Conectar
by Yu Cui, Yuxuan Gao, Na Meng, Xiaojuan Li, Na Zhao, Lili Yu
Atezolizumab is a widely used immune checkpoint inhibitor (ICI) for cancer treatment, and postmarketing testing is important. This study aims to provide a reference for the safe and rational use of drugs in clinical practice by mining and analyzing the adverse event (AE) signals of atezolizumab on the basis of the FDA Adverse Event Reporting System (FAERS). This research extracted AE reports from the second quarter (Q2) of 2016 to Q2 of 2024 from the FAERS. AEs were standardized and classified on the basis of the System Organ Class (SOC) and Preferred Term (PT) from the Medical Dictionary for Regulatory Activities (MedDRA) version 23.0. This study utilized disproportionality analysis (DPA) for signal mining and analysis, including the reporting odds ratio (ROR) method, the Medicines and Healthcare Products Regulatory Agency (MHRA) method, and the Bayesian confidence propagation neural network (BCPNN) method. We obtained a total of 3,124 AE signals and identified 640 PTs and 21 SOCs for atezolizumab. The highest signal intensity was systemic immune activation (n = 15, ROR = 449.20, PRR = 449.07, IC = 8.06), and the most frequently reported AEs were death, pyrexia, infectious pneumonia, anaemia, and febrile neutropenia. The top 100 PTs in terms of signal intensity involved a total of 16 SOCs, including those associated with endocrine disorders; respiratory, thoracic and mediastinal disorders; and renal and urinary disorders. This study revealed that AEs in the endocrine, respiratory and urinary systems need to be monitored in clinical practice.Acute pain following pulmonary surgery can affect the recovery process of patients. The use of intrathecal morphine (ITM) injections offers a long-lasting analgesic effect, but its clinical application remains controversial. This study aims to investigate the impact of combining bupivacaine with ITM injections on the quality of postoperative recovery in patients who have undergone pulmonary surgery.
This multicentre, randomised, double-blind, controlled trial will enrol 254 patients undergoing elective lung surgery, who will be randomly assigned in a 1:1 ratio to either group IT (receiving an intrathecal injection of 3 mg bupivacaine and 0.25 mg morphine before general anaesthesia induction) or the control group (C group). The primary outcome includes postoperative recovery quality on day 1 (quality of recovery, QoR-15), with secondary outcomes encompassing postoperative recovery quality on days 2 and 3 (QoR-15), pain scores within 72 hours postoperatively, analgesic rescue, intraoperative haemodynamic parameters, opioid consumption, postoperative adverse reactions, recovery metrics, complications, chronic pain incidence and sleep quality.
The results will be disseminated through peer-reviewed publications. This study protocol (V.2.0, 30 October 2024) involves human participants and has been approved by the Ethics Committee of Affiliated Hospital of Yangzhou University (number 2024-08-02-2), Taicang Hospital Affiliated to Soochow University (number 2025 SR-041) and Yichang Central People’s Hospital (number 2024-513-02). Each individual who agrees to participate in the research will provide written informed consent after the objectives and procedures of this study are explained to them.
ChiCTR2400092935. Registered on 26 November 2024.
The optimal maternal age at childbirth has been a topic of bourgeoning literature, with earlier ages offering physiological benefits for maternal recovery. In contrast, later ages to give birth may provide psychological advantages due to greater emotional maturity. This study investigates the impact of maternal age at childbirth on children’s internalising problems and explores the mediating roles of housing instability and family support in this relationship.
Cross-sectional study; mediation analysis of the 2022 National Survey of Children’s Health (NSCH) data.
Response in the 2022 NSCH in the USA.
This study is based on the 2022 NSCH, collecting a total of 54 103 completed surveys from randomly selected households across the USA. In this study, after excluding participants due to missing values in critical variables, 48 073 participants were included in the final analysis.
Our findings are consistent with the hypothesis that increasing maternal age at childbirth is associated with lower children’s internalising problems. Analysis suggested this association operates directly and is indirectly linked to child outcomes through lower levels of housing instability and higher levels of family support. However, a distinct indirect effect emerged: increased maternal age was also associated with reduced family support, which was in turn linked to more internalising problems. The results illuminate potential mechanisms linking maternal age at childbirth to children’s internalising problems and underscore the importance of stable housing and family support in mitigating risk factors for children’s emotional well-being.
We found an association between advanced maternal age and fewer internalising problems in children. This relationship appears to operate directly and indirectly via a sequential pathway: higher maternal age correlates with lower housing instability, which in turn is associated with increased family support, ultimately correlating with improved child mental health outcomes.
Active self-management by patients following acute coronary syndrome (ACS) can reduce recurrent events. Patient education for transitioning from hospital to home promotes effective self-management but can be limited in the acute setting due to time and resource pressures. Patients from ethnic minority and immigrant backgrounds face additional language, cultural and health literacy barriers to receiving patient education. Self-administered virtual patient education presents an innovative solution to these challenges. This study aims to evaluate a co-adapted, virtual avatar nurse-guided, discharge education application (app) for Chinese-speaking patients following ACS.
This multicentre, assessor-blinded, randomised controlled trial will recruit 98 Chinese-speaking inpatients following ACS with evaluation at 1 and 3 months postdischarge. Control participants in the control group will receive the usual ward-based patient discharge education. Intervention participants will additionally receive the education app installed on their devices before hospital discharge with unlimited access during the study period. Cultural relevance and linguistic accuracy for this Chinese version of an existing app were ensured through co-adaptation with Chinese-speaking consumers; the primary outcome will be coronary heart disease (CHD) knowledge, and secondary outcomes will include knowledge, attitudes and beliefs regarding heart attack symptoms and responses, CHD self-management behaviours, utilisation of healthcare services and quality of life. A process evaluation will be conducted alongside the trial to assess the acceptability and feasibility of the app. Between-group comparisons will be made using 95% CIs, accounting for baseline differences using linear mixed effects or mixed effects logistic regression models.
The Western Sydney Local Health District Human Research Ethics Committee has approved this study protocol (26 February 2024, amendment number 2) (2024/STE00147), with site-specific authorisations obtained from each participating hospital. The results will be disseminated through peer-reviewed journal articles and presentations at scientific conferences.
ACTRN12624000408583.
by Ruyi Li, Shaoping Jiang, Zhaoke Pi, Guisu Chen
Pathological and neuroimaging changes in the cerebellum of Alzheimer’s disease (AD) patients have been well documented. However, the changes in cerebellar amyloid plaque deposition connectivity networks during AD progression based on positron emission tomography (PET) imaging remain unclear. We selected 18F-florbetapir PET (18F-AV45 PET) imaging data from the Alzheimer’s disease neuroimaging initiative (ADNI) dataset (n = 612) and employed graph theoretical analysis to examine amyloid plaque deposition connectivity, comparing the connectivity differences across cognitively normal (CN), early mild cognitive impairment (EMCI), late mild cognitive impairment (LMCI), and AD groups. In addition, we combined graph theoretical features with the standardized uptake value ratio (SUVR) of regions of interest and applied them to machine learning models for the early diagnosis of AD. As cognitive decline progressed, significant changes in cerebellar network connectivity were observed across groups. Regarding local connectivity, changes in betweenness centrality were evident in multiple cerebellar regions at different cognitive stages. Cerebellar amyloid networks revealed early changes in amyloid plaque deposition connectivity. The machine learning model achieved an area under the curve (AUC) of 0.950 for distinguishing AD from CN, 0.995 for CN vs. EMCI, 0.964 for EMCI vs. LMCI and 0.632 for LMCI vs. AD. These findings provide new insights into the cerebellar pathological features of AD and highlight the potential of this approach for early identification and prediction of AD progression.Atrial fibrillation (AF), with a prevalence of 1–2%, is the most common cardiac arrhythmia. AF is associated with a fivefold increased risk of cardioembolic events; approximately 20% of all strokes are caused by AF. Pulmonary vein isolation (PVI) has become the first-line treatment for AF. However, PVI cannot eliminate the residual stroke risk. Current guidelines recommend that anticoagulation be continued in this specific group of patients, regardless of the presence or absence of AF. In this large AF population post-PVI, who are considered to be in an earlier stage of AF, it is unknown whether left atrial appendage closure (LAAC) offers an alternative to direct oral anticoagulant (DOAC) therapy.
The trial will be a prospective, randomised, multicentre non-inferiority study comparing two treatment strategies in AF patients after atrial ablation. Patients will be randomly assigned to either percutaneous LAAC (group A) or DOAC treatment (group B) in a 1:1 ratio; both sequential and concomitant planned ablation with or without LAAC are accepted. Randomisation will be conducted using web-based randomisation software. A total of 1012 participants (506 patients per group) will be enrolled. The primary effectiveness measure will be the occurrence of any of the specified events within 24 months after randomisation: stroke/transient ischaemic attack/systemic thromboembolism, cerebral haemorrhage, other major haemorrhages (Bleeding Academic Research Consortium ≥2), cardiovascular mortality and all-cause mortality.
The study was approved by the Ethical Review Board of Shanghai Chest Hospital, China (KS(Y)20287). Written informed consent will be obtained from all participants. The trial will follow the Declaration of Helsinki and Good Clinical Practice. Confidentiality will be maintained with anonymised, securely stored data. Findings will be disseminated through peer-reviewed publications and conferences.
ChiCTR2000036538.
To combine the Job Demand-Resource (JD-R) model with machine learning (ML) techniques to identify the key factors affecting job burnout (JB) among Chinese nurses.
A Cross-Sectional Study.
This study utilised a stratified sampling method to recruit 3449 eligible nurses from eight cities in Shandong Province between June and December 2021. After data cleaning, 2998 valid samples were retained. The dataset was randomly split into a training set (75%) and a test set (25%). The Boruta algorithm was used to select relevant variables for model construction. Six-millilitre models were compared using cross-validation, with mean absolute error (MAE), root mean square error (RMSE) and R-squared (R 2) used to select the best model. The Shapley Additive Explanation (SHAP) method was used to identify key predictors of JB.
The average JB score among nurses was (32.88 ± 11.45). Among the 20 variables, 17 were identified by the Boruta algorithm as strongly associated with JB, including 7 job demand-related variables and 10 job resource-related variables. After comparing 6-ml models, the Random Forest was identified as the optimal model (MAE = 6.56, RMSE = 8.86, R 2 = 0.63). SHAP analysis further revealed the importance ranking of these 17 variables and identified four key predictors: psychological distress (SHAP = 4.07), perceived organisational support (SHAP = 2.03), emotional intelligence (SHAP = 1.81) and D-type personality (SHAP = 1.73).
By integrating the JD-R model framework, ML algorithms proved effective in identifying critical predictors of nurses' JB. SHAP analysis identified four primary determinants: psychological distress, perceived organisational support, emotional intelligence and D-type personality. These findings provide novel insights for nursing administrators to optimise intervention strategies.
Not applicable.
This study did not include patient or public involvement in its design, conduct or reporting.
To systematically review published studies on fall risk prediction models for inpatients.
A systematic review and meta-analysis of prognostic model studies.
A literature search was carried out in Web of Science, the Cochrane Library, PubMed, Embase, CINAHL, SinoMed, VIP Database, CNKI and Wanfang Database. The search covered studies on risk prediction models for falls in inpatients from inception to March 9, 2024.
The research question was formulated using the PICOTS framework. Data extraction was performed following the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS). The quality of studies related to risk prediction models was evaluated with the Prediction Model Risk of Bias Assessment Tool (PROBAST). Meta-analysis was conducted using STATA 18.0 software.
A total of 15 studies were included, with 13 eligible for meta-analysis. Only 2 of these 15 studies had external validation. The reported AUC values ranged from 0.681 to 0.900. The overall risk of bias was high, mainly attributed to inappropriate data sources and improper processing in the analysis domain. The pooled AUC from the meta-analysis was 0.799. After reviewing the predictors included in various models, FRIDs, fall history, age, gait, mental status, gender and incontinence were relatively common.
The fall risk prediction model for inpatients performs well overall, but it has a high risk of bias. Future development of risk prediction models should strictly adhere to the PROBAST, combine clinical reality, optimise study design and improve methodological quality.
This study provides medical professionals with a clear overview of constructing fall risk prediction models for inpatients. The fall-related predictors in these models help healthcare providers identify high-risk patients and implement preventive strategies. It also offers valuable insights for the development of future prediction models.
This study did not include patient or public involvement in its design, conduct, or reporting.
Chronic non-specific low back pain (CNLBP) is a multifactorial disease involving physical dysfunction and psychological distress. Acupuncture and mindfulness-based stress reduction (MBSR) are two non-pharmacological therapies recommended by guidelines, which have been proven effective in improving the clinical symptoms of CNLBP. However, the efficacy of their combined use has yet to be explored. This study aims to explore whether the combination of acupuncture and MBSR would have different synergistic effects in patients with CNLBP compared with acupuncture or MBSR alone.
This protocol describes a randomised controlled trial with a 2x2 factorial design involving 120 CNLBP patients. Participants will be randomly allocated to four groups: (1) acupuncture, (2) MBSR, (3) acupuncture combined with MBSR, and (4) health education. The intervention period is 6 weeks. The outcome measurements will include the Visual Analogue Scale (VAS), Tactile Acuity Test, Short-form of McGill Pain Questionnairethe(SF-MPQ); Roland-Morris Functional Disability Questionnaire (RMDQ), Oswestry Disability Index(ODI), the Five Facet Mindfulness Questionnaire (FFMQ), the 21-item Depression Anxiety Stress Scales (DASS-21), the Regulatory Self-Efficacy Scale (RESE), the Beck Depression Inventory (BDI-II), the Beck Anxiety Inventory (BAI), the Fear-Avoidance Beliefs Questionnaire (FABQ) and the Pain Catastrophizing Scale (PCS);Pain Sensitivity Questionnaire(PSQ); Pittsburgh Sleep Quality Index(PSQI). All evaluations will be conducted at the baseline stage as well as 6 weeks and 4 months after the implementation of the intervention measures.
Ethics approval was obtained from the Ethics Committee of the Affiliated Rehabilitation Hospital of the Fujian University of Traditional Chinese Medicine (2024KY-041-04). The results of the study will be disseminated through peer-reviewed publications and at scientific conferences.
ITMCTR2025000764.
by Achilleas Livieratos, Maria Kudela, Yuxi Zhao, All-shine Chen, Xin Luo, Junjing Lin, Di Zhang, Sai Dharmarajan, Sotirios Tsiodras, Vivek Rudrapatna, Margaret Gamalo
BackgroundNetwork meta-analysis (NMA) can compare several interventions at once by combining head-to-head and indirect trial evidence. However, identifying, extracting, and modelling these often takes months, delaying updates in many therapeutic areas.
ObjectiveTo develop and validate MetaMind, an end-to-end, transformer-driven framework that automates NMA processes—including study retrieval, structured data extraction, and meta-analysis execution—while minimizing human input.
MethodsMetaMind integrates Promptriever, a fine-tuned retrieval model, to semantically retrieve high-impact clinical trials from PubMed; a multi-agent LLM architecture--Mixture of Agents (MoA)-- pipeline to extract PICO-structured (Population, Intervention, Comparison, Outcome) endpoints; and GPT-4o–generated Python and R scripts to perform Bayesian random-effects NMA and other NMA designs within a unified workflow. Validation was conducted by comparing MetaMind’s outputs against manually performed NMAs in ulcerative colitis (UC) and Crohn’s disease (CD).
ResultsPromptriever outperformed baseline SentenceTransformer with higher similarity scores (0.7403 vs. 0.7049 for UC; 0.7142 vs. 0.7049 for CD) and narrower relevance ranges. Promptriever performance achieved 82.1% recall, 91.1% precision and an F1 score of 86.4% when compared to a previously published NMA. MetaMind achieved 100% accuracy on a limited set of remission endpoints regarding PICO (Population, Intervention, Comparator, Outcome) element extraction and produced comparative effect estimates and credible intervals closely matching manual analyses.
ConclusionsIn our validation studies, MetaMind reduced the end-to-end NMA process to less than a week, compared with the several months typically needed for manual workflows, while preserving statistical rigor. This suggests its potential for future scaling of evidence synthesis to additional therapeutic areas.
Loneliness and social isolation are prevalent and persistent in cancer patients, affecting their psychosocial adjustment. Non-pharmacological interventions have been shown to be effective in previous studies; however, the most effective types of non-pharmacological interventions for this population remain unclear.
The aim of this systematic review and network meta-analysis (NMA) was to synthesize the existing evidence and compare the effectiveness of different types of non-pharmacological interventions in treating loneliness and social isolation among cancer patients.
A systematic search was conducted in PubMed, Web of Science, Cochrane Library, Embase, CINAHL, PsycINFO, and MEDLINE databases from their inception to December 2024. Randomized controlled trials (RCTs) evaluating non-pharmacological interventions targeting loneliness and social isolation in cancer patients were included. NMA was performed using Stata 17.0 software under a frequentist framework.
A total of 13 RCTs were included, including 9 non-pharmacological interventions and 1151 cancer patients. In order of probability, group logotherapy (SUCRA: 99.9%, SMD: −1.62, 95% CI: −2.23 to −1.01) was the most effective intervention for alleviating loneliness and social isolation, followed by psychoeducational therapy (SUCRA: 76.9%, SMD: −0.62, 95% CI: −1.16 to −0.07) and supportive expressive group therapy (SUCRA: 65.7%, SMD: −0.40, 95% CI: −0.75 to −0.05).
The NMA suggests that, in terms of short-term efficacy, group logotherapy may be considered the optimal choice for reducing loneliness and social isolation levels in cancer patients. Healthcare professionals could regularly conduct group logotherapy among cancer patients to promote their psychosocial adaptation.
PROSPERO Registration Number: CRD42024616937
Coronary artery bypass grafting (CABG) is a technically demanding procedure where surgical skill directly influences outcomes. Traditional evaluation relies on expert subjective judgement, which is resource-intensive and lacks scalability. The emergence of computer vision and deep learning offers potential for objective, automated skill assessment. Prior research has explored phase recognition and gesture classification in surgery; however, few studies have applied AI-driven evaluation in high-stakes cardiac procedures. Therefore, the objective of this study is to develop and validate an artificial intelligence (AI)-based framework for the automated assessment of surgical technical skills in CABG using real-world surgical videos, benchmarked against expert ratings.
This study is a prospective, single-centre observational study conducted in a high-volume surgical hospital. Eligible participants are adult patients undergoing elective CABG with complete intraoperative video data. Videos are analysed using a hybrid AI pipeline to generate scores based on visual impression and tool trajectory accuracy. The primary outcome is the feasibility of AI annotation, that is, the intraclass correlation coefficient value of AI predicted score and human rating data. Secondary outcomes include the consistency between AI and expert skill assessments, analysis of surgical instrument trajectories and the correlation of AI-derived skill scores with intraoperative graft flow and resistance. Exploratory outcomes aim to correlate surgical skill with graft patency at 1 year and major adverse cardiovascular events within 6 months and 12 months postoperatively.
The Ethics Committee in Fuwai hospital approved this study (2024-2563). The results of the study will be submitted for publication in a peer-reviewed journal.
This study aimed to investigate the self-management experiences of individuals living with systemic lupus erythematosus (SLE) through the lens of the Capability, Opportunity, and Motivation-Behaviour model to inform the design of personalised self-management interventions.
A phenomenological method, common in qualitative research, was used. Data were collected using semistructured in-depth interviews. Data collection and analysis were conducted concurrently, guided by the principle of reaching data saturation. The data were evaluated using thematic analysis.
The study was conducted in a quiet, private setting, either a classroom or consultation room, free from external disturbances.
Between March and September 2023, 15 individuals diagnosed with SLE who met the inclusion criteria participated in the in-depth interviews.
A total of 15 patients were interviewed, and 3 themes and 9 subthemes regarding self-management experiences were extracted: (1) Capability level: Deficiency in disease knowledge and insufficient self-management skills; (2) Motivation level: Lack of self-management awareness, perceived benefits and risks, uncertainty about disease progression and appearance-related anxiety; (3) Opportunity level: Family understanding and support, social support and environmental facilitation.
SLE patients’ self-management behaviours are influenced by both personal experiences and external environments. Healthcare professionals should enhance health education, deliver individualised guidance, strengthen patients’ self-management awareness and psychological positivity, optimise medical resource allocation, and bolster social support to improve patients’self-management capabilities.
To describe self-care behaviours and explore factors associated with self-care behaviours in older adults with multiple chronic conditions (MCCs).
The prevalence of MCCs is increasing in a rising trend. MCCs complicate the self-care behaviours of older adults. There is limited evidence regarding the factors associated with self-care behaviours in older adults with MCCs.
A cross-sectional design was adopted using the convenience sampling method.
Participants were recruited from a community health service centre. Measurements included the Self-Care of Chronic Illness Inventory, a single item for loneliness, the 6-item Lubben Social Network Scale, the 4-item Patient Health Questionnaire, the 15-item Tilburg Frailty Indicator, and a self-developed questionnaire for sociodemographic and disease-related characteristics. Descriptive statistics were used as appropriate. Multiple linear regression and multivariate logistic regression were adopted to examine the influencing factors.
A total of 223 participants were enrolled in this study. Among the 223 participants, 49.3%, 32.7% and 28.7% achieved a cut-off score of ≥ 70 in self-care maintenance, monitoring and management, respectively. The linear regression models indicated that smoking status, frailty and self-care confidence were significantly associated with self-care maintenance; education level, per capita monthly household income and self-care confidence were significantly associated with self-care monitoring; and employment status and self-care confidence were significantly associated with self-care management. In addition, multivariate logistic regression showed that living in cities or towns was significantly associated with higher odds of adequate self-care management.
Three domains of self-care behaviours were influenced by distinct factors, and self-care confidence demonstrated consistent associations with all three domains of self-care behaviours. Self-efficacy-focused interventions may have the potential to promote self-care behaviours in older adults with MCCs.
Healthcare providers need to take into account the pivotal factors influencing self-care behaviours of this cohort to deliver structured and effective education and support. Clinicians should consider adopting confidence-building strategies in routine education for this cohort.
We adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.
No patient or public contribution.
To refine fall risk assessment scale among older adults with cognitive impairment in nursing homes.
A cross-sectional survey.
Mokken analysis was conducted to refine the assessment scale based on unidimensionality, local independence, monotonicity, dimensionality, and reliability. Data were gathered from cognitively impaired older adults in a nursing home from January to February 2023. Trained nursing assistants conducted face-to-face assessments and reviewed medical records to administer the scale.
Emotion and State Dimension did not meet unidimensionality criteria (H = 0.14), particularly item Q9, which also violated local independence. Monotonicity analysis showed all items exhibited monotonic increases. After refinement at c = 0.3, the scale consists of nine items. With increasing c-values, the first seven items were ultimately retained to form the final version of the scale. Both optimised scales (9-item and 7-item) satisfied reliability requirements, with all coefficients (Cronbach's α, Guttman's lambda-2, Molenaar-Sijtsma, Latent Class Reliability Coefficient) ≥ 0.74.
The scale is suitable for assessing fall risk among older adults with cognitive impairment, with a unidimensional scale of the first seven items recommended for practical use. Future efforts should refine the scale by exploring additional risk factors, especially emotion-related ones.
The refined 7-item scale provides nursing home staff with a practical, reliable tool for assessing fall risk in cognitively impaired older adults, enabling targeted prevention strategies to enhance safety and reduce injuries.
The refined 7-item scale provides nursing home staff with a reliable, practical, and scientifically validated tool specifically designed for assessing fall risk in older adults with cognitive impairment. Its simplicity enables efficient integration into routine clinical workflows, empowering caregivers to proactively identify risk factors and implement timely, targeted interventions. This approach directly enhances resident safety by translating assessment results into actionable prevention strategies within daily care practices.
This study was reported in accordance with the STROBE guidelines.
No Patient or Public Contribution.
To examine published studies on nursing academics' experience with student incivility, explore their management strategies, and identify existing knowledge gaps.
This scoping review was guided by Arksey and O'Malley's five-stage framework.
Studies published between 2009 and June 2024 in English were retrieved from PubMed, CINAHL Complete, ProQuest, and Scopus.
The review included qualitative, quantitative, and mixed-methods studies on nursing academics' experiences or perceptions of student incivility and/or interventions to manage it in higher education. Data were analysed using descriptive methods.
Thirty-five studies met the inclusion criteria. The studies mostly explored nursing academics' experiences (n = 18) or perceptions (n = 15) of student incivility. Of the eleven studies that investigated how academic staff address student incivility, nine were interventional studies and two qualitative studies explored academics' experiences.
The prevalence of reported nursing student incivility is substantial in the literature, yet there is limited evidence on sustainable, targeted management strategies to address the issue and support nursing academics.
Further research is needed to evaluate the feasibility and long-term effectiveness of strategies and interventions aimed at reducing student incivility and to explore effective management strategies adopted by nursing academics across diverse cultural and online learning settings. It is critical to develop interventions that address the root causes of student nurse incivility and strengthen institutional support systems.
This scoping review addresses gaps in the literature on managing nursing student incivility across diverse learning environments, providing evidence to inform the development of contextually appropriate strategies that support nursing academics in managing incivility effectively within evolving educational settings.
This review followed the PRISMA Extension for Scoping Review (PRISMA-ScR) Checklist.
No patient or public involvement.
FreshRSS 