Aims Liver transplant recipients require complex self-management after transplantation. This study aimed to validate an artificial intelligence (AI)-based chatbot designed to support self-management. Methods A mixed-methods study was conducted at a medical center in Northern Taiwan (October 2022–December 2024). The chatbot was developed through four stages: creation of a self-management Q&A database, system development, validation, and usability testing. Interview findings from patients and healthcare professionals informed the database. The chatbot was deployed via LINE@ using a hybrid framework that retrieves validated responses from a predefined database and uses ChatGPT-4o-mini only for unmatched queries. Content validity index (CVI), intraclass correlation coefficient (ICC), Cohen's kappa, satisfaction, usability, and intention to use were evaluated. Results A total of 112 questions were classified into four domains and 21 subcategories. Two rounds of expert validation demonstrated acceptable-to-excellent agreement. The CVI improved from 0.79 to 0.88, ICC increased from 0.957 to 0.976, and Cohen's kappa reached 0.88. The satisfaction score was 4.71 (standard deviation [SD] = 0.39) on a 5-point Likert scale. The usability and intention-to-use scores were 6.04 (SD = 0.98) and 6.12 (SD = 1.02), respectively, on a 7-point scale. Conclusions The AI-based chatbot demonstrated strong validity and usability, supporting its readiness for larger-scale clinical evaluation. This hybrid approach shows promise for improving post-discharge self-management and personalized support for liver transplant recipients.
Aims To examine advance care planning (ACP) readiness among non-dialysis patients with chronic kidney disease (CKD) and to identify factors associated with readiness. Background CKD progression is often marked by acute events and sudden deterioration, reflecting an unpredictable clinical course. ACP is increasingly advocated as an essential component of CKD care; however, discussions are frequently deferred until advanced stages of disease or the initiation of renal replacement therapy. Consequently, patients with non-dialysis CKD, who may benefit from anticipatory planning, remain underrepresented in the literature. Methods A cross-sectional study adhering to STROBE guidelines was conducted. Participants were recruited from nephrology outpatient clinics and inpatient wards at a medical center using CKD stage–stratified quota sampling. Data were collected through self-administered questionnaires. ACP readiness was assessed using the readiness domain of the Advance Care Planning Engagement Survey. Demographic, clinical, and relational variables were measured. Descriptive statistics, non-parametric tests, and hierarchical regression analyses were conducted. Results Among 218 participants, ACP readiness was low to modest, particularly for initiating discussions with healthcare providers. Demographic variables explained 6.1% of the variance, increasing to 8.0% with comorbidities and 12.7% with patient–provider partnership. Older age and stronger patient–provider partnerships were associated with higher readiness, whereas disease stage and renal function were not. Conclusion ACP readiness among non-dialysis patients with CKD is not solely determined by disease severity but is closely linked to relational aspects of care. Patient–provider partnership may serve as a key mechanism shaping readiness, underscoring the importance of relationship-centered approaches in facilitating engagement in ACP.
Background In emergency settings, effective clinical decision-making and teamwork play crucial roles in delivering safe, high quality nursing care. Because the likelihood of missed nursing care increases under critical conditions, this study aimed to examine the relationship between clinical decision-making and teamwork with missed nursing care among emergency nurses. Methods This cross-sectional descriptive correlational study was conducted in 2025 among 289 nurses working in the emergency departments of hospitals affiliated with Alborz University of Medical Sciences. Data were collected using a demographic questionnaire, the clinical decision-making questionnaire (Lauri et al., 2001), the TeamSTEPPS teamwork perception questionnaire (Keebler et al., 2014), and the missed nursing care Questionnaire (Kalisch et al., 2009). Results Of the nurses, 60.9% were female. Interpretive-intuitive decision-making was the most common decision-making style (47.1%). Most nurses demonstrated acceptable teamwork (74.7%) and low levels of missed nursing care (82.7%). Teamwork (p < .001, β = −3.69) and clinical decision-making (p < .001, β = −0.36) were inversely associated with missed nursing care. Work experience was positively correlated with clinical decision-making (p < .001, r = 0.349) and teamwork (β = 0.049, SE (β) = 0.01, p < .001, R2_adj = 0.149). Work experience was also significantly and negatively correlated with missed nursing care (p < .001, r = −0.516). Conclusion The findings indicate that in emergency departments, higher levels of clinical decision-making and teamwork are significantly associated with lower levels of missed nursing care. To achieve a more comprehensive understanding of the variables studied, future research using mixed quantitative and qualitative methods are recommended.
BACKGROUND:AI-driven virtual standardized patients (VSPs) integrated within virtual reality (VR) environments offer structured opportunities for safe communication practice in nursing education; however, empirical evidence regarding their preliminary feasibility and educational effects remains limited, particularly in domain-specific clinical contexts such as preoperative nursing care. METHODS:This mixed-methods pilot study pursued two objectives: (1) to develop a VR simulation integrating an AI-driven VSP (AI-VSP) for preoperative nursing communication, and (2) to pilot-test its preliminary feasibility and exploratory pre-post effects. Ten third-year nursing students completed a single 50-minute preoperative care simulation using the VIRTI platform (Meta Quest 3). Quantitative data on satisfaction, self-confidence, simulation design perceptions, and immersion were collected using four validated instruments and analysed using paired-samples t-tests with effect sizes and 95% confidence intervals. Qualitative data were collected via semi-structured interviews and analysed using inductive thematic analysis. RESULTS:All four outcome variables showed statistically significant pre-post differences (all p ≤ .004), with large effect sizes (Cohen's d = 1.10-1.75). Qualitative themes indicated realistic conversational learning experiences and perceived clinical relevance, while identifying technical limitations in nonverbal feedback and scenario-level construct alignment as areas for refinement. CONCLUSION:These preliminary findings suggest that AI-VSP-based VR simulation may offer a feasible and structured pre-clinical learning environment for preoperative nursing communication competency development. Future work should prioritise multimodal feedback enhancement and controlled comparative designs to evaluate educational effectiveness more rigorously.
AIM:To develop and validate SN-READY, a context-specific, self-reporting instrument that measures perceived disaster preparedness and self-efficacy among Spanish registered nurses. BACKGROUND:In light of the escalating frequency and severity of disasters, there is an imperative for a nursing workforce that can respond in an effective and coordinated manner. While the World Health Organization recognises the indispensable role of nurses in disaster health systems, there was previously no validated instrument to measure perceived preparedness specifically within the Spanish nursing context. DESIGN:Cross-sectional psychometric validation study. METHOD:A purposive sample of 301 registered Spanish nurses was recruited for the study. Participants were recruited via professional associations, hospital departments and social media. The SN-READY instrument was developed through a systematic literature review and expert content validation (assessed using I-CVI, S-CVI/Ave and modified Kappa). Psychometric validation was achieved through the implementation of a split-sample approach, with a sample size of 150 for the exploratory factor analysis (EFA) and 151 for the confirmatory factor analysis (CFA). The construct validity was analysed using exploratory factor analysis (polychoric correlations, oblique Promax rotation and parallel analysis) and confirmatory factor analysis (the WLSMV estimator). The convergent and discriminant validity of the model were evaluated using factor loadings, average variance extracted (AVE), the Fornell-Larcker criterion and HTMT ratios. The reliability of the system was assessed using three different methods: Cronbach's alpha, McDonald's omega and item-total correlations. The known-groups validity of the study was analysed using the Mann-Whitney U test. RESULTS:The EFA identified five factors of perceived disaster preparedness, accounting for 69.61% of the cumulative variance. The CFA confirmed adequate model fit (chi-square/df = 2.80; CFI = 0.92; TLI = 0.91; RMSEA = 0.07; SRMR = 0.06). The convergent validity of the model was supported by factor loadings greater than 0.40 and AVE values ranging from 0.54 to 0.69. Discriminant validity was confirmed via Fornell-Larcker criterion and HTMT ratios (< 0.90). The reliability of the instrument was found to be excellent, with Cronbach's alpha and McDonald's omega both measuring 0.96, and composite reliability ranging from 0.88 to 0.93. The results of the known-groups analysis demonstrated that nurses with formal disaster training obtained significantly higher scores (p < .001). CONCLUSIONS:The SN-READY scale demonstrates robust content, construct, convergent, and discriminant validity, along with excellent internal consistency. The instrument has been found to be psychometrically sound for the purpose of assessing perceived preparedness and self-efficacy in disaster management among Spanish nurses. Nevertheless, further criterion validity studies are required. The subsequent phases of the research process are recommended to be focused on the assessment of test-retest reliability and the validation of the simulation-based criteria.
BACKGROUND:The growing integration of artificial intelligence (AI) into healthcare is transforming nursing practice and clinical decision-making. However, evidence regarding the relationship between nursing students' attitudes toward AI and ethical sensitivity remains limited. AIM:This study examined the relationship between nursing students' attitudes toward AI and their ethical sensitivity in patient care and identified factors associated with these variables. METHODS:This descriptive, cross-sectional correlational study was conducted with 278 nursing students at a public university in Türkiye. Data were collected through an online survey using the Ethical Sensitivity Questionnaire in Nurses (ESQN), the Artificial Intelligence Attitude Scale-Short Form (AIAS-4), and a sociodemographic form. Data were analyzed using non-parametric tests, Spearman's correlation, and multiple linear regression analyses. RESULTS:The mean ESQ-N score was 39.82 ± 5.41, and the mean AIAS-4 score was 27.16 ± 6.82. Ethical sensitivity scores differed significantly according to AI ethics education (p = 0.008). AI attitudes differed significantly by academic year (χ2(3) = 8.04, p = 0.018), with fourth-year students reporting higher scores than first-year students (p_adj < 0.05). No significant correlation was found between ESQ-N and AIAS-4 scores (p > 0.05). Regression analyses showed that ethical sensitivity was predicted by academic year and AI ethics education (Adj. R2 = 0.13), whereas AI attitudes were predicted only by academic year (Adj. R2 = 0.15). CONCLUSIONS:Attitudes toward AI and ethical sensitivity appear to represent distinct dimensions of professional competence. Integrating AI-related ethical content into nursing curricula may support the development of both digital and ethical competencies in future nurses.
Background Although breast cancer survival rates have improved, routine admission-based holistic screening remains uncommon. A structured holistic needs assessment may help identify unmet supportive care needs and improve quality of life after diagnosis. Aims To assess holistic needs among hospitalized patients with breast cancer using the self-reported Sheffield Profile for Assessment and Referral for Care—Taiwan version (SPARC-T). Methods In this cross-sectional study, hospitalized patients with breast cancer completed the SPARC-T questionnaire at admission. Scores exceeding predefined thresholds triggered referrals for psychiatric, social work, or discharge planning services. Chi-square tests and logistic regression were used to examine the prevalence of holistic needs and their associated factor. Results A total of 115 patients participated, most with stage I or II breast cancer. More than 10% reported scores above the referral threshold in at least one SPARC domain. Spiritual distress was the most common concern (10.43%). Logistic regression showed that patients with stage II (OR = 3.69, p = 0.02) and stage IV disease (OR = 11.99, p = 0.03) were more likely to experience distress than those with stage I disease. These findings highlight the importance of addressing patient's holistic concerns. Conclusions SPARC-T is a feasible tool for assessing holistic needs in hospitalized patients with breast cancer. When integrated with an automated referral system, it may facilitate early identification of patients requiring multidisciplinary support. Implications for nursing practice Incorporating holistic needs assessment into routine breast cancer care may enhance patient-centered evaluation and supportive care, promoting overall well-being.
OBJECTIVE:This study aimed to investigate the impact of stigma and psychological resilience (PR) on the quality of life (QOL) of these caregivers and to explore the potential mediating role of PR in the relationship between stigma and QOL. METHODS:A cross-sectional study was conducted involving 334 primary caregivers of adolescents with depression recruited from two tertiary hospitals in Chongqing, China. Participants completed the Perceived Devaluation-Discrimination Scale (PDD), Psychological Resilience Scale-10 (CD-RISC-10), and the World Health Organization Quality of Life-BREF scale (WHOQOL-BREF). RESULTS:Structural equation modeling revealed that stigma had a direct negative effect on PR. PR, in turn, had a direct positive effect on QOL. After controlling for PR, the direct effect of stigma on QOL was not significant (path cplus:β = -0.102, 95% CI: -0.401, 0.039). The indirect effect of stigma on QOL through PR was statistically significant (β = -0.192, 95% CI:-0.362, -0.088), indicating a full mediation effect of PR. CONCLUSION:Stigma and PR are significant influence factor of the psychological and social QOL among caregivers of adolescents with depression. PR fully mediates the relationship between stigma and QOL. Interventions focused on enhancing PR may be particularly effective in improving the QOL for this population.
BACKGROUND:Cancer pain management competency among oncology nurses remains suboptimal, although it is essential for improving patient outcomes and quality of care. Existing evidence has primarily focused on individual-level determinants, such as knowledge, clinical experience, and training, whereas less is known about how organizational resources influence this competency. In particular, the psychological mechanisms through which perceived organizational support affects cancer pain management competency remain insufficiently understood. AIM:This study aimed to examine the association between perceived organizational support and oncology nurses' cancer pain management competency and to test the chain-mediating roles of psychological capital and pain management self-efficacy. METHODS:A multicenter cross-sectional survey was conducted among oncology nurses from 48 hospitals in Anhui Province, China, between July and September 2025. Eligible participants were registered nurses with at least one year of oncology nursing experience who provided informed consent. Nurses on leave or visiting nurses were excluded. Data were collected through an online survey comprising measures of demographic and professional characteristics, perceived organizational support, psychological capital, pain management self-efficacy, and cancer pain management competency. Spearman correlation analysis, group comparisons, and structural equation modeling were performed. Bias-corrected bootstrapping with 5000 resamples was used to test mediation effects. RESULTS:A total of 391 oncology nurses were included. Most participants were female (98.47%), held a bachelor's degree (91.05%), and worked in tertiary hospitals (86.70%). Perceived organizational support, psychological capital, pain management self-efficacy, and cancer pain management competency were significantly and positively correlated with each other (all P < 0.01). Structural equation modeling showed that perceived organizational support did not directly predict cancer pain management competency (β = 0.027; Boot SE = 0.050; 95% CI [-0.068, 0.127]). However, the total indirect effect was significant (β = 0.399; Boot SE = 0.046; 95% CI [0.313, 0.492]), accounting for 93.7% of the total effect. Two significant indirect pathways were identified: mediation through psychological capital alone (β = 0.149; Boot SE = 0.042; 95% CI [0.072, 0.239]) and chain mediation through psychological capital and pain management self-efficacy (β = 0.188; Boot SE = 0.030; 95% CI [0.137, 0.256]). The indirect pathway through pain management self-efficacy alone was not statistically significant (β = 0.062; Boot SE = 0.035; 95% CI [-0.005, 0.135]). CONCLUSIONS:Perceived organizational support was associated with oncology nurses' cancer pain management competency primarily through indirect psychological pathways, particularly the chain-mediating pathway involving psychological capital and pain management self-efficacy. Nursing managers, educators, and clinical leaders should combine supportive organizational environments with strategies that strengthen psychological capital and task-specific self-efficacy to improve cancer pain management competency and the quality of nursing care.
OBJECTIVE:To test a moderated mediation model examining how interpersonal management stress (IMS) is associated with nurses' intention to stay (NIS), focusing on the mediating role of proactive socialization behavior (PSB) and the moderating role of digital communication-collaboration literacy (DCCL). METHODS:A cross-sectional online survey was conducted with 305 registered nurses recruited from 12 hospitals in Western China via WeChat-based snowball sampling. Validated instruments measured IMS, PSB, DCCL, and NIS. Descriptive statistics and Pearson correlation analyses were performed using SPSS 30.0. Path relationships between variables were analyzed using AMOS 30.0. PROCESS macro v4.3 (Model 4, 6, 7, and 58) was employed to examine direct, mediating, and moderated mediating effects with 5000-10,000 bootstrap samples. RESULTS:PSB partially mediated the IMS-NIS association (β = -0.154, 95% CI [-0.242, -0.081]). This indirect effect was conditional on DCCL (index of moderated mediation = 0.054, 95% CI [0.026, 0.089]). The negative indirect effect of IMS on NIS via PSB was significant only when DCCL was below a key threshold (Johnson-Neyman point = 0.312; 30.9% of the sample), becoming non-significant at higher DCCL levels. Furthermore, high DCCL amplified the positive association between PSB and NIS by 62.6% compared to low DCCL. Nurses aged 31-40 years and those in tertiary hospitals exhibited relatively higher DCCL levels. CONCLUSION:PSB partially mediated the negative association between IMS and NIS, with DCCL acting as a dual-stage moderator. DCCL buffers the negative impact of IMS on PSB and enhances the positive impact of PSB on NIS, thereby weakening the indirect stress-retention link and strengthening retention intention. Nursing administrators should prioritize screening for low DCCL and implement dual-focused training to mitigate interpersonal stress and boost retention.
BACKGROUND:Nurses report frustration with and avoidance of mechanically ventilated patients with communication impairments. The SPEACS-2 program provides online training in patient communication assessment and assistive communication strategies. This study measured frustration and avoidance among ICU nurses and student nurses after SPEACS-2 training. PURPOSE:(1) Determine the relationship between frustration with communication and avoidance of patients who are difficult to understand; (2) Describe changes in frustration and avoidance after SPEACS-2 training relative to before (ICU nurses only); and (3) Compare post-training frustration and avoidance between ICU nurses and student nurses. METHODS:We conducted a descriptive, comparative secondary analysis of Nurse Communication Survey (NCS) data collected in two separate SPEACS-2 studies with ICU nurses and pre-licensure student nurses. ICU nurses completed the post-intervention survey 3 months after SPEACS-2 training, whereas student nurses completed the post-intervention survey 1 year after training. RESULTS:263 ICU nurses and 85 student nurses participated in the survey. Findings suggest a weak-to-moderate positive correlation between avoidance and frustration, indicating that participants who reported greater frustration also tended to report greater avoidance, although the relationship was modest (Spearman's ρ = 0.302, p < 0.0001). The ICU nurse group showed a significant change post-intervention in feeling frustrated (p = 0.0001) but no change in avoidance. Most ICU nurses (84.1%) and student nurses (87.0%) reported never or rarely avoiding contact with patients. CONCLUSION:The significant reduction in nurse frustration as a result of this communication training intervention may translate into greater nurse satisfaction and better patient experience.
AIM:To evaluate the effects of a 12-week Otago Exercise Program (OEP) on physical frailty and cognitive function in cognitively frail older adults residing in nursing homes. BACKGROUND:Cognitive frailty increases the risk of dementia, disability, and mortality in older adults. Exercise interventions are crucial for primary prevention, but evidence on the OEP for cognitively frail nursing home residents is limited. METHODS:A randomized controlled trial was conducted in a nursing home in Changsha. A total of 62 older adults aged 75-95 years with cognitive frailty were randomly assigned to the OEP group (n = 31) or control group (n = 31). The OEP group received 30-min sessions three times weekly for 12 weeks, comprising warm-up, resistance, and balance exercises. Both groups received monthly health education. Primary outcomes were physical frailty and cognitive function assessed at baseline, 6 weeks, and 12 weeks. RESULTS:The two-way repeated-measures ANOVA revealed significant time-by-group interactions for physical frailty and cognitive function (both F = 34.347, P < 0.001, partial η2 = 0.364, large effect size). Specifically, the OEP group exhibited superior improvements in reducing frailty severity and enhancing cognitive function compared with the control group. A significant main group effect was also observed (F = 4.397, P = 0.040), with the OEP group showing better overall outcomes. CONCLUSIONS:The 12-week OEP intervention effectively reduced physical frailty and improved cognitive function in cognitively frail nursing home residents. This simple program can be readily implemented by nursing staff in long-term care settings. TRIAL REGISTRATION:Clinical Trial Registry, ChiCTR2000039592 (registered 02/11/2020. Accessed on http://www.chictr.org.cn/index.aspx). The study was originally planned for 2020 but was postponed due to the COVID-19 pandemic; it was conducted in 2025 with no changes to the registered protocol.
BACKGROUND:The return to work from maternity leave is a time when the professional demands overlap with the new responsibilities of caring for children, which may result in psychological stress for nurses. Perceived social support can be a protective resource to buffer stress and promote adaptation. OBJECTIVE:To determine if perceived social support would moderate the relationship between occupational stress and psychological well-being for nurses who returned to work after childbirth. METHOD:A cross-sectional descriptive study was carried out in ten health care facilities in Dakahlia Governorate, Egypt. Four validated Arabic questionnaires were completed by a convenience sample of 200 nurses who had returned to work within 12 months after giving birth: a demographic questionnaire, a Brief Nursing Stress Scale, a 18-item Swedish adaptation of Ryff's Psychological Well-Being Scale, and a Perceived Social Support Scale for postpartum nurses. Descriptive statistics, correlation tests, multiple regression, and Hayes' PROCESS macro were used for analyses. RESULTS:Occupational stress had significant negative correlation with perceived social support (r = -0.332, p < .01) and psychological well-being (r = -0.506, p < .01). Psychological well-being was positively related to perceived social support (r = 0.410, p < .01). Occupational stress was a significant negative predictor of well-being (β = -0.506, p < .001) for regression results. Moderation analysis confirmed that the negative relationship between stress and well-being was significantly mitigated by perceived social support (β = 2.500, p < .001), accounting for 52% of the variance in well-being. CONCLUSION:The importance of perceived social support in decreasing stress and enhancing wellbeing of postpartum nurses suggests that multi-level supportive interventions are necessary.
Artificial intelligence (AI) has emerged as a transformative technology in nursing informatics. Despite rapid developments, evidence on AI's holistic integration into nursing practice remains fragmented. This review aimed to evaluate the effectiveness of integrating AI into nursing informatics for enhanced care planning, workflow optimization, and health outcome analysis. A systematic review was conducted using PubMed, CINAHL, Scopus, Web of Science, and IEEE Xplore databases. Search terms included “artificial intelligence,” “nursing informatics,” “care plan enhancement,” “workflow optimization,” and “health outcome analysis.” Studies published between January 2019 and December 2025 in English were included. Thirteen studies met eligibility criteria. Data were extracted using a standardized form and analyzed thematically. The results of this review revealed that AI-driven models improved diagnostic accuracy by 30% and personalized treatment plans by up to 70%. Workflow efficiency improved, with reductions of 50% in data processing time and 40% in scheduling efficiency. AI-enabled monitoring reduced hospital readmission rates by 15% and improved adherence to sepsis treatment protocols. Psychiatric nursing interventions demonstrated a 30% reduction in depressive symptoms and 40% improvement in treatment adherence. However, challenges included concerns about data privacy, algorithmic bias, and the need for adequate training. In conclusion, AI holds significant promise for advancing nursing informatics. To ensure ethical and effective integration, robust data security, bias mitigation, and tailored professional training are essential.
AIM:To develop a nurse-led clinical algorithm based on recommendations from high- and average-quality clinical guidance documents (CGDs), using the nursing process as a framework, to standardize sexual healthcare for female breast cancer survivors (FBCS) and clarify core nursing roles in multidisciplinary care. BACKGROUND:Sexual health is a prevalent yet frequently neglected concern among FBCS, significantly impacting their quality of life. Current evidence-summary literature synthesizes recommendations from CGDs, yet often fails to translate them into executable clinical pathways due to thematic fragmentation, definitional inconsistency and unclear leadership. METHODS:A systematic review was conducted for CGDs published from May 1, 2015, to May 1, 2025, following systematic review reporting guidelines. A structured problem-establishment model was applied. Methodological quality was assessed using a guideline-appraisal instrument. Recommendations for managing sexual health in FBCS were summarized from a nursing perspective to develop a nurse-led algorithm. RESULTS:Out of 2110 identified records, 13 CGDs were included. Thirty-five recommendations were synthesized into a framework comprising five categories: Fundamental Principles, Nursing Assessment, Nursing Diagnosis, Nursing Planning & Intervention, and Nursing Evaluation & Follow-up. This framework informed the development of a nurse-led clinical algorithm. CONCLUSIONS:By translating high-quality evidence into a structured nursing process framework, this algorithm operationalizes CGD recommendations into actionable interventions and standardizes survivorship care, potentially enhancing team coordination and clarifying nursing roles. In the future, we should focus on continuously refining the algorithm by incorporating emerging evidence. Additionally, researchers could further explore the integration of adjacent themes within the nursing process framework. REGISTRATION:Not registered.
Purpose Newly established hospitals often face difficulty retaining young nurses due to organizational instability; however, traditional compensation-based strategies may be insufficient. This study examined the relative contribution of person–environment fit factors—emotional intelligence, emotional leadership, and work–life balance—to job embeddedness among young shift-working nurses in a newly established hospital. Methods This cross-sectional descriptive correlational study included 132 shift-working nurses younger than 30 years who were employed at a newly established university hospital in South Korea, which opened in 2021. Data were collected using the Wong and Law Emotional Intelligence Scale, the Emotional Leadership Scale, the Work–Life Balance Scale, and the Job Embeddedness Scale. Hierarchical multiple regression analysis was conducted. Results Hierarchical regression analysis showed that demographic variables alone accounted for 10.5% of the variance in job embeddedness in Model 1. After the fit-related variables were added in Model 2, the explanatory power increased significantly to 40.8% (ΔR2 = 30.4%, p < .001). Emotional intelligence emerged as the strongest predictor (β = 0.29, p < .001), followed by work–life balance (β = 0.27, p = .001) and emotional leadership (β = 0.21, p = .017). Notably, work unit, which was significant in Model 1, was no longer significant after the inclusion of fit-related variables. Conclusions In the context of organizational instability, job embeddedness was more strongly associated with fit-related proxy variables conceptually related to person–environment fit than with structural characteristics alone. These findings suggest that fit-oriented strategies may help support nurse retention in resource-constrained, newly established healthcare organizations.
BACKGROUND:Missed nursing care compromises patient safety and care quality worldwide. Although inadequate staffing, high workloads, and poor work environments contribute, brief structured team interventions may reduce care omissions. Proactive huddles aim to enhance communication, coordination, and early risk identification, yet the mediating role of safety climate remains unclear. OBJECTIVE:To evaluate the effectiveness of proactive huddles in reducing missed nursing care and examine the mediating role of safety climate. DESIGN:Randomized controlled design. METHODS:Data were collected between July 2022 and May 2023 from ten hospital wards, pair-matched by type and size and randomly assigned to proactive huddles or usual practice. The sample comprised 180 nurses (85 intervention, 95 control). The MISSCARE Survey, Safety Organizing Scale, and NASA Task Load Index were administered pre- and post-intervention across three shifts. Linear mixed-effects models and moderated mediation analysis were conducted. RESULTS:Proactive huddles were associated with improved safety climate compared with usual practice (b = -0.217, p < .001) and with reduced missed nursing care (b = 0.123, p < .001). Higher safety climate was associated with lower missed nursing care (b = -0.184, p < .001). Moderated mediation indicated a greater mediated reduction in missed nursing care via safety climate in the intervention group (difference in average causal mediation effect = -0.038; 95% CI [-0.059, -0.018]; p < .0001). CONCLUSION:Proactive huddles may offer a feasible, time-efficient strategy for reducing missed nursing care. Safety climate may be one mechanism linking structured communication with improved care quality, alongside other team-level mechanisms.
Background Measuring nursing workload is essential for staffing decisions and patient allocation, yet evidence remains limited on whether the PERROCA Patient Classification System reflects actual nursing workload across heterogeneous hospital settings. Purpose To evaluate the strength and independence of the association between PERROCA Patient Classification System and nursing workload, measured as real-time recorded nursing care time, across different hospital ward settings. Methods We conducted a prospective multicentre cross-sectional study in 12 wards across five hospitals. Adult inpatients present on designated study days were enrolled. Nursing workload was measured as the total time spent on nurse-performed activities over 24 h. Associations were analysed using linear regression, mixed-effects linear regression with ward-level clustering, and logistic regression. Results A total of 472 patients were included. Median PERROCA score was 17, and median total daily nursing care time was 155 min. In simple linear regression, each 1-point increase in PERROCA was associated with 12.8 additional minutes of nursing care time. In the mixed model, PERROCA remained independently associated with nursing care time, with 7.45 additional minutes per point increase. High nursing workload occurred in 112 patients (23.7%), and PERROCA was independently associated with this outcome. Conclusions PERROCA was significantly associated with nursing workload and may represent a practical tool for estimating nursing workload across different hospital ward settings.
BACKGROUND:Atrial fibrillation (AF) is associated with a significant clinical and psychosocial burden. It requires adequate informational, emotional, and functional support in addition to evidence-based treatment. Existing social support measures are largely generic and do not address the specific needs of AF care. AIM:To develop and psychometrically validate the Social Support for Patients with Atrial Fibrillation Instrument (SSAFI). METHODS:A methodological, cross-sectional validation study was conducted among 265 adults with AF in Finland. Data were collected using an online survey. Item characteristics were examined using descriptive statistics and correlation analyses. Exploratory factor analysis (EFA) was applied to examine empirical clustering patterns, followed by confirmatory factor analysis (CFA) to test a theoretically derived hierarchical model. Model fit, internal consistency, and construct validity were evaluated using established psychometric criteria. RESULTS:EFA suggested source-influenced clustering, whereas CFA supported a hierarchical model with informational, emotional, and functional support domains, showing acceptable fit (χ2/df = 2.29; CFI = 0.936; TLI = 0.926; IFI = 0.937; RMSEA = 0.077). Standardized loadings ranged from 0.301 to 0.864 with weaker loadings interpreted cautiously according to the predefined retention criterion, second-order loadings were strong (λ = 0.928-0.963), and reliability and validity indices supported the multidimensional structure. CONCLUSIONS:The SSAFI demonstrated satisfactory psychometric properties and provides a disease-specific tool for assessing perceived informational, emotional, and functional support. At the group and service levels, the instrument may provide nursing services and healthcare systems with a structured means to identify perceived gaps in patient education and support, informing the development of nurse-led AF care pathways.
BACKGROUND:Nursing handoff is critical for patient safety but faces challenges like unstructured communication. While standardized assessment tools exist internationally, China lacks such a tool for evaluating handoff competency. This study aimed to translate and validate the Nursing Handoff Competency Scale (NHCS) for use in China. DESIGN:A methodological study comprising cross-cultural adaptation and psychometric validation. METHODS:Following the Brislin model, the NHCS was translated and cross-culturally adapted via Delphi expert consultation (18 experts) and pilot testing (10 nurses). Psychometric evaluation involved 285 nurses from tertiary hospitals. Content validity, construct validity, internal consistency (Cronbach alpha and McDonald omega), and split-half reliability were assessed. RESULTS:The final 23-item, four-dimensional scale showed acceptable content validity (S-CVI = 0.961, modified kappa = 0.833-1.000), internal consistency (Cronbach's α = 0.977, McDonald's ω = 0.979), and a four-factor structure explaining 84.639% of variance. CFA indicated acceptable fit (χ2/df = 2.666, RMSEA = 0.077, CFI = 0.958, TLI = 0.952). CONCLUSION:The Chinese NHCS demonstrated satisfactory psychometric properties, providing initial evidence for assessing nursing handoff competency in China. Further validation in diverse settings is recommended.
