Objective: To analyze the consumption frequency of major foods among Chinese children aged 6-17 years old, and to provide a basis for optimizing the dietary structure of children in China. Methods: Using data from the China Nutrition and Health System Survey and Application Program for Children 0-18 years old, 56 734 children aged 6-17 years old from North, Norththeast East, Central, South, Southwest and Northwest seven regions in China were selected for the study using stratified cluster random sampling from 2019 to 2021. A food frequency questionnaire was used to investigate the intake frequency of eight food groups in a month, including fresh vegetables, fresh fruits, livestock and poultry meats, aquatic products, eggs, dairy products, legumes, and cereals and potatoes. The foods were grouped according to whether they met the recommended intake criteria outlined in the Dietary Guidelines for Chinese Residents 2022. The〖KG*2〗χ2 test was used to compare the differences in the proportion of childrens intake frequency of each food group meeting the standard in different regions and age groups. Results: The proportions of Chinese children aged 6-17 years who consumed fresh vegetables and cereals and potatoes ≥3 times/d were 12.1% and 67.2%, respectively. The proportions of children who consumed fresh fruits, livestock and poultry meats, eggs and dairy products ≥1 time/d were 50.8%, 58.8%, 36.0% and 54.3%, respectively. The proportion of legumes consumed ≥4 times/week was 37.4%, and the proportion of aquatic products consumed ≥2 times/week was 39.7%. Fresh vegetables (5.5%), fresh fruits (33.1%), and dairy products (36.4%) had the lowest frequency of meeting the recommended standards in South China, and aquatic products (27.4%) and eggs (21.1%) had the lowest frequency of meeting the recommended standards in Northwest (P<0.008 3). Conclusion The overall intake frequency of fresh vegetables, fresh fruits, legumes, and dairy products are insufficient among Chinese children, with significant regional variations.

Objective:To evaluate the efficacy and safety of oliceridine for treatment of moderate to severe pain after surgery with general anesthesia in patients.Methods:The patients with moderate to severe pain (numeric pain rating scale ≥4) after abdominal surgery with general anesthesia from 14 hospitals between July 6, 2021 and November 9, 2021 were included in this study. The patients were assigned to either experiment group or control group using a random number table method. Experiment group received oliceridine, while control group received morphine, and both groups were treated with a loading dose plus patient-controlled analgesia and supplemental doses for 24 h. The primary efficacy endpoint was the drug response rate within 24 h after giving the loading dose. Secondary efficacy endpoints included early (within 1 h after giving the loading dose) drug response rates and use of rescue medication. Safety endpoints encompassed the development of respiratory depression and other adverse reactions during treatment.Results:After randomization, both the full analysis set and safety analysis set comprised 180 cases, with 92 in experiment group and 88 in control group. The per-protocol set included 170 cases, with 86 in experiment group and 84 in control group. There were no statistically significant differences between the two groups in 24-h drug response rates, rescue analgesia rates, respiratory depression, and incidence of other adverse reactions ( P>0.05). The analysis of full analysis set showed that the experiment group had a higher drug response rate at 5-30 min after giving the loading dose compared to control group ( P<0.05). The per-protocol set analysis indicated that experiment group had a higher drug response rate at 5-15 min after giving the loading dose than control group ( P<0.05). Conclusions:When used for treatment of moderate to severe pain after surgery with general anesthesia in patients, oliceridine provides comparable analgesic efficacy to morphine, with a faster onset.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.

Objective To explore the doctor's willingness to adopt artificial intelligence aided diagnosis and treatment system(ADTS)and its influencing factors,clarify the key links in the implementation of ADTS,and then propose suggestions for optimizing technology and management.Methods On the basis of UTAUT model,factors such as perceived risk,cognitive trust and legal supervision were added to design a questionnaire.After pre-investigation,226 officially recovered questionnaire data were analyzed for reliability and validity,hypothesis testing and SEM fitting,and the relationship chain model of doctors'ADTS adoption intention was obtained.Results Performance expectation,cognitive trust and social influence have a direct positive impact on doctors'willingness,among which social influence has the greatest effect.Facilitating conditions and legal supervision have indirect influence.It also found that doctors who have used ADTS have higher scores in various aspects such as performance expectations,effort expectations,and learning adaptability.Conclusion To implement the application of ADTS,attention should be paid to training,the software and hardware operation and maintenance system,and risk responsibility regulations should be improved,requiring joint efforts from multiple parties.