Objective To investigate the risk factors of cognitive impairment in post-intensive care syndrome patient (PICS-CI).Methods A retrospective study was conducted. The patient who transferred from post-intensive care unit (ICU) to the general ward for more than 7 days, and with the age ≥ 18 years old in the First Affiliated Hospital of Jinzhou Medical University from October 2015 to November 2016 were enrolled. The gender, age, marital status, education, occupation, salary, economic income, smoking, alcohol drinking, previous of history, mechanical ventilation, the length of ICU stay, sedative and delirium, and initial diagnosis were recorded. According to mini-mental state examination (MMSE), the patients were divided into cognitive impairment (CI) group and non-CI group. Univariate analysis was performed to identify the risk factors of PICS-CI, and variables with statistical difference were selected to do multivariate binary logistic regression analysis for the confirmable independence risk factors.Results 104 of the 290 patients developed CI, and the incidence was 35.86%. Univariate analysis showed that the gender, age, education, financial situation, smoking, alcohol drinking, previous of history, mechanical ventilation, the length of ICU stay, sedative and delirium, and initial diagnosis were recorded of ICU were main predictors of PICS-CI patients. It was shown by multivariate binary logistic regression analysis that the age > 60 years old [odds ratio (OR) = 7.523, 95% confidence interval (95%CI) = 2.572-37.851,P = 0.001], mechanical ventilation (OR = 8.773, 95%CI = 2.588-36.344,P < 0.001), sedation (OR = 9.376, 95%CI = 2.661-42.011,P = 0.002), and delirium (OR = 13.201, 95%CI = 2.502-41.433, P < 0.001) were PICS-CI independence risk factors.Conclusions Nurse staffs should strength care and attention on ICU transferred out patients. In order to minimize PICS impairment, special precaution should be implemented according to different aspects.

The negative experience such as burden and positive experience such as benefits may engender in caregivers in the process of caring for stroke patients,which present both mutual independence and coexistence.Negative experience was paid more attention,but positive experience received less.The article analyzed the current situation of assessment in care burden of stroke patients' caregivers,summarized the shortcomings,made suggestions.Based on these summaries,the care benefits were suggested to do research on three levels (individual,family and social).

Objective To investigate the relationship between positive experience and social support of spouses' of community stroke patients.Methods 100 stroke patients and their spouses in two communities were conveniently selected and investigated about their positive experience and social support with General Information Questionnaire (GIQ),Modified Barthel Index(MBI),Positive Aspects of Caregiver (PAC),Perceived Social Support Scale (PSSS).Results The mean score of the spouses' positive experience was (22.74±5.85); the dimension of serf-affirmation was (15.82±3.84),higher than the dimension of life expectation(6.92±2.95).The scores of the spouses' positive experience were significantly different among age,gender,education of spouses and age and ability of daily life of stroke patients; the score of the spouses' positive experience was positively correlated with social support,subjective support,utility of support;multiple linear regression showed that age of spouses,ability of daily life of stroke patients and utility of support were influential important factors of spouses' positive experience.Conclusions The spouses' positive experience was below average level,we must pay more attention to improve it,utility of support can improve spouses' positive experience.

Objective To explore the influencing factors of dwarfism in children and construct a nomogram model. Methods From June 2020 to December 2022, 1, 500 children were selected as the research objects, and 1, 422 cases were effectively investigated. According to incidence of dwarfism, the children were divided into normal group (n=1, 351) and dwarfism group (n=71). Univariate and multivariate Logistic regression analyses were used to explore the influencing factors of dwarfism in children; the R software was used to construct a nomogram model for prediction of the occurrence of dwarfism in children, and the receiver operating characteristic (ROC) curve and calibration curve were used to evaluate the discrimination and consistency of the nomogram model. Results Among the 1 422 children, 71 cases had dwarfism, with an incidence rate of 4.99%. Multivariate Logistic regression analysis showed that birth weight, family history of dwarfism, milk intake and physical exercise were the influencing factors for the occurrence of dwarfism in children (P < 0.05). The area under the curve of the ROC curve predicted by the nomogram model for the occurrence of dwarfism in children was 0.897 (95%CI, 0.856 to 0.938), with good discrimination; the calibration curve slope of the nomogram model for predicting the occurrence of dwarfism in children approached 1, and the Hosmer-Lemeshow goodness of fit test showed that the was 5.020 and P was 0.740, indicating good consistency. Conclusion The nomogram model for predicting the occurrence of dwarfism in children based on four influencing factors of birth weight, family history of dwarfism, milk intake and physical exercise has good discrimination and consistency, which can provide reference for the development of personalized intervention measures in clinical practice.

Objective To investigate the influencing factors of facial pressure injury related to ventilation in prone positioning in children with severe pneumonia and to construct a nomogram prediction model. Methods A total of 158 children with severe pneumonia who underwent prone positioning ventilation were selected as research subjects. Clinical data were collected, and the children were divided into injury group (31 cases) and non-injury group (127 cases) based on whether facial pressure injury occurred. Univariate and multivariate Logistic regression analysis were used to explore the influencing factors of facial pressure injury related to prone positioning ventilation in children with severe pneumonia; the receiver operating characteristic (ROC) curve, consistency index, and Hosmer-Lemeshow goodness-of-fit test were used to evaluate the predictive efficiency of the nomogram model for facial pressure injury related to prone positioning ventilation in children with severe pneumonia. Results Univariate analysis showed that the proportion of children aged < 3 years, the proportion of those with complications, ventilation time in prone positioning, the proportions of children with sedative drugs and poor nutritional status, no decompression dressings, and the proportions of children without prone positioning ventilation training for medical staff in the injury group were higher or longer than that in the non-injury group (P < 0.05). Multivariate Logistic regression analysis showed that age < 3 years, presence of complications, longer prone positioning ventilation time, no decompression dressings, and lack of prone positioning ventilation training for medical staff were independent risk factors for facial pressure injury related to prone positioning ventilation in children with severe pneumonia (P < 0.05), and a nomogram prediction model was constructed based on these factors. The consistency index of the nomogram model was 0.940, and the area under the ROC curve was 0.978 (95%CI, 0.958 to 0.999). The calibration curve of predicting facial pressure injury related to prone positioning ventilation in children with severe pneumonia approached the ideal curve, and the Hosmer-Lemeshow goodness-of-fit test showed good fitting (χ²=12.416, P < 0.05). Conclusion The nomogram prediction model constructed based on 5 independent risk factors in this study has high risk identification ability and can early identify high-risk children with facial pressure injury related to prone positioning ventilation in severe pneumonia.

Objective To explore the impact of WeChat-assisted follow-up on self-administer medication capability of stroke survivors.Methods Seventy patients were recruited from a tertiary hospital and randomly divided into intervention group (n=35) and control group (n=35).Patients in intervention group were given WeChat-assisted follow-up including health education program and behavior guidance,and patients in control group received regular discharge care.The effects of WeChat-assisted follow-up and regular care on self-administer medication ability,cognitive and behavior level were assessed.Results After three months' follow-up,the scores of self-administer medication capability (38 (32,42)),experience (25 (20,28) and the integral level (87 (71,92)) in intervention group were significantly higher than those in control group (capability 25(16,38),experience 21 (8.75,27),total score 68 (38,87)) (Z=-2.511,-2.033,-2.209,P＜0.05).The self-administer medication experience,cognitive,capability and total scores increased significantly in intervention group after intervention(Z=-4.525,-4.610,-3.806,-4.718,all P＜ 0.01),while only the cognitive level increased slightly in control group (18 (10,24) vs 13 (11,18),Z =-1.794,P=0.073).Conclusions Follow-up intervention based on WeChat platform can improve the stroke patients' self-administration medication capability,however,the long-term effects on cognitive level and further reform need to be strengthened.

Patient activation is the core part of the chronic disease health care model, which plays a significant role in promoting patients' healthy behaviors, improving clinical indicators, and reducing medical utilization and costs. This article reviews the relevant theories, measurement tools, effects and intervention strategies of patient activation. This article puts forward the suggestion that Chinese medical system should include the Patient Activation Measure and carry out personalized intervention according to patients' activation level, which aims at providing a reference for improving the activation and self-management of patients with chronic diseases.

Objective To explore the categories of dyadic mental health literacy among stroke patients and their caregivers,and to analyze the differences in the characteristics of different classes of stroke patients and their caregivers.Methods A convenient sampling method was used to select 287 dyads of stroke patients and their caregivers who were treated at a tertiary general hospital in Henan province from July to October 2020.The general information questionnaire,Multicomponent Mental Health Literacy and Social Support Rating Scale were used for investigation.Latent profile analysis was adopted to explore the categories of dyadic mental health literacy,and multiple logistic regression was used to analyze the influencing factors of each category.Results Stroke patients and their caregivers were divided into 4 categories based on scores of mental health literacy:dyadic low resource group(19.86％),dyadic low literacy group(54.36％),dyadic low belief group(11.15％),dyadic high literacy group(14.63％).The patient's age,average monthly household income,the caregiver's age,the caregiver's Social Support Rating Scale score,the caregiver's educational level,daily care time and total time length of care were the factors influencing the categories of dyadic mental health literacy among stroke patients and their caregivers(P＜0.05).Conclusion Stroke patients and their caregivers were divided into 4 categories based on scores of mental health literacy.Medical staff should carry out comprehensive psychological interventions for stroke patients and their caregivers with different dyadic mental health literacy characteristics,so as to improve dyadic mental health literacy.

Purpose: To understand the recurrence risk perception of stroke patients and develop a chain mediation model of recurrence risk perception and health behavior. Methods: A cross-sectional study and convenience sampling were used. Stroke survivors were recruited from the neurology departments of three tertiary hospitals. Their recurrence risk perception, behavioral decision-making, social support, self-efficacy, recurrence worry, and health behavior were measured by relevant tools. Data was analyzed through one-way analysis and regression analysis, and the AMOS 21.0 software was used to explore the mediating relationships between variables. Results: Of the 419 participants, 74.7% were aware of stroke recurrence risk. However, only 28.2% could accurately estimate their own recurrence risk. Recurrence risk perception was significantly correlated with behavioral decision-making, social support, self-efficacy, and health behavior (r = .19 ∼ .50, p < .05). Social support and recurrence risk perception could affect health behavior indirectly through self-efficacy, behavioral decision-making, and worry. Behavioral decision-making acted as a main mediator between recurrence risk perception and health behavior, while the path coefficient was .47 and .37, respectively. The chain mediation effect between recurrence risk perception and health behavior was established with a total effect value of .19 (p < .01). Conclusion Most stroke survivors could be aware of recurrence risk but failed to accurately estimate their individual risk. In the mediation model of recurrence risk perception and health behavior, social support seemed to be an important external factor, while self-efficacy, behavioral decision-making, and worry seemed to act as key internal factors.

Purpose: To understand the recurrence risk perception of stroke patients and develop a chain mediation model of recurrence risk perception and health behavior. Methods: A cross-sectional study and convenience sampling were used. Stroke survivors were recruited from the neurology departments of three tertiary hospitals. Their recurrence risk perception, behavioral decision-making, social support, self-efficacy, recurrence worry, and health behavior were measured by relevant tools. Data was analyzed through one-way analysis and regression analysis, and the AMOS 21.0 software was used to explore the mediating relationships between variables. Results: Of the 419 participants, 74.7% were aware of stroke recurrence risk. However, only 28.2% could accurately estimate their own recurrence risk. Recurrence risk perception was significantly correlated with behavioral decision-making, social support, self-efficacy, and health behavior (r = .19 ∼ .50, p < .05). Social support and recurrence risk perception could affect health behavior indirectly through self-efficacy, behavioral decision-making, and worry. Behavioral decision-making acted as a main mediator between recurrence risk perception and health behavior, while the path coefficient was .47 and .37, respectively. The chain mediation effect between recurrence risk perception and health behavior was established with a total effect value of .19 (p < .01). Conclusion Most stroke survivors could be aware of recurrence risk but failed to accurately estimate their individual risk. In the mediation model of recurrence risk perception and health behavior, social support seemed to be an important external factor, while self-efficacy, behavioral decision-making, and worry seemed to act as key internal factors.