Objective:To adapt the Interdependent Happiness Scale(IHS)into Chinese(IHS-C)version and evaluate its validity and reliability.Methods:Item analysis and exploratory factor analysis(EFA)were conducted on data from 500 adults collected via Credamo.Confirmatory factor analysis(CFA)and multi-group measurement invariance tests were performed on an additional 600 adults.The Simplified Chinese versions of the Depression-Anxiety-Stress Scale(DASS-21),Satisfaction with Life Scale(SWLS),and Flourishing Scale(FS)were used to assess criterion validity and incremental validity.Furthermore,test-retest reliability over a four-week interval was examined in a sample of 245 adults,collected through three university-wide elective courses and two WeChat groups.Internal consistency was assessed with the total sample(n=1 345).Results:EFA revealed a single common factor,explaining 53.80％of the variance,with factor loadings of the items ranging from 0.63 to 0.84.CFA indi-cated a good fit for the one-factor model(x2/df=1.97,CFI=0.99,TLI=0.98,SRMR=0.03,RMSEA=0.04).The scale demonstrated measurement invariance across gender and identity groups(ΔCFI ≤ 0.01,ΔRMSEA 0.015).The scores of IHS-C were negatively correlated with DASS-21 subscale scores(r=-0.65,-0.48,-0.58,Ps＜0.001)and positively correlated with SWLS scores(r=0.82,P＜0.001)and FS scores(r=0.84,P＜0.001).The Cronbach α for IHS-C was 0.89,and the test-retest reliability was 0.73.Conclusion:The Chinese version of the Interdependent Happiness Scale(IHS-C)is a valid and reliable tool for assessing happiness in adults.

Objective:To observe the effectiveness and safety of the application of Wei nasal jet tube(WNJT)in anesthesia induction for patients with extensive facial burns.Methods:A total of 60 patients who underwent multiple systemic scab removal and skin graft-ing surgery in our hospital from July 2021 to July 2023 were enrolled in this study.The patients were 18-60 years of age,with a body mass index of 18-29 kg/m2,ASA II or III,and Mallampati I-III.Using a random number table method,the patients were divided into WNJT ventilation group(W group)and mask ventilation group(M group),with 30 cases in each group.Before anesthesia induction,WNJT was inserted into one side of the nasal cavity for hand controlled normal frequency supraglottic jet ventilation in group W pa-tients,while oxygen ventilation was administered to group M patients through conventional two-hand clasped face masks.After 5 min,tracheal intubation was performed under a visual laryngoscope.The mean amplitude of diaphragm fluctuations,end expiratory carbon dioxide partial pressure(PETCO2),and blood oxygen saturation(SpO2)measured by ultrasound were recorded during spontaneous respi-ration at 5 min of oxygenation and nitrogen removal(T0),as well as at 1 min(T1),2 min(T2),3 min(T3),4 min(T4),and 5 min(T5,im-mediately before intubation)of anesthetic induction.Arterial blood gas(PaO2 and PaCO2)at T0 and T5 were measured.Heart rate(HR)and mean arterial pressure(MAP)were recorded at T0-T5 in both groups of patients.The occurrence of postoperative pharyngeal pain,facial or mandibular angle bleeding,gastrointestinal bloating,and nasal mucosal bleeding were recorded in both groups of pa-tients.Results:At T0,there were no statistically significant differences in mean amplitude of diaphragm fluctuations,HR,MAP,PaO2,PaCO2,PETCO2,and SpO2 between the two groups of patients.At T1-T5,the HR and MAP of patients in the W group were significantly lower than those in the M group(P<0.05).At T5,the PaO2 of patients in the W group was significantly higher than that in the M group,while the PaCO2 and PETCO2 were significantly lower than those in the M group(P<0.05).However,the difference in SpO2 was not sta-tistically significant.The W group had less facial or mandibular angle bleeding and postoperative gastrointestinal bloating than the M group,and the differences were statistically significant(P<0.05).There were no statistically significant differences between the two groups of patients in postoperative pharyngitis and nasal mucosal bleeding(P>0.05).Conclusion:During general anesthesia induction in patients with extensive facial burns,WNJT has the advantages of good ventilation effect,high safety,less complications such as gas-trointestinal bloating and facial or mandibular angle bleeding,and more stable hemodynamics.WNJT has good application prospects in clinical anesthesia.

Objective:To investigate the knowledge, attitudes, practices (KAP), and demands of medical staff in family physician teams regarding the application of artificial intelligence (AI) in contracted services, and to analyze the influencing factors.Methods:A cross-sectional study was conducted from June to July 2023. A total of 602 medical staff members from family physician teams in Shanghai Minhang District were selected as subjects. Data on demographics (age, gender, institution, position, education, work experience, household registration, professional title, marital status, fertility status) and KAP/demand regarding AI application in contracted services were collected using a self-designed questionnaire. Intergroup differences were analyzed. Multiple stepwise linear regression was employed to identify the main factors influencing AI application demand.Results:Among the 602 participants, 484 (80.4%) were aged 30-49 years, 466 (77.40%) were females, 559 (92.9%) held a bachelor′s degree or higher, and 505 (83.9%) had intermediate or senior professional titles. The awareness rate for knowledge, positive attitude rate, and practice implementation rate regarding AI application were 47.2% (284/602), 73.1% (440/602), and 32.1% (193/602), respectively. The mean scores for knowledge, attitude, and practice were 15.72±3.40, 18.34±3.41, and 14.60±3.89, respectively. Significant differences were found among the items within each KAP dimension (knowledge: F=7.688, P<0.001; attitude: F=5.106, P<0.001; practice: F=6.763, P<0.001). Within knowledge, item K3 (awareness of intelligent elderly monitoring devices) scored lowest (3.00±0.79), differing significantly from K1, K2, K4, and K5 (all P<0.05). Within attitude, item A5 (willingness to fully trust AI′s accuracy and convenience in contracted services) scored lowest (3.57±0.75), differing significantly from A3 and A4 (all P<0.05). Within practice, item P3 (increasing reliance on AI in daily contracted services) scored lowest (2.79±0.93), differing significantly from P1 and P2 (all P<0.05). KAP scores differed significantly across demographic subgroups. Knowledge scores differed significantly by age, gender, and marital status (all P<0.05). Attitude scores differed significantly by gender, household registration, and fertility status (all P<0.05). Practice scores differed significantly by gender, position, and marital status (all P<0.05). Regarding demand, the most frequently selected areas were follow-up services (28.74%, 173/602), data management (26.25%, 158/602), and data collection (25.42%, 153/602). Univariate analysis identified age, gender, education, professional title, fertility status, and KAP scores as significant factors influencing AI application demand (all P<0.05). Multiple stepwise linear regression revealed that older age ( t=3.905, P<0.001), female gender ( t=3.548, P<0.001), and higher practice scores ( t=-3.044, P=0.002) were significant predictors of greater AI application demand. Conclusions:Significant variations exist in the KAP levels regarding AI application among family physician team members. Gender, age, and practice behavior significantly influence demand. Tailored strategies for different subgroups, coupled with timely targeted training and practical exercises, are recommended to enhance the effective and widespread adoption of AI technology in family physician contracted services.

Objective:To adapt the Interdependent Happiness Scale(IHS)into Chinese(IHS-C)version and evaluate its validity and reliability.Methods:Item analysis and exploratory factor analysis(EFA)were conducted on data from 500 adults collected via Credamo.Confirmatory factor analysis(CFA)and multi-group measurement invariance tests were performed on an additional 600 adults.The Simplified Chinese versions of the Depression-Anxiety-Stress Scale(DASS-21),Satisfaction with Life Scale(SWLS),and Flourishing Scale(FS)were used to assess criterion validity and incremental validity.Furthermore,test-retest reliability over a four-week interval was examined in a sample of 245 adults,collected through three university-wide elective courses and two WeChat groups.Internal consistency was assessed with the total sample(n=1 345).Results:EFA revealed a single common factor,explaining 53.80％of the variance,with factor loadings of the items ranging from 0.63 to 0.84.CFA indi-cated a good fit for the one-factor model(x2/df=1.97,CFI=0.99,TLI=0.98,SRMR=0.03,RMSEA=0.04).The scale demonstrated measurement invariance across gender and identity groups(ΔCFI ≤ 0.01,ΔRMSEA 0.015).The scores of IHS-C were negatively correlated with DASS-21 subscale scores(r=-0.65,-0.48,-0.58,Ps＜0.001)and positively correlated with SWLS scores(r=0.82,P＜0.001)and FS scores(r=0.84,P＜0.001).The Cronbach α for IHS-C was 0.89,and the test-retest reliability was 0.73.Conclusion:The Chinese version of the Interdependent Happiness Scale(IHS-C)is a valid and reliable tool for assessing happiness in adults.

Objective:To investigate the knowledge, attitudes, practices (KAP), and demands of medical staff in family physician teams regarding the application of artificial intelligence (AI) in contracted services, and to analyze the influencing factors.Methods:A cross-sectional study was conducted from June to July 2023. A total of 602 medical staff members from family physician teams in Shanghai Minhang District were selected as subjects. Data on demographics (age, gender, institution, position, education, work experience, household registration, professional title, marital status, fertility status) and KAP/demand regarding AI application in contracted services were collected using a self-designed questionnaire. Intergroup differences were analyzed. Multiple stepwise linear regression was employed to identify the main factors influencing AI application demand.Results:Among the 602 participants, 484 (80.4%) were aged 30-49 years, 466 (77.40%) were females, 559 (92.9%) held a bachelor′s degree or higher, and 505 (83.9%) had intermediate or senior professional titles. The awareness rate for knowledge, positive attitude rate, and practice implementation rate regarding AI application were 47.2% (284/602), 73.1% (440/602), and 32.1% (193/602), respectively. The mean scores for knowledge, attitude, and practice were 15.72±3.40, 18.34±3.41, and 14.60±3.89, respectively. Significant differences were found among the items within each KAP dimension (knowledge: F=7.688, P<0.001; attitude: F=5.106, P<0.001; practice: F=6.763, P<0.001). Within knowledge, item K3 (awareness of intelligent elderly monitoring devices) scored lowest (3.00±0.79), differing significantly from K1, K2, K4, and K5 (all P<0.05). Within attitude, item A5 (willingness to fully trust AI′s accuracy and convenience in contracted services) scored lowest (3.57±0.75), differing significantly from A3 and A4 (all P<0.05). Within practice, item P3 (increasing reliance on AI in daily contracted services) scored lowest (2.79±0.93), differing significantly from P1 and P2 (all P<0.05). KAP scores differed significantly across demographic subgroups. Knowledge scores differed significantly by age, gender, and marital status (all P<0.05). Attitude scores differed significantly by gender, household registration, and fertility status (all P<0.05). Practice scores differed significantly by gender, position, and marital status (all P<0.05). Regarding demand, the most frequently selected areas were follow-up services (28.74%, 173/602), data management (26.25%, 158/602), and data collection (25.42%, 153/602). Univariate analysis identified age, gender, education, professional title, fertility status, and KAP scores as significant factors influencing AI application demand (all P<0.05). Multiple stepwise linear regression revealed that older age ( t=3.905, P<0.001), female gender ( t=3.548, P<0.001), and higher practice scores ( t=-3.044, P=0.002) were significant predictors of greater AI application demand. Conclusions:Significant variations exist in the KAP levels regarding AI application among family physician team members. Gender, age, and practice behavior significantly influence demand. Tailored strategies for different subgroups, coupled with timely targeted training and practical exercises, are recommended to enhance the effective and widespread adoption of AI technology in family physician contracted services.