Aims: To establish a sensitive, scientific and practical evaluation system for haemodialysis nursing and to provide a reference for the evaluation of haemodialysis nursing quality.Design: Through a literature review and Delphi method.Method: According to the literature review, a preliminary nursing‐sensitive quality indicators for haemodialysis were established, and an expert survey questionnaire was designed. Finally, the evaluation system for the nursing‐sensitive quality indicators was determined using the Delphi method.Results: Thirteen nursing‐sensitive quality indicators for haemodialysis were finally constructed, including two structural indicators, three process indicators and eight outcome indicators. The effective recovery rate of the two rounds of expert survey questionnaires was 100%, the coefficient of judgement basis is 0.956, the coefficient of familiarity is 0.833, the coefficient of authority is 0.895, and the Kendall's harmony coefficients of the two rounds of expert consultation were 0.158 ~ 0.307 and 0.170 ~ 0.315, respectively, with statistical significance (p < .05).Clinical relevance: In this study, the nursing‐sensitive quality indicators for haemodialysis were developed by the Delphi method and included structural indicators, outcome indicators and process indicators, which made up for some deficiencies noted in previous studies. The authors have provided a more reliable and comprehensive basis for evaluating the quality and safety of haemodialysis nursing in the future.

Background: Within hemodialysis patient populations, eHealth interventions have been considered as an alternative and complementary option to routine care services. However, the efficacy of eHealth interventions for hemodialysis patients remains poorly understood owing to a lack of rigorous quantitative evidence synthesis. Objective: This meta-analysis aimed to evaluate the efficacy of eHealth interventions in improving quality of life, treatment adherence, and psychological outcomes (anxiety and depression) among hemodialysis patients. In addition, the study sought to identify specific intervention components and methodological quality associated with enhanced quality of life and health outcomes in this population. Methods: A comprehensive search was performed across PubMed, Web of Science, Embase, CINAHL, Cochrane Library, PsycINFO, China National Knowledge Infrastructure, WanFang, China Science and Technology Journal Database, and China BioMedical Literature Database databases from their inception to September 7, 2024. Randomized controlled trials on eHealth interventions for hemodialysis patients published in English or Chinese were included. Critical appraisal was carried out independently by 2 reviewers to assess the bias risk of the studies included. Quantitative synthesis of the outcomes of interest was conducted using a random-effects model. The quality of evidence for the outcomes was evaluated following the Grading of Recommendations, Assessment, Development, and Evaluation approach. Results: A total of 17 randomized controlled trials involving 1728 participants were included in this meta-analysis out of 5741 articles identified in the initial database search and additional search references. In the 17 studies, 8 kinds of eHealth intervention delivery formats were used, including text messages, telephone sessions, video, network platforms, social media, computers, websites, and mobile apps. The majority of research studies used a single form of eHealth intervention, and 7 studies adopted a combined approach of 2 or more eHealth technologies. The duration of eHealth interventions demonstrated substantial variability across studies, spanning from 4 weeks to 12 months, of which 3 months was the most common. A total of 14 (82%) studies were considered to have “some concern” about selection bias. In addition, 15 (88%) trials were classified as having a “high risk” of performance and detection bias, and all trials were judged to be at “low risk” of attrition and reporting bias. The pooled results revealed a significant difference between the eHealth interventions and control groups on quality of life (standardized mean difference [SMD]=0.87, 95 % CI 0.38 to 1.37, low certainty evidence), treatment adherence (SMD=1.11, 95 % CI 0.30 to 1.91, moderate certainty evidence), anxiety (SMD=–2.11, 95 % CI –3.25 to –0.97, moderate certainty evidence), and depression (SMD=–2.46, 95 % CI –3.68 to –1.25, moderate certainty evidence). Conclusions: eHealth interventions could be a beneficial approach for improving quality of life and treatment adherence and reducing anxiety and depression among hemodialysis patients. However, future high-quality randomized controlled trials are essential to draw more reliable conclusions. Trial Registration: PROSPERO CRD42024589799; https://www.crd.york.ac.uk/PROSPERO/view/CRD42024589799

Background: Poor sleep quality is associated with various adverse outcomes among hemodialysis (HD) patients. Although poor sleep quality is a widely recognized health issue in HD patients, the reported prevalence in the current literature are remarkably inconsistent. This study aimed to determine the global prevalence of poor sleep quality in HD patients. Methods: A comprehensive literature search was conducted across seven electronic databases (PubMed, Web of Science, Scopus, Embase, Cochrane Library, CINAHL, PsycINFO) from their inception to October 20, 2025. Data extraction was performed using a standardized form, and the methodological quality of included studies was evaluated with the Joanna Briggs Institute (JBI) critical appraisal checklist for prevalence studies. A random-effects model was applied to calculate the pooled prevalence of poor sleep quality, and the heterogeneity was quantified using the I ² statistic. Subgroup analyses and meta-regression were conducted to explore potential sources of heterogeneity. Results: A total of 69 studies involving 14,998 HD patients were included in the meta-analysis. The pooled global prevalence of poor sleep quality was 64.2% (95% CI: 60.5–67.8%). Based on the JBI critical appraisal tool, 55 studies were rated as having a low risk of bias, while 14 were considered to have a moderate risk of bias. Subgroup analysis revealed that the pooled prevalence varied significantly by the cut-off values. Meta-regression results indicated that prevalence was not significantly associated with sample size, mean age, dialysis duration, and proportion of females. Conclusion: Our findings demonstrate a high prevalence of poor sleep quality among HD patients. To mitigate the adverse effects of poor sleep quality on HD patients, healthcare providers should routinely conduct screenings and deliver evidence-based interventions.

Aim: This study aimed to investigate the current situation of sarcopenia and anorexia of elderly maintenance haemodialysis patients and analyse the influencing factors.Design: A cross‐sectional design was used in this study.Methods: One hundred and twelve elderly patients on MHD in 3 haemodialysis centres in Sichuan, China, were selected. Sarcopenia was diagnosed according to the criteria of the Asian Working Group for Sarcopenia (AWGS). Anorexia was assessed with the Functional Assessment of Anorexia Cachexia Therapy/Anorexia Cachexia Subscale (FAACT/ACS). The relationship between sarcopenia and anorexia was analysed by logistic regression.Results: The prevalences of sarcopenia and severe sarcopenia in elderly MHD patients were 52.7% and 39.3%, respectively, and the prevalence of anorexia was 25.9%. Severe sarcopenia was independently associated with anorexia, and weekly exercise frequency was independently associated with anorexia. The low SMI value and slow gait speed were strongly associated with anorexia. This study complied with the STROBE checklist.

Aims: This study aimed to classify the latent profiles of team job crafting of nurses and to examine their effect on professional quality of life (ProQOL). Background: Team job crafting, as an emerging concept, could promote team productivity and performance by enhancing collaboration among team members and might affect nurses’ ProQOL. However, whether different population characteristics of team job crafting for nurses pattern latent profiles and how these subgroups correlate with nurses’ ProQOL remains to be determined. Methods: This cross‐sectional study was conducted at a general tertiary hospital in Sichuan Province, China. Two thousand two hundred fifty‐three nurses completed an online investigation encompassing the Team Job Crafting Scale for Nurses and the Professional Quality of Life Scale. Latent profile analysis and hierarchical regression analysis were employed to validate our research hypotheses. Results: The team job crafting of nurses was classified into two subgroups: “poor team job crafting group” ( n = 973, 43.2%) and “excellent team job crafting group” ( n = 1280, 56.8%). The different profiles of team job crafting exhibited significant effects on three subvariables of nurses’ ProQOL: compassion satisfaction (adjusted R ² = 0.208, p < 0.001), burnout (adjusted R ² = 0.192, p < 0.001), and secondary traumatic stress (adjusted R ² = 0.043, p < 0.001). Conclusions: Team job crafting for nurses was characterized by a strong population heterogeneity. The majority of nurses perform excellent in the team job crafting. The team job crafting was significantly associated with the ProQOL among nurses. Nursing managers should draw up targeted continuing educational training programs and organizational policies to promote the positive participation of nurses in team job crafting, thereby improving their ProQOL.

Learning engagement served as a primary determinant of learning outcomes, but nursing students’ engagement in learning often remains unimpressive due