Jingjing Ma

Quality of Life (QoL) after stroke is a multidimensional construct, yet its internal interactive architecture and how objective functional capacity, specif

Stroke is a leading cause of global disability, with survivors often experiencing complex, co-occurring symptoms that significantly impair health-related quality of life (HRQoL). Conventional analytical methods often fail to capture the interdependent nature of these symptoms. Network analysis offers a novel approach to understanding symptom interactions and their collective impact on HRQoL. A cross-sectional study using symptom network analysis. A total of 311 convalescent stroke survivors were recruited using a convenience sampling method from two Grade A tertiary hospitals in Zhejiang Province, China, between October 20, 2024, and July 31, 2025. Data were collected using a general information questionnaire, the Stroke Symptom Experience Scale, and the Stroke-Specific Quality of Life Scale (SS-QOL). Symptom network analysis was performed using R 4.4.2 software. The EBICglasso model was applied to construct the partial correlation network using Spearman rank correlation as input. The stability of the network structure was also evaluated using the case-dropping bootstrap method. The most frequently reported symptom was a decline in self-care ability (83.28%). Symptom network analysis revealed that limited limb mobility was the central symptom, with the highest strength centrality (strength centrality = 1.144). Symptoms most strongly associated with poorer HRQoL included decline in self-care ability (edge weight = -0.229) and slurred speech (edge weight = -0.181). Stability tests indicated that the network model performed well, with a correlation stability coefficient of 0.437 for strength centrality. Symptoms in convalescent stroke patients are interrelated, and different symptoms are associated with HRQoL through distinct mechanisms. Our findings suggest that intervention strategies based on central symptoms and their interrelationships may offer potential benefits for improving rehabilitation outcomes and enhancing patients’ HRQoL. These propositions require confirmation through future longitudinal or interventional studies.

Stroke is a leading cause of death and disability worldwide. Survivors often experience multiple co-occurring symptoms that interact in complex ways. These interactions create significant symptom burden and reduce quality of life. However, substantial heterogeneity exists in how patients experience post-stroke symptoms. Traditional approaches often treat patients as a homogeneous profile. They also focus on individual symptoms in isolation. This limits the development of tailored symptom management strategies. This study aimed to identify distinct symptom burden based on patients' reported symptom experiences, compare their symptom network structures, and simulate potential intervention targets using computational modeling. A total of 451 stroke survivors were recruited from three hospitals in Zhejiang Province, China. Symptoms were assessed using the Stroke Symptom Experience Scale. Exploratory factor analysis was used to identify symptom domains. Latent profile analysis was applied to categorize patients based on these domains. Network analysis with EBICglasso regularization was employed to estimate symptom networks for the full sample and each identified profile. The stability of centrality indices was assessed via the case-dropping bootstrap, and network structures were compared using a Network Comparison Test. Finally, the NodeIdentifyR algorithm was used to simulate the potential impact of aggravating and alleviating interventions on each symptom. The goal was to generate hypotheses about potential high-risk and high-benefit targets for future study. Four symptom domains were identified: Motor Dysfunction, Emotional Disorders, Cognitive and Language Disorders, and Pain and Foot Morphological Abnormalities. Latent profile analysis revealed two distinct patient profiles based on symptom experience: a low symptom burden profile (Profile 1, 65.4%) and a high symptom burden profile (Profile 2, 34.6%). In the overall network, limited limb mobility (S1), impaired memory (S9), and impaired attention (S10) showed the highest centrality. The two profiles exhibited significantly different network structures (M = 0.285, p = 0.026). Core symptoms shifted from motor and self-care deficits (S1, S19) in Profile 1 to cognitive symptoms (S9, S10) in Profile 2. In simulated interventions, targeting central symptoms such as S1 was associated with the greatest predicted alleviating impact. This intervention corresponded to a reduction in overall burden by 11.8% in the model. However, the simulations also suggested a dissociation between centrality and risk. In Profile 1, worsening a non-central symptom (foot varus, S6) was predicted to be associated with an elevation in total burden by 26.2%. This effect size was larger than that of most central symptoms. In this cohort of 451 stroke survivors, symptom experience was not homogeneous. Patients could be grouped into low and high symptom burden profiles with different network structures. Simulation analyses showed that targeting high-centrality symptoms was associated with the largest predicted burden reductions, while worsening a non-central symptom (foot varus, S6) in the low-burden subgroup was predicted to increase burden by 26.2%. A sensitivity analysis confirmed that motor, cognitive, and emotional symptom domains play important roles, though the precise ranking of individual symptoms should be interpreted with caution. We introduce a benefit-risk framework as a hypothesis-generating tool for symptom management. Future longitudinal studies are needed to validate these predictions.

Background: Decision fatigue, conceptualized within Baumeister’s strength model of self‐control, describes the deterioration of decision‐making quality following protracted choice‐making processes. The intensive cognitive and managerial demands inherent in nursing leadership render head nurses particularly susceptible to this phenomenon, with subsequent deleterious effects on patient safety, staff well‐being, and organizational performance. Aims: This study aims to delineate the characteristics of decision fatigue among head nurses and identify the specific occupational and environmental factors associated with this phenomenon, particularly within the intricacies of complex clinical management. Furthermore, the research seeks to provide a robust evidence base for healthcare administrators to inform the design and implementation of targeted intervention strategies aimed at mitigating cognitive exhaustion in nurse leaders. Methods: A descriptive, multicenter, cross‐sectional study was conducted. Data were collected between November and December 2024 across 17 healthcare institutions in China. A total of 144 head nurses were recruited via convenience sampling. Data were collected using a sociodemographic questionnaire, the Decision Fatigue Scale (DFS), and the Nurse Manager Practice Environment Scale (NMPES). Statistical analyses included Mann–Whitney U and Kruskal–Wallis H tests for group comparisons, Spearman correlation, and multiple linear regression to identify independent predictors. Results: Participants reported low‐to‐moderate levels of decision fatigue, with a median score of 9 (IQR = 7.25–10.75), while practice environment scores were relatively optimal (median = 225, IQR = 216–249). Multiple linear regression identified cultural heritage ( β = −0.296), physical status (absence of fatigue) ( β = −0.234), and organizational planning ability ( β = −0.228) as significantly associated with lower decision fatigue. Notably, head nurses in tertiary hospitals exhibited significantly higher fatigue levels (median = 10, IQR = 8.5–12.5), underscoring the impact of systemic institutional pressures. Conclusions: Decision fatigue may be understood through a proposed dual‐pathway framework: a direct pathway involving task overload and ego depletion and an indirect pathway involving emotional labor and cognitive interference. Psychological training was associated with lower fatigue levels, potentially by facilitating cognitive reappraisal of stress. Effective mitigation strategies may benefit from a multifaceted approach incorporating situational leadership and nonmonetary support. Furthermore, cultural heritage and organizational planning ability were identified as factors associated with reduced fatigue, while addressing structural constraints may help optimize decision‐making efficacy among nurse leaders. Implications for Nursing Management: The identified three‐tier protective framework—comprising cultural heritage, organizational planning ability, and physical resilience—offers an actionable framework for intervention. Supported by a robust cultural heritage, nurse managers may benefit from structured daily planning, algorithmic cognitive outsourcing, and proactive fatigue self‐monitoring. At the institutional level, administrators could consider formalizing mentorship programs, integrating evidence‐based psychological training, and addressing structural staffing constraints. Furthermore, policymakers might re‐examine resource allocation strategies that disproportionately burden midtier hospital leaders. Multilevel, coordinated interventions may be essential to safeguard head nurse decision‐making capacity, patient safety, and staff well‐being.

Introduction: Caring for stroke survivors poses significant challenges to survivors and caregivers; understanding these relationships can inform targeted interventions and support systems.Aim: This study investigates the influencing factors of caregiver burden and the potential mediating roles of family resilience and perceived social support between caregiver burden and caregiver capacity.Design: This is a cross-sectional study.Methods: The participants in this study included 462 stroke survivors and their primary caregivers from Ningbo Lihuili Hospital in Zhejiang Province, China. Primary caregivers completed several assessments, including the Shortened Chinese Version of the Family Resilience Assessment Scale (FRAS), the Perceived Social Support Scale (PSSS), the Zarit Caregiver Burden Interview (ZCBI), and the Family Caregiver Task Inventory (FCTI). The ZCBI was used to evaluate caregiver burden, while the activities of daily living (ADL) were assessed for stroke survivors to measure their actual level of dependence. The mediating effect of family resilience was estimated using the bootstrap method through Jamovi version 2.3.0 with the mediation plug-in, while controlling for sociodemographic variables.Results: The results showed that caregiver burden was influenced by stroke survivors’ level of dependence on activities of daily living (ADL), caregiver education level, caregiver health status, and average daily care time. The family resilience mediated the relationship between caregiver burden and caregiver capacity (b = 0.141; 95% confidence interval: 0.091 to 0.176). Additionally, perceived social support mediated the relationship between caregiver burden and caregiver capacity (b = 0.080; 95% confidence interval: 0.041 to 0.110).Conclusion: These findings indicate that enhancing family resilience and perceived social support can be strategies for alleviating caregiver burden. Clinical practitioners should actively assess the family resilience and social support of stroke survivors, and implement interventions that promote resilience and strengthen social support, thereby reducing caregiver burden and improving the health outcomes of stroke survivors.

During the COVID-19 pandemic, hospitals implemented visitor restrictions to curtail the spread of the virus. The study aims to understand the perspectives of hospitalized patients and their family visitors on visitation restrictions and the factors influencing their willingness to adhere to these restrictions. This cross-sectional survey invited 1,200 participants, with 1,032 valid responses received, including 460 hospitalized patients and 572 family visitors. The survey indicated that 88.91% of hospitalized patients and 93.00% of family visitors complied and adhered to the visitor restrictions. The predominant mode of communication was via phone (77.62%), with emotional support (56.40%) recognized as the primary purpose of visitation. Visitor restrictions significantly affected hospitalized patients, with 51.65% reporting feelings of loneliness and 42.44% reporting anxiety. After adjusting for age, gender, and other factors, hospitalized patients‘ willingness to follow visitation restrictions was linked to their awareness of the restrictions (odds ratio [OR] = 0.20, 95% confidence interval [CI]: 0.09–0.44) and their desire to protect (OR = 0.32, 95% CI: 0.14–0.76). Family members’ willingness to follow the restrictions was related to their awareness of them (OR = 0.34, 95% CI: 0.12–0.95) and how well they communicated (OR = 0.23, 95% CI: 0.09–0.58). Participants generally followed visitation restrictions, but these measures negatively impacted the psychological and social well-being of patients and their families, leading to increased feelings of loneliness and anxiety. Healthcare providers, hospital administrators, and policymakers should acknowledge the complex effects of these restrictions and focus on improving patient experiences in the future.

Objectives To investigate the relationships among caregiver burden, family resilience, and caregiver capacity in the care of stroke survivors. We hypothesised that family resilience would mediate the relationship between caregiver burden and caregiver capacity. Design A cross-sectional study design was used. Setting The study was conducted in a tertiary care setting in Ningbo City, Zhejiang Province, China. Participants The study involved 413 stroke survivors and their primary caregivers. Outcome measures The primary caregivers completed the Shortened Chinese Version of the Family Resilience Assessment Scale, Zarit Caregiver Burden Interview and Family Caregiver Task Inventor and provided their sociodemographic information. Stroke survivors were assessed for activities of daily living, and their sociodemographic information was provided. Data were analysed, controlling for sociodemographic variables and focusing on the mediating effect of family resilience. Results Caregiver burden was influenced by the activities of daily living of stroke survivors, caregiver age and caregiver health status (pConclusions Enhancing family resilience can reduce caregiver burden and improve caregiver capacity in stroke care. These findings underscore the importance of developing interventions focused on nursing skills and family resilience.

To determine the effect of auricular acupuncture on preoperative blood pressure (BP) elevation in different age groups.Auricular acupuncture treats elevated BP among patients before surgery. This p...

Guidelines and recommendations from public health authorities related to face masks have been essential for containing the COVID-19 pandemic. A cross-sectional survey was conducted in Ningbo City, China, from April 8 to 12, 2022. We assessed the behavioral differences and correlates of mask usage, primarily mask-removal. We examined public mask-wearing behavior during on-site COVID-19 nucleic acid detection. The survey instrument was developed based on the guidelines issued by the World Health Organization and consisted of demographics, mask-wearing knowledge, and behavior. We analyzed data from 1180 participants; 73.2% demonstrated good mask-wearing knowledge. However, regarding mask-wearing behavior, only 53.7% knew the correct way to remove a mask; 70.3% maintained hand hygiene after touching the outside. Binary logistic regression analyses revealed that health prevention knowledge and free mask distribution were positively associated with two types of mask-wearing behaviors. Most participants used masks during the COVID-19 pandemic; however, mask-removal and hand hygiene were neglected when touching the outside of the mask. More attention must be paid to mask-removal and hand hygiene details. Local health authorities should consider introducing the free distribution of masks.

Background: Guidelines and recommendations from public health authorities related to face masks have been essential for containing the COVID-19 pandemic. We assessed the behavioral differences and correlates of mask usage, mainly mask removal.Methods: We examined public mask-wearing behavior during on-site COVID-19 nucleic acid detection. We examined 1180 responses to a cross-sectional survey by NingBo of China, completed from April 8 to April 12, 2022. The outcome was face mask usage in public settings and hand hygiene. Descriptive statistics were used to assess public mask-wearing behaviors. A binary logistic regression analysis was performed to identify the risk factors affecting mask-wearing behavior and hand hygiene.Results: We analyzed data from 1180 participants; 73.2% demonstrated good knowledge regarding face mask use. However, only 53.7% know the correct way to remove a mask; 70.3% maintain hand hygiene after touching the outside of the mask. Health prevention knowledge (odds ratio [OR] = 6.60, 95% confidential interval [CI] = 4.79–9.08, p＜0.001; OR = 2.37, 95% CI = 1.79–3.13, p＜0.001) and free face mask distribution (OR = 0.71, 95% CI = 0.54–0.94, p = 0.017; OR = 0.49, 95% CI = 0.37–0.64, p＜0.001) predicted health prevention behavior (removal during nucleic acid sampling and hand hygiene after touching the outside of the mask).Conclusions: Most participants used masks during the COVID-19 pandemic; however, mask removal and hand hygiene when touching the outside of the mask were neglected. More attention needs to be paid to details of mask removal and hand hygiene. Local health authorities should consider introducing free distribution of masks.