Search Results (43)

Background: Pain is a problem faced by critically ill surgical patients and has a major impact on their outcomes. Pain assessment is therefore essential for effective pain management, with a combination of pharmacological and non-pharmacological treatment. Clinical supervision, supported by models such as SafeCare, can improve professional development, safety and the quality of care in intensive care units. Objectives: This study aimed to: (1) assess current pain assessment practices in a polyvalent Intensive Care Unit (ICU) in the Porto district; (2) identify nurses’ training needs regarding the Clinical Supervision-Sensitive Indicator—Pain; and (3) evaluate the impact of clinical supervision sessions on pain assessment practices. Methods: A quantitative, quasi-experimental, cross-sectional study with a pre- and post-intervention design was conducted. Based on the SafeCare model, it included a situational diagnosis, 6 clinical supervision sessions (February 2023), and outcome evaluation via nursing record audits (November 2022 and May 2023) in 31 total critical ill patients. Pain was assessed using standardised tools, in line with institutional protocols. Data was analysed using Software Statistical Package for the Social Sciences v25.0. Results: Pain was highly prevalent in the first 24 h, decreasing during hospitalisation. Generalised acute abdominal pain predominated, with mild to moderate intensity, and was exacerbated by wound care and mobilisation/positioning. Pain management combined pharmacological and non-pharmacological treatment. There was an improvement in all the parameters of the pain indicator post-intervention. Conclusions: Despite routine assessments, gaps remained in reassessing pain post-analgesia and during invasive procedures. Targeted clinical supervision and ongoing training proved effective in improving compliance with protocols and supporting safer, more consistent pain management. Full article

Background: Early identification of sepsis is critical for improving outcomes, particularly in low-resource emergency settings. In Thai community hospitals, where physicians may not always be available, triage is often nurse-led. Selecting accurate and practical sepsis screening tools is essential not only for timely clinical decision-making but also for timely diagnosis and promoting appropriate antibiotic use. Methods: This cross-sectional study analyzed 475 adult patients with suspected sepsis who presented to the emergency department of a Thai community hospital, using retrospective data from January 2021 to December 2022. Six screening tools were evaluated: Systemic Inflammatory Response Syndrome (SIRS), Quick Sequential Organ Failure Assessment (qSOFA), Modified Early Warning Score (MEWS), National Early Warning Score (NEWS), National Early Warning Score version 2 (NEWS2), and Search Out Severity (SOS). Diagnostic accuracy was assessed using International Classification of Diseases, Tenth Revision (ICD-10) codes as the reference standard. Performance metrics included sensitivity, specificity, predictive values, likelihood ratios, and the area under the receiver operating characteristic (AUROC) curve, all reported with 95% confidence intervals. Results: SIRS had the highest sensitivity (84%), while qSOFA demonstrated the highest specificity (91%). NEWS2, NEWS, and MEWS showed moderate and balanced diagnostic accuracy. SOS also demonstrated moderate accuracy. Conclusions: A two-step screening approach—using SIRS for initial triage followed by NEWS2 for confirmation—is recommended. This strategy enhances nurse-led screening and optimizes limited resources in emergency care. Early sepsis detection through accurate screening tools constitutes a feasible public health intervention to support appropriate antibiotic use and mitigate antimicrobial resistance, especially in resource-limited community hospital settings. Full article

Antimicrobial resistance (AMR) is a pressing global health challenge, driving the need for effective antimicrobial stewardship (AMS) programmes. Despite nurses’ critical role in care delivery, their involvement in AMS remains under-recognized. Objectives: This mapping review aims to identify barriers and facilitators influencing nurses’ engagement in AMS programmes and examine nursing-sensitive outcomes associated with their participation, using Irvine’s Nursing Role Effectiveness Model (NREM) as a guiding framework. Methods: A systematic mapping review was conducted following Joanna Briggs Institute (JBI) guidance and reported using the PRISMA-ScR checklist. The protocol was registered on the Open Science Framework. Searches were conducted in MEDLINE, CI-NAHL, Scopus, LILACS, Scielo, and grey literature sources. Data were extracted and categorized according to the NREM domains: structure, process, and outcomes. Results: Thirty-two studies were included. Key barriers included limited AMS knowledge, role ambiguity, hierarchical dynamics, communication gaps, and lack of standardized nursing outcomes. Facilitators encompassed targeted AMS education, participation in multidisciplinary discussions, managerial support, and defined nursing roles. Nurse-led interventions showed potential to improve infection control and antibiotic administration, although standardized outcome reporting remains scarce. Conclusions: Framed by the NREM, this review underscores the essential contribution of nurses to AMS. Addressing structural barriers, enhancing role clarity, and fostering interdisciplinary collaboration are critical to enabling nurses’ full participation. Strengthening nursing engagement in AMS not only supports effective antimicrobial use and patient safety but also reinforces health system resilience and sustainability. Full article

Background/Objectives: The use of standardized assessment tools within the nursing care process is a globally established practice, widely recognized as a foundation for evidence-based evaluation. Accurate translation is essential to ensure their correct and consistent clinical use. While effective, traditional procedures are time-consuming and resource-intensive, leading to increasing interest in whether artificial intelligence can assist or streamline this process for nursing researchers. Therefore, this study aimed to assess the translation’s quality of nursing assessment scales performed by ChatGPT 4.0. Methods: A total of 31 nursing rating scales with 772 items were translated from English to Italian using two different prompts, and then underwent a deep lexicometric analysis. To assess the semantic accuracy of the translations the Sentence-BERT, Jaccard similarity, TF-IDF cosine similarity, and Overlap ratio were used. Sensitivity, specificity, AUC, and AUROC were calculated to assess the quality of the translation classification. Paired-sample t-tests were conducted to compare the similarity scores. Results: The Maastricht prompt produced translations that are marginally but consistently more semantically and lexically faithful to the original. While all differences were found to be statistically significant, the corresponding effect sizes indicate that the advantage of the Maastricht prompt is slight but consistent across all measures. The sensitivity of the prompts was 0.929 (92.9%) for York and 0.932 (93.2%) for Maastricht. Specificity and precision remained for both at 1.000. Conclusions: Findings highlight the potential of prompt engineering as a low-cost, effective method to enhance translation outcomes. Nonetheless, as translation represents only a preliminary step in the full validation process, further studies should investigate the integration of AI-assisted translation within the broader framework of instrument adaptation and validation. Full article

Background/Objective: Type 2 diabetes mellitus (T2D) is a chronic metabolic disorder characterized by hyperglycemia. Plant-based interventions have gained attention as potential complementary treatments alongside conventional therapies. This systematic review evaluates the efficacy of plant-based interventions in improving glycemic control, insulin sensitivity, lipid profiles, and other outcomes such as GLUT-4, Tumor Necrosis Facto-alpha, dietary inflammation index, plasma lipopolysaccharide, total antioxidant capacity, and malondialdehyde in individuals with T2D. Methods: We conducted a systematic search of PubMed, Scopus, and ScienceDirect databases to identify randomized controlled trials (RCTs) and observational studies. RCTs were used as an additional screening criterion. The review included studies on the effects of plant-based interventions, encompassing fruits, vegetables, herbs, spices, and their extracts. We analyzed data on glycemic control, insulin sensitivity, lipid profiles, and other metabolic markers. Results: Twenty-six studies were included in our analysis. Various interventions showed potential benefits, with improved glycemic control, insulin sensitivity, and lipid profiles. Specific interventions such as Ziziphus jujuba juice, black tea, caper fruit extract, and balanced diets were linked with positive outcomes. Based on the Functional Food Claim framework, all 26 studies met the quality criteria for novel foods. However, the novel food score varied, and results were inconsistent across different interventions. Conclusion: Although some plant-based interventions appear promising in managing T2D, the evidence remains inconclusive due to variability in study quality and methodology. Further high-quality RCTs are necessary to confirm these findings and to establish the optimal dosage, duration, and combinations of interventions for effective T2D management. Despite inconclusive results, few plant-based diets have promising outcomes. Healthcare providers, especially nurse case managers, can incorporate the findings of this study into their practice protocol to support self-management for individuals with TD2. Full article

Background: Depressive symptoms (DepS) are prevalent among patients with breast cancer. Offering an anti-inflammatory diet is a promising strategy for DepS management, but it is costly and difficult to scale up. Instead, anti-inflammatory dietary education is cost-effective and may be more conducive to the promotion of an anti-inflammatory diet strategy. Methods: A prospective, assessor-blinded, two-arm randomized controlled trial was designed to determine the effects of 12-week anti-inflammatory dietary education on DepS in breast cancer patients with depression. Adult female patients with depression and receiving adjuvant chemotherapy were recruited. Participants in the intervention group received anti-inflammatory dietary education, while the control group received routine nursing care. Outcomes included the Center for Epidemiologic Studies Depression Scale (CES-D) score, energy-adjusted dietary inflammatory index (E-DII), plasma inflammatory biomarkers, and quality of life (QoL), which were all assessed at baseline and after a 12-week follow-up. The robustness of the estimates was investigated through sensitivity analyses. A post hoc power analysis was conducted to establish the observed effect sizes for the primary outcomes. Results: A total of 88.6% (62/70) of the participants completed the entire 12-week follow-up. No statistically significant between-group differences were found in the baseline characteristics, including sociodemographic factors, disease-related characteristics, and lifestyle factors. After the intervention, both the CES-D score (p = 0.040) and E-DII (p < 0.001) in the intervention group were significantly lower than in the control group, while the QoL was significantly increased (p < 0.001). Compared with the baseline, the tumor necrosis factor-α (TNF-α) (p = 0.002) and C-reactive protein (CRP) (p = 0.045) levels were significantly lower in the intervention group but not in the control group. Conclusions: Anti-inflammatory dietary education may improve DepS and QoL in breast cancer patients with depression and undergoing chemotherapy by regulating inflammation. Given its acceptability and practicality, this strategy may be incorporated into routine cancer care. Full article

VID-KIDS (Video-Feedback Interaction Guidance for Depressed Mothers and their Infants) is a positive parenting programme comprising three brief nurse-guided video-feedback sessions (offered in-person or virtually via Zoom) that promote “serve and return” interactions by helping depressed mothers to be more sensitive and responsive to infant cues. We examined whether mothers who received the VID-KIDS programme demonstrated improved maternal–infant interaction quality. The secondary hypotheses examined VID-KIDS’ effects on maternal depression, anxiety, perceived parenting stress, infant developmental outcomes, and infant cortisol patterns. A parallel group randomized controlled trial (n = 140) compared the VID-KIDS programme to standard care controls (e.g., a resource and referral programme). The trial was registered in the US Clinical Trials Registry (number NCT03052374). Outcomes were assessed at baseline, nine weeks post-randomization (immediate post-test), and two months post-intervention. Maternal–infant interaction quality significantly improved for the intervention group with moderate to large effects. These improvements persisted during the post-test two months after the final video-feedback session. No significant group differences were detected for secondary outcomes. This study demonstrated that nurse-guided video-feedback can improve maternal–infant interaction in the context of PPD. These findings are promising, as sensitive and responsive parenting is crucial for promoting children’s healthy development. Full article

Background/Objectives: The COVID-19 pandemic has highlighted the challenges faced by essential professionals, such as nurse managers and early childhood educators (ECEs), who grapple with heightened stress, burnout, and compassion fatigue. In response, the Compassion, Practice, Relationships, and Restoration (CPR²) program was designed as a virtual, structured wellness intervention to address these pressing concerns among caregiving professionals. Methods: A mixed-methods study was employed to evaluate the feasibility, acceptability, and preliminary outcomes of CPR², implemented across two cohorts: nurse managers in a pediatric hospital and early childhood educators (ECEs) serving equity-deserving communities. Participants completed electronic surveys at pre- and post-test assessing mindfulness, professional quality of life, healthy lifestyle behaviors, and perceived social cohesion. One month post-program, focus groups were conducted using a facilitation guide to evaluate program elements, including group structure, expectations, discussion themes, and sustainability. Results: Quantitative findings suggest that while nurse managers experienced significant reductions in compassion fatigue, along with improvements in mindfulness and perceived cohesion, ECEs exhibited stable levels of stress and burnout. Both cohorts reported enhanced sleep quality, emphasizing the program’s potential to foster critical aspects of wellbeing. Qualitative participant feedback highlighted the importance of organizational readiness, leadership engagement, and program flexibility for successful implementation. Conclusions: The study highlights the need for tailored, context-sensitive wellness interventions that recognize the unique challenges faced by different caregiving roles. It also emphasizes the potential for sustained impact when wellness initiatives are integrated into the organizational culture, further reinforcing the importance of ongoing commitment to workforce wellbeing in high-stress environments. Full article

Background: Artificial intelligence (AI) has been increasingly employed in healthcare across diverse domains, including medical imaging, personalized diagnostics, therapeutic interventions, and predictive analytics using electronic health records. Its integration is particularly impactful in critical care, where AI has demonstrated the potential to enhance patient outcomes. This systematic review critically evaluates the current applications of AI within the domain of critical care nursing. Methods: This systematic review is registered with PROSPERO (CRD42024545955) and was conducted in accordance with PRISMA guidelines. Comprehensive searches were performed across MEDLINE/PubMed, SCOPUS, CINAHL, and Web of Science. Results: The initial review identified 1364 articles, of which 24 studies met the inclusion criteria. These studies employed diverse AI techniques, including classical models (e.g., logistic regression), machine learning approaches (e.g., support vector machines, random forests), deep learning architectures (e.g., neural networks), and generative AI tools (e.g., ChatGPT). The analyzed health outcomes encompassed postoperative complications, ICU admissions and discharges, triage assessments, pressure injuries, sepsis, delirium, and predictions of adverse events or critical vital signs. Most studies relied on structured data from electronic medical records, such as vital signs and laboratory results, supplemented by unstructured data, including nursing notes and patient histories; two studies also integrated audio data. Conclusion: AI demonstrates significant potential in nursing, facilitating the use of clinical practice data for research and decision-making. The choice of AI techniques varies based on the specific objectives and requirements of the model. However, the heterogeneity of the studies included in this review limits the ability to draw definitive conclusions about the effectiveness of AI applications in critical care nursing. Future research should focus on more robust, interventional studies to assess the impact of AI on nursing-sensitive outcomes. Additionally, exploring a broader range of health outcomes and AI applications in critical care will be crucial for advancing AI integration in nursing practices. Full article

Background: This study aimed to evaluate Emergency Department and Intensive Care Unit nurses’ skills in interpreting blood gas analysis results and to use those interpretations in clinical decision-making. Methods: In this prospective, multicenter, simulation-based study, nurses from the Emergency Department (ED) of Merano Hospital and the Intensive Care Unit (ICU) of Bolzano Hospital, Italy, were presented with 16 clinical vignettes based on real patient cases. These vignettes were designed to evaluate the nurses’ ability to identify patients with time-dependent conditions and recommend appropriate therapeutic interventions. Outcomes measured included sensitivity, specificity, and agreement with physician-assigned urgency levels and therapy recommendations. Results: Among the 43 participants (26 ICU and 17 ED nurses), specificity in excluding patients without time-dependent conditions or organ replacement needs was high. However, sensitivity in identifying time-dependent conditions was less than 50%. Agreement with physician-assigned urgency levels was low, with Cohen’s kappa values of 0.139 for ICU nurses and 0.218 for ED nurses. Nurses with lower self-confidence in interpreting BGA results made more errors, while other personal or professional factors did not significantly impact performance. Conclusions: Although critical care nurses can effectively rule out patients without time-dependent conditions, their ability to identify such conditions requires improvement. These findings underscore the need for targeted training programs to enhance nurses’ BGA interpretation skills and clinical decision-making in high-pressure, time-sensitive situations. Full article

The lack of evidence synthesis studies on the role of psychiatric mental health nursing in the context of psychiatric home hospitalization underscores the limited research on nurses providing care in these teams, particularly concerning their experiences and responsibilities and the actual role of nurses in this context. This knowledge has the potential to improve the quality of mental healthcare by guiding nursing practices. Objective: To map the concepts related to the role of mental health nurses in psychiatric home hospitalization. Methods: A scoping review was conducted using the methodology proposed by the JBI, involving five methodological stages. No search limits were applied except for language. Results: The review identified five key dimensions of nursing in psychiatric home hospitalization: satisfaction; care models; the therapeutic relationship; the care environment; the organization of care. These interconnected dimensions influence quality care. Satisfaction among nurses, patients, and families is associated with improved outcomes and reduced stigma. The therapeutic relationship is characterized by a humanistic approach, emphasizing dialogue, empathy, and shared decision making. Additionally, the importance of care organization is highlighted, including individualized care plans, medication management, and intersectoral collaboration. Discussion: The five nursing dimensions align with the Quality Standards of the Portuguese Nursing Council and are consistent with the scientific literature. Conclusions: Although there is a shortage of studies on this topic, this review allows for the synthesis of nursing interventions and reflection on the paradigm shift in care within the scope of psychiatric mental health nursing interventions. Future studies highlighting the value of mental health nursing interventions, with a particular focus on nursing-sensitive indicators and employing quantitative or mixed methods, will be crucial to furthering the analysis conducted thus far. Full article

Background/Objectives: Extensive research has emphasised the persistent challenges and failures in providing hospitalised patients with fundamental evidence-based nursing care, often resulting in grave consequences for patient safety. Recommendations from implementation research indicate that a tailored theory- and research-based implementation strategy targeting contextual determinants can optimise the implementation of evidence-based clinical practice for the benefit of patients. This study evaluated the feasibility of an implementation strategy designed to improve the quality of nursing care by targeting behavioural and environmental barriers in a hospital setting. Methods: Proctor’s conceptual model for implementation was applied to evaluate the strategy based on eight outcomes: adoption, acceptability, appropriateness, fidelity, feasibility, penetration, sustainability, and costs. Data collection methods included field observations, informal and focus group interviews, registrations, and audits of electronic patient records. Results: The strategy was adoptive, acceptable, appropriate, and feasible in targeting complex environmental and behavioural determinants (at the individual, team, and management level), enabling successful implementation of fundamental evidence-based nursing care. However, fidelity, feasibility, and sustainability were challenged by competing organisational demands and time constraints. Conclusions: The tailored, multifaceted strategy proved effective in addressing complex environmental and behavioural determinants across multiple levels, facilitating the implementation of fundamental evidence-based nursing care in a clinical practice. Further testing and larger-scale studies is needed to assess the strategy’s transferability and its impact on nursing-sensitive patient outcomes in different clinical settings. Full article

Background/Objectives: While breastfeeding is highly recommended, breastfed infants may be exposed to drugs by milk due to maternal pharmacotherapy, resulting in a risk of adverse drug events (ADE) or reactions (ADRs). The U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) is an online pharmacovigilance database, while the Drugs and Lactation Database (LactMed^®) includes accurate and evidence-based information on levels of substances in breast milk and infant blood, and possible ADRs in nursing infants. We aimed to explore the FAERS database and compare ADE/ADR information patterns between both databases. Methods: The FAERS database was explored (29 July 2024) for ADEs related to drug exposure during lactation to determine annual trends, infant outcomes, and regions of reporting. The active pharmaceutical ingredients (APIs) associated with these ADEs were categorized based on the Anatomical Therapeutic Chemical (ATC, first level) classification. The top five APIs in each ATC group were explored in terms of the type of ADEs reported and compared to information in LactMed^®. Results: In total, 2628 ADEs were obtained from the FAERS database, with increased reporting over time. In the FAERS database, 68.4% of the patients were under 2 months old, 5.5% had life threatening ADEs, and 3.6% died, while 84.70% of the cases were categorized as serious. Most ADEs were from North America (44.9%). Most drugs (50.9%) were nervous system drugs. The most frequent reported outcome was “other outcomes (without additional subdivision or information)” (58.2%), reflecting the diversity in outcomes reported. When related to the same drug, the FAERS database and LactMed^® resource exhibited both similarities and differences in the types of reported ADE/ADR. Conclusions: The FAERS database is a useful tool to detect potential ADEs (rather sensitive), without ADR assessment, while LactMed^® provides guidance driven by relevant ADRs (rather specific). The FAERS database is useful to obtain exploratory information about ADEs during lactation to increase the knowledge about drug safety during breastfeeding and the awareness of the possible risks in nursing infants, while LactMed^® translates all available information into guidance. Full article

Introduction: This qualitative literature review explored the intersection of art, creativity, and the nurse–patient relationship in the context of oncology nursing. It delved into the perceptions and reflections of nurses as captured by Generative Artificial Intelligence (GAI) analysis from two specialized nursing databases. Methods: The protocol was registered on the Open Science Framework (OSF) Platform. A comprehensive search was conducted in CINAHL, the British Nursing Database, and the Nursing & Allied Health Database, using keywords related to art, cancer, creativity, nursing, and relationships. The extracted qualitative research studies were then analyzed using GAI to identify key themes and insights. Results: The analysis revealed profound considerations regarding the role of nurses in oncology and palliative patient care. Nurses acknowledged the spiritual dimension through religious and spiritual practices, while emphasizing authentic presence and empathic communication. They actively addressed patient concerns, adapted to challenges, and engaged in continuous professional development. The insights from the GAI interpretation underscored the significance of empathy, creativity, and artistry in nurturing meaningful nurse–patient connections. Conclusions: The GAI-enabled exploration provided valuable insights into several dimensions of care, emphasizing the importance of spiritual sensitivity, empathic communication, and ongoing professional growth. As technology and human care converge, integrating artistry into the nurse–patient relationship could enhance patient experiences, improve outcomes, and enrich the oncology nursing practice. Full article

The healthcare sector has changed dramatically in recent years due to depending more and more on big data to improve patient care, enhance or improve operational effectiveness, and forward medical research. Protecting patient privacy in the era of digital health records is a major challenge, as there could be a chance of privacy leakage during the process of collecting patient data. To overcome this issue, we propose a secure, privacy-preserving scheme for healthcare data to ensure maximum privacy of an individual while also maintaining their utility and allowing for the performance of queries based on sensitive attributes under differential privacy. We implemented differential privacy on two publicly available healthcare datasets, the Breast Cancer Prediction Dataset and the Nursing Home COVID-19 Dataset. Moreover, we examined the impact of varying privacy parameter ($\epsilon$) values on both the privacy and utility of the data. A significant part of this study involved the selection of $\epsilon$, which determines the degree of privacy protection. We also conducted a computational time comparison by performing multiple complex queries on these datasets to analyse the computational overhead introduced by differential privacy. The outcomes demonstrate that, despite a slight increase in query processing time, it remains within reasonable bounds, ensuring the practicality of differential privacy for real-time applications. Full article