Hui Wu

Background and Objectives: Population aging and the rising prevalence of Alzheimer’s disease and related dementias (AD/ADRD) have created an urgent need for innovative care solutions. Artificial intelligence (AI) has emerged as a critical tool, yet a macro-level quantitative analysis of its evolutionary trajectory in geriatric care remains scarce. This study conducts a comprehensive bibliometric analysis to map the knowledge domain of AI-empowered geriatric care for AD/ADRD from 2004 to 2025, elucidating spatial distributions, evolutionary trajectories, and emerging research frontiers. Research Design and Methods: A total of 1,197 eligible records were retrieved from the Web of Science Core Collection. Bibliometric analyses including co-occurrence networks, burst detection, and thematic evolution were conducted utilizing CiteSpace, VOSviewer, and the Bibliometrix R package. Results: The 1,197 documents (402 sources; 7,268 authors) show an annual growth rate of 30.36%, peaking at 262 publications in 2025. The United States (242 articles; 6,640 citations) and China (213 articles; 3,649 citations) dominate global output, with Harvard University and the University of London as primary hubs, though the Global South remains underrepresented. Thematic evolution reveals three phases: early “smart homes” and “activity detection”; middle “home monitoring” and “social robots”; and a current frontier of “explainable AI” and biomarker-driven risk assessment. Keyword bursts confirm “tau” and “intervention” as leading hotspots to 2025. Discussion and Implications: AI in AD/ADRD care is transitioning from environmental assistance to neuro-precision diagnostics and therapeutics. Future research should integrate ethical, multimodal AI to bridge care gaps and facilitate high-quality aging-in-place.

Background: Breast cancer survivors frequently experience significant posttraumatic stress symptoms (PTSS). Using the Conservation of Resources (COR) theory as a framework, this study aimed to investigate the configurational patterns and underlying psychological associations linked to high PTSS in post-operative patients. Methods: A cross-sectional study was conducted with 172 post-operative breast cancer patients. Participants completed measures for PTSS, resilience, perceived social support (PSS), self-efficacy, fear of progression (FoP), body image disturbance (BID), and shared decision-making (SDM). The analysis employed fuzzy-set Qualitative Comparative Analysis (fsQCA) to identify sufficient combinations of factors associated with high PTSS. This was followed by mediation analysis to test interrelationships among the identified core conditions. Results: The prevalence of PTSS was 89.5%. fsQCA identified five sufficient configurations for high PTSS. The combination of high BID and high FoP emerged as a core condition across these patterns. Mediation analysis demonstrated that FoP was associated with the link between BID and PTSS, and linked PSS to PTSS. Conclusion: High FoP and high BID are central factors correlated with PTSS in breast cancer survivors, operating within a COR-based “loss spiral.” Low SDM functions as a conditional factor related to resource obstruction. Findings suggest a need for stratified interventions targeting these specific resource depletions.

Background: Ovarian cancer is one of the most common gynecological cancers in women. Its diagnosis and treatment often cause significant psychological distress, mainly reflected in depression and anxiety, which arise from multiple interacting factors. This study, grounded in Lazarus’s Stress and Coping Model and from the perspective of set theory, aimed to investigate the correlates and configurational pathways of high and low levels of depression and anxiety symptoms in ovarian cancer patients by integrating stress sources, coping styles, and coping resources. Methods: The study recruited ovarian cancer patients from a tertiary general hospital in Shenyang, China. The analysis included 169 ovarian cancer patients. The configurational factors included self‐perceived burden (SPB), positive and negative coping styles, self‐esteem, and general self‐efficacy. Multiple linear regression and fuzzy‐set qualitative comparative analysis (fsQCA) were used to explore the factors and configurational pathways related to depression and anxiety symptoms. Results: The fsQCA identified six configurational pathways linked to high and low levels of depression symptoms. Similarly, the fsQCA identified two configurations linked to high anxiety symptoms and four configurations related to low anxiety symptoms. Moreover, the configurations associated with low psychological symptoms did not stand in opposition to those associated with high psychological symptoms. Substitutability and complementarity were observed among the various elements in the configuration. Conclusion: The study generated multiple configurational pathways for depression and anxiety symptoms in ovarian cancer patients by examining the combined effects of stress sources, coping styles, and coping resources. The configuration allows caregivers and medical staff to implement targeted measures to reduce burden perception and negative coping, enhance positive coping and self‐esteem considering their substitutability and complementarity.

Background: Ovarian cancer, the most lethal gynecologic malignancy, is characterized by a poor health-related quality of life (HRQoL). The present study examined the mediating role of self-perceived burden (SPB) in the impact of self-esteem on HRQoL and whether age moderated the associations among ovarian cancer patients. Methods: 203 patients effectively completed the Functional Assessment of Cancer Therapy-General (FACT-G), Rosenberg Self-Esteem Scale, and SPB scale, respectively. For the FACT-G, physical (PWB), social/family (SFWB), emotional (EWB), and functional well-being (FWB) were scored separately. Results: Significant mediation of SPB in the impacts of self-esteem on PWB (a × b = 0.074, 95% CI: 0.018, 0.153), EWB (a × b = 0.048, 95% CI: 0.001, 0.125), and FWB (a × b = 0.056, 95% CI: 0.009, 0.114) were revealed. Age positively moderated the impact of self-esteem on SPB (β = 0.159, p < 0.05), and the associations of SPB with PWB (β = 0.173, p < 0.05) and EWB (β = 0.240, p < 0.01), indicating a moderated mediation. Conclusions: Ovarian cancer patients’ self-esteem could improve the PWB, EWB, and FWB domains of HRQoL by reducing SPB. Age could attenuate SPB’s mediation in the impacts of self-esteem on PWB and EWB, indicating stronger impacts in younger patients. Clinical programs integrating components that strengthen self-esteem and reduce SPB may be particularly beneficial for younger women with ovarian cancer.

The demands of nursing work include high pressure, high intensity, and low substitutability. Coupled with the complex work environment, including patient-nurse relationships, colleague interactions, shift work, and night shifts, these factors present significant sleep challenges for nurses. A risk prediction model for sleep disturbances in nurses was developed using various machine learning (ML) algorithms to enhance the accuracy of identifying associated predictive factors. From November 2019 to February 2020, the research team distributed self-assessment questionnaires to 900 nurses in two tertiary general hospitals in China, collecting a total of 728 valid responses. These questionnaires covered baseline characteristics, work-related information, and data on physical and mental health. By integrating multiple ML models, a predictive model for sleep disturbances among nurses was developed using an important subset of features selected through recursive feature elimination. The performance of various ML models was evaluated on the test set and external validation set using metrics such as the area under the curve (AUC), accuracy, sensitivity, specificity, and positive predictive value. Model performance and effectiveness at different thresholds were assessed using calibration curves and decision curve analysis (DCA). Additionally, the optimal model was selected, and the SHapley Additive exPlanations (SHAP) method was employed for visual interpretation of model features and individual predictions. The prevalence of sleep disturbances in Chinese nurses was 41.6%. The multi-layer perceptron (MLP) emerged as the best-performing model, achieving the highest AUC of 0.814 on the test set, slightly ahead of logistic regression (0.808) and XGBoost (0.805). It also demonstrated a competitive accuracy of 0.725. In the external validation set, MLP’ s AUC was 0.798, with an accuracy of 0.728. MLP exhibited balanced performance across various metrics, including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F1-score. Patient/family incivility, workplace incivility, overcommitment, optimism, hope, ERR, physical fatigue, and years of work experience were identified as significant predictors of sleep disturbances among nurses. Based on baseline data, psychological characteristics, and work environment information, we developed ML models to predict sleep disturbances in nurses. Using the SHAP method, we successfully identified key predictive factors. This study highlights the association between work environment/psychological factors and sleep disturbances, suggesting that these factors should be considered in future intervention studies aimed at improving nurses’ sleep quality. Not applicable.

Psychiatric healthcare workers experience prolonged exposure to psychological trauma and negative emotions, which ultimately predisposes them to mental health issues. The effectiveness of online mindfulness-based stress reduction training on depression and anxiety symptoms among psychiatric healthcare workers (HCWs) and the possible mechanisms that benefit these outcomes remain unclear. This randomized controlled trial evaluated the effect of an 8-week online MBSR among psychiatric HCWs (165 participants) at the mental health center in Shenyang, China from August to November 2022, compared with the waitlist control group. The effective sample size that actually completed the intervention was 135 (74 participants in the intervention group and 61 in the control group), and the loss-to-follow-up rate was approximately 18%. Participants completed assessments of depression and anxiety symptoms (Hospital Anxiety and Depression Scale, HADS), and emotional suppression (Courtauld Emotional Control Scale, CECS) at baseline and week 8 online via the “Wenjuanxing” Platform. Intervention outcomes were estimated via analysis of covariance (ANCOVA). Multiple linear regression and mediation models with bias-corrected bootstrapping were performed to explore the mediating role of emotional suppression. Compared with those in the control group, the participants in the online MBSR group presented lower emotional suppression (P < 0.001), symptoms of depression (P < 0.001) and anxiety (P = 0.002). The decrease in emotional suppression mediated the effects of online MBSR on 8-week symptoms of depression (indirect effect = − 1.106, 95% CI [− 1.683, − 0.600]) and anxiety (indirect effect = − 1.182, 95% CI [− 1.731, − 0.706]). Online MBSR training could be utilized to alleviate depression and anxiety symptoms in psychiatric HCWs. It might weaken depression and anxiety symptoms by reducing emotional suppression. Emotional suppression might be the key change process of the effects of online MBSR on depression and anxiety symptoms in psychiatric HCWs. The clinical trial registration code was obtained from the Chinese Clinical Trial Registry (date of registration: 02/08/2022, registration number: ChiCTR2200062347).

Background The prevalence of loneliness among college students has elevated during the 2019 Coronavirus disease (COVID-19) pandemic. Thus, it is essential to clarify the factors that contribute to loneliness and seek out measures to reduce the influence of these factors on college students. Objective To explore the mediating mechanisms underlying the association between perceived social support and loneliness among Chinese college students, and the multiple mediating roles of hope and resilience in this relationship. Method This online survey was conducted through the Wenjuanxing platform on March 3–15, 2020. A total of 1,627 effective questionnaires were received and the response rate was 94.3%. The UCLA loneliness scale, the Multi-Dimensional Scale of Perceived Social Support, the Herth Hope Index and Resilience Scale, and the scale of demographic variables were used for gathering data. Hierarchical multiple regression and the bootstrap method were used to explore and examine the chain mediation model. Results The prevalence of loneliness among undergraduates was 55.2% (898/1627) during the COVID-19 pandemic, and there were significant differences in loneliness in gender (t = 4.131, p < 0.001) and sleeping duration (t = 3.971, p < 0.001). A significant chain mediation model was obtained in which college students’ loneliness was affected by perceived social support through 3 different pathways: the mediating role of hope (42.28% of total effect), the mediating role of resilience (6.44% of total effect), and the chain mediating role of both hope, and resilience (4.91% of total effect). The total mediation effect was − 0.266, which accounted for 53.52% of the total effect. Conclusion Perceived social support, hope and resilience could relieve the feeling of loneliness effectively among Chinese college students. Hope and resilience play the chain mediation role in the association between perceived social support and loneliness. The psychological interventions about enhancing social support and improving hope and resilience may help to alleviate loneliness during the pandemic of COVID-19.

Psychiatric nurses often encounter patients with mental health disorders and consequently experience prolonged periods of high stress, increased workload, and frequent incidents of workplace violence. These aspects can lead to a higher incidence of poor sleep quality. This study examined the interplay between workplace violence and emotional labour (surface and deep acting) to suggest measures for enhancing sleep quality among psychiatric nurses. A total of 300 completed and valid online questionnaires were collected. The Pittsburgh Sleep Quality Index was used to measure sleep quality, Workplace Violence Scale (WVS) to measure the occurrence of workplace violence, and Emotional Labour Scale to measure surface and deep acting. The data were analysed using Hayes’ PROCESS macro with SPSS. Independent samples t-tests and one-way ANOVA were used to compare differences in sleep quality and emotional labour (surface and deep acting) between psychiatric nurses with different demographics. The prevalence of poor sleep quality (PSQI > 5) was 55% among the nurses. Surface acting in emotional labour partially mediated the relationship between workplace violence and sleep quality(a1*b1=0.035,95%CI: 0.002, 0.079), whereas deep acting had a suppressive effect(a2*b2=-0.033,95%CI: -0.071, -0.003). Occupational identity had a positive moderating effect on the relationship between workplace violence and surface acting(Effect=0.091,95%CI: 0.004, 0.179). The relationship between workplace violence and poor sleep quality was partially mediated by surface acting and suppressed by deep acting. Moreover, nurses with higher occupational identity engaged in more surface acting after workplace violence. Workplace violence, surface acting, and deep acting emerged as significant factors influencing sleep quality among psychiatric nurses. Deep acting can reduce the impact of workplace violence on sleep quality. The results provide a new and expanded view of the interplay between workplace violence and emotional labour concerning sleep quality. Interprofessional collaboration with clinicians, administrators, educators, and spiritual leaders can contribute to the development of related education and training. Chinese Clinical Trial Registry ChiCTR2200062347. https://www.chictr.org.cn/showproj.html?proj=173264

The persistent destructive power of cancer-related fatigue (CRF) has been regarded as the biggest influencing factor affecting the postoperative physical and mental health of patients with cervical cancer. During this process, patients might also experience different feelings of disease-related psychological. Therefore, this study aimed to adopt mindfulness-based stress reduction (MBSR) to intervene in patients with cervical cancer, and conducted follow-up for 3 and 6 months to observe the effects of changes in CRF, uncertainty in illness, coping styles, sense of coherence (SOC), and perceived social support (PSS). A randomized controlled trial was conducted in ShengJing Hospital of China Medical University. A total of 102 patients were selected, and 78 patients completed the whole process, including 40 in the experimental group and 38 in the control group. Data were collected according to Cancer Fatigue Scale, Medical Coping Modes Questionnaire, Multidimensional Scale of Perceived Social Support, and Sense of Coherence-13. The change trend and difference of the two groups of research data were compared by repeated measurement analysis of variance. Bonferroni test was used for multiple tests between groups. The CRF, SOC, and coping styles of the MBSR group showed a decreasing trend (P < 0.001) at after MBSR, 3 months follow-up, and 6 months follow-up compared to the before MBSR. However, the uncertainty in illness of the MBSR group showed a decreasing trend (P < 0.001) at after MBSR compared to the before MBSR, and it rose in 3 months follow-up and 6 months follow-up. MBSR can effectively alleviate the fatigue of CRF after treatment, while improving their psychological environment. Medical workers can consider implementing online MBSR for patients with cervical cancer in their daily rehabilitation nursing, which is beneficial for their recovery. China Clinical Trial Registration Center ChiCTR2000040122 (https//www.chictr.org.cn/). Registered on November 21, 2020.