall Cronbach's with a coefficient of 0.941 for 6 dimensions.The coefficient is between 0.782 and 0.963,and the retest reliability is 0.967.The Average Standardized Content Validity Index is 0.972,and the Item-level Content Validity Index is between 0.86 and 1.00.The correlation coefficient between the six dimensions of the scale and the System Usability Scale is 0.606-0.653,and the overall correlation coefficient is 0.647.Conclusion The usability scale of the smart hospital platform developed based on QoE theory has good reliability and validity,and can be used to measure the user experience of the smart hospital platform.

Objective To construct a usability scale for smart hospital platforms based on Quality of Experience(QoE)theory,and provide scientific measurement tool for the construction,operation,and improvement of smart hospitals.Method Literature review,focus meeting method,and pre survey were used to screen and revise the scale items,forming a formal scale.Using convenience sampling method,1 000 users from 8 smart hospital platforms in Shandong Province were selected as the research subjects to evaluate the reliability and validity of the scale.Result The availability scale of the smart hospital platform includes 6 dimensions and 24 items.Exploratory factor extraction identified 6 common factors,with a cumulative variance contribution rate of 64.045%.The overall Cronbach's with a coefficient of 0.941 for 6 dimensions.The coefficient is between 0.782 and 0.963,and the retest reliability is 0.967.The Average Standardized Content Validity Index is 0.972,and the Item-level Content Validity Index is between 0.86 and 1.00.The correlation coefficient between the six dimensions of the scale and the System Usability Scale is 0.606-0.653,and the overall correlation coefficient is 0.647.Conclusion The usability scale of the smart hospital platform developed based on QoE theory has good reliability and validity,and can be used to measure the user experience of the smart hospital platform.

Objective To construct a usability scale for smart hospital platforms based on Quality of Experience(QoE)theory,and provide scientific measurement tool for the construction,operation,and improvement of smart hospitals.Method Literature review,focus meeting method,and pre survey were used to screen and revise the scale items,forming a formal scale.Using convenience sampling method,1 000 users from 8 smart hospital platforms in Shandong Province were selected as the research subjects to evaluate the reliability and validity of the scale.Result The availability scale of the smart hospital platform includes 6 dimensions and 24 items.Exploratory factor extraction identified 6 common factors,with a cumulative variance contribution rate of 64.045%.The overall Cronbach's with a coefficient of 0.941 for 6 dimensions.The coefficient is between 0.782 and 0.963,and the retest reliability is 0.967.The Average Standardized Content Validity Index is 0.972,and the Item-level Content Validity Index is between 0.86 and 1.00.The correlation coefficient between the six dimensions of the scale and the System Usability Scale is 0.606-0.653,and the overall correlation coefficient is 0.647.Conclusion The usability scale of the smart hospital platform developed based on QoE theory has good reliability and validity,and can be used to measure the user experience of the smart hospital platform.

Objective To construct a usability scale for smart hospital platforms based on Quality of Experience(QoE)theory,and provide scientific measurement tool for the construction,operation,and improvement of smart hospitals.Method Literature review,focus meeting method,and pre survey were used to screen and revise the scale items,forming a formal scale.Using convenience sampling method,1 000 users from 8 smart hospital platforms in Shandong Province were selected as the research subjects to evaluate the reliability and validity of the scale.Result The availability scale of the smart hospital platform includes 6 dimensions and 24 items.Exploratory factor extraction identified 6 common factors,with a cumulative variance contribution rate of 64.045%.The overall Cronbach's with a coefficient of 0.941 for 6 dimensions.The coefficient is between 0.782 and 0.963,and the retest reliability is 0.967.The Average Standardized Content Validity Index is 0.972,and the Item-level Content Validity Index is between 0.86 and 1.00.The correlation coefficient between the six dimensions of the scale and the System Usability Scale is 0.606-0.653,and the overall correlation coefficient is 0.647.Conclusion The usability scale of the smart hospital platform developed based on QoE theory has good reliability and validity,and can be used to measure the user experience of the smart hospital platform.

Objective To construct a usability scale for smart hospital platforms based on Quality of Experience(QoE)theory,and provide scientific measurement tool for the construction,operation,and improvement of smart hospitals.Method Literature review,focus meeting method,and pre survey were used to screen and revise the scale items,forming a formal scale.Using convenience sampling method,1 000 users from 8 smart hospital platforms in Shandong Province were selected as the research subjects to evaluate the reliability and validity of the scale.Result The availability scale of the smart hospital platform includes 6 dimensions and 24 items.Exploratory factor extraction identified 6 common factors,with a cumulative variance contribution rate of 64.045%.The overall Cronbach's with a coefficient of 0.941 for 6 dimensions.The coefficient is between 0.782 and 0.963,and the retest reliability is 0.967.The Average Standardized Content Validity Index is 0.972,and the Item-level Content Validity Index is between 0.86 and 1.00.The correlation coefficient between the six dimensions of the scale and the System Usability Scale is 0.606-0.653,and the overall correlation coefficient is 0.647.Conclusion The usability scale of the smart hospital platform developed based on QoE theory has good reliability and validity,and can be used to measure the user experience of the smart hospital platform.

Objective To construct a usability scale for smart hospital platforms based on Quality of Experience(QoE)theory,and provide scientific measurement tool for the construction,operation,and improvement of smart hospitals.Method Literature review,focus meeting method,and pre survey were used to screen and revise the scale items,forming a formal scale.Using convenience sampling method,1 000 users from 8 smart hospital platforms in Shandong Province were selected as the research subjects to evaluate the reliability and validity of the scale.Result The availability scale of the smart hospital platform includes 6 dimensions and 24 items.Exploratory factor extraction identified 6 common factors,with a cumulative variance contribution rate of 64.045%.The overall Cronbach's with a coefficient of 0.941 for 6 dimensions.The coefficient is between 0.782 and 0.963,and the retest reliability is 0.967.The Average Standardized Content Validity Index is 0.972,and the Item-level Content Validity Index is between 0.86 and 1.00.The correlation coefficient between the six dimensions of the scale and the System Usability Scale is 0.606-0.653,and the overall correlation coefficient is 0.647.Conclusion The usability scale of the smart hospital platform developed based on QoE theory has good reliability and validity,and can be used to measure the user experience of the smart hospital platform.

Objective To construct a usability scale for smart hospital platforms based on Quality of Experience(QoE)theory,and provide scientific measurement tool for the construction,operation,and improvement of smart hospitals.Method Literature review,focus meeting method,and pre survey were used to screen and revise the scale items,forming a formal scale.Using convenience sampling method,1 000 users from 8 smart hospital platforms in Shandong Province were selected as the research subjects to evaluate the reliability and validity of the scale.Result The availability scale of the smart hospital platform includes 6 dimensions and 24 items.Exploratory factor extraction identified 6 common factors,with a cumulative variance contribution rate of 64.045%.The overall Cronbach's with a coefficient of 0.941 for 6 dimensions.The coefficient is between 0.782 and 0.963,and the retest reliability is 0.967.The Average Standardized Content Validity Index is 0.972,and the Item-level Content Validity Index is between 0.86 and 1.00.The correlation coefficient between the six dimensions of the scale and the System Usability Scale is 0.606-0.653,and the overall correlation coefficient is 0.647.Conclusion The usability scale of the smart hospital platform developed based on QoE theory has good reliability and validity,and can be used to measure the user experience of the smart hospital platform.

Objective:To gain a deeper understanding of the fear of recurrence in patients with atrial fibrillation during the "blanking period" after catheter ablation.Methods:The interview outline was developed based on common-sense model of self-regulated. From July to September 2023, purposive sampling was used to select 15 patients with atrial fibrillation in the "blanking period" after catheter ablation at the Cardiovascular Outpatient of the Affiliated Hospital of Qingdao University as research subjects, and semi-structured interviews were conducted. The targeted content analysis method was used to analyze data.Results:Four themes were extracted, namely triggering factors of fear of recurrence, perception of atrial fibrillation recurrence, negative emotional distress, and insufficient ability to cope with atrial fibrillation recurrence.Conclusions:For patients with atrial fibrillation during the "blanking period" after catheter ablation, medical and nursing staff should closely monitor the patient's cognitive level and psychological state, and carry out targeted health education to meet the patient's needs for postoperative disease management, life adaptation, and other aspects, so as to reduce the fear of recurrence in atrial fibrillation patients during the "blanking period" after surgery.