Journal of Nursing最新文献

{"title":"[Concept Analysis of Quiet Quitting].","authors":"Huei-Ru Liu, Hsiao-Yu Chen","doi":"10.6224/JN.26211","DOIUrl":"10.6224/JN.26211","url":null,"abstract":"<p><p>\"Quiet quitting\" has become an important work culture issue since the global outbreak of COVID-19, with the pandemic helping heighten awareness of the importance of physical, psychological, and emotional well-being. A growing number of employees have adopted \"quiet quitting\" to rebalance work and life priorities, operating as a social strategy reflecting their personal commitment to reducing the centrality of work in their overall life. Currently, a clear definition and systematic conceptual analysis of quiet quitting are not provided in the domestic (Taiwan) literature. Following the steps of Walker and Avant's concept analysis, the concept of quiet quitting is analyzed by verifying dictionary and literature definitions; identifying defining attributes; providing model, borderline, contrary, and related case illustrations; establishing antecedents and consequences; and defining empirical references. Quiet quitting may be seen as a precursor of employee turnover and a predictor of resignation behavior. The objective of this conceptual analysis is to clarify the scholarly understanding of quiet quitting to help guide future nursing practices and related research on the current state of quiet quitting among nursing staff and, ultimately, enable organizations and managers to deploy effective management and improve workplace culture.</p>","PeriodicalId":35672,"journal":{"name":"Journal of Nursing","volume":"73 2","pages":"e26211"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147515193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Developing a Clinical Nurse Specialist System in Taiwan: A Mixed-Methods Study].","authors":"Sue-Hsien Chen, Shiah-Lian Chen, Shu-Hua Kao, Tsun-Mei Chiu, Mei-Nan Liao","doi":"10.6224/JN.26207","DOIUrl":"10.6224/JN.26207","url":null,"abstract":"<p><strong>Background: </strong>Population aging and increasing disease complexity have increased the demand for specialized care provided by clinical nurse specialists (CNSs). However, Taiwan still lacks a comprehensive institutional framework, highlighting an urgent need to establish a structured CNS system to enhance the quality of care.</p><p><strong>Purpose: </strong>This study was designed to develop a CNS system to strengthen the nursing profession and improve the overall quality of healthcare delivery.</p><p><strong>Methods: </strong>A mixed-methods approach combining a literature review, the modified Delphi technique, focus group interviews, and expert consensus forums was used to develop a locally adapted CNS framework for Taiwan.</p><p><strong>Results: </strong>The CNS framework was developed through a rigorous and systematic process. Initially, three rounds of expert focus group discussions were conducted to identify core components and inform the development of a structured questionnaire. Subsequently, 30 expert panelists participated in two rounds of Delphi surveys to evaluate and refine the proposed framework. The finalized framework comprised 19 articles organized into six chapters and demonstrated a high level of consensus, with convergence rates of 94.0%-94.3% for feasibility and 93.6%-95.8% for appropriateness. The resulting CNS system structure consists of: general principles (3 articles), appointment (6 articles), core competencies and responsibilities (4 articles), selection (2 articles), continuing education (2 articles), and performance evaluation (2 articles).</p><p><strong>Conclusions / implications for practice: </strong>The CNS system developed in this study contributes substantively to expanding nursing roles and enhancing care quality in Taiwan. Future implementation should focus on strengthening interprofessional support to improve system feasibility in practice. Also, an appropriately funded and supported CNS certification system should be established. Finally, CNS contents must be incorporated into graduate-level nursing education to ensure the quality of CNS practice.</p>","PeriodicalId":35672,"journal":{"name":"Journal of Nursing","volume":"73 2","pages":"e26207"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147515259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Application and Effectiveness of Repetitive Transcranial Magnetic Stimulation (rTMS) in Post-Stroke Patients: Exploration of Nursing Care Roles and Application Guidelines].","authors":"Rui-Ying Li, Yu-Ming Chang","doi":"10.6224/JN.26210","DOIUrl":"10.6224/JN.26210","url":null,"abstract":"<p><p>Repetitive transcranial magnetic stimulation (rTMS), a non-invasive neuromodulation technique, has emerged as a promising intervention in post-stroke rehabilitation. With approximately 12 million new stroke cases annually, stroke remains the second leading cause of death and the third leading cause of disability worldwide, with this condition particularly prevalent in individuals over 60 years of age. Strokes are primarily classified as ischemic (85%) or hemorrhagic (10%-15%), with acute-phase treatments involving thrombolytics or surgery, and chronic-phase management integrating rehabilitation and techniques such as rTMS. The current evidence suggests that 85% of patients affected by stroke show functional improvement within 3-6 months of rehabilitation. rTMS modulates cortical excitability and neuroplasticity by inducing electric currents in the magnetic fields across the skull. High-frequency rTMS ( > 1 Hz) enhances excitability in lesioned regions, while low-frequency rTMS ( ≤ 1 Hz) inhibits hyperactivity in non-lesioned areas, thereby rebalancing interhemispheric activity and regulating neurotransmitters such as γ-aminobutyric acid and glutamate. Clinical studies have demonstrated rTMS to significantly enhance the recovery of motor skills, including increased upper limb Fugl-Meyer scores (p = .037) and standardized mean differences in Barthel Index (SMD = 0.580, p < .05), with effects lasting up to one year. In cases with aphasia, 20 sessions of low- or dual-frequency rTMS have been shown to improve fluency and naming ability as well as swallowing function. Cognitively, rTMS has been shown to enhance Montreal Cognitive Assessment scores (p < .001) and reduce task completion time on executive function tests. Psychologically, stimulation of the dorsolateral prefrontal cortex has been shown to reduce Hamilton Depression Rating Scale scores in post-stroke depression patients by 25%-30% (p < .01). Nurses play a pivotal role in rTMS treatments, including pre-treatment screening for contraindications (e.g., pacemakers, metal implants), providing patient education to alleviate anxiety, ensuring an interference-free environment, monitoring vital signs and adverse effects (e.g., headache, seizures), and conducting post-treatment follow-ups. In conclusion, future research should be conducted to explore optimal stimulation parameters and long-term efficacy to further advance clinical applications and enhance quality of care.</p>","PeriodicalId":35672,"journal":{"name":"Journal of Nursing","volume":"73 2","pages":"e26210"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147515241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Application of Evidence-Based Healthcare in Clinical Translation: An Interdisciplinary Collaboration Experience].","authors":"Shirling Lin, Hao-Min Cheng, Jen-Feng Liang, Teh-Fu Hsu, Yen-Po Tsao, Wei-Chih Chen, Lok-Hi Chow, Jin-Wei Lin, Hsiao-Chin Shen, Ching-Ching Sheng","doi":"10.6224/JN.26205","DOIUrl":"10.6224/JN.26205","url":null,"abstract":"&lt;p&gt;&lt;p&gt;This article was written to describe the authors' interprofessional collaboration experience with regard to the clinical translation of evidence-based healthcare. Building upon the spirit of evidence-based medicine invoked at the founding of the Cochrane Centre at Oxford University under the United Kingdom's National Health Service in 1992, our institution recognizes nursing as the core driving force supporting the translation of evidence-based healthcare in clinical settings. Using interdisciplinary collaboration mechanisms, systematic education and training, and knowledge translation strategies, the best research evidence is integrated into clinical decision-making and improving care quality, thus deepening the application of evidence-based clinical healthcare. In clinical care, nursing teams have led multiple evidence-based initiatives targeting patient safety and care quality improvement. Issues addressed have included fall prevention, infection control, nasogastric tube dislodgement prevention, hypothermia interventions to improve neurological outcomes in patients with traumatic brain injury, post-operative positioning adjustments, acute-phase COVID-19 pulmonary rehabilitation, and family-centered interventions in intensive care units to reduce the incidence of delirium. These initiatives have been significantly grounded in the findings of systematic literature reviews and outcome evaluations, with results demonstrating a notable reduction in adverse event rates and significant improvements in functional recovery and quality of life in patients. Nursing personnel play an integrative and leading role in assessment-tool development, care process design, outcome monitoring, and the continuous provision of quality feedback, reflecting their professional autonomy in the clinical application of evidence-based practice. In terms of guideline development, the nursing department has taken the lead in constructing guidelines for cancer symptom management and post-curative follow-up care for patients with liver cancer, advocating for an integrated model centered on holistic care, and collaborating with physicians, pharmacists, and dietitians to jointly establish interdisciplinary care standards. Also, the department has actively mentored advanced practice nurses in writing evidence-based clinical care guidelines at an advanced level, strengthening advanced nursing practice competencies and academic output. With regard to shared decision-making and Choosing Wisely initiatives, nursing staff participate in the development of decision support tools and the application of structured communication models to facilitate patient value clarification and engagement in decision-making, while concurrently enhancing healthcare resource-utilization appropriateness and safety. Overall, within the evidence-based clinical system, the nursing profession fulfills multiple functions in the realms of care practice, research participation, education promotion, and kno","PeriodicalId":35672,"journal":{"name":"Journal of Nursing","volume":"73 2","pages":"e26205"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147515196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[The Translation, Innovation, and Interprofessional Application of Evidence-Based Health Care in Clinical Practice].","authors":"Shu-Yu Chen","doi":"10.6224/JN.26201","DOIUrl":"10.6224/JN.26201","url":null,"abstract":"&lt;p&gt;&lt;p&gt;Only when scientific evidence moves beyond research conclusions and is translated into clinical decision-making, organizational systems, and standard patient care can the true value of evidence-based practice be fully realized. Current scholarship suggests that, in addition to high-quality research, leadership capacity, appropriate implementation strategies, and the effective integration and governance of technology-enabled systems within clinical contexts are all critical to ensuring the adoption, practice, and impact of evidence-based healthcare strategies (Fontaine et al., 2024). Reflecting this broader development trajectory, the articles in this issue tackle evidence-based implementation strategies, nursing workforce considerations, systems thinking, and the evolving role of artificial intelligence (AI) in clinical care. At the nursing leadership and organizational governance level, the findings of a recent systematic review indicate nurse leaders with strong evidence-based competencies are well positioned to facilitate changes in clinical practice, strengthen interprofessional collaboration, and enhance both quality of care and organizational performance (V̈lim̈ki et al., 2024). The studies in this review reinforce the view that evidence-based practice, rather than being a responsibility shouldered by frontline nurses alone, must be a shared institutional capacity embedded within leadership and organizational structures. Implementation strategies are central to effectively translating evidence into practice. The findings of a systematic review and meta-analysis by Fontaine et al. (2024) demonstrate multifaceted and integrated approaches such as education and training, clinical reminders, leadership engagement, and structured feedback mechanisms help promote sustained improvements in nursing practice and, in turn, positively influence patient outcomes. As digital health technologies continue to advance, the role of AI in supporting clinical decision-making has become an increasingly prominent focus of evidence-based care discussions. While AI technologies hold considerable promise in supporting nurse clinical decision-making, enhancing efficiency, and reducing workload, their effectiveness in real-world clinical settings remains highly contingent upon user trust, system transparency, and organizational support (Mikkonen et al., 2026; Ouanes & Farhah, 2024). In high-intensity clinical environments, appropriately designed and well-governed AI systems may enable nurses to direct more time and professional judgment toward making complex, person-centered care decisions. Concurrently, emerging evidence cautions that, more than a technical endeavor, the implementation of AI has significant implications in the realms of workflow design, professional autonomy, and ethical responsibility. Almagharbeh (2025) emphasizes that, in the absence of clear role delineation and meaningful clinical engagement, AI-based decision support systems may inadvert","PeriodicalId":35672,"journal":{"name":"Journal of Nursing","volume":"73 2","pages":"e26201"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147515286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Sustainable Development and the Challenges of Integrating AI Into Evidence-Based Practice].","authors":"Mei-Ling Yeh, Jia-Yu Yuan, Albert Lou Yeh","doi":"10.6224/JN.26203","DOIUrl":"10.6224/JN.26203","url":null,"abstract":"<p><p>Under the framework of evidence-based practice (EBP), evidence-based knowledge is integrated systematically into clinical care and continuously updated to enhance decision-making, ensure patient safety, and showcase nursing excellence. The rapid evolution and popularization of artificial intelligence (AI) has encouraged its incorporation into EBP, including as a tool for clinical nurses to further increase efficiencies in care provision and decision-making. However, AI integration poses challenges in terms of both care practices and ethics. This article was designed to explore the various applications of AI in EBP, emphasizing sustainability alongside ethical, institutional, and technological issues. While AI can improve care efficiency and quality, it also introduces risks such as data errors, algorithmic bias, privacy concerns, intellectual property issues, access inequities, and ethical accountability concerns. Without transparency and oversight, large language models have the potential to exacerbate health disparities and resource gaps. To achieve the core values of improving care quality and patient safety through technology, integrating AI into EBP requires the building of a robust framework that is clinically practical, regularly updated with new algorithms, and includes monitoring systems and ethical governance. Ultimately, the harmonization of AI capabilities and care principles may be expected to achieve healthcare that is more resilient, value-driven, high-quality, and sustainable.</p>","PeriodicalId":35672,"journal":{"name":"Journal of Nursing","volume":"73 2","pages":"e26203"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147515327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Empirical Concept Overview: Analysis of Optimal Nursing Staff Allocation in Hospital Acute Care Wards and Related Decision-Making].","authors":"Wen-Yi Chen, Shu-Fen Su","doi":"10.6224/JN.26204","DOIUrl":"10.6224/JN.26204","url":null,"abstract":"<p><p>Research on nursing workforce policy has increasingly shifted from the examining relationship between nurse staffing levels and care quality toward considering a more comprehensive framework that simultaneously considers nurse staffing levels, care quality, and care costs in analyses of optimal nursing staff allocation. In line with this trend, an extended version of Park's Sweet Spot Theory adapted as a multiple inputs and outputs model is proposed in this study. This adapted model may be used to estimate the optimal level of inpatient care quality based on actual inpatient quality indicators and, in concert with a hospital's cost-minimization production model, identify the optimal allocation of nursing staff across three shifts in acute care hospital wards. Beyond providing an empirical framework for analyzing and making decisions regarding optimal nursing staff allocation in hospital acute care wards, the extended theory proposed in this study may be used as an evidence-based tool by the Taiwan Ministry of Health and Welfare for future policymaking related to three-shift staffing standards and nursing salary adjustments.</p>","PeriodicalId":35672,"journal":{"name":"Journal of Nursing","volume":"73 2","pages":"e26204"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147515253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Nursing Assessment of the Oral Feeding Readiness of Premature Infants and Related Factors].","authors":"Ching-Wei Lin, Chien-Chi Liu","doi":"10.6224/JN.26209","DOIUrl":"10.6224/JN.26209","url":null,"abstract":"<p><strong>Background: </strong>With the growing emphasis on neonatal developmental care, nurses are being encouraged to provide responsive feeding based on preterm infant behavioral cues. The responsive feeding approach has been shown to reduce stress stimuli, stabilize physiological maturity, and optimize neurodevelopment, making it an important model of care for preterm infants. Consequently, nurses who are proficient in recognizing the behavioral signals of oral feeding readiness in preterm infants are better able to facilitate the safe transition to oral feeding, thereby supporting infant growth and development.</p><p><strong>Purpose: </strong>This study was designed to examine the associated factors of nurses in assessment of oral feeding in preterm infants.</p><p><strong>Methods: </strong>In this cross-sectional correlational study, neonatal nursing staff were recruited using convenience sampling. Data were collected using a demographic questionnaire, the Developmental Care Knowledge and Support Ability Scale, and the Recognition of Preterm Oral Feeding Readiness Scale. Independent t-tests, one-way analysis of variance, and Pearson's product-moment correlation were used in correlation analyses. Stepwise multiple regression was employed for the inferential statistics.</p><p><strong>Results: </strong>Recognition of oral feeding readiness differed significantly by work unit. Specifically, nurses in the sick baby room recognized cues indicating oral feeding readiness more accurately than those in the NICU (t = -3.95, p < .01), while those with prior oral feeding training scored higher than those without (t = 2.03, p < .05). In addition, a positive correlation was found between recognition of oral feeding readiness and developmental care knowledge (r = .28, p < .05). The results of the stepwise regression identified three significant predictors of recognition of oral feeding readiness, which collectively explained 13.8% of the variance. These were: developmental care knowledge (β = 0.28, p < .01), work unit (β = 0.22, p < .001), and oral feeding training (β = 0.17, p < .001).</p><p><strong>Conclusions / implications for practice: </strong>In-service education on preterm oral feeding should be incorporated into the training provided to all nurses working with preterm infants to enhance their developmental care knowledge and improve their ability to recognize the signals of oral feeding readiness. Such targeted training may be expected to facilitate the successful implementation of developmental care practices and promote the safe transition to oral feeding in preterm infants.</p>","PeriodicalId":35672,"journal":{"name":"Journal of Nursing","volume":"73 2","pages":"e26209"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147515181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Promoting Innovative Nursing Education Through STEAM Interdisciplinary Thinking: Constructing an AI-NURSE Innovative Teaching Model].","authors":"Pao-Chen Lin, Te-Yu Chen, Hui-Fang Kao, Chih-Chao Chung","doi":"10.6224/JN.26206","DOIUrl":"10.6224/JN.26206","url":null,"abstract":"<p><strong>Background: </strong>The role of artificial intelligence (AI) in medical care has become increasingly prominent. There is an urgent need to integrate the cross-disciplinary thinking of science, technology, engineering, arts, and mathematics (STEAM) into nursing education to strengthen cross-disciplinary competencies and AI literacy in students.</p><p><strong>Purpose: </strong>This study was developed to explore the current status of STEAM literacy, learning interest, and career interest among nursing students. Based on the findings, a targeted, innovative nursing teaching model that integrates AI was developed to improve the cross-disciplinary competencies and workplace competitiveness of these students.</p><p><strong>Methods: </strong>A self-developed questionnaire on STEAM literacy, learning interest, and career interest was used to collect study data. All 270 first-year nursing students from a junior college in southern Taiwan were invited to participate on a voluntary basis, with 259 valid questionnaires collected. Descriptive statistics, t-tests, correlation analysis, and regression analysis were conducted to examine the predictive power of STEAM literacy and learning interest on career interest. A standardized Z-score matrix was adopted to present the distribution of STEAM learning and career interests visually, establishing an innovative teaching model that helps integrate AI into nursing education.</p><p><strong>Results: </strong>The participants performed well in STEAM literacy, particularly in terms of ethics and social responsibility, collaboration and communication, and problem solving competencies. The survey on STEAM learning interest and STEAM career interest revealed most of the participants exhibited significantly positive affirmation of the science and art fields. STEAM literacy, learning interest, and career interest were found to be significantly positively correlated, with STEAM literacy and STEAM learning interest identified as significant predictors of STEAM career interest. Finally, the results of the Z-score matrix analysis indicate engineering and mathematics fields are associated with the low learning-interest / career-interest quadrant, while the science and technology field is associated with the low learning-interest / high career-interest quadrant.</p><p><strong>Conclusions / implications for practice: </strong>The innovative student-centered AI-NURSE (artificial intelligence-navigate, utilize, reflect, solve, execute) teaching model proposed in this study provides specific evaluation criteria as a practical reference for integrating AI into nursing education. The findings may be used to promote the cultivation of nursing professionals, laying the foundation for the future development of smart medical technology.</p>","PeriodicalId":35672,"journal":{"name":"Journal of Nursing","volume":"73 2","pages":"e26206"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147515288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Death Literacy: A Concept Analysis].","authors":"Tsz-Shiou Hu, Wei-Yun Wang, Kwua-Yun Wang","doi":"10.6224/JN.26212","DOIUrl":"10.6224/JN.26212","url":null,"abstract":"<p><p>\"Death literacy\" refers to the acquisition, understanding, and application of knowledge related to death and end-of-life care during the final stages of life. Although there is extensive research on health literacy, studies on death literacy remain relatively scarce. In this article, the conceptual analysis approach described by Walker and Avant is applied to define the characteristics of death literacy, which include: (1) the ability to possess and comprehend fundamental knowledge related to death and end-of-life care; (2) communication skills to discuss end-of-life care options with family members and others; (3) the accumulation of wisdom regarding life and death through hands-on experience in end-of-life care and experiential learning in life education; and (4) the dissemination of wisdom on life and death through sharing personal experiences with others. Using typical, borderline, contrary, and related cases, this analysis clarifies the concept, identifies the antecedents and consequences of death literacy, lists current empirical measurement tools, and explores applications in nursing practice, research, and theory. The overall goal of this article is to enhance the understanding of nursing personnel regarding this concept, provide a clinical reference for caregivers, increase public awareness of life and death issues, and, ultimately, ensure and improve the quality of end-of-life care provided to patients.</p>","PeriodicalId":35672,"journal":{"name":"Journal of Nursing","volume":"73 2","pages":"e26212"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147515189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}