Journal of Clinical Nursing最新文献

Aim(s): The aim was to validate the stoma self-efficacy scale and assess the psychometric properties of the Czech version of the scale in patients with intestinal stoma. Another aim was to assess self-efficacy in patients with intestinal stoma.

Design: Descriptive, cross-sectional and validation study.

Methods: Two hundred and ninety patients with intestinal stoma participated in the study during 2023. The original SSES instrument was linguistically validated into Czech. Content validity of the scale, test-retest, intraclass coefficient, Cronbach's alpha, McDonald's ω, construct and convergent validity were assessed for psychometric properties. The study followed STROBE guidelines.

Results: The stoma self-efficacy scale was adopted into Czech, demonstrating excellent content validity. An intraclass correlation coefficient was calculated to establish test-retest reliability, showing excellent reliability of the Czech version. Cronbach's alpha and McDonald's ω showed high reliability. Factor analysis was applied for construct validity. Exploratory factor analysis was used to extract three factors on the Czech version of the scale: Stoma care self-efficacy, social self-efficacy and burden self-efficacy. The factors accounted for 62.05% of the total variance and showed strong internal consistency. Confirmatory factor analysis was applied separately to the data of respondents with colostomy and respondents with ileostomy. The fit indices were satisfactory for respondents with colostomy after adjustment. The composite reliability coefficient showed acceptable values in each factor.

Conclusion: The Czech version of the stoma self-efficacy scale has excellent psychometric properties in patients with intestinal stoma. It is a reliable tool for use in patients with intestinal stoma to assess self-efficacy. The scale can also be used by nurses who care for these patients and based on this, meet the individual needs related to patients' self-efficacy.

Aim(s): To develop theories about how Nursing Associate (NA) roles are implemented and working within NHS practice: What works, for whom, in what contexts and how?

Methods: Rapid realist synthesis of: (1) empirical and grey literature; (2) realist interviews with stakeholders. Sources were analysed using a realist approach that explored the data for novel or causal insights to generate initial programme theories.

Results: Empirical and grey sources (n = 15) and transcripts from stakeholder interviews (n = 11) were synthesised which identified three theory areas relating to NA implementation: (1) Scope of NA role: Communication and expectations; (2) Variations to the NA model of working; and (3) Career progression: Entry point, stepping stone and career in itself.

Conclusion: The NA holds the potential to improve nursing workforce stability by encouraging locally based, non-registered healthcare staff to transition to an NA. However, the lack of collective understanding of the NA scope of practice can cause staff friction. It is unknown whether this friction will reduce over time or if staff divisions will lead to further deterioration of the workforce.

Implications for the profession and/or patient care: Ongoing clear communication regarding NA scope of practice needs to be provided to aid understanding of their supplementary role and its potential contribution to nursing teams.

Impact: This work represents a first step to support both researchers and nursing workforce leaders in furthering knowledge of the impact of integrating NAs in diverse healthcare contexts and to unearth the mechanisms underpinning the success or failure of this new role.

Reporting method: Realist and meta-narrative evidence syntheses: Evolving standards.

Community inclusion and engagement (cie): Planning of the research design and interpretation of the results was completed with nurse clinicians with experience in the NA role.

Objective: This study aimed to develop and validate a standardised transitional care programme for postoperative gynaecologic cancer patients utilising the Omaha system framework.

Methods: A preliminary transitional care programme was constructed through literature review, semi-structured interviews and multidisciplinary team discussions. The programme was refined via two rounds of Delphi expert consultations involving 17 oncology nursing specialists. Consensus criteria included expert authority coefficient (Cr), Kendall's W test and coefficient of variation (CV).

Results: The Delphi consultation demonstrated robust expert consensus, with high authority coefficients (Cr: 0.886 in Round 1; 0.906 in Round 2), exceptional participation rates (88.2% and 100% response rates across two rounds) and statistically significant concordance as evidenced by Kendall's W values (0.233-0.358 and 0.326-0.383; all p < 0.01). All coefficients of variation (CV) metrics fell within acceptable ranges (0.09-0.42 in the initial phase; 0.08-0.27 post-refinement).

Conclusion: The Omaha system-based transitional care programme exhibits strong expert consensus, scientific rigour and clinical applicability, providing a structured approach to improving postoperative recovery in gynaecologic cancer patients.

Relevance to clinical practice: This protocol standardises postoperative care transitions for gynaecologic oncology patients by integrating multidimensional assessments (physiological, psychosocial and health behaviour domains) and family-centred education. Clinicians can utilise its evidence-based framework to reduce preventable complications, enhance caregiver preparedness and improve continuity of care between hospital and home settings.

Patient or public contribution: Six postoperative gynaecologic cancer patients and eight family caregivers participated in semi-structured interviews to identify unmet transitional care needs. Their insights informed the design of intervention components, including self-management education and psychosocial support strategies. Patients reviewed draft materials for clarity and cultural appropriateness during Delphi Round 2.

Aim: The aim of this integrative review is to critically appraise and synthesise empirical evidence on the clinical applications, outcomes, and implications of generative artificial intelligence in nursing practice.

Design: Integrative review following Whittemore and Knafl's five-stage framework.

Methods: Systematic searches were performed for peer-reviewed articles and book chapters published between 1 January 2018 and 30 June 2025. Two reviewers independently screened titles/abstracts and full texts against predefined inclusion/exclusion criteria focused on generative artificial intelligence tools embedded in nursing clinical workflow (excluding nursing education-only applications). Data were extracted into a standardised matrix and appraised for quality using design-appropriate checklists. Guided by Whittemore and Knafl's integrative review framework, a constant comparative analysis was applied to derive the main themes and subthemes.

Data sources: CINAHL, MEDLINE, and Embase.

Results: Included literature was a representative mix of single-group quality improvement pilots, mixed-method usability and feasibility studies, randomised controlled trials, qualitative descriptive and phenomenological studies, as well as preliminary and proof-of-concept observational research. Four overarching themes emerged: (1) Workflow Integration and Efficiency, (2) AI-Augmented Clinical Reasoning, (3) Patient-Facing Communication and Education, and (4) Role Boundaries, Ethics and Trust.

Conclusion: Generative artificial intelligence holds promise for enhancing nursing efficiency, supporting clinical decision making, and extending patient communication. However, consistent human validation, ethical boundary setting, and more rigorous, longitudinal outcome and equity evaluations are essential before widespread clinical adoption.

Implications for the profession and patient care: Although generative artificial intelligence could reduce nurses' documentation workload and routine decision-making burden, these gains cannot be assumed. Safe and effective integration will require rigorous nurse training, robust governance, transparent labelling of AI-generated content, and ongoing evaluation of both clinical outcomes and equity impacts. Without these safeguards, generative artificial intelligence risks introducing new errors and undermining patient safety and trust.

Reporting method: PRISMA 2020.

Aims: To examine residential aged care staff's experience of death and grief, and their support needs.

Methods: A mixed-methods sequential explanatory design, using an online cross-sectional survey that included the Texas Revised Inventory of Grief and the Grief Support in Health Care Scale. Followed by semi-structured interviews with direct care workers and managers working in residential aged care homes were conducted.

Results: Over 60% of participants experienced five or more resident deaths in the previous 12 months. Although, different levels of grief were experienced among different roles, the importance of open communication and opportunities for farewells after resident death was highlighted. Participants suggested support and education to normalise grief and promote self-care.

Conclusion: Recognising staff grief following the resident death is important. Providing support and education may help improve staff wellbeing and contribute to the delivery of high-quality care for both residents and their families.

Implication for the profession and/or patient care: Staff grief after a resident death needs to be recognised, and continuing education and support are required for their wellbeing.

Reporting method: The STROBE and SRQR checklists were applied.

Patient or public contribution: No Patient or Public contribution.

Background: The use of technology to support nurses' decision-making is increasing in response to growing healthcare demands. AI, a global trend, holds great potential to enhance nurses' daily work if implemented systematically, paving the way for a promising future in healthcare.

Objectives: To identify and describe AI technologies for nurses' clinical decision-making in healthcare settings.

Design: A systematic literature review.

Data sources: CINAHL, PubMed, Scopus, ProQuest, and Medic were searched for studies with experimental design published between 2005 and 2024.

Review methods: JBI guidelines guided the review. At least two researchers independently assessed the eligibility of the studies based on title, abstract, and full text, as well as the methodological quality of the studies. Narrative analysis of the study findings was performed.

Results: Eight studies showed AI tools improved decision-making, patient care, and staff performance. A discharge support system reduced 30-day readmissions from 22.2% to 9.4% (p = 0.015); a deterioration algorithm cut time to contact senior staff (p = 0.040) and order tests (p = 0.049). Neonatal resuscitation accuracy rose to 94%-95% versus 55%-80% (p < 0.001); seizure assessment confidence improved (p = 0.01); pressure ulcer prevention (p = 0.002) and visual differentiation (p < 0.001) improved. Documentation quality increased (p < 0.001).

Conclusions: AI integration in nursing has the potential to optimise decision-making, improve patient care quality, and enhance workflow efficiency. Ethical considerations must address transparency, bias mitigation, data privacy, and accountability in AI-driven decisions, ensuring patient safety and trust while supporting equitable, evidence-based care delivery.

Impact: The findings underline the transformative role of AI in addressing pressing nursing challenges such as staffing shortages, workload management, and error reduction. By supporting clinical decision-making and workflow efficiency, AI can enhance patient safety, care quality, and nurses' capacity to focus on direct patient care. A stronger emphasis on research and implementation will help bridge usability and scalability gaps, ensuring sustainable integration of AI across diverse healthcare settings.

Background: Post-intensive care syndrome (PICS) is defined as mental, physical, cognitive, and social sequelae in survivors of critical illness. Survivors of liver transplantation exhibit a complex clinical condition following discharge from the intensive care unit (ICU). There is a lack of knowledge about the lived experience of PICS in survivors after liver transplantation.

Objectives: Describe the lived experiences of PICS in ICU survivors following liver transplantation.

Methods: A phenomenological study was carried out using interpretative phenomenological analysis (IPA). Semi-structured interviews were conducted with ICU survivors one month after discharge.

Results: Twenty ICU survivors were enrolled and interviewed after critical illness. The main themes that emerged from the data analysis were: (1) Profound life reorientation, (2) Physical impairment, (3) Psychological distress experiences, (4) Human-Centred Nursing Care, and (5) Return to daily life. Our results showed a particular impact of the dimensions of PICS, such as mental, physical, and social dimensions, on ICU survivors after liver transplantation.

Conclusion: The study concludes that ICU survivors experience profound life reorientation, physical impairment, and psychological distress experiences, yet benefit from human-centred nursing care, which facilitates their eventual return to daily life.

Patient or public contribution: The findings highlight the importance of human-centred nursing care in the post-ICU recovery process, where the multidisciplinary team plays a critical role in addressing both psychological distress and physical rehabilitation, supporting survivors' reintegration into daily life.

Impact: Post-liver transplant ICU survivors experience profound physical, psychological, and social impacts. Life reorientation, altered body image, and emotional distress emerge. Human-centred nursing facilitates rehabilitation, reintegration, and overall recovery.

Reporting method: Reporting was structured based on the COREQ checklist.

Protocol registration: Prot. N. 00014635-31/05/2023.