Objective:To explore the interaction effectiveness of residence and social support on physical function for older adults.Methods:Using multistage sampling method, the older adults in 9 provinces were chosen to investigate from January 2022 to January 2023 by using general information questionnaire and Short Physical Performance Battery.Binary Logistic regression analysis was used to explore the independent effectiveness of social support and residence category on physical function.The additive and multiplicative models were used to analyze the interactions between above two factors.Results:A total of 23 922 older adults were investigated.And 18 719(78.3%)older adults had poor physical function.There were significant independent effect of social support and residence category on physical function of older adults( P<0.001). Besides, the results showed that residence category and social support had a significant multiplicative interaction on physical function( OR=0.763, 95% CI: 0.615-0.947, P=0.014). The crossover analysis showed that older adults living in rural as well as lack of social support had the highest probability of impaired physical function( OR=1.521, 95% CI: 1.308-1.769, P<0.001). But there was no difference found in additive interaction. Conclusions:An interaction effect was found in rural living and lack of social support.Older adults living in rural as well as lack of social support have a higher risk of impaired physical function.

Objective:To explore the latent classes of doctors′ behaviors in the process of shared decision-making between doctors and patients, and analyze the influencing factors for the latent classes.Methods:From August to September 2023, doctors from 4 tertiary hospitals in Dongcheng district, Beijing were selected using convenience sampling method. The general information questionnaire, shared decision making questionnaire-physician version(SDM-Q-Doc), doctor patient relationship questionnaire, the Jefferson scale of empathy health professionals, physician trust in the patient scale were administered to the participants. Latent profile analysis was performed based on the items of SDM-Q-Doc. The ordinal logistic regression analysis was conducted to explore the influencing factors of the latent classes of shared decision making.Results:A total of 480 doctors were included in the study. The results of latent profile analysis showed that doctors could be classified into 3 subgroups by shared decision making, namely shared decision missing group(17.3%, 83/480), collective balance deficiency group(52.5%, 252/480), and shared decision making group(30.2%, 145/480). The results of ordinal logistic regression analysis showed that career development opportunity( OR=0.509, 95% CI: 0.269-0.965, P=0.038), working years( OR=1.103, 95% CI: 1.016-1.196, P=0.019), empathic ability( OR=1.096, 95% CI: 1.079-1.113, P<0.001) and doctor-patient trust( OR=1.053, 95% CI: 1.027-1.080, P<0.001) were independent influencing factors of doctors′ shared decision making. Conclusions:The shared decision making of doctors showed significant population heterogeneity. Longer working years, sufficient career opportunities, high empathy ability and strong doctor-patient trust could enhance shared decision making behavior of the doctors. Intervention can be planned based on above factors from the perspectives of hospital managers and doctors in the future.