Objective To explore the potential profiles of symptom burden among stroke patients and to analyze the differences in the characteristics of different classes of stroke patients,providing references for clinical nursing practice.Methods A convenience sampling method was used to select 485 stroke patients treated at 4 tertiary-level general hospitals in Anhui Province from July to December 2024 as the study population.The general information questionnaire,Stroke Symptom Cluster Scale,Personal Mastery Scale,and Cognitive Reserve Index questionnaire.Latent profile analysis was employed to explore the categories of symptom burden among stroke patients,and multiple logistic regression was used to assess the influence factors of each category.Results A total of 456 valid questionnaires were collected,with a valid response rate of 94.02％.Symptom burden among stroke patients can be divided into 4 latent profiles:low symptom burden group(69.08％),multiple symptom burden group(8.12％),moderate burden-physical activity impairment group(11.18％),and moderate burden-emotional and cognitive language impairment group(11.62％).The patient's age,number of stroke episodes,number of chronic diseases,systemic inflammation response index,personal mastery,and cognitive reserve were the factors influencing the latent profiles of symptom burden in stroke patients(P＜0.05).Conclusion The symptom burden of stroke patients shows significant heterogeneity.Medical staff can develop targeted nursing interventions based on the category characteristics and influencing factors of the symptom burden in stroke patients.

Objective:To investigate the current status of subjective well-being among stroke patients, and to explore the pathways and effects of influencing factors using structural equation model, so as to provide reference for improving subjective well-being among stroke patients.Methods:From July to November 2024, the stroke patients admitted to the First Affiliated Hospital of Bengbu Medical University, the Second Affiliated Hospital of Bengbu Medical University, Hefei First People′s Hospital were selected by convenience sampling method. A cross-sectional survey was conducted using a general demographic questionnaire, General Well-Being Scale, Cognitive Reserve Index questionnaire, Social Support Rating Scale, Stroke Symptom Cluster Scale, and FRAIL Scale, and AMOS 26.0 was used to analyse the pathways and effects of influencing factors of subjective well-being.Results:A total of 435 questionnaires were collected, 410 were valid.Among 410 cases, 266 case were males, 144 were females, with an age of (65.96 ± 12.15) years. The subjective well-being scores of stroke patients were (72.58 ± 11.66) points. Cognitive reserve and social support were positively correlated with subjective well-being ( r = 0.517, 0.554, both P<0.01), while symptom burden and frailty were negatively correlated with subjective well-being ( r = -0.687, -0.670, both P<0.01). Path analysis showed that symptom burden, frailty, cognitive reserve, and social support had a direct impact on subjective well-being (path coefficients were -0.500, -0.266, 0.148, and 0.144, respectively, all P<0.05), while cognitive reserve, social support, and symptom burden had an indirect impact on subjective well-being (path coefficients were 0.287, 0.249, and 0.108, respectively, all P<0.05). Conclusions:The subjective well-being of stroke patients is influenced by multiple factors, with symptom burden being an important factor affecting subjective well-being. Intervention strategies such as improving cognitive reserve, strengthening social support systems, and preventing frailty can improve the subjective well-being of patients.

Objective To explore the potential profiles of symptom burden among stroke patients and to analyze the differences in the characteristics of different classes of stroke patients,providing references for clinical nursing practice.Methods A convenience sampling method was used to select 485 stroke patients treated at 4 tertiary-level general hospitals in Anhui Province from July to December 2024 as the study population.The general information questionnaire,Stroke Symptom Cluster Scale,Personal Mastery Scale,and Cognitive Reserve Index questionnaire.Latent profile analysis was employed to explore the categories of symptom burden among stroke patients,and multiple logistic regression was used to assess the influence factors of each category.Results A total of 456 valid questionnaires were collected,with a valid response rate of 94.02％.Symptom burden among stroke patients can be divided into 4 latent profiles:low symptom burden group(69.08％),multiple symptom burden group(8.12％),moderate burden-physical activity impairment group(11.18％),and moderate burden-emotional and cognitive language impairment group(11.62％).The patient's age,number of stroke episodes,number of chronic diseases,systemic inflammation response index,personal mastery,and cognitive reserve were the factors influencing the latent profiles of symptom burden in stroke patients(P＜0.05).Conclusion The symptom burden of stroke patients shows significant heterogeneity.Medical staff can develop targeted nursing interventions based on the category characteristics and influencing factors of the symptom burden in stroke patients.

Objective:To investigate the current status of subjective well-being among stroke patients, and to explore the pathways and effects of influencing factors using structural equation model, so as to provide reference for improving subjective well-being among stroke patients.Methods:From July to November 2024, the stroke patients admitted to the First Affiliated Hospital of Bengbu Medical University, the Second Affiliated Hospital of Bengbu Medical University, Hefei First People′s Hospital were selected by convenience sampling method. A cross-sectional survey was conducted using a general demographic questionnaire, General Well-Being Scale, Cognitive Reserve Index questionnaire, Social Support Rating Scale, Stroke Symptom Cluster Scale, and FRAIL Scale, and AMOS 26.0 was used to analyse the pathways and effects of influencing factors of subjective well-being.Results:A total of 435 questionnaires were collected, 410 were valid.Among 410 cases, 266 case were males, 144 were females, with an age of (65.96 ± 12.15) years. The subjective well-being scores of stroke patients were (72.58 ± 11.66) points. Cognitive reserve and social support were positively correlated with subjective well-being ( r = 0.517, 0.554, both P<0.01), while symptom burden and frailty were negatively correlated with subjective well-being ( r = -0.687, -0.670, both P<0.01). Path analysis showed that symptom burden, frailty, cognitive reserve, and social support had a direct impact on subjective well-being (path coefficients were -0.500, -0.266, 0.148, and 0.144, respectively, all P<0.05), while cognitive reserve, social support, and symptom burden had an indirect impact on subjective well-being (path coefficients were 0.287, 0.249, and 0.108, respectively, all P<0.05). Conclusions:The subjective well-being of stroke patients is influenced by multiple factors, with symptom burden being an important factor affecting subjective well-being. Intervention strategies such as improving cognitive reserve, strengthening social support systems, and preventing frailty can improve the subjective well-being of patients.

Objective:To construct a quality evaluation index system for nursing simulation teaching, and determine the weight of each index.Methods:The research team was established on January 1, 2018. The first draft of the quality evaluation index system for nursing simulation teaching was constructed based on extensive literature and Jeffries simulation theory model. The Delphi method was used to conduct 2 rounds of consultation with 27 experts. We calculated the experts' active coefficient, authority coefficient, Kendall harmony coefficient and the concentration degree of opinion. The analytic hierarchy process was used to determine the weight of each index in the index system.Results:The effective questionnaire response rates for the 2 rounds of expert consultation were 96.30% and 100.00%, and the expert authority coefficient was 0.89. The Kendall harmony coefficients of the second and third levels in the second round of expert consultation were 0.515 and 0.589 respectively, and the difference was statistically significant ( P<0.01) . The final quality evaluation index system for nursing simulation teaching included 5 first-level indicators, 14 second-level indicators and 62 third-level indicators. Conclusions:The weight distribution of the quality evaluation index system for nursing simulation teaching is scientific and reliable. This system has guiding significance for high-quality nursing simulation teaching and is an effective tool for evaluating the quality of nursing simulation teaching.

Objective To perform theory construction and empirical study of the competency model of rural general practitioners. Methods Through literature study, job analysis, interviews, and expert team discussion, the questionnaire of rural general practitioners competency was constructed. A total of 1458 rural general practitioners were surveyed by the questionnaire in 6 central provinces. The common factors were constructed using the principal component method of exploratory factor analysis and confirmatory factor analysis. The influence of the competency characteristics on the working performance was analyzed using regression equation analysis. Results The Cronbach 's alpha coefficient of the questionnaire was 0.974. The model consisted of 9 dimensions and 59 items. The 9 competency dimensions included basic public health service ability, basic clinical skills, system analysis capability, information management capability, communication and cooperation ability, occupational moral ability, non- medical professional knowledge, personal traits and psychological adaptability. The rate of explained cumulative total variance was 76.855%. The model fitting index were X2/df 1.88, GFI=0.94, NFI=0.96, NNFI=0.98, PNFI=0.91, RMSEA=0.068, CFI=0.97, IFI=0.97, RFI=0.96, suggesting good model fitting. Regression analysis showed that the competency characteristics had a significant effect on job performance. Conclusion The rural general practitioners competency model provides reference for rural doctor training, rural order directional cultivation of medical students, and competency performance management of the rural general practitioners.

Objective To perform theory construction and empirical study of the competency model of rural general practitioners. Methods Through literature study, job analysis, interviews, and expert team discussion, the questionnaire of rural general practitioners competency was constructed. A total of 1458 rural general practitioners were surveyed by the questionnaire in 6 central provinces. The common factors were constructed using the principal component method of exploratory factor analysis and confirmatory factor analysis. The influence of the competency characteristics on the working performance was analyzed using regression equation analysis. Results The Cronbach 's alpha coefficient of the questionnaire was 0.974. The model consisted of 9 dimensions and 59 items. The 9 competency dimensions included basic public health service ability, basic clinical skills, system analysis capability, information management capability, communication and cooperation ability, occupational moral ability, non- medical professional knowledge, personal traits and psychological adaptability. The rate of explained cumulative total variance was 76.855%. The model fitting index were X2/df 1.88, GFI=0.94, NFI=0.96, NNFI=0.98, PNFI=0.91, RMSEA=0.068, CFI=0.97, IFI=0.97, RFI=0.96, suggesting good model fitting. Regression analysis showed that the competency characteristics had a significant effect on job performance. Conclusion The rural general practitioners competency model provides reference for rural doctor training, rural order directional cultivation of medical students, and competency performance management of the rural general practitioners.