Objective: To understand the current status of short video addiction among vocational nursing students in higher vocational colleges (hereinafter referred to as "nursing students") and its related factors, so as to provide a reference for formulating online education programs in colleges. Methods: From March to May 2025, a stratified random sample of 2 223 nursing students from four vocational colleges in Henan Province was selected. Short Video Addiction Scale for College Students, Short form Egna Minnen av Barndoms Uppfostran for Chinese, Peer Rejection Scale, and University of California at Los Angels Loneliness Scale were used for investigation. Chi square test and multivariate Logistic regression analysis were used to explore the related factors of short video addiction among nursing students. Results: The detection rate of short video addiction of higher vocational nursing students was 26.95%, and the scores for avoidance, loss of control, inefficiency and withdrawal were (8.05±2.97) (10.24±3.09) (4.99±1.88) and (11.97±4.10), respectively. Multivariate Logistic regression analysis showed that sophomore year 2 ( OR=1.83, 95%CI =1.39-2.40), higher maternal education level (secondary school/vocational college: OR =1.34, 95% CI =1.06-1.68; college/undergraduate: OR =1.38, 95% CI =1.05-1.82), paternal overprotection ( OR=1.59, 95%CI =1.27-2.00), high peer rejection ( OR=1.40, 95%CI =1.19-1.66), and strong loneliness ( OR=1.57, 95%CI =1.07-2.28) were associated with a higher risk of short video addiction among nursing students (all P <0.05). Paternal affectionate and warm rearing style ( OR=0.82, 95%CI = 0.71- 0.95) was associated with a lower risk of short video addiction ( P <0.05). Conclusions The detection rate of short video addiction among nursing students is relatively high. Short video addiction is related to the nursing students grade, maternal education level, paternal overprotection and affectionate rearing style, peer rejection, and loneliness.

Objective To review the application scope of risk communication based on eHealth technology in the primary prevention of cardiovascular diseases,so as to provide references for future research and application.Methods A systematic search was conducted in PubMed,Cochrane Library,Embase,Web of Science,CINAHL,PsycINFO,CNKI,Wanfang database,and SinoMed.The search time limit was from the establishment of databases to March 1,2024.The included literature was summarized and analyzed.Results A total of 24 articles were included.The forms of eHealth technology applied in risk communication for primary prevention of cardiovascular include online websites,computerized decision support systems,electronic health records,mobile applications,email,telephone,and text messages.The functions include risk assessment,risk notification,personalized advice,risk tracking and reminders.The outcome indicators include risk perception,physiological indicators,lifestyle and behavior,psychological indicators,feasibility evaluation,decision correlation,doctor-patient communication,intention,risk score,and physician drug prescription.Conclusion The use of eHealth technology in risk communication of cardiovascular diseases has potential value in improving patients'risk perception and promoting healthy behaviors.It is necessary to continuously improve the functions of eHealth technology and enhance its precision and intelligence,so as to better meet the needs of medical staff and patients and promote the efficient implementation of primary prevention of cardiovascular diseases.

Objective To analyze and clarify the concept and connotation of care-resistant behavior in dementia patients,so as to provide references for the evaluation and practice of care-resistant behavior in clinical dementia patients.Methods PubMed,Scopus,Web of Science,Cochrane Library,Embase,CINAHL,CNKI,VIP,Wanfang database and Chinese Biomedical Literature Database were systematically searched for the literature on care-resistant behavior in dementia patients.The search time limit was from the establishment of the database to December 2024.Walker and Avant's classical concept analysis method was used to analyze the literature.Results The care-resistant behav-ior in dementia patients included 5 conceptual attributes,including nursing background,perceived threat,unmet needs,lack of understanding and multi-dimensional performance.The antecedent factors include patient factors,care-giver factors,environmental factors and organizational factors.Post-impact includes the impact on patients and the impact on caregivers.Conclusion This study clarified the conceptual attributes,antecedents and post-effects of care-resistant behavior in dementia patients through concept analysis.In the future,researchers should combine the connotation of dementia patients' care-resistant behavior,develop localized assessment tools for dementia patients' care-resistant behavior,and construct targeted intervention programs,so as to improve the quality of nursing staff and enhance the care experience of dementia patients.

Objective To explore the potential categories of dyadic psychological capital and related factors among stroke patients and their spouses,in order to inform the improvement of their mental health.Methods Stroke patients and their spouses were recruited in the Neurology Department of 3 tertiary general hospitals from March,2023 to August,2023 by convenience sampling method.The general information questionnaire,Modified Rankin Scale(mRs),Psychological Capital Questionnaire,The Kessler Psychological Distress Scale(K10)and Perceived Social Support Scale(PSSS)were used for investigation.Latent profile analysis was adopted to explore the categories of dyadic psychological capital,and multiple Logistic regression analysis was used to assess the effect of various factors on different categories.Results A total of 232 returned questionnaires(out of the 235)were valid,resulting an effective response rate of 98.7％.Stroke patients and their spouses were divided into 3 categories,including dyadic low psychological capital-low self-efficacy group(6.0％),dyadic high psychological capital-low resilience group(15.9％)and dyadic medium psychological capital group(78.1％).The stroke patients'education level,mRs scores,occupational status after the illness,level of perceived social support,and spouses'working condition were the influencing factors on potential profiles of dyadic psychological capital(P＜0.05).Conclusion There are heterogeneity and interdependence in the level of dyadic psychological capital of stroke patients and their spouses.Healthcare professionals should promote dyadic mental health by developing targeted interventions for stroke patients and their spouses with different psychological capital characteristics from a dyadic holistic perspective.

Objective To review the application scope of risk communication based on eHealth technology in the primary prevention of cardiovascular diseases,so as to provide references for future research and application.Methods A systematic search was conducted in PubMed,Cochrane Library,Embase,Web of Science,CINAHL,PsycINFO,CNKI,Wanfang database,and SinoMed.The search time limit was from the establishment of databases to March 1,2024.The included literature was summarized and analyzed.Results A total of 24 articles were included.The forms of eHealth technology applied in risk communication for primary prevention of cardiovascular include online websites,computerized decision support systems,electronic health records,mobile applications,email,telephone,and text messages.The functions include risk assessment,risk notification,personalized advice,risk tracking and reminders.The outcome indicators include risk perception,physiological indicators,lifestyle and behavior,psychological indicators,feasibility evaluation,decision correlation,doctor-patient communication,intention,risk score,and physician drug prescription.Conclusion The use of eHealth technology in risk communication of cardiovascular diseases has potential value in improving patients'risk perception and promoting healthy behaviors.It is necessary to continuously improve the functions of eHealth technology and enhance its precision and intelligence,so as to better meet the needs of medical staff and patients and promote the efficient implementation of primary prevention of cardiovascular diseases.

Objective To explore the potential categories of dyadic psychological capital and related factors among stroke patients and their spouses,in order to inform the improvement of their mental health.Methods Stroke patients and their spouses were recruited in the Neurology Department of 3 tertiary general hospitals from March,2023 to August,2023 by convenience sampling method.The general information questionnaire,Modified Rankin Scale(mRs),Psychological Capital Questionnaire,The Kessler Psychological Distress Scale(K10)and Perceived Social Support Scale(PSSS)were used for investigation.Latent profile analysis was adopted to explore the categories of dyadic psychological capital,and multiple Logistic regression analysis was used to assess the effect of various factors on different categories.Results A total of 232 returned questionnaires(out of the 235)were valid,resulting an effective response rate of 98.7％.Stroke patients and their spouses were divided into 3 categories,including dyadic low psychological capital-low self-efficacy group(6.0％),dyadic high psychological capital-low resilience group(15.9％)and dyadic medium psychological capital group(78.1％).The stroke patients'education level,mRs scores,occupational status after the illness,level of perceived social support,and spouses'working condition were the influencing factors on potential profiles of dyadic psychological capital(P＜0.05).Conclusion There are heterogeneity and interdependence in the level of dyadic psychological capital of stroke patients and their spouses.Healthcare professionals should promote dyadic mental health by developing targeted interventions for stroke patients and their spouses with different psychological capital characteristics from a dyadic holistic perspective.

Objective To analyze and clarify the concept and connotation of care-resistant behavior in dementia patients,so as to provide references for the evaluation and practice of care-resistant behavior in clinical dementia patients.Methods PubMed,Scopus,Web of Science,Cochrane Library,Embase,CINAHL,CNKI,VIP,Wanfang database and Chinese Biomedical Literature Database were systematically searched for the literature on care-resistant behavior in dementia patients.The search time limit was from the establishment of the database to December 2024.Walker and Avant's classical concept analysis method was used to analyze the literature.Results The care-resistant behav-ior in dementia patients included 5 conceptual attributes,including nursing background,perceived threat,unmet needs,lack of understanding and multi-dimensional performance.The antecedent factors include patient factors,care-giver factors,environmental factors and organizational factors.Post-impact includes the impact on patients and the impact on caregivers.Conclusion This study clarified the conceptual attributes,antecedents and post-effects of care-resistant behavior in dementia patients through concept analysis.In the future,researchers should combine the connotation of dementia patients' care-resistant behavior,develop localized assessment tools for dementia patients' care-resistant behavior,and construct targeted intervention programs,so as to improve the quality of nursing staff and enhance the care experience of dementia patients.

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.